Latin American Monographs Second Series Population and Energy A Systems Analysis of Resource Utilization in the Dominican Republic 14 Center for Latin American Studies University of Florida Latin American Monographs Second Series Population and Energy A Systems Analysis of Resource Utilization in the Dominican Republic Latin American Monographs Second Series Population and Energy A Systems Analysis of Resource Utilization in the Dominican Republic 14 14 Center for Latin American Studies University of Florida Center for Latin American Studies University of Florida   Population and Energy A Systems Analysis of Resource Utilization in the Dominican Republic Gustavo A. Antonini Katherine Carter Ewel Howard M. Tupper A University of Florida Book The University Presses of Florida Gainesville-1975 Population and Energy A Systems Analysis of Resource Utilization in the Dominican Republic Population and Energy A Systems Analysis of Resource Utilization in the Dominican Republic Gustavo A. Antonini Katherine Carter Ewel Howard M. Tupper Gustavo A. Antonini Katherine Carter Ewel Howard M. Tupper A University of Florida Book The University Presses of Florida Gainesville-1975 A University of Florida Book The University Presses of Florida Gainesville-1975  This ontibution to Latins Asmerican populatios sudiess hass beens fundd ussders grans-t fromss thes Tisnker Fosunsdations. A Unissity-ss of Florsida Book CENTERss FOss LATIN- AMERIsCoN STUDIES COPYRIGHT s© 1975 B BoTHEBOARD OFRGNSOF THE STAOF LORIDAs This contributsiont Latsin Americansss pospuslatons osdies has beens fundettd unsder gransts fromsts he Tinsker Foun dation. 4(_A Unwssit-sy of Florisda Book CENTER OR LATN AMERICsoN OSTDIES COPYRIGHTs © 1975 BYoTHE BOR --o OFRGNSOTHE STATE OF FORIDA This contr-ibuons to Latins Amersicant poplatsion suies htts beest funded undeaos grans-t from the~s Tinsker Foundaonss. y~A Unisversity sof Flsorida Book CoOPYRIGHT © 1975 BYTEBODOFos- REEN S H SAOFFLOD All rights...s-oed Al ight rs-sod All r-ightsoss rserve Library of Congress Cataloginsg iss Publications Data Antsonini, Gutavso A., 1938- Population and enegy: ssystms anlysis of reoreutlzto inth Domsinican Republic. (LatinsAmeri oogrphs;2d sers., 14) Bibliography:s p. IncluIdes index. 1. Domin-ican Republic-Poplaiont. 2. Natural rs-ourcs-Doisicano Republic. 3. Ener-gy coupiont- Domtinican- Republic. I. Ewel, Katheriness Carsstr 1944- joint austhor-. II. Tupper, Hloward M., 1941- joint author-. III. Tile. IV. Series: Florida. Uiverosity, Gainsvisslle. Center for Latint Amersicans Studist. Latin American mon ographs. 2d ser-.. 14. HB3552.A58 333.7'097293 75-2495 ISBN 0-8130-0502-7 Librarsy of Cssngss Cataslogintg in Publications Data Anonsini, Gustaoso A., 1938- Popultion- and enegy: a systems analysis of reore tlzaini thes Domtisnican Republi. (LatinsAmeroian mongrphs; d st, 14) Bibliograophy: p. Inluds indets. 1. Dominicanst Re-public-Poplaton. 2. Natural resources-Dom5inican Republic. 3. Ener-gy onosumptio- Doinican Respublic. I. Ewel, Kathersines Carters, 1944- joint author-. II. Tuppert, Howarod M., 1941- joint autho. III. Title. IV. Series Florida. Univeshity, Gainesvill. Cens-ter for bLain Amesricans Studies. Lain- Amerssican mtonograophs; 2d set5., 14. 14B3552.A58 333.7'097293 75-2495 ISBN 0-8130-0502-7 Librar-y of Congre-ss Cataloginsg in- Publication Data An-tonin-i, Gstavo A., 1938- Populaht ot andenergy: systes-s anlysis of reoreuiiaiint he Doms-insican Re-public. (Latin-American-U onoogaps;2d ses.,14) Bibliography: p. IsIlds indexo. 1. Domsiican Republic-Populatio. 2. Natosua reosurs--Dominican Republic. 3. Ener-sgyconsumoption- Dosinsican- Republi. I. Eol, Katheine Carter-, 1944- joist author. II. Tuppers, Howard- M., 1941- joist author. I11. Tile. IV. Seris: Florida. Univesty Gasinsvill. Ceterlt for Latint Asssericass Studies. Latin Asssericass ssonsographs; 2d se., 14. HB3552.A58 333.7'097293 75-2495 ISBN 0-8130-0502-7  The cost of building dams is always underestimated- There's erosion of the delta that the river has created, There's fertile soil below the dam that's likely to be looted, And the tangled mat of forest that has got to be uprooted. There's the breaking up of cultures with old haunts' and habits' loss, There's the education program that just doesn't come across, And the wasted fruits of progress that are seldom much enjoyed By expelled subsistence farmers who are urban unemployed. There are benefits, of course, which may be countable, but which Have a tendency to fall into the pockets of the rich, While the costs are apt to fall upon the shoulders of the poor. So cost-benefit analysis is nearly always sure, To justify the building of a solid concrete fact, While the Ecologic Truth is left behind in the Abstract. Kenneth E. Boulding The cost of building dams is always underestimated- There's erosion of the delta that the river has created, There's fertile soil below the dam that's likely to be looted, And the tangled mat of forest that has got to be uprooted. There's the breaking up of cultures with old haunts' and habits' loss, There's the education program that just doesn't come across, And the wasted fruits of progress that are seldom much enjoyed By expelled subsistence farmers who are urban unemployed. There are benefits, of course, which may be countable, but which Have a tendency to fall into the pockets of the rich, While the costs are apt to fall upon the shoulders of the poor. So cost-benefit analysis is nearly always sure, To justify the building of a solid concrete fact, While the Ecologic Truth is left behind in the Abstract. Kenneth E. Boulding The cost of building dams is always underestimated- There's erosion of the delta that the river has created, There's fertile soil below the dam that's likely to be looted, And the tangled mat of forest that has got to be uprooted. There's the breaking up of cultures with old haunts' and habits' loss, There's the education program that just doesn't come across, And the wasted fruits of progress that are seldom much enjoyed By expelled subsistence farmers who are urban unemployed. There are benefits, of course, which may be countable, but which Have a tendency to fall into the pockets of the rich, While the costs are apt to fall upon the shoulders of the poor. So cost-benefit'analysis is nearly always sure, To justify the building of a solid concrete fact, While the Ecologic Truth is left behind in the Abstract. Kenneth E. Boulding   Contents Contents Contents List of Tables / ix List of Illustrations / xi List of Plates / xv List of Appendixes / xvii Preface / xix 1. Dominican Republic: A Microcosm of Regional Development / 1 2. Physical Setting / 11 3. Cultural Background / 39 4. Land Use / 57 5. Las Placetas: A Case Study / 77 6. Integrated Land Use-Water Balance Modeling / 101 7. Ecological Factors in Development / 119 Appendixes / 125 Bibliography / 159 Index / 165 List of Tables / ix List of Illustrations / xi List of Plates / xv List of Appendixes / xvii Preface / xix 1. Dominican Republic: A Microcosm of Regional Development / 1 2. Physical Setting / 11 3. Cultural Background / 39 4. Land Use / 57 5. Las Placetas: A Case Study / 77 6. Integrated Land Use-Water Balance Modeling / 101 7. Ecological Factors in Development / 119 Appendixes / 125 Bibliography / 159 Index / 165 List of Tables / ix List of Illustrations / xi List of Plates / xv List of Appendixes / xvii Preface / xix 1. Dominican Republic: A Microcosm of Regional Development / 1 2. Physical Setting / 11 3. Cultural Background / 39 4. Land Use / 57 5. Las Placetas: A Case Study / 77 6. Integrated Land Use-Water Balance Modeling / 101 7. Ecological Factors in Development / 119 Appendixes / 125 Bibliography / 159 Index / 165   List of Tables List of Tables List of Tables 1. Major Characteristics of Jagua-Bao Soils / 18 2. Relative Erosion Values for Varying Land-Use Practices / 27 3. Mean Annual Runoff in m3 - sec' by Life Zone and Soil Depth / 29 4. Comparison of Discharge Data for Jagua River Basin / 32 5. Composite Median Moisture Status by Life Zones and Seasons / 33 6. Agricultural Calendar of Farm Crops / 50 7. Summary of Map Measurements for Total Areas of Land Uses for 1948, 1958, and 1966 / 67 8. Natural Power Density Values for the Three Base Map Years / 72 9. Harvested-Yield Power Density Values for the Three Base Map Years / 74 10. Population Estimates and Emigration, 1948-70 / 80 1. Major Characteristics of Jagua-Bao Soils / 18 2. Relative Erosion Values for Varying Land-Use Practices / 27 3. Mean Annual Runoff in m3 - sec' by Life Zone and Soil Depth / 29 4. Comparison of Discharge Data for Jagua River Basin / 32 5. Composite Median Moisture Status by Life Zones and Seasons / 33 6. Agricultural Calendar of Farm Crops / 50 7. Summary of Map Measurements for Total Areas of Land Uses for 1948, 1958, and 1966 / 67 8. Natural Power Density Values for the Three Base Map Years / 72 9. Harvested-Yield Power Density Values for the Three Base Map Years / 74 10. Population Estimates and Emigration, 1948-70 / 80 1. Major Characteristics of Jagua-Bao Soils / 18 2. Relative Erosion Values for Varying Land-Use Practices / 27 3. Mean Annual Runoff in m3 - sec' by Life Zone and Soil Depth / 29 4. Comparison of Discharge Data for Jagua River Basin / 32 5. Composite Median Moisture Status by Life Zones and Seasons / 33 6. Agricultural Calendar of Farm Crops / 50 7. Summary of Map Measurements for Total Areas of Land Uses for 1948, 1958, and 1966 / 67 8. Natural Power Density Values for the Three Base Map Years / 72 9. Harvested-Yield Power Density Values for the Three Base Map Years / 74 10. Population Estimates and Emigration, 1948-70 / 80  x Population and Energy 11. Land-Use Change, 1948-66 / 82 12. Approximate Local Measures of Principal Agricultural Products / 84 13. Rates of Energy Flow Associated with Principal Agricultural Activities / 86 14. Rates of Energy Flow and Land-Use Conversion Affecting Las Placetas / 94 15. Relative Erosion Coefficients Selected for Use in Jagua-Bao Region / 106 16. Rates of Energy Flow and Land-Use Conversion Affecting Jagua-Bao Region / 108 x Population and Energy 11. Land-Use Change, 1948-66 / 82 12. Approximate Local Measures of Principal Agricultural Products / 84 13. Rates of Energy Flow Associated with Principal Agricultural Activities / 86 14. Rates of Energy Flow and Land-Use Conversion Affecting Las Placetas / 94 15. Relative Erosion Coefficients Selected for Use in Jagua-Bao Region / 106 16. Rates of Energy Flow and Land-Use Conversion Affecting Jagua-Bao Region / 108 x Population and Energy 11. Land-Use Change, 1948-66 / 82 12. Approximate Local Measures of Principal Agricultural Products / 84 13. Rates of Energy Flow Associated with Principal Agricultural Activities / 86 14. Rates of Energy Flow and Land-Use Conversion Affecting Las Placetas / 94 15. Relative Erosion Coefficients Selected for Use in Jagua-Bao Region / 106 16. Rates of Energy Flow and Land-Use Conversion Affecting Jagua-Bao Region / 108  List of Illustrations List of Illustrations List of Illustrations 1. Map showing Jagua-Bao study region / 7 2. Reconnaissance geologic map of Jagua-Bao study region / 12 3. Geomorphic subregions of Duarte Province / 14 4. Geomorphic characteristics of Tavera Province / 16 5. Map showing landforms that influence climate in central Dominican Republic / 20 6. Water balance graphs of selected climatological stations in central Dominican Republic / 21 7. Map showing Jagua River catchment basin with climatological and stream-gauging station locations / 26 8. Mean monthly runoff for each life zone within Jagua watershed / 30 9. Variations in mean monthly runoff by life zone due to changes in soil depth / 31 10. Map showing soil moisture status for December-January period / 34 11. Map showing soil moisture status for February-March period / 35 12. Map showing soil moisture status for April-July period / 36 13. Map showing soil moisture status for August-November period / 37 1. Map showing Jagua-Bao study region / 7 2. Reconnaissance geologic map of Jagua-Bao study region / 12 3. Geomorphic subregions of Duarte Province / 14 4. Geomorphic characteristics of Tavera Province / 16 5. Map showing landforms that influence climate in central Dominican Republic / 20 6. Water balance graphs of selected climatological stations in central Dominican Republic / 21 7. Map showing Jagua River catchment basin with climatological and stream-gauging station locations / 26 8. Mean monthly runoff for each life zone within Jagua watershed / 30 9. Variations in mean monthly runoff by life zone due to changes in soil depth / 31 10. Map showing soil moisture status for December-January period / 34 11. Map showing soil moisture status for February-March period / 35 12. Map showing soil moisture status for April-July period / 36 13. Map showing soil moisture status for August-November period / 37 1. Map showing Jagua-Bao study region / 7 2. Reconnaissance geologic map of Jagua-Bao study region / 12 3. Geomorphic subregions of Duarte Province / 14 4. Geomorphic characteristics of Tavera Province / 16 5. Map showing landforms that influence climate in central Dominican Republic / 20 6. Water balance graphs of selected climatological stations in central Dominican Republic / 21 7. Map showing Jagua River catchment basin with climatological and stream-gauging station locations / 26 8. Mean monthly runoff for each life zone within Jagua watershed / 30 9. Variations in mean monthly runoff by life zone due to changes in soil depth / 31 10. Map showing soil moisture status for December-January period / 34 11. Map showing soil moisture status for February-March period / 35 12. Map showing soil moisture status for April-July period / 36 13. Map showing soil moisture status for August-November period / 37  xii Population and Energy 14. Population growth for selected communities and the nation: 1790-1970 / 41 15. Map showing historical settlements and penetration roads in Jagua-Bao region during early twentieth century / 43 16. Selected forms of land use / 47 17. Selected land-use practices / 49 18. Lumbering activities / 55 19. Symbols of the energy flow language / 60 20. Initial energy flow model of land use and population in Jagua-Bao region / 62 21. Sections of Jagua-Bao region / 64 22. Revised energy flow model of land use and population in study region / 69 23. Settlement pattern in Las Placetas / 78 24. Simulation results of Las Placetas, Pinalito, and Juncalito Abajo models for 1948-2025 period / 96 25. Simulation of land use and population changes in Las Placetas, assuming that conditions which applied to 1948-70 period will hold in the future / 98 26. Simulation of land use and population changes in Las Placetas which might occur if forest cutting were resumed in 1975 / 98 27. Simulation of land use and population changes in Las Placetas which might occur if rate of conversion of forest into pasture were 5.5 per cent per year / 98 28. Simulation of land use and population changes in Las Placetas which might occur if land could be converted to farmland more readily / 99 29. Simulation of land use and population changes in Las Placetas which might occur if rate of emigration observed from 1962 to 1975 were to double in 1975 / 99 30. Simulation of land use and population changes in Las Placetas which might occur if rate of emigration observed from 1962 to 1975 were to quadruple in 1975 / 99 31. Simulation of land use and population changes in Las Placetas which might occur if rate of money inflow to the area were to double or quadruple in 1975 / 99 32. Energy flow model of water budget and sediment accumulation in Jagua-Bao region / 102 33. Simulation outputs of water balance model for one year / 104 34. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025 / 110 xii Population and Energy 14. Population growth for selected communities and the nation: 1790-1970 / 41 15. Map showing historical settlements and penetration roads in Jagua-Bao region during early twentieth century / 43 16. Selected forms of land use / 47 17. Selected land-use practices / 49 18. Lumbering activities / 55 19. Symbols of the energy flow language / 60 20. Initial energy flow model of land use and population in Jagua-Bao region / 62 21. Sections of Jagua-Bao region / 64 22. Revised energy flow model of land use and population in study region / 69 23. Settlement pattern in Las Placetas / 78 24. Simulation results of Las Placetas, Pinalito, and Juncalito Abajo models for 1948-2025 period / 96 25. Simulation of land use and population changes in Las Placetas, assuming that conditions which applied to 1948-70 period will hold in the future / 98 26. Simulation of land use and population changes in Las Placetas which might occur if forest cutting were resumed in 1975 / 98 27. Simulation of land use and population changes in Las Placetas which might occur if rate of conversion of forest into pasture were 5.5 per cent per year / 98 28. Simulation of land use and population changes in Las Placetas which might occur if land could be converted to farmland more readily / 99 29. Simulation of land use and population changes in Las Placetas which might occur if rate of emigration observed from 1962 to 1975 were to double in 1975 / 99 30. Simulation of land use and population changes in Las Placetas which might occur if rate of emigration observed from 1962 to 1975 were to quadruple in 1975 / 99 31. Simulation of land use and population changes in Las Placetas which might occur if rate of money inflow to the area were to double or quadruple in 1975 / 99 32. Energy flow model of water budget and sediment accumulation in Jagua-Bao region / 102 33. Simulation outputs of water balance model for one year / 104 34. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025 / 110 xii Population and Energy 14. Population growth for selected communities and the nation: 1790-1970 / 41 15. Map showing historical settlements and penetration roads in Jagua-Bao region during early twentieth century / 43 16. Selected forms of land use / 47 17. Selected land-use practices / 49 18. Lumbering activities / 55 19. Symbols of the energy flow language / 60 20. Initial energy flow model of land use and population in Jagua-Bao region / 62 21. Sections of Jagua-Bao region / 64 22. Revised energy flow model of land use and population in study region / 69 23. Settlement pattern in Las Placetas / 78 24. Simulation results of Las Placetas, Pinalito, and Juncalito Abajo models for 1948-2025 period / 96 25. Simulation of land use and population changes in Las Placetas, assuming that conditions which applied to 1948-70 period will hold in the future / 98 26. Simulation of land use and population changes in Las Placetas which might occur if forest cutting were resumed in 1975 / 98 27. Simulation of land use and population changes in Las Placetas which might occur if rate of conversion of forest into pasture were 5.5 per cent per year / 98 28. Simulation of land use and population changes in Las Placetas which might occur if land could be converted to farmland more readily / 99 29. Simulation of land use and population changes in Las Placetas which might occur if rate of emigration observed from 1962 to 1975 were to double in 1975 / 99 30. Simulation of land use and population changes in Las Placetas which might occur if rate of emigration observed from 1962 to 1975 were to quadruple in 1975 / 99 31. Simulation of land use and population changes in Las Placetas which might occur if rate of money inflow to the area were to double or quadruple in 1975 / 99 32. Energy flow model of water budget and sediment accumulation in Jagua-Bao region / 102 33. Simulation outputs of water balance model for one year / 104 34. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025 / 110  List of Illustrations xiii 35. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming forest cutting continues in spite of 1967 legislation / 110 36. Relative accumulation of sediment from Jagua-Bao region as simulated from 1975 through 2025 for twelve different land use policies / 112 37. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest cutting is prohibited in 1967 and that forest is permitted to regrow after 1975 / 113 38. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that amounts of land in each category are held constant at their 1975 level / 113 39. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest cutting continues through 1967 and that rate of conversion of forest to mixed farming is doubled / 113 40. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that rate of conversion of forest to pasture after 1975 is double the pre-1975 rate / 114 41. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that emigration rate after 1975 is double the pre-1975 rate / 114 42. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest is continually cut despite 1967 legislation, and that rate of emigration after 1975 is double the pre-1975 rate / 114 43. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that emigration rate after 1975 is quadruple the pre-1975 rate / 115 44. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest continues to be cut and that emigration rate is quadrupled after 1975 / 115 45. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming a doubling of the rate at which money is supplied to residents / 115 46. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming both a doubling of the rate at which money is provided and continued forest cutting / 115 47. Relative sediment accumulation under twelve land management conditions over 2015-45 period / 122 List of Illustrations xiii 35. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming forest cutting continues in spite of 1967 legislation / 110 36. Relative accumulation of sediment from Jagua-Bao region as simulated from 1975 through 2025 for twelve different land use policies / 112 37. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest cutting is prohibited in 1967 and that forest is permitted to regrow after 1975 / 113 38. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that amounts of land in each category are held constant at their 1975 level / 113 39. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest cutting continues through 1967 and that rate of conversion of forest to mixed farming is doubled / 113 40. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that rate of conversion of forest to pasture after 1975 is double the pre-1975 rate / 114 41. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that emigration rate after 1975 is double the pre-1975 rate / 114 42. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest is continually cut despite 1967 legislation, and that rate of emigration after 1975 is double the pre-1975 rate / 114 43. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that emigration rate after 1975 is quadruple the pre-1975 rate / 115 44. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest continues to be cut and that emigration rate is quadrupled after 1975 / 115 45. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming a doubling of the rate at which money is supplied to residents / 115 46. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming both a doubling of the rate at which money is provided and continued forest cutting / 115 47. Relative sediment accumulation under twelve land management conditions over 2015-45 period / 122 List of Illustrations xiii 35. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming forest cutting continues in spite of 1967 legislation / 110 36. Relative accumulation of sediment from Jagua-Bao region as simulated from 1975 through 2025 for twelve different land use policies / 112 37. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest cutting is prohibited in 1967 and that forest is permitted to regrow after 1975 / 113 38. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that amounts of land in each category are held constant at their 1975 level / 113 39. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest cutting continues through 1967 and that rate of conversion of forest to mixed farming is doubled / 113 40. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that rate of conversion of forest to pasture after 1975 is double the pre-1975 rate / 114 41. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that emigration rate after 1975 is double the pre-1975 rate / 114 42. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest is continually cut despite 1967 legislation, and that rate of emigration after 1975 is double the pre-1975 rate / 114 43. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that emigration rate after 1975 is quadruple the pre-1975 rate / 115 44. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming that forest continues to be cut and that emigration rate is quadrupled after 1975 / 115 45. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming a doubling of the rate at which money is supplied to residents / 115 46. Simulated changes in land use and population size in Jagua-Bao region from 1948 to 2025, assuming both a doubling of the rate at which money is provided and continued forest cutting / 115 47. Relative sediment accumulation under twelve land management conditions over 2015-45 period / 122   List of Plates List of Plates List of Plates . Population Distribution in 1968, Jagua-Bao, Dominican Republic I. Land Use in 1948, Jagua-Bao, Dominican Republic IIL. Land Use in 1958, Jagua-Bao, Dominican Republic IV. Land Use in 1966, Jagua-Bao, Dominican Republic V. Natural Power Density Change, 1948-1958, Jagua-Bao, Dominican Republic V. Natural Power Density Change, 1958-1966, Jagua-Bao, Dominican Republic VI. Harvested-Yield Power Density Change, 1948-1958, Jagua-Bao, Dominican Republic VII. Harvested-Yield Power Density Change, 1958-1966, Jagua-Bao, Dominican Republic . Population Distribution in 1968, Jagua-Bao, Dominican Republic I. Land Use in 1948, Jagua-Bao, Dominican Republic IIL. Land Use in 1958, Jagua-Bao, Dominican Republic IV. Land Use in 1966, Jagua-Bao, Dominican Republic V. Natural Power Density Change, 1948-1958, Jagua-Bao, Dominican Republic Vt. Natural Power Density Change, 1958-1966, Jagua-Bao, Dominican Republic VI. Harvested-Yield Power Density Change, 1948-1958, Jagua-Bao, Dominican Republic VII. Harvested-Yield Power Density Change, 1958-1966, Jagua-Bao, Dominican Republic . Population Distribution in 1968, Jagua-Bao, Dominican Republic I. Land Use in 1948, Jagua-Bao, Dominican Republic II. Land Use in 1958, Jagua-Bao, Dominican Republic IV. Land Use in 1966, Jagua-Bao, Dominican Republic V. Natural Power Density Change, 1948-1958, Jagua-Bao, Dominican Republic V. Natural Power Density Change, 1958-1966, Jagua-Bao, Dominican Republic VI. Harvested-Yield Power Density Change, 1948-1958, Jagua-Bao, Dominican Republic VIII. Harvested-Yield Power Density Change, 1958-1966, Jagua-Bao, Dominican Republic   List of Appendixes List of Appendixes List of Appendixes A. Hydrological Characteristics of Jagua River Drainage Basin / 125 B. Computer Program and Water Balance Calculations for Representative Life Zones at 300-, 200-, and 100-Millimeter Soil Depths / 127 C. Subroutine Runoff Program for the IBM-360 and Runoff Calculations for Representative Life Zones at 300-, 200-, and 100-Millimeter Soil Depths / 148 D. Section-Level Field Schedule / 151 E. Circuit Diagrams for Land-Use and Water Balance Analog Models / 156 A. Hydrological Characteristics of Jagua River Drainage Basin / 125 B. Computer Program and Water Balance Calculations for Representative Life Zones at 300-, 200-, and 100-Millimeter Soil Depths / 127 C. Subroutine Runoff Program for the IBM-360 and Runoff Calculations for Representative Life Zones at 300-, 200-, and 100-Millimeter Soil Depths / 148 D. Section-Level Field Schedule / 151 E. Circuit Diagrams for Land-Use and Water Balance Analog Models / 156 A. Hydrological Characteristics of Jagua River Drainage Basin / 125 B. Computer Program and Water Balance Calculations for Representative Life Zones at 300-, 200-, and 100-Millimeter Soil Depths / 127 C. Subroutine Runoff Program for the IBM-360 and Runoff Calculations for Representative Life Zones at 300-, 200-, and 100-Millimeter Soil Depths / 148 D. Section-Level Field Schedule / 151 E. Circuit Diagrams for Land-Use and Water Balance Analog Models / 156   Preface Preface Preface T HIS MONOGRAPH stems from a series of field-based studies under- taken by the senior author in the Dominican Republic, all of which dealt with processes of landscape change and the cultural features produced by change. The first of the studies were analytical but nonquan- titative, and employed both diachronic and spatial techniques. From the results, it became evident that, for a full understanding of landscape evolution, the cumulative effects of land-use change would have to be evaluated quantitatively. Only in this manner could the impact of carry- over trends on the availability of physical resources be accurately meas- ured over both the short and the long run. Evaluation of landscape evolution is of practical, as well as academic, importance. Planners recognize the critical need for an evaluative and predictive method for understanding the wide-ranging ecological impact of human activities on the physical resource base. There is a particular need to gauge people's probable impact through changing land use on the life expectancy of dams and reservoirs within watershed areas. Prompted by a personal request from the president of the Dominican Republic, Joaquin Balaguer, to undertake the study of such impact, and taking into account the broad implications of the research problem, an interdiscipli- T HIS MONOGRAPH stems from a series of field-based studies under- taken by the senior author in the Dominican Republic, all of which dealt with processes of landscape change and the cultural features produced by change. The first of the studies were analytical but nonquan- titative, and employed both diachronic and spatial techniques. From the results, it became evident that, for a full understanding of landscape evolution, the cumulative effects of land-use change would have to be evaluated quantitatively. Only in this manner could the impact of carry- over trends on the availability of physical resources be accurately meas- ured over both the short and the long run. Evaluation of landscape evolution is of practical, as well as academic, importance. Planners recognize the critical need for an evaluative and predictive method for understanding the wide-ranging ecological impact of human activities on the physical resource base. There is a particular need to gauge people's probable impact through changing land use on the life expectancy of dams and reservoirs within watershed areas. Prompted by a personal request from the president of the Dominican Republic, Joaquin Balaguer, to undertake the study of such impact, and taking into account the broad implications of the research problem, an interdiscipli- tIS MONOGRAPH stems from a series of field-based studies under- taken by the senior author in the Dominican Republic, all of which dealt with processes of landscape change and the cultural features produced by change. The first of the studies were analytical but nonquan- titative, and employed both diachronic and spatial techniques. From the results, it became evident that, for a full understanding of landscape evolution, the cumulative effects of land-use change would have to be evaluated quantitatively. Only in this manner could the impact of carry- over trends on the availability of physical resources be accurately meas- ured over both the short and the long run. Evaluation of landscape evolution is of practical, as well as academic, importance. Planners recognize the critical need for an evaluative and predictive method for understanding the wide-ranging ecological impact of human activities on the physical resource base. There is a particular need to gauge people's probable impact through changing land use on the life expectancy of dams and reservoirs within watershed areas. Prompted by a personal request from the president of the Dominican Republic, Joaquin Balaguer, to undertake the study of such impact, and taking into account the broad implications of the research problem, an interdiscipli-  xx Population and Energy nary team was assembled to carry out the research in that country during the spring 1971-summer 1973 period. As an example of interdisciplinary cooperation, the effort warrants singular attention. It exemplifies to what extent integration of research methodologies and disciplinary foci from distinct fields within the social and natural sciences can be molded into a holistic framework, bonded by a common desire to resolve substantive problems. To a large measure, the successful completion of the project and the publication of its findings are due to the unselfish manner in which all members of the team gave unstintingly of their time and effort. For those of us who formed the nexus of the group, the professional camaraderie and cooperative spirit that de- veloped proved to be as essential an ingredient of the experience as did the research itself. A number of staff and students, both from the University of Florida and the Dominican Republic, became associated with the project in mean- ingful ways. Howard T. Odum provided thoughtful counsel on matters related to systems analysis and ecological modeling throughout the entire course of research. Early in the program, Ariel Lugo assisted in develop- ing the initial model and guided the formulation of field data collection procedures. In the field, agronomist Juan Francisco Garcia de los Santos, Industrias Portela de Navarrete, assisted immeasurably in interviewing and data collection. During the early period of data analysis in the laboratory, Glenn Fish and Michael Stearman, Florida students in geography, pro- vided assistance in compilation of cartographic materials and water balance-runoff calculations, respectively. John J. Ewel worked on the initial water balance model which formed an integral part of our prelim- inary findings already reported in the literature. Glenn Fish was also responsible for developing the power density mapping component as an independent study under the Master of Science thesis requirements in geography. As a field study undertaken in a developing country, this project owes an incalculable debt to the friendship and generosity of the Dominican people. A devoted friend, Victor Espaillat Mera, deserves very special thanks for his valuable counsel and unflinching moral support. Tomas Pastoriza and Jos6 Joaquin Hungria Morell aided immensely in making government policy makers aware of the project and its implications. These leaders of the Dominican community did much to advance the cause of applied social science research in the Dominican Republic. We wish also to acknowledge the participation of the rural folk and their meaningful contribution. Each community within Jagua-Bao, no matter how small and seemingly insignificant, responded immediately and xx Population and Energy nary team was assembled to carry out the research in that country during the spring 1971-summer 1973 period. As an example of interdisciplinary cooperation, the effort warrants singular attention. It exemplifies to what extent integration of research methodologies and disciplinary foci from distinct fields within the social and natural sciences can be molded into a holistic framework, bonded by a common desire to resolve substantive problems. To a large measure, the successful completion of the project and the publication of its findings are due to the unselfish manner in which all members of the team gave unstintingly of their time and effort. For those of us who formed the nexus of the group, the professional camaraderie and cooperative spirit that de- veloped proved to be as essential an ingredient of the experience as did the research itself. A number of staff and students, both from the University of Florida and the Dominican Republic, became associated with the project in mean- ingful ways. Howard T. Odum provided thoughtful counsel on matters related to systems analysis and ecological modeling throughout the entire course of research. Early in the program, Ariel Lugo assisted in develop- ing the initial model and guided the formulation of field data collection procedures. In the field, agronomist Juan Francisco Garcia de los Santos, Industrias Portela de Navarrete, assisted immeasurably in interviewing and data collection. During the early period of data analysis in the laboratory, Glenn Fish and Michael Stearman, Florida students in geography, pro- vided assistance in compilation of cartographic materials and water balance-runoff calculations, respectively. John J. Ewel worked on the initial water balance model which formed an integral part of our prelim- inary findings already reported in the literature. Glenn Fish was also responsible for developing the power density mapping component as an independent study under the Master of Science thesis requirements in geography. As a field study undertaken in a developing country, this project owes an incalculable debt to the friendship and generosity of the Dominican people. A devoted friend, Victor Espaillat Mera, deserves very special thanks for his valuable counsel and unflinching moral support. Tomis Pastoriza and Jos6 Joaquin Hungria Morell aided immensely in making government policy makers aware of the project and its implications. These leaders of the Dominican community did much to advance the cause of applied social science research in the Dominican Republic. We wish also to acknowledge the participation of the rural folk and their meaningful contribution. Each community within Jagua-Bao, no matter how small and seemingly insignificant, responded immediately and xx Population and Energy nary team was assembled to carry out the research in that country during the spring 1971-summer 1973 period. As an example of interdisciplinary cooperation, the effort warrants singular attention. It exemplifies to what extent integration of research methodologies and disciplinary foci from distinct fields within the social and natural sciences can be molded into a holistic framework, bonded by a common desire to resolve substantive problems. To a large measure, the successful completion of the project and the publication of its findings are due to the unselfish manner in which all members of the team gave unstintingly of their time and effort. For those of us who formed the nexus of the group, the professional camaraderie and cooperative spirit that de- veloped proved to be as essential an ingredient of the experience as did the research itself. A number of staff and students, both from the University of Florida and the Dominican Republic, became associated with the project in mean- ingful ways. Howard T. Odum provided thoughtful counsel on matters related to systems analysis and ecological modeling throughout the entire course of research. Early in the program, Ariel Lugo assisted in develop- ing the initial model and guided the formulation of field data collection procedures. In the field, agronomist Juan Francisco Garcia de los Santos, Industrias Portela de Navarrete, assisted immeasurably in interviewing and data collection. During the early period of data analysis in the laboratory, Glenn Fish and Michael Stearman, Florida students in geography, pro- vided assistance in compilation of cartographic materials and water balance-runoff calculations, respectively. John J. Ewel worked on the initial water balance model which formed an integral part of our prelim- inary findings already reported in the literature. Glenn Fish was also responsible for developing the power density mapping component as an independent study under the Master of Science thesis requirements in geography. As a field study undertaken in a developing country, this project owes an incalculable debt to the friendship and generosity of the Dominican people. A devoted friend, Victor Espaillat Mera, deserves very special thanks for his valuable counsel and unflinching moral support. Tomas Pastoriza and Jose Joaquin Hungria Morell aided immensely in making government policy makers aware of the project and its implications. These leaders of the Dominican community did much to advance the cause of applied social science research in the Dominican Republic. We wish also to acknowledge the participation of the rural folk and their meaningful contribution. Each community within Jagua-Bao, no matter how small and seemingly insignificant, responded immediately and  Preface xxi enthusiastically with people, material aid, and agronomic information in whatever way was deemed most helpful. It can truthfully be said that the Dominican Republic's greatest resource is its people. The University of Florida supported this study financially through the joint auspices of the Center for Latin American Studies and a grant for studies in population geography from the Tinker Foundation of New York. Analog computer facilities were provided by the Department of Nuclear Engineering Sciences of the University of Florida. Particular thanks are due to William E. Carter, friend and colleague, for moral encouragement and personal support. The lines on page v are from the poem "A Ballad of Ecological Aware- ness," by Kenneth E. Boulding, published in The Careless Technology, by M. T. Farvar and J. P. Milton, copyright © 1972, and reprinted with the permission of Doubleday & Company, Inc. Gustavo A. Antonini Katherine Carter Ewel Howard M. Tupper Preface xxi enthusiastically with people, material aid, and agronomic information in whatever way was deemed most helpful. It can truthfully be said that the Dominican Republic's greatest resource is its people. The University of Florida supported this study financially through the joint auspices of the Center for Latin American Studies and a grant for studies in population geography from the Tinker Foundation of New York. Analog computer facilities were provided by the Department of Nuclear Engineering Sciences of the University of Florida. Particular thanks are due to William E. Carter, friend and colleague, for moral encouragement and personal support. The lines on page v are from the poem "A Ballad of Ecological Aware- ness," by Kenneth E. Boulding, published in The Careless Technology, by M. T. Farvar and J. P. Milton, copyright © 1972, and reprinted with the permission of Doubleday & Company, Inc. Gustavo A. Antonini Katherine Carter Ewel Howard M. Tupper Preface xxi enthusiastically with people, material aid, and agronomic information in whatever way was deemed most helpful. It can truthfully be said that the Dominican Republic's greatest resource is its people. The University of Florida supported this study financially through the joint auspices of the Center for Latin American Studies and a grant for studies in population geography from the Tinker Foundation of New York. Analog computer facilities were provided by the Department of Nuclear Engineering Sciences of the University of Florida. Particular thanks are due to William E. Carter, friend and colleague, for moral encouragement and personal support. The lines on page v are from the poem "A Ballad of Ecological Aware- ness," by Kenneth E. Boulding, published in The Careless Technology, by M. T. Farvar and J. P. Milton, copyright © 1972, and reprinted with the permission of Doubleday & Company, Inc. Gustavo A. Antonini Katherine Carter Ewel Howard M. Tupper   1. Dominican Republic A Microcosm of Regional Development INCREASED population pressures on the limited resources of the earth make the study of resource utilization one of the most urgent needs of our society today. The need is particularly great in tropi- cal regions, for it is there that population growth is the most rapid and resource management is, in general, the least technically developed. In endeavoring to meet their growing needs, emerging nations within the tropics are attempting to leap across centuries, bypassing intermediate stages of development and making very rapid transitions from traditional to modem society.' Increasingly, the vehicle for these transitions is invest- ment in and dependence upon large-scale social and economic programs. One such vehicle for implementing these programs is whole-basin devel- opment. Whole-basin, or integrated river basin, development is a modern tech- nique which has been used in planning and coordinating growth for entire 1. United Nations, Science and Technology for Development, Report on the United Nations Conference on the Application of Science and Technology for the Benefit of the Less Developed Areas, 8 vols. (New York: United Nations, 1963), 1:221. 1. Dominican Republic A Microcosm of Regional Development INCREASED population pressures on the limited resources of the earth make the study of resource utilization one of the most urgent needs of our society today. The need is particularly great in tropi- cal regions, for it is there that population growth is the most rapid and resource management is, in general, the least technically developed. In endeavoring to meet their growing needs, emerging nations within the tropics are attempting to leap across centuries, bypassing intermediate stages of development and making very rapid transitions from traditional to modern society.' Increasingly, the vehicle for these transitions is invest- ment in and dependence upon large-scale social and economic programs. One such vehicle for implementing these programs is whole-basin devel- opment. Whole-basin, or integrated river basin, development is a modern tech- nique which has been used in planning and coordinating growth for entire 1. United Nations, Science and Technology for Development, Report on the United Nations Conference on the Application of Science and Technology for the Benefit of the Less Developed Areas, 8 vols. (New York: United Nations, 1963), 1:221. 1. Dominican Republic A Microcosm of Regional Development INCREASED population pressures on the limited resources of the earth make the study of resource utilization one of the most urgent needs of our society today. The need is particularly great in tropi- cal regions, for it is there that population growth is the most rapid and resource management is, in general, the least technically developed. In endeavoring to meet their growing needs, emerging nations within the tropics are attempting to leap across centuries, bypassing intermediate stages of development and making very rapid transitions from traditional to modem society.' Increasingly, the vehicle for these transitions is invest- ment in and dependence upon large-scale social and economic programs. One such vehicle for implementing these programs is whole-basin devel- opment. Whole-basin, or integrated river basin, development is a modem tech- nique which has been used in planning and coordinating growth for entire 1. United Nations, Science and Technology for Development, Report on the United Nations Conference on the Application of Science and Technology for the Benefit of the Less Developed Areas, 8 vols. (New York: United Nations, 1963), 1:221.  2 Population and Energy drainage areas? It takes into account all available resources within the basin and makes it possible to conserve and to utilize them for the benefit of its population. Its unifying element is the river, and the natural balance between people and the land within the basin reflects interrelated forces operating simultaneously on land, water, vegetation, and animal life. Be- cause of the river system's impact upon the physical and social environ- ment, actions taken at one point within the system, whether for single or multiple purposes, are apt to affect, for better or worse, conditions along the entire river course. Soil erosion in the catchment basin upsets the river's regime, causing higher floods and longer droughts and increasing the river's sediment load.t Sedimentation adds to canal scouring and subsequent reservoir siltation, in this manner seriously affecting the very basis on which the development plan rests. It is argued increasingly that land-use practices such as poorly managed cultivation, burning and cutting of forests, overgrazing, and grass fires increase runoff, cause soil erosion, and consequently increase sediment transport." Such cultural practices disturb the natural equilibrium between 2. The classic example is of course the work of the Tennessee Valley Authority. the first of the large-scale whole-basin programs and still one of the most com- prehensive. For a very readable statement, see D. E. Lilienthal, TVA: Democracy on the March (New York: Harper and Brothers, 1944). A broad overview of the concept with interesting applications to the developing countries may be found in United Nations, Science and Technology, 2:83-93. 3. United Nations, Economic Commission for Asia and the Far East. Multiple- Purpose River Basin Development, pt. I (New York: United Nations, 1955). pp. 65-66. 4. An excellent dicussion correlating measures of land improvement in the drainage basin with engineering works on the stream is found in the report of a panel of experts: United Nations, Department of Economic and Social Affairs, Integrated River Basin Development, rev. ed. (New York: United Nations, 1970), pp. 51-55. Case studies deronstrating increasing silt yields as a function of more intensive land use and deforestation are given for a number of tropical Asian countries in: United Nations, Economic Commission for Asia and the Far East, The Sediment Problem (Bangkok: United Nations, 1953), pp. 11-16. For Africa. H. C. Pereira reports on the matter in "Hydrological Effects of Changes in Land Use in Some East African Catchment Areas," East African Agricultural and Forestry Journal 27 (March 1962): 1-15. Robert Allen's study, "The Anchicaya Hydro- electric Project in Colombia: Design and Sedimentation Problems," which appeared in The Careless Technology: Ecology and International Development, ed. M. Taghi Farvar and a. P. Milton (Garden City, N.Y.: Natural History Press. 1972), pp. 318-d8, describes the failure to recognize the very serious sediment and debris problems associated with deforestation of a watershed in tropical montane Colombia. J. . Noll's classic study, The Silting of Caonillas Reservoir, Puerto Rico, Soil Conservation Service TP-119 (Washington: U.S. Department of Agriculture, 1953), provides ample reference to a Caribbean island example. The report by H. E. Hudson et al., "Effects of Land Use on Reservoir Siltation," American Water Works Association Journal 40 (October 1949): 913-31, gives noteworthy examples for the United States. 2 Population and Energy drainage areas? It takes into account all available resources within the basin and makes it possible to conserve and to utilize them for the benefit of its population. Its unifying element is the river, and the natural balance between people and the land within the basin reflects interrelated forces operating simultaneously on land, water, vegetation, and animal life. Be- cause of the river system's impact upon the physical and social environ- ment, actions taken at one point within the system, whether for single or multiple purposes, are apt to affect, for better or worse, conditions along the entire river course. Soil erosion in the catchment basin upsets the river's regime, causing higher floods and longer droughts and increasing the river's sediment load.t Sedimentation adds to canal scouring and subsequent reservoir siltation, in this manner seriously affecting the very basis on which the development plan rests. It is argued increasingly that land-use practices such as poorly managed cultivation, burning and cutting of forests, overgrazing, and grass fires increase runoff, cause soil erosion, and consequently increase sediment transport0 Such cultural practices disturb the natural equilibrium between 2. The classic example is of course the work of the Tennessee Valley Authority. the first of the large-scale whole-basin programs and still one of the most com- prehensive. For a very readable statement, see D. E. Lilienthal, TVA: Democracy on the March (New York: Harper and Brothers, 1944). A broad overview of the concept with interesting applications to the developing countries may be found in United Nations, Science and Technology, 2:83-93. 3. United Nations, Economic Commission for Asia and the Far East, Multiple- Purpose River Basin Development, pt. 1 (New York: United Nations, 1955). pp. 65-66. 4. An excellent dicussion correlating measures of land improvement in the drainage basin with engineering works on the stream is found in the report of a panel of experts: United Nations, Department of Economic and Social Affairs, Integrated River Basin Development, rev. ed. (New York: United Nations, 1970), pp. 51-55. Case studies demonstrating increasing silt yields as a function of more intensive land use and deforestation are given for a number of tropical Asian countries in: United Nations, Economic Commission for Asia and the Far East, The Sediment Problem (Bangkok: United Nations, 1953), pp. 11-16. For Africa, H. C. Pereira reports on the matter in "Hydrological Effects of Changes in Land Use in Some East African Catchment Areas," East African Agricultural and Forestry Journal 27 (March 1962): 1-15. Robert A11en's study, "The Anchicaya Hydro. electric Project in Colombia: Design and Sedimentation Problems," which appeared in The Careless Technology: Ecology and International Development, ed. M. Taghi Farvar and I. P. Milton (Garden City, N.Y.: Natural History Press, 1972), pp. 318-48, describes the failure to recognize the very serious sediment and debris problems associated with deforestation of a watershed in tropical montane Colombia. a. a. Noll's classic study, The Silting of Caonillas Reservoir, Puerto Rico, Soil Conservation Service TP-119 (Washington: U.S. Department of Agriculture, 1953), provides ample reference to a Caribbean island example. The report by H. E. Hudson et al., "Effects of Land Use on Reservoir Siltation," American Water Works Association Journal 40 (October 1949): 913-31, gives noteworthy examples for the United States. 2 Population and Energy drainage areas.' It takes into account all available resources within the basin and makes it possible to conserve and to utilize them for the benefit of its population. Its unifying element is the river, and the natural balance between people and the land within the basin reflects interrelated forces operating simultaneously on land, water, vegetation, and animal life. Be- cause of the river system's impact upon the physical and social environ- ment, actions taken at one point within the system, whether for single or multiple purposes, are apt to affect, for better or worse, conditions along the entire river course. Soil erosion in the catchment basin upsets the river's regime, causing higher floods and longer droughts and increasing the river's sediment load.t Sedimentation adds to canal scouring and subsequent reservoir siltation, in this manner seriously affecting the very basis on which the development plan rests. It is argued increasingly that land-use practices such as poorly managed cultivation, burning and cutting of forests, overgrazing, and grass fires increase runoff, cause soil erosion, and consequently increase sediment transport.4 Such cultural practices disturb the natural equilibrium between 2. The classic example is of course the work of the Tennessee Valley Authority, the first of the large-scale whole-basin programs and still one of the most com- prehensive. For a very readable statement, see D. E. Lilienthal, TVA: Democracy on the March (New York: Harper and Brothers, 1944). A broad overview of the concept with interesting applications to the developing countries may be found in United Nations, Science and Technology, 2:83-93. 3. United Nations, Economic Commission for Asia and the Far East, Multiple- Purpose River Basin Development, pt. 1 (New York: United Nations, 1955), pp. 65-66. 4. An excellent dicussion correlating measures of land improvement in the drainage basin with engineering works on the stream is found in the report of a panel of experts: United Nations, Department of Economic and Social Affairs. Integrated River Basin Development, rev. ed. (New York: United Nations, 1970), pp. 51-55. Case studies demonstrating increasing silt yields as a function of more intensive land use and deforestation are given for a number of tropical Asian countries in: United Nations, Economic Commission for Asia and the Far East, The Sediment Problem (Bangkok: United Nations, 1953), pp. 11-16. For Africa, H. C. Pereira reports on the matter in "Hydrological Effects of Changes in Land Use in Some East African Catchment Areas," East African Agricultural and Forestry Journal 27 (March 1962): 1-15. Robert Allen's study, "The Anchicaya Hydro- electric Project in Colombia: Design and Sedimentation Problems," which appeared in The Careless Technology: Ecology and International Development, ed. M. Taghi Farvar and J. P. Milton (Garden City, N.Y.: Natural History Press, 1972), pp. 318-48, describes the failure to recognize the very serious sediment and debris problems associated with deforestation of a watershed in tropical montane Colombia. J. J. Noll's classic study, The Silting of Caonillas Reservoir, Puerto Rico, Soil Conservation Service TP-119 (Washington: U.S. Department of Agriculture, 1953), provides ample reference to a Caribbean island example. The report by H. E. Hudson et al., "Effects of Land Use on Reservoir Siltation," American Water Works Association Journal 40 (October 1949): 913-31, gives noteworthy examples for the United States.  A Microcosm of Regional Development 3 slope denudation and soil formation, and unless modified according to conditions specific to each region, may so accelerate the wasting away of slopes that soil which would normally be washed or blown away in a century could disappear in a year or even a day. As elsewhere in the world, erosion and sedimentation in the tropics are essentially a result of the failure of human beings to harmonize their actions with the preva- lent ecological conditions. Accordingly, the amount and extent of erosion and its concomitant siltation are proportional to the density of the popu- lation. What seriously aggravates the problem in the tropics is the juxta- position of such combined environmental conditions as highly seasonal precipitation, large-scale mass wasting, and rapid chemical weathering with the region's rapid population growth rate and traditional cultural in- stitutions. Heavy silting--caused by extended cultivation, deforestation, and the destruction of natural vegetation by overgrazing-is already a problem in a great number of major reservoirs within the tropics and has impaired the economic value of entire river basin development projects. Many examples can be cited in which storage space once available for useful purposes is rapidly disappearing and, in many cases, no new storage space can be found to replace reservoirs that are swiftly silting upst In the tropics the resource management picture is quite clear: soil erosion and sediment control are vital developmental issues. For these reasons, a rational use of land resources is inextricably bound to the conservation and utilization of the entire resource heritage of the region, particularly its water resources. SOCIAL AND ECONOMIC GOALS The Dominican Republic is characteristic of emerging nations currently facing such environmental problems as it attempts to achieve accelerated socioeconomic development under the twin pressures of rapid population growth and rising expectations. Relatively rich in natural resources and labor but poor in capital, the country is attempting to utilize its resource base to bolster primary agricultural production and to develop ancillary food-processing industries rapidly.t These measures will assist in trans- forming the nation over the next two decades into a self-sufficient food producer and a major supplier of processed agricultural commodities to the United States and food-scarce Caribbean neighbors. 5. United Nations, The Sediment Problem, and F. E. Dendy, "Sedimentation in the Nation's Reservoirs," Journal of Soil and Water Conservation 23 (July-August 1968): 135-37. 6. Dominican Republic, Secretariado T6cnico de la Posidencia, Oficina Nacional de Planificacion (OxAPLAN), Primer plan nacional de desarrollo (Santo Domingo: Eco-Dom Offset, 1970), pp. 1-7. A Microcosm of Regional Development 3 slope denudation and soil formation, and unless modified according to conditions specific to each region, may so accelerate the wasting away of slopes that soil which would normally be washed or blown away in a century could disappear in a year or even a day. As elsewhere in the world, erosion and sedimentation in the tropics are essentially a result of the failure of human beings to harmonize their actions with the preva- lent ecological conditions. Accordingly, the amount and extent of erosion and its concomitant siltation are proportional to the density of the popu- lation. What seriously aggravates the problem in the tropics is the juxta- position of such combined environmental conditions as highly seasonal precipitation, large-scale mass wasting, and rapid chemical weathering with the region's rapid population growth rate and traditional cultural in- stitutions. Heavy silting-paused by extended cultivation, deforestation, and the destruction of natural vegetation by overgrazing-is already a problem in a great number of major reservoirs within the tropics and has impaired the economic value of entire river basin development projects. Many examples can be cited in which storage space once available for useful purposes is rapidly disappearing and, in many cases, no new storage space can be found to replace reservoirs that are swiftly silting up.5 In the tropics the resource management picture is quite clear: soil erosion and sediment control are vital developmental issues. For these reasons, a rational use of land resources is inextricably bound to the conservation and utilization of the entire resource heritage of the region, particularly its water resources. SOCIAL AND ECONOMIC GOALS The Dominican Republic is characteristic of emerging nations currently facing such environmental problems as it attempts to achieve accelerated socioeconomic development under the twin pressures of rapid population growth and rising expectations. Relatively rich in natural resources and labor but poor in capital, the country is attempting to utilize its resource base to bolster primary agricultural production and to develop ancillary food-processing industries rapidly.t These measures will assist in trans- forming the nation over the next two decades into a self-sufficient food producer and a major supplier of processed agricultural commodities to the United States and food-scarce Caribbean neighbors. 5. United Nations, The Sediment Problem, and F. E. Dendy, "Sedimentation in the Nation's Reservoirs," Journal of Soil and Water Conservation 23 (July-August 1968): 135-37. 6. Dominican Republic, Secretariado Ticnico de la Presidencia, Oficina Nacional de Planificacion (oNAPLAN), Primer plan nacional de desarrollo (Santo Domingo: Eco-Dom Offset, 1970), pp. 1-7. A Microcosm of Regional Development 3 slope denudation and soil formation, and unless modified according to conditions specific to each region, may so accelerate the wasting away of slopes that soil which would normally be washed or blown away in a century could disappear in a year or even a day. As elsewhere in the world, erosion and sedimentation in the tropics are essentially a result of the failure of human beings to harmonize their actions with the preva- lent ecological conditions. Accordingly, the amount and extent of erosion and its concomitant siltation are proportional to the density of the popu- lation. What seriously aggravates the problem in the tropics is the juxta- position of such combined environmental conditions as highly seasonal precipitation, large-scale mass wasting, and rapid chemical weathering with the region's rapid population growth rate and traditional cultural in- stitutions. Heavy silting-caused by extended cultivation, deforestation, and the destruction of natural vegetation by overgrazing-is already a problem in a great number of major reservoirs within the tropics and has impaired the economic value of entire river basin development projects. Many examples can be cited in which storage space once available for useful purposes is rapidly disappearing and, in many cases, no new storage space can be found to replace reservoirs that are swiftly silting up.5 In the tropics the resource management picture is quite clear: soil erosion and sediment control are vital developmental issues. For these reasons, a rational use of land resources is inextricably bound to the conservation and utilization of the entire resource heritage of the region, particularly its water resources. SOCIAL AND ECONOMIC GOALS The Dominican Republic is characteristic of emerging nations currently facing such environmental problems as it attempts to achieve accelerated socioeconomic development under the twin pressures of rapid population growth and rising expectations. Relatively rich in natural resources and labor but poor in capital, the country is attempting to utilize its resource base to bolster primary agricultural production and to develop ancillary food-processing industries rapidly.' These measures will assist in trans- forming the nation over the next two decades into a self-sufficient food producer and a major supplier of processed agricultural commodities to the United States and food-scarce Caribbean neighbors. 5. United Nations, The Sediment Problem, and F. E. Dendy, "Sedimentation in the Nation's Reservoirs," Journal of Soil and Water Conservation 23 (July-August 1968): 135-37. 6. Dominican Republic, Secretariado Tecnico de la Presidencia, Oficina Nacional de Planificacion (ONAPLAN), Primer plan nacional de desarrollo (Santo Domingo: Eco-Dom Offset, 1970), pp. 1-7.  4 Population and Energy The attainment of these ambitious goals will be a major undertaking. Presently, economic activities and incomes in the republic are largely determined by the export earnings of cane sugar and a few other unpro- cessed tropical commodities. Coupled with this traditional, export-oriented economy is the country's land tenure system, which remains one of its most serious problems: more than half of all farms are under one hectare in size, and peasant farmers in general lack resources to improve their operations.' The duality of the Dominican economy places additional burdens on the development process: on the one hand, there is a modern export sector with some light manufacturing and service industries sus- taining relatively high per capita income in two urban centers; on the other hand, there is a large rural subsistence sector of small landholdings marked by limited output and low income.s Yet, both the urban export and the rural subsistence sectors of the economy impose demands for financing infrastructure and support services to achieve the nation's long- term development goal. With 40 per cent of its people living in cities, a 6 per cent annual urban growth rate, and an average 11 per cent annual growth of manufacturing, it is clear that the Dominican Republic is changing from a predominantly rural to an urban society.a The demand for energy to extend basic public services and fuel industries in the cities is growing at an accelerating rate.1t [Linked to the urban centers through migration, the republic's agri- cultural heartland supplies food and raw materials, producing 24 per cent of the gross domestic product and employing 60 per cent of the labor 7. Inter-American Development Bank (IADB), Socio-Economic Progress in Latin America, Annual Report (Washington: IADn, 1971), pp. 185-86. 8. Orlando Haza, "Urban Growth in the Dominican Republic: A Descriptive Overview," in Public Policy and Urbanization in the Dominican Republic and Costa Rica, ed. Gustavo A. Antonini (Gainesville, Fla.: Center for Latin American Studies, 1973), pp. 23-54. 9. Ibid. 10. Lahmeyer International's study, Feasibility Bericht Mehrzweckprojekt Ta- vera (Frankfurt: Lahmeyer International GMBH, 1967) indicated that in 1966 the country's maximum load was 121.5 MW (megawatts). The thirty-seven power sta- tions existing at that time with a total installed capacity of 140 MW generated and fed 441.5 Gwh (gigawatt hours) to the country's power network. From this study, it is possible to deduce that, considering the unsatisfied demand of some 32 MW, the peak load would increase by 320 MW between 1967 and 1972, and by 454 MW from 1973 to 1975. The estimated needed Gwh power for 1975 is 1,900 Gwh. In order to cover this peak load and energy demand, the country has had the fore- sight to construct several power plants. But even after placing these facilities- Las Damas, Rio Haina, and Tavera-in operation, it still will not be possible to guarantee a solid reserve should there be a breakdown of one of the larger units. There is no doubt that the new, large, hydroelectric facilities-Tavera, Jagua-Bao, and Valdesia-will have to be used exclusively for peaking purposes, for only in this manner will the national power network function with the highest economic returns. 4 Population and Energy The attainment of these ambitious goals will be a major undertaking. Presently, economic activities and incomes in the republic are largely determined by the export earnings of cane sugar and a few other unpro- cessed tropical commodities. Coupled with this traditional, export-oriented economy is the country's land tenure system, which remains one of its most serious problems: more than half of all farms are under one hectare in size, and peasant farmers in general lack resources to improve their operations.? The duality of the Dominican economy places additional burdens on the development process: on the one hand, there is a modem export sector with some light manufacturing and service industries sus- taining relatively high per capita income in two urban centers; on the other hand, there is a large rural subsistence sector of small landholdings marked by limited output and low income.s Yet, both the urban export and 'the rural subsistence sectors of the economy impose demands for financing infrastructure and support services to achieve the nation's long- term development goal. With 40 per cent of its people living in cities, a 6 per cent annual urban growth rate, and an average 11 per cent annual growth of manufacturing, it is clear that the Dominican Republic is changing from a predominantly rural to an urban society.? The demand for energy to extend basic public services and fuel industries in the cities is growing at an accelerating rate.10 Linked to the urban centers through migration, the republic's agri- cultural heartland supplies food and raw materials, producing 24 per cent of the gross domestic product and employing 60 per cent of the labor 7. Inter-American Development Bank (sAr), Socio-Economic Progress in Latin America, Annual Report (Washington: tcaB, 1971), pp. 185-86. 8. Orlando Haza, "Urban Growth in the Dominican Republic: A Descriptive Overview," in Public Policy and Urbanization in the Dominican Republic and Costa Rica, ed. Gustavo A. Antonini (Gainesville, Fla.: Center for Latin American Studies, 1973), pp. 23-54. 9. Ibid. 10. Lahmeyer International's study, Feasibility Bericht Mehrzweckprojekt Ta- vera (Frankfurt: Lahmeyer International GMsH, 1967) indicated that in 1966 the country's maximum load was 121.5 MW (megawatts). The thirty-seven power sta- tions existing at that time with a total installed capacity of 140 MW generated and fed 441.5 Gwh (gigawatt hours) to the country's power network. From this study, it is possible to deduce that, considering the unsatisfied demand of some 32 MW, the peak load would increase by 320 MW between 1967 and 1972, and by 454 MW from 1973 to 1975. The estimated needed Gwh power for 1975 is 1,900 Gwh. In order to cover this peak load and energy demand, the country has had the fore- sight to construct several power plants. But even after placing these facilities- Las Damas, Rio Haina, and Tavera-in operation, it still will not be possible to guarantee a solid reserve should there be a breakdown of one of the larger units. There is no doubt that the new, large, hydroelectric facilities-Tavera, Jagua-Bao, and Valdesia-will have to be used exclusively for peaking purposes, for only in this manner will the national power network function with the highest economic returns. 4 Population and Energy The attainment of these ambitious goals will be a major undertaking. Presently, economic activities and incomes in the republic are largely determined by the export earnings of cane sugar and a few other unpro- cessed tropical commodities. Coupled with this traditional, export-oriented economy is the country's land tenure system, which remains one of its most serious problems: more than half of all farms are under one hectare in size, and peasant farmers in general lack resources to improve their operations.t The duality of the Dominican economy places additional burdens on the development process: on the one hand, there is a modem export sector with some light manufacturing and service industries sus- taining relatively high per capita income in two urban centers; on the other hand, there is a large rural subsistence sector of small landholdings marked by limited output and low income t Yet, both the urban export and 'the rural subsistence sectors of the economy impose demands for financing infrastructure and support services to achieve the nation's long- term development goal. With 40 per cent of its people living in cities, a 6 per cent annual urban growth rate, and an average 11 per cent annual growth of manufacturing, it is clear that the Dominican Republic is changing from a predominantly rural to an urban society.t The demand for energy to extend basic public services and fuel industries in the cities is growing at an accelerating rate.10 [Linked to the urban centers through migration, the republic's agri- cultural heartland supplies food and raw materials, producing 24 per cent of the gross domestic product and employing 60 per cent of the labor 7. Inter-American Development Bank (iADB), SociO-Economic Progress in Latin America, Annual Report (Washington: IAtB, 1971), pp. 185-86. 8. Orlando Haza, "Urban Growth in the Dominican Republic: A Descriptive Overview," in Public Policy and Urbanization in the Dominican Republic and Costa Rica, ed. Gustavo A. Antonini (Gainesville, Fla.: Center for Latin American Studies, 1973), pp. 23-54. 9. Ibid. 10. Lahmeyer International's study, Feasibility Bericht Mehrzweckprojekt Ta- vera (Frankfurt: Lahmeyer International GMBH, 1967) indicated that in 1966 the country's maximum load was 121.5 MW (megawatts). The thirty-seven power sta- tions existing at that time with a total installed capacity of 140 MW generated and fed 441.5 Gwh (gigawatt hours) to the country's power network. From this study, it is possible to deduce that, considering the unsatisfied demand of some 32 MW, the peak load would increase by 320 MW between 1967 and 1972, and by 454 MW from 1973 to 1975. The estimated needed Gwh power for 1975 is 1,900 Gwh. In order to cover this peak load and energy demand, the country has had the fore- sight to construct several power plants. But even after placing these faciities-- Las Damas, Rio Haina, and Tavera-in operation, it still will not be possible to guarantee a solid reserve should there be a breakdown of one of the larger units. There is no doubt that the new, large, hydroelectric facilities-Tavera, Jagua-Bao, and Valdesia-will have to be used exclusively for peaking purposes, for only in this manner will the national power network function with the highest economic returns.  A Microcosm of Regional Development 5 force." Because of the traditional structure of the agricultural sector, rural development requires not only basic energy inputs but, in addition, dramatic across-the-board changes to incorporate the isolated peasants into the national economic stream. Improved technology, credit for small farmers, agrarian reform, marketing facilities, farm-to-market roads, and community development and extension are a few of the many needs that challenge the national leadership.?c All in all, the requirements for devel- opment in this small tropical nation are many and varied.] 'The attainment of national development goals, particularly that of be- coming self-sufficient in food production, will mean the achievement of a more equitable income distribution through an accelerated expansion of the farm sector. Major paths to such attainment appear to be the utiliza- tion of the country's hydraulic resources and the diversification of its agricultural base.'3 Specific plans include a series of integrated multipur- pose river basin development programs scheduled for completion under the government's National Development Plan for the 1971-74 period. Through such measures, the republic will be able to eliminate its over- dependence on a few raw agricultural products, to reduce the flow of rural migrants to the cities by offering increased employment opportuni- ties in the countryside, and to assist the majority of Dominicans in meeting the goals of improved social benefits and a higher standard of living in the twenty-first century. PROJECTED DEvELOPMENT OF POWER FACILITIEs River basin development in the Dominican Republic is closely tied to realization of the country's hydroelectric potential. For the southeastern part of the country, the government signed in 1970 a formal agreement with Gulf & Western to build hydroelectric facilities on the Duey, Sanate, and Chavon rivers. This project will cost an estimated $RD 25 million." A total of 3,240 hectares will be irrigated with an estimated annual $RD 1.6 million return on the initial investment. For the southern provinces, the planners have focused on construction of an integrated hydroelectric network along the Nizao River. The system will consist of four dams, at Valdesia (Phase 1 to be completed in 1974), Jiguey, Aguacate, and Rancho Arriba, with a total regulating capacity of 11. IADB, Socio-Economic Progress in Latin America, p. 192. 12. Dominican Republic, ONAPLAN, Proyecto integrado de desarrollo agropecuario, 13 vols. (Santo Domingo: ONAPLAN, 1971), 1:1-14. 13. Public address by President Joaquin Balaguer, inaugurating the completion of the first stage of the Tavera hydroelectric project, February 27, 1973, published in Economia Dominicana Asiste 103 (March 2, 1973). 14. The Dominican peso ($RD) is equivalent to the U.S. dollar. A Microcosm of Regional Development 5 force." Because of the traditional structure of the agricultural sector, rural development requires not only basic energy inputs but, in addition, dramatic across-the-board changes to incorporate the isolated peasants into the national economic stream. Improved technology, credit for small farmers, agrarian reform, marketing facilities, farm-to-market roads, and community development and extension are a few of the many needs that challenge the national leadership.5 All in all, the requirements for devel- opment in this small tropical nation are many and varied.] The attainment of national development goals, particularly that of be- coming self-sufflicient in food production, will mean the achievement of a more equitable income distribution through an accelerated expansion of the farm sector. Major paths to such attainment appear to be the utiliza- tion of the country's hydraulic resources and the diversification of its agricultural base."I Specific plans include a series of integrated multipur- pose river basin development programs scheduled for completion under the government's National Development Plan for the 1971-74 period. Through such measures, the republic will be able to eliminate its over- dependence on a few raw agricultural products, to reduce the flow of rural migrants to the cities by offering increased employment opportuni- ties in the countryside, and to assist the majority of Dominicans in meeting the goals of improved social benefits and a higher standard of living in the twenty-first century. PROJECTED DEVELOPMENT OF POWER FACILITIES River basin development in the Dominican Republic is closely tied to realization of the country's hydroelectric potential. For the southeastern part of the country, the government signed in 1970 a formal agreement with Gulf & Western to build hydroelectric facilities on the Duey, Sanate, and Chavon rivers. This project will cost an estimated $RD 25 million. A total of 3,240 hectares will be irrigated with an estimated annual $RD 1.6 million return on the initial investment. For the southern provinces, the planners have focused on construction of an integrated hydroelectric network along the Nizao River. The system will consist of four dams, at Valdesia (Phase 1 to be completed in 1974), Jiguey, Aguacate, and Rancho Arriba, with a total regulating capacity of 11. IADs, Socio-Economic Progress in Latin America, p. 192. 12. Dominican Republic, oNAPLAN, Proyecto integrado de desarrollo agropecuario, 13 vols. (Santo Domingo: ONAPLAN, 1971), 1:1-14. 13. Public address by President Joaquin Balaguer, inaugurating the completion of the first stage of the Tavera hydroelectric project, February 27, 1973, published in Economia Dominicana Asiste 103 (March 2, 1973). 14. The Dominican peso ($RD) is equivalent to the U.S. dollar. A Microcosm of Regional Development 5 force." Because of the traditional structure of the agricultural sector, rural development requires not only basic energy inputs but, in addition, dramatic across-the-board changes to incorporate the isolated peasants into the national economic stream. Improved technology, credit for small farmers, agrarian reform, marketing facilities, farm-to-market roads, and community development and extension are a few of the many needs that challenge the national leadership." All in all, the requirements for devel- opment in this small tropical nation are many and varied.] LThe attainment of national development goals, particularly that of be- coming self-sufficient in food production, will mean the achievement of a more equitable income distribution through an accelerated expansion of the farm sector. Major paths to such attainment appear to be the utiliza- tion of the country's hydraulic resources and the diversification of its agricultural base3 Specific plans include a series of integrated multipur- pose river basin development programs scheduled for completion under the government's National Development Plan for the 1971-74 period. Through such measures, the republic will be able to eliminate its over- dependence on a few raw agricultural products, to reduce the flow of rural migrants to the cities by offering increased employment opportuni- ties in the countryside, and to assist the majority of Dominicans in meeting the goals of improved social benefits and a higher standard of living in the twenty-first century. PROJECTED DEVELOPMENT OF POWER FACILITIES River basin development in the Dominican Republic is closely tied to realization of the country's hydroelectric potential. For the southeastern part of the country, the government signed in 1970 a formal agreement with Gulf & Western to build hydroelectric facilities on the Duey, Sanate, and Chavon rivers. This project will cost an estimated $RD 25 million.5 A total of 3,240 hectares will be irrigated with an estimated annual $RD 1.6 million return on the initial investment. For the southern provinces, the planners have focused on construction of an integrated hydroelectric network along the Nizao River. The system will consist of four dams, at Valdesia (Phase 1 to be completed in 1974), Jiguey, Aguacate, and Rancho Arriba, with a total regulating capacity of 11. ine, Socio-Ecoonmic Progress in Latin America, p. 192. 12. Dominican Republic, ONAPLAN, Proyecto integrado de desarrollo agropecuario, 13 vo1s. (Santo Domingo: ONAPLAN, 1971), 1:1-14. 13. Public address by President Joaquin Balaguer, inaugurating the completion of the first stage of the Tavera hydroelectric project, February 27, 1973, published in Economia Dominicana Asiste 103 (March 2, 1973). 14. The Dominican peso ($RD) is equivalent to the U.S. dollar.  6 Population and Energy 25 million cubic meters of water. The first phase of the $RD 25 million Valdesia project will irrigate 32,400 hectares of fertile but arid lands, holding back some 5 million cubic meters of water to generate 110 million kilowatt hours of electricity per year during peak hours. Later, the three additional dams are to be constructed and are expected to produce an added 200,000 kilowatts.15 Valdesia will provide a means for transform- ing traditional subsistence farming along the south coast into irrigated commercial agriculture. It will supply needed extra power for Santo Do- mingo's expanding urban industrial base and will provide a new supply of water for this rapidly growing capital city. Along the western frontier and in the southwest provinces, work is under way on two multipurpose hydropower facilities, the first on the San Juan River at Sabaneta and the second along the Yaque del Sur River at Sabana Yegua. In both cases, the major objective is to regulate the flow of water, stabilize irrigation in Azua Province, and provide a local source of energy. Approximately 25,000 hectares of new lands will be irrigated, mainly for growing food crops for local consumption in the Neiba-Barahona Valley.1t Of all the hydroelectric projects, the one of greatest significance to the country's economic development consists of a series of hydroelectric power and water storage installations within the northwesternmost Yaque del Norte River basin. Begun in 1969, the Tavera project consists of an inte- grated network of multiple stage units to be completed over a decade, with installations at Tavera and Lopez on the Yaque del Norte River and near Sabana Iglesia on the Jagua River (see Figure 1). The complex, when completed, will have a total installed power capacity of 131,000 kilowatts and will sustain the irrigation requirements of a 27,500-hectare tract downstream in the semiarid but potentially fertile northwest region. Valued at $RD 112.3 million, Tavera represents a substantial investment and is considered the cornerstone of future national economic growth. The first phase of construction was inaugurated in February 1973 and includes a storage dam at Tavera which impounds 145 million cubic 15. "Valdesia: Great Hydroelectric Project to Provide Power for Industry, Water for Farming," New York Times Magazine Supplement, January 28. 1973, p. 5, and "Valdesia: Will-Power Becomes Water Power," New York Times Maga- zine Supplement, October 3, 1971, pp. 18, 27. 16. Balaguer address. 17. Lahmeyer International GMH, Proyecto multiple Rio Jagua/Rio Bao: estudio de pre-inversidn (Frankfurt: Lahmeyer International GMBH, 1967), p. 27; Balaguer address; "Primera turbina de presa comienza a funcionar," Economia Dominicna Asiste 93 (December 22, 1972): 3; "Llega equipo de unidad de presa de Tavera." Economia Dominican Asiste 96 (January 12, 1973): 3; and "BU prestara a RD $62 millones," Economia Dominicana Asiste 98 (January 26, 1973): 8. 6 Population and Energy 25 million cubic meters of water. The first phase of the $RD 25 million Valdesia project will irrigate 32,400 hectares of fertile but arid lands, holding back some 5 million cubic meters of water to generate 110 million kilowatt hours of electricity per year during peak hours. Later, the three additional dams are to be constructed and are expected to produce an added 200,000 kilowatts.'t Valdesia will provide a means for transform- ing traditional subsistence farming along the south coast into irrigated commercial agriculture. It will supply needed extra power for Santo Do- mingo's expanding urban industrial base and will provide a new supply of water for this rapidly growing capital city. Along the western frontier and in the southwest provinces, work is under way on two multipurpose hydropower facilities, the first on the San Juan River at Sabaneta and the second along the Yaque del Sur River at Sabana Yegua. In both cases, the major objective is to regulate the flow of water, stabilize irrigation in Azua Province, and provide a local source of energy. Approximately 25,000 hectares of new lands will be irrigated, mainly for growing food crops for local consumption in the Neiba-Barahona Valley.st Of all the hydroelectric projects, the one of greatest significance to the country's economic development consists of a series of hydroelectric power and water storage installations within the northwesternmost Yaque del Norte River basin. Begun in 1969, the Tavera project consists of an inte- grated network of multiple stage units to be completed over a decade, with installations at Tavera and Lopez on the Yaque del Norte River and near Sabana Iglesia on the Jagua River (see Figure 1). The complex, when completed, will have a total installed power capacity of 131,000 kilowatts and will sustain the irrigation requirements of a 27,500-hectare tract downstream in the semiarid but potentially fertile northwest region. Valued at $RD 112.3 million, Tavera represents a substantial investment and is considered the cornerstone of future national economic growth.r The first phase of construction was inaugurated in February 1973 and includes a storage dam at Tavera which impounds 145 million cubic 15. "Valdesia: Great Hydroelectric Project to Provide Power for Industry, Water for Farming," New York Times Magazine Supplement, January 28, 1973, p. 5, and "Valdesia: Will-Power Becomes Water Power," New York Times Maga- zine Supplement, October 3, 1971, pp. 18, 27. 16. Balaguer address. 17. Lahmeyer International GMBH, Proyecto multiple Rio Jagua/Rio fao: estudio de pre-inversidn (Frankfurt: Lahmeyer International GMBH, 1967), p. 27; Balaguer address; "Primera turbina de presa comienza a funcionar," Economia Dominicana Asiste 93 (December 22, 1972): 3; "Llega equipo de unidad de presa de Tavera." Economia Dominican Asiste 96 (January 12, 1973): 3; and "no prestari a RD $62 millones," Economia Dominican Asiste 98 (January 26, 1973): 8. 6 Population and Energy 25 million cubic meters of water. The first phase of the $RD 25 million Valdesia project will irrigate 32,400 hectares of fertile but arid lands, holding back some 5 million cubic meters of water to generate 110 million kilowatt hours of electricity per year during peak hours. Later, the three additional dams are to be constructed and are expected to produce an added 200,000 kilowatts.5 Valdesia will provide a means for transform- ing traditional subsistence farming along the south coast into irrigated commercial agriculture. It will supply needed extra power for Santo Do- mingo's expanding urban industrial base and will provide a new supply of water for this rapidly growing capital city. Along the western frontier and in the southwest provinces, work is under way on two multipurpose hydropower facilities, the first on the San Juan River at Sabaneta and the second along the Yaque del Sur River at Sabana Yegua. In both cases, the major objective is to regulate the flow of water, stabilize irrigation in Azua Province, and provide a local source of energy. Approximately 25,000 hectares of new lands will be irrigated, mainly for growing food crops for local consumption in the Neiba-Barahona Valley." Of all the hydroelectric projects, the one of greatest significance to the country's economic development consists of a series of hydroelectric power and water storage installations within the northwesternmost Yaque del Norte River basin. Begun in 1969, the Tavera project consists of an inte- grated network of multiple stage units to be completed over a decade, with installations at Tavera and Lopez on the Yaque del Norte River and near Sabana Iglesia on the Jagua River (see Figure 1). The complex, when completed, will have a total installed power capacity of 131,000 kilowatts and will sustain the irrigation requirements of a 27,500-hectare tract downstream in the semiarid but potentially fertile northwest region. Valued at $RD 112.3 million, Tavera represents a substantial investment and is considered the cornerstone of future national economic growth.?1 The first phase of construction was inaugurated in February 1973 and includes a storage dam at Tavera which impounds 145 million cubic 15. "Valdesia: Great Hydroelectric Project to Provide Power for Industry. Water for Farming," New York Times Magazine Supplement, January 28. 1973, p. 5, and "Valdesia: Will-Power Becomes Water Power," New York Times Maga- zine Supplement, October 3, 1971, pp. 18, 27. 16. Balaguer address. 17. Lahmeyer International GMBH, Proyecto multiple Rio Jagua/Rio Bao: estudio de pre-inversidn (Frankfurt: Lahmeyer International oMBH, 1967), p. 27; Balaguer address; "Primera turbina de presa comienza a funcionar," Economia Dominicana Asiste 93 (December 22, 1972): 3; "Llega equipo de unidad de presa de Tavera," Economifa Dominican Asiste 96 (January 12, 1973): 3; and "Bm prestara a RD $62 millones," Economa Dominicana Asiste 98 (January 26, 1973): 8.  A Microcosm of Regional Development 7 A Microcosm of Regional Development 7 A Microcosm of Regional Development 7 20 -- 20" meters of dsal irrigto waeapesr Ounl CEctngteTvr DOMlINIC AN REPUBL IC SiceT IGU'pwr mos Mahowingt atisfya study eregn tdsdin metrs leube irrigation psewather downsureamnne conerting ama mute uplt dsysteramwith the powerhouse td old the BoutRiw verer aincelTveoar per Thist rbuaigmwle usduoiatsf lpa atnergy lo cteduig downstream from the juncture of the Boo and Jagua rivers? 5 18. Lahrmeyer International ossuH, Proyrecto wditiple de Tavera (Fraurt:r Lahmeyer International GMBHn, 19671, p. 9; Economfa Domnicanoa 93 and 98; and interview with Lois del Rosario Cehallos, chief engineer, Tavera project, Corpo- racion Dominicans dc Elctricidad, Jne 1971. FIGURE 1. Map showing Jagua-Bao study region. meters of usable irrigation water, a pressure tunnel connecting the Tavera water supply system with the powerhouse located on the Bao River near Sabana Iglesia, and the powerhouse itself, where two turbines have been installed with a present operational capacity of 80,000 kilowatts (Plate I). Since Tavera's power must be used to satisfy peak energy loads during the evening hours, and since water must be utilized during the daylight hours for irrigation purposes farther downstream, a reregulating dam must be built downstream from the powerhouse to hold the outflow over a twelve-hour period. This reregulating dam will be built at Lopez, located downstream from the juncture of the Bao and Jagua rivers.? 18. Lahmeyer International GMBH, Proyecto maltiple de Tavera (Frankfurt: Lahmeyer International sMBH, 1967), p. 9; Economia Donisicana 93 and 98; and interview with Luis del Rosario Ceballos, chief engineer, Tavera project, Corpo- raci6n Dominicana de Electricidad, June 1971. FIGUrE 1. Map showing Jagua-Bao study region. meters of usable irrigation water, a pressure tunnel connecting the Tavera water supply system with the powerhouse located on the Bao River near Sabana Iglesia, and the powerhouse itself, where two turbines have been installed with a present operational capacity of 80,000 kilowatts (Plate I). Since Tavera's power must be used to satisfy peak energy loads during the evening hours, and since water must be utilized during the daylight hours for irrigation purposes farther downstream, a reregulating dam must be built downstream from the powerhouse to hold the outflow over a twelve-hour period. This reregulating dam will be built at Lopez, located downstream from the juncture of the Bao and Jagua rivers.5 18. Lahmeyer International GMBH, Proyecto mdltiple de Tavera (Frankfurt: Lahmeyer International GMBH, 1967), p. 9; Economia Dominicans 93 and 98; and interview with Luis del Rosario Ceballos, chief engineer, Tavera project, Corpo- raci6n Dominicana de Electricidad, June 1971.  8 Population and Energy In late February 1973 the Inter-American Development Bank an- nounced a new loan to the Dominican Republic totaling $RD 39 million and cosponsored by the International Development Association of the World Bank. This loan will finance the construction of irrigation works covering 27,500 hectares and using discharge provided by the Tavera dam's regulated flow from the Yaque River catchment basin. Under the terms of the loan, 14,000 hectares of presently irrigated lands will be rehabilitated and improved, and an additional 13,500 hectares of new lands will be added. Seventy-five per cent of the irrigable lands will come under the jurisdiction of the Agrarian Reform Institute for redistribution to approximately 2,000 landless peasant farmers. It is estimated that 50,000 peasants can be resettled within the Tavera irrigated zone.'t With the funding of the downstream irrigation works came the an- nouncement that the Inter-American Development Bank would loan $RD 20 million of the $RD 28.1 million estimated overall cost for construction of the second-stage Jagua-Bao dam. To be completed by 1975, this dam will impound 119 million cubic meters of usable irrigation water. A unique feature of the reservoir will be the impounding of water from both the Jagua and Bao rivers, which is possible due to the construction of a diver- sion tunnel connecting both rivers upstream from their confluence. Dis- charge from the dam will be capable of irrigating an additional 19,000 hectares downstream from Santiago. It will increase power capacity by 51,000 kilowatts at the Tavera powerhouse and, together with Tavera's discharge, will utilize the reregulating reservoir facilities at Lopez on the Yaque del Norte Rivera5 The list of power and water facilities projected for development in the Dominican Republic is impressive; it demonstrates a decidedly heavy commitment to the continued use of renewable resources. Over the long run, realization of these projects-and in particular the Tavera project- will accomplish several purposes: facilitation of major foreign exchange savings by replacing foreign-fuel-dependent thermoelectric production with increasing amounts of locally produced hydropower; intensification of agricultural production through extensions of irrigation and the introduc- tion of improved farm technology; and implementation of social change 19. Public address by Henry Costanzo, vice-president, Inter-American Develop- ment Bank, at the inauguration ceremony of the Tavera project, February 27, 1973, published in Economia Dominicana Asiste 103 (March 2, 1973); "Prestara 13 millones a R.D. para plan agricola," Economia Dominicana Asiste 98 (January 26, 1973): 8; "Grupo del banco mundial ayuda a Guyana y R.D.," Economia Dominicana Asiste 100 (February 9, 1973): 8; "600 mil tareas para Ia reforma agraria," Economia Dominicana Asiste 103 (March 2, 1973): 3; "uxD Asentari agricultores en zona Tavera," Economia Dominicana Asiste 104 (March 9, 1973). 20. "BID prestari $62 millones," Economia Dominicana Asiste, p. 8, and Lah- meyer International GMBn, Proyecto mdltiple Rio Jagua/Rio Bao, pp. 1, 71, 73. 8 Population and Energy In late February 1973 the Inter-American Development Bank an- nounced a new loan to the Dominican Republic totaling $RD 39 million and cosponsored by the International Development Association of the World Bank. This loan will finance the construction of irrigation works covering 27,500 hectares and using discharge provided by the Tavera dam's regulated flow from the Yaque River catchment basin. Under the terms of the loan, 14,000 hectares of presently irrigated lands will be rehabilitated and improved, and an additional 13,500 hectares of new lands will be added. Seventy-five per cent of the irrigable lands will come under the jurisdiction of the Agrarian Reform Institute for redistribution to approximately 2,000 landless peasant farmers. It is estimated that 50,000 peasants can be resettled within the Tavera irrigated zone.'0 With the funding of the downstream irrigation works came the an- nouncement that the Inter-American Development Bank would loan $RD 20 million of the $RD 28.1 million estimated overall cost for construction of the second-stage Jagua-Bao dam. To be completed by 1975, this dam will impound 119 million cubic meters of usable irrigation water. A unique feature of the reservoir will be the impounding of water from both the Jagua and Bao rivers, which is possible due to the construction of a diver- sion tunnel connecting both rivers upstream from their confluence. Dis- charge from the dam will be capable of irrigating an additional 19,000 hectares downstream from Santiago. It will increase power capacity by 51,000 kilowatts at the Tavera powerhouse and, together with Tavera's discharge, will utilize the reregulating reservoir facilities at Lopez on the Yaque del Norte Riverac The list of power and water facilities projected for development in the Dominican Republic is impressive; it demonstrates a decidedly heavy commitment to the continued use of renewable resources. Over the long run, realization of these projects-and in particular the Tavera project- will accomplish several purposes: facilitation of major foreign exchange savings by replacing foreign-fuel-dependent thermoelectric production with increasing amounts of locally produced hydropower; intensification of agricultural production through extensions of irrigation and the introduc- tion of improved farm technology; and implementation of social change 19. Public address by Henry Costanzo, vice-president, Inter-American Develop- ment Bank, at the inauguration ceremony of the Tavera project, February 27. 1973, published in Economia Dominicana Asiste 103 (March 2, 1973); "Prestari 13 millones a R.D. para plan agricola," Economia Dominicana Asiste 98 (January 26, 1973): 8; "Grupo del banco mundial ayuda a Guyana y RD.," Economia Dominicana Asiste 100 (February 9, 1973): 8; '600 mil tareas para la reforma agraria," Economia Dominicana Asiste 103 (March 2, 1973): 3; "u Asentari agricultores en zona Tavera," Economia Dominicana Asiste 104 (March 9. 1973). 20. "BID prestari $62 millones," Economia Dominicana Asiste, p. 8, and lah- meyer International GMBH, Proyecto multiple Rio Jagua/Rio Bao, pp. 1, 71, 73. 8 Population and Energy In late February 1973 the Inter-American Development Bank an- nounced a new loan to the Dominican Republic totaling $RD 39 million and cosponsored by the International Development Association of the World Bank. This loan will finance the construction of irrigation works covering 27,500 hectares and using discharge provided by the Tavera dam's regulated flow from the Yaque River catchment basin. Under the terms of the loan, 14,000 hectares of presently irrigated lands will be rehabilitated and improved, and an additional 13,500 hectares of new lands will be added. Seventy-five per cent of the irrigable lands will come under the jurisdiction of the Agrarian Reform Institute for redistribution to approximately 2,000 landless peasant farmers. It is estimated that 50,000 peasants can be resettled within the Tavera irrigated zone.? With the funding of the downstream irrigation works came the an- nouncement that the Inter-American Development Bank would loan $RD 20 million of the $RD 28.1 million estimated overall cost for construction of the second-stage Jagua-Bao dam. To be completed by 1975, this dam will impound 119 million cubic meters of usable irrigation water. A unique feature of the reservoir will be the impounding of water from both the Jagua and Bao rivers, which is possible due to the construction of a diver- sion tunnel connecting both rivers upstream from their confluence. Dis- charge from the dam will be capable of irrigating an additional 19,000 hectares downstream from Santiago. It will increase power capacity by 51,000 kilowatts at the Tavera powerhouse and, together with Tavera's discharge, will utilize the reregulating reservoir facilities at Lopez on the Yaque del Norte River.0 The list of power and water facilities projected for development in the Dominican Republic is impressive; it demonstrates a decidedly heavy commitment to the continued use of renewable resources. Over the long run, realization of these projects-and in particular the Tavera project- will accomplish several purposes: facilitation of major foreign exchange savings by replacing foreign-fuel-dependent thermoelectric production with increasing amounts of locally produced hydropower; intensification of agricultural production through extensions of irrigation and the introduc- tion of improved farm technology; and implementation of social change 19. Public address by Henry Costanzo, vice-president, Inter-American Develop- ment Bank, at the inauguration ceremony of the Tavera project, February 27, 1973, published in Economia Dominicana Asiste 103 (March 2, 1973); "Prestari 13 millones a R.D. para plan agricola," Economia Dominicana Asiste 98 (January 26, 1973): 8; "Grupo del banco mundial ayuda a Guyana y RD.," Economia Dominicana Asiste 100 (February 9, 1973): 8; "600 mil tareas para la reforma agraria," Economia Dominicana Asiste 103 (March 2, 1973): 3; "roe Asentari agricultores en zona Tavera," Economia Dominicana Asiste 104 (March 9, 1973). 20. "BID prestari $62 millones," Economia Dominicana Asiste, p. 8, and Lah- meyer International GMBH, Proyecto mdltiple Rio Jagua/Rio Bao, pp. 1, 71, 73.  A Microcosm of Regional Development 9 and economic development of the Dominican peasantry through large- scale resettlement and agrarian reform programs 21 The sizable fiscal expenditures and the planning commitment to river basin development within the republic demand that a rational, long-term use of each region's physical resources be assured. To preserve such re- sources from unwise exploitation, a thorough understanding must be developed of the wide-ranging effect of human activities on the landscape and, in particular, their probable impact through changing land use on downstream dams and reservoirs. Destructive effects on the land already are apparent in all of the project regions; soil erosion and siltation are very real problems.22 Such problems are of particular concern within the Yaque del Norte River basin, where increased sedimentation due to poor land-management practices impinges upon the very viability of the criti- cally important Tavera project. OBJECTIVES AND THE STUDY REGION A 150-square-kilometer area of low-yield, seasonally cultivated land was selected in 1967 by an OAS survey team as a possible pilot reforestation site. This area was experiencing severe erosion and siltation which, in turn, was directly affecting the viability of a proposed site for the second- stage Jagua-Bao dam (Figure 1). This situation exemplifies the growing realization that sedimentation rates within a given watershed vary as a function of changing land use over time, and that land-use change there- fore affects substantially the regime of the river and the movement of sediments. Such change has a direct influence on the effectiveness of dams, reservoirs, and irrigation canals. In order to explore the ecological implications of such change, 257 square kilometers of land was added to the core area; the additional land was selected on the basis of field reconnaissance, to obtain a more repre- sentative cross-section of the region. This area included contiguous pas- ture, coffee, and forest lands.n For the resulting 407 square kilometers, 21. Dominican Republic, Secretariado T6cnico de la Presidencia, ONAPLAN, Plataforma para el desarrollo econ6mico y social de to Republica Dominican (1968-1985) (Santo Domingo: oNAPLAN, 1968), pp. 285-88. 22. The need for watershed management in the project catchment basins is underlined in Dominican Republic, Primer plan nacional de desarrollo, pp. 25-26. President Balaguer, in his address inaugurating the opening of Tavera, called for a scientifically based plan upon which conservation legislation can be built to pre- serve the forest reserves (see note 13). 23. The study region includes the rural sections of Los Cagueyes, Jagua Abajo, Pinalito, La Guama, Juncalito Abajo, Janey, and Franco Bid6 in Janico Municipality and the Las Placetas section in San Jos6 de las Matas Municipality. For a description of the proposed reforestation program, see Organization of American States, Recono- cimiento y evaluacidn de los recursos naturales de la Repdblica Dominican, 3 vols. (Washington: Pan American Union, Department of Economic Affairs, 1967), 1: 307-12. A Microcosm of Regional Development 9 and economic development of the Dominican peasantry through large- scale resettlement and agrarian reform programs.2 The sizable fiscal expenditures and the planning commitment to river basin development within the republic demand that a rational, long-term use of each region's physical resources be assured. To preserve such re- sources from unwise exploitation, a thorough understanding must be developed of the wide-ranging effect of human activities on the landscape and, in particular, their probable impact through changing land use on downstream dams and reservoirs. Destructive effects on the land already are apparent in all of the project regions; soil erosion and siltation are very real problems.22 Such problems are of particular concern within the Yaque del Norte River basin, where increased sedimentation due to poor land-management practices impinges upon the very viability of the criti- cally important Tavera project. OBJECTIvEs AND THE STUDY REGION A 150-square-kilometer area of low-yield, seasonally cultivated land was selected in 1967 by an oAs survey team as a possible pilot reforestation site. This area was experiencing severe erosion and siltation which, in turn, was directly affecting the viability of a proposed site for the second- stage Jagua-Bao dam (Figure 1). This situation exemplifies the growing realization that sedimentation rates within a given watershed vary as a function of changing land use over time, and that land-use change there- fore affects substantially the regime of the river and the movement of sediments. Such change has a direct influence on the effectiveness of dams, reservoirs, and irrigation canals. In order to explore the ecological implications of such change, 257 square kilometers of land was added to the core area; the additional land was selected on the basis of field reconnaissance, to obtain a more repre- sentative cross-section of the region. This area included contiguous pas- ture, coffee, and forest lands."0 For the resulting 407 square kilometers, 21. Dominican Republic, Secretariado Ticnico de la Presidencia, ONAPLAN, Plataforma para el desarrollo econ6mico y social de la Repablica Dominicana (1968-1985) (Santo Domingo: ONAPLAN, 1968), pp. 285-88. 22. The need for watershed management in the project catchment basins is underlined in Dominican Republic, Primer plan nacional de desarrollo, pp. 25-26. President Balaguer, in his address inaugurating the opening of Tavern, called for a scientifically based plan upon which conservation legislation can be built to pre- serve the forest reserves (see note 13). 23. The study region includes the rural sections of Los Cagueyes, Jagua Abajo, Pinalito, La Guama, Juncalito Abajo, Janey, and Franco Bidd in Janico Municipality and the Las Placetas section in San Jose de las Matas Municipality. For a description of the proposed eforeestation program, are Organization of American States, Recono- cimiento y evaluacdn de los recursos naturales de la Repdblica Dominican, 3 vols. (Washington: Pan American Union, Department of Economic Affairs, 1967), 1: 307-12. A Microcosm of Regional Development 9 and economic development of the Dominican peasantry through large- scale resettlement and agrarian reform programs.21 The sizable fiscal expenditures and the planning commitment to river basin development within the republic demand that a rational, long-term use of each region's physical resources be assured. To preserve such re- sources from unwise exploitation, a thorough understanding must be developed of the wide-ranging effect of human activities on the landscape and, in particular, their probable impact through changing land use on downstream dams and reservoirs. Destructive effects on the land already are apparent in all of the project regions; soil erosion and siltation are very real problems.22 Such problems are of particular concern within the Yaque del Norte River basin, where increased sedimentation due to poor land-management practices impinges upon the very viability of the criti- cally important Tavera project. OBJECTIVES AND THE STUDY REGION A 150-square-kilometer area of low-yield, seasonally cultivated land was selected in 1967 by an OAs survey team as a possible pilot reforestation site. This area was experiencing severe erosion and siltation which, in turn, was directly affecting the viability of a proposed site for the second- stage Jagua-Bao dam (Figure 1). This situation exemplifies the growing realization that sedimentation rates within a given watershed vary as a function of changing land use over time, and that land-use change there- fore affects substantially the regime of the river and the movement of sediments. Such change has a direct influence on the effectiveness of dams, reservoirs, and irrigation canals. In order to explore the ecological implications of such change, 257 square kilometers of land was added to the core area; the additional land was selected on the basis of field reconnaissance, to obtain a more repre- sentative cross-section of the region. This area included contiguous pas- ture, coffee, and forest landst3 For the resulting 407 square kilometers, 21. Dominican Republic, Secretariado Tecnico de la Presidencia, ONAPLAN, Plataforma para el desarrollo econ6mico y social de la Repdblica Dominicana (1968-1985) (Santo Domingo: ONAPLAN, 1968), pp. 285-88. 22. The need for watershed management in the project catchment basins is underlined in Dominican Republic, Primer plan naional de desarrollo, pp. 25-26. President Balaguer, in his address inaugurating the opening of Taver, called for a scientifically based plan upon which conservation legislation can be built to pre- serve the forest reserves (see note 13). 23. The study region includes the rural sections of Los Cagueyes, Jagua Abajo, Pinalito, La Gunmo, Juncalito Abajo, Janey, and Franco Bid6 in Janico Municipality and the Las Placetas section in San Jos6 de Ias Matas Municipality. For a description of the proposed reforestation program, see Organization of American States, Recono- cimiento y evaluacidn de los recursos naturales de la Repdblica Dominican, 3 vols. (Washington: Pan American Union, Department of Economic Affairs, 1967), 1: 307-12.  10 Population and Energy the pattern of changing land use since 1948 was examined and predictive techniques, including the simulation of models, were developed and applied. In the study region, population has increased by 20 per cent since 1950 and much of the area formerly in pine forest has been subjected to slash- and-bum farming and extensive grazing.m These practices, juxtaposed with the cessation of lumbering operations since 1967, have been respon- sible for the emigration of some 4,000 laborers, principally to New York City. In this populated upland, the links between people and nature are so direct that the continued practice of marginal farming and illegal logging will cause increased erosion of the soil and depletion of the region's resource base. Increased demand for downstream irrigation water requires that both sedimentation and erosion be controlled. Conflicting conditions thus exist: the more intense the land use upstream, the greater the hazard from erosion and siltation. For the Jagua-Bao region, the study reported here provides a basis on which alternative policies can be developed for increasing returns on hydropower investments. There are much broader implications, however. While models presented here have been designed specifically to evaluate ecosystem components within a specific region, similarities of both land use and environmental conditions with other developing nations within the tropics make possible a wide application of the knowledge obtained and the research techniques developed. Our findings demonstrate that possible answers to the problems of imbalance between population and resources can be obtained through a culturally oriented ecological ap- proach. Such an approach builds on historical changes that are quantified in order to predict the behavior of elements of imbalance within the total landscape. 24. United Nations, Inventariaci6n y fomento de los recursos forestales: Re- pfiblica Dominicana, Working Document no. 1 (Santo Domingo: Programa de las Naciones Unidas parn el Desarrollo, 1971), pp. 24-29. 10 Population and Energy the pattern of changing land use since 1948 was examined and predictive techniques, including the simulation of models, were developed and applied. In the study region, population has increased by 20 per cent since 1950 and much of the area formerly in pine forest has been subjected to slash- and-burn farming and extensive grazing.0 These practices, juxtaposed with the cessation of lumbering operations since 1967, have been respon- sible for the emigration of some 4,000 laborers, principally to New York City. In this populated upland, the links between people and nature are so direct that the continued practice of marginal farming and illegal logging will cause increased erosion of the soil and depletion of the region's resource base. Increased demand for downstream irrigation water requires that both sedimentation and erosion be controlled. Conflicting conditions thus exist: the more intense the land use upstream, the greater the hazard from erosion and siltation. For the Jagua-Bao region, the study reported here provides a basis on which alternative policies can be developed for increasing returns on hydropower investments. There are much broader implications, however. While models presented here have been designed specifically to evaluate ecosystem components within a specific region, similarities of both land use and environmental conditions with other developing nations within the tropics make possible a wide application of the knowledge obtained and the research techniques developed. Our findings demonstrate that possible answers to the problems of imbalance between population and resources can be obtained through a culturally oriented ecological ap- proach. Such an approach builds on historical changes that are quantified in order to predict the behavior of elements of imbalance within the total landscape. 24. United Nations, Inventariacidn y fomento de los recursos forestales: Re- pdblica Dominicana, Working Document no. 1 (Santo Domingo: Programsa de las Naciones Unidas para el Desarrollo, 1971), pp. 24-29. 10 Population and Energy the pattern of changing land use since 1948 was examined and predictive techniques, including the simulation of models, were developed and applied. In the study region, population has increased by 20 per cent since 1950 and much of the area formerly in pine forest has been subjected to slash- and-burn farming and extensive grazing." These practices, juxtaposed with the cessation of lumbering operations since 1967, have been respon- sible for the emigration of some 4,000 laborers, principally to New York City. In this populated upland, the links between people and nature are so direct that the continued practice of marginal farming and illegal logging will cause increased erosion of the soil and depletion of the region's resource base. Increased demand for downstream irrigation water requires that both sedimentation and erosion be controlled. Conflicting conditions thus exist: the more intense the land use upstream, the greater the hazard from erosion and siltation. For the Jagua-Bao region, the study reported here provides a basis on which alternative policies can be developed for increasing returns on hydropower investments. There are much broader implications, however. While models presented here have been designed specifically to evaluate ecosystem components within a specific region, similarities of both land use and environmental conditions with other developing nations within the tropics make possible a wide application of the knowledge obtained and the research techniques developed. Our findings demonstrate that possible answers to the problems of imbalance between population and resources can be obtained through a culturally oriented ecological ap- proach. Such an approach builds on historical changes that are quantified in order to predict the behavior of elements of imbalance within the total landscape. 24. United Nations, Inventariaci6n y fomento de los recursos forestales: Re- pdblica Dominicana, Working Document no. 1 (Santo Domingo: Programa de las Naciones Unidas para el Desarrollo, 1971), pp. 24-29.  2. Physical Setting 2. Physical Setting 2. Physical Setting EROSION and sedimentation are companion processes in nature, responding to both physical and cultural conditions. Topog- raphy, steepness of slope, parent material and erodibility of soils, climate, and existing vegetative cover are the major physical factors impinging upon rates of sedimentation in a watershed. Often overlooked are the cultural activities of man, including farming and grazing practices which significantly influence erosion and sedimentation. In the Jagua-Bao region, current land-use practices and settlement patterns are deeply rooted in the past. Because of recent population pressures, however, the landscape has undergone dramatic changes since the 1940s. REGIONAL GEOLOGY Situated along the northern flank of the Central Mountain Range, the Jagua-Bao region is characterized by broad physiographic patterns which are due to geologic structures associated with volcanic, plutonic, and metamorphic country rocks.r The two geologic provinces which coincide with the boundaries of the major formational contacts have been identi- fied and mapped in Figure 2. 1. H. C. Palmer, "Geology of the Monci6n-Jarabacoa Area, Dominican Re- public" (Ph.D diss., Princeton University, 1963), pp. 219-36. 11 EROSION and sedimentation are companion processes in nature, responding to both physical and cultural conditions. Topog- raphy, steepness of slope, parent material and erodibility of soils, climate, and existing vegetative cover are the major physical factors impinging upon rates of sedimentation in a watershed. Often overlooked are the l cultural activities of man, including farming and grazing practices which significantly influence erosion and sedimentation. In the Jagua-Bao region, current land-use practices and settlement patterns are deeply rooted in the past. Because of recent population pressures, however, the landscape has undergone dramatic changes since the 1940s. REGIONAL GEOLOGY Situated along the northern flank of the Central Mountain Range, the Jagua-Bao region is characterized by broad physiographic patterns which are due to geologic structures associated with volcanic, plutonic, and metamorphic country rocks. The two geologic provinces which coincide with the boundaries of the major formational contacts have been identi- fied and mapped in Figure 2. 1. H. C. Palmer, "Geology of the Moncidn-Jarabacoa Area, Dominican Re- public" (Ph.D diss., Princeton University, 1963), pp. 219-36. EROSION and sedimentation are companion processes in nature, responding to both physical and cultural conditions. Topog- raphy, steepness of slope, parent material and erodibility of soils, climate, and existing vegetative cover are the major physical factors impinging upon rates of sedimentation in a watershed. Often overlooked are the cultural activities of man, including farming and grazing practices which significantly influence erosion and sedimentation. In the Jagua-Bao region, current land-use practices and settlement patterns are deeply rooted in the past. Because of recent population pressures, however, the landscape has undergone dramatic changes since the 1940s. REGIONAL GEOLOGY Situated along the northern flank of the Central Mountain Range, the Jagua-Bao region is characterized by broad physiographic patterns which are due to geologic structures associated with volcanic, plutonic, and metamorphic country rocks. The two geologic provinces which coincide with the boundaries of the major formational contacts have been identi- fied and mapped in Figure 2. 1. H. C. Palmer, "Geology of the Monci6n-Jarabacoa Area, Dominican Re- public" (Ph.D diss., Princeton University, 1963), pp. 219-36. 11  _ _ ., _ , - - _- - _ _ X _ ', - - _- - - -- - r o ? IIf {CCCg 0 O  Physical Setting 13 Duarte Province covers much of the study region and consists of vol- canic and regionally metamorphosed, mafic, volcanic rocks including amygdaloidal basalt, massive and schistose greenstone, amphibolite, and basic calcareous hornfels. Hornblende tonalite intrudes greenschist facies rocks in the central west and central east portions at Las Placetas and Janey, respectively. Where intrusions have occurred, the metavolcanics flanking the plutons are very fine-grained, generally display schistosity, and are hornfelsic in mineralogic assemblage. Intense shearing occurs along the contact and throughout the metamorphic aureole. Tavera Province is limited to the extreme northernmost tip of the mapped area, occurring in parts of the Los Cagueyes, Pinalito, and Guana- juma sections, and it includes partially metamorphosed sedimentary rocks of the Tavera Group. Two normal faults dominate the geology of the province. The Inoa Fault on the south separates the Tavera Group from the Duarte country rock region to the south; the contact is a prominent fault scarp. On the north, the Tavera Fault bounds the study region with the south side of the fault downthrown relative to the north, thus produc- ing a graben, or rift valley. The general trend of the geological formations of both structural provinces is northwest-southeast, parallel to the Central Mountain Range's crystalline basement. Viewed as a whole, Duarte Province displays complex structures that have suffered folding, faulting, and intrusion by igneous rocks. Yet, upon closer examination, two landform assemblages can be identified: a ma- turely dissected upland and a youthful plateau. Figures 3A and 3B show these natural landscape units. Quite clearly, the massive metavolcanics underlie the maturely dissected uplands. With local relative relief averag- ing 220 meters, the divides show moderate reduction and average 100 meters in width; slopes are steep and rugged. Excessive sheet wash and stream erosion are the major denudational agents. Over the larger out- crops, the drainage pattern is subparallel and higher-order streams are subsequent?. Topographic texture can be described as coarse.? In contrast, the topography developed on the homogeneous crystallines is subdued and indicates a more youthful stage of development. There is still some 2. For a classification of drainage patterns and a discussion of interpreting structural controls of drainage evolution, see E. R. Zernitz, "Drainage Patterns and Their Significance," Journal of Geology 40 (August-September 1932): 498-521. Douglas Johnson, "Streams and Their Significance," Journal of Geology 40 (Au- gust-September 1932): 481-97, presents criteria for classifying streams according to their genetic properties and associated structures. 3. Morphometric studies of fluvial landscape units were determined by selective sampling. Texture grades were measured on topographic maps by using Smith's texture ratio. See G. K. Smith, "Standards for Grading Texture of Erosional Topog- raphy," American Journal of Science 248 (September 1950): 655-68. Physical Setting 13 Duarte Province covers much of the study region and consists of vol- canic and regionally metamorphosed, mafic, volcanic rocks including amygdaloidal basalt, massive and schistose greenstone, amphibolite, and basic calcareous hornfels. Hornblende tonalite intrudes greenschist facies rocks in the central west and central east portions at Las Placetas and Janey, respectively. Where intrusions have occurred, the metavolcanics flanking the plutons are very fine-grained, generally display schistosity, and are hornfelsic in mineralogic assemblage. Intense shearing occurs along the contact and throughout the metamorphic aureole. Tavera Province is limited to the extreme northernmost tip of the mapped area, occurring in parts of the Los Cagueyes, Pinalito, and Guana- juma sections, and it includes partially metamorphosed sedimentary rocks of the Tavera Group. Two normal faults dominate the geology of the province. The Inoa Fault on the south separates the Tavera Group from the Duarte country rock region to the south; the contact is a prominent fault scarp. On the north, the Tavera Fault bounds the study region with the south side of the fault downthrown relative to the north, thus produc- ing a graben, or rift valley. The general trend of the geological formations of both structural provinces is northwest-southeast, parallel to the Central Mountain Range's crystalline basement. Viewed as a whole, Duarte Province displays complex structures that have suffered folding, faulting, and intrusion by igneous rocks. Yet, upon closer examination, two landform assemblages can be identified: a ma- turely dissected upland and a youthful plateau. Figures 3A and 3B show these natural landscape units. Quite clearly, the massive metavolcanics underlie the maturely dissected uplands. With local relative relief averag- ing 220 meters, the divides show moderate reduction and average 100 meters in width; slopes are steep and rugged. Excessive sheet wash and stream erosion are the major denudational agents. Over the larger out- crops, the drainage pattern is subparallel and higher-order streams are subsequent?. Topographic texture can be described as coarse.3 In contrast, the topography developed on the homogeneous crystallines is subdued and indicates a more youthful stage of development. There is still some 2. For a classification of drainage patterns and a discussion of interpreting structural controls of drainage evolution, see E. R. Zernitz, "Drainage Patterns and Their Significance," Journal of Geology 40 (August-September 1932): 498-521. Douglas Johnson, "Streams and Their Significance," Journal of Geology 40 (Au- gust-September 1932): 481-97, presents criteria for classifying streams according to their genetic properties and associated structures. 3. Morphometric studies of fluvial landscape units were determined by selective sampling. Texture grades were measured on topographic maps by using Smith's texture ratio. See G. K. Smith, "Standards for Grading Texture of Erosional Topog- raphy," American Journal of Science 248 (September 1950): 655-68. Physical Setting 13 Duarte Province covers much of the study region and consists of vol- canic and regionally metamorphosed, mafic, volcanic rocks including amygdaloidal basalt, massive and schistose greenstone, amphibolite, and basic calcareous hornfels. Hornblende tonalite intrudes greenschist facies rocks in the central west and central east portions at Las Placetas and Janey, respectively. Where intrusions have occurred, the metavolcanics flanking the plutons are very fine-grained, generally display schistosity, and are hornfelsic in mineralogic assemblage. Intense shearing occurs along the contact and throughout the metamorphic aureole. Tavera Province is limited to the extreme northernmost tip of the mapped area, occurring in parts of the Los Cagueyes, Pinalito, and Guana- juma sections, and it includes partially metamorphosed sedimentary rocks of the Tavera Group. Two normal faults dominate the geology of the province. The Inoa Fault on the south separates the Tavera Group from the Duarte country rock region to the south; the contact is a prominent fault scarp. On the north, the Tavera Fault bounds the study region with the south side of the fault downthrown relative to the north, thus produc- ing a graben, or rift valley. The general trend of the geological formations of both structural provinces is northwest-southeast, parallel to the Central Mountain Range's crystalline basement. Viewed as a whole, Duarte Province displays complex structures that have suffered folding, faulting, and intrusion by igneous rocks. Yet, upon closer examination, two landform assemblages can be identified: a ma- turely dissected upland and a youthful plateau. Figures 3A and 3B show these natural landscape units. Quite clearly, the massive metavolcanics underlie the maturely dissected uplands. With local relative relief averag- ing 220 meters, the divides show moderate reduction and average 100 meters in width; slopes are steep and rugged. Excessive sheet wash and stream erosion are the major denudational agents. Over the larger out- crops, the drainage pattern is subparallel and higher-order streams are subsequent.2 Topographic texture can be described as coarse. In contrast, the topography developed on the homogeneous crystallines is subdued and indicates a more youthful stage of development. There is still some 2. For a classification of drainage patterns and a discussion of interpreting structural controls of drainage evolution, see E. R. Zernitz, "Drainage Patterns and Their Significance," Journal of Geology 40 (August-September 1932): 498-521. Douglas Johnson, "Streams and Their Significance," Journal of Geology 40 (Au- gust-September 1932): 481-97, presents criteria for classifying streams according to their genetic properties and associated structures. 3. Morphometric studies of fluvial landscape units were determined by selective sampling. Texture grades were measured on topographic maps by using Smith's texture ratio. See G. K. Smith, "Standards for Grading Texture of Erosional Topog- raphy," American Journal of Science 248 (September 1950): 655-68.  AMatrl disce eaocnculn fJgu ie aly iwsuhtw A. Maturely dissected metavolcanic upland of Jagua River valley; view south toward Rinctin Llano Parrish on ridgeline. A. Maturely dissected metavolcanic upland of Jagua River valley; view south toward Rinc6n Llano Parrish on ridgeline. B. Youthful plateau landscape developed on hornblende tonalite with Las Placetas on left in midground; view north toward Las Carreras Mountain (Duarte Formation). FIGURE 3. Geomorphic subregions of Duarte Province. B. Youthful plateau landscape developed on hornblende tonalite with Las Placetas on left in midground; view north toward Las Carreras Mountain (Duarte Formation). FmURB 3. Geomorphic subregions of Duarte Province. B. Youthful plateau landscape developed on hornblende tonalite with Las Placetas on left in midground; view north toward Las Carreras Mountain (Duarte Formation). FIGURE 3. Geomorphic subregions of Duarte Province.  Physical Setting 15 structural control as shown by the rectangular drainage pattern, particu- larly on the Las Placetas pluton. Where this is found, first- and second- order stream development is subsequent along zones of weakness. The action of running water is still the dominant erosional agent. However, due to the more youthful landscape, with less area in slopes and conse- quently more land in broad interstream divides, the action of streams is more moderate. Topographic texture is coarse on the west central Las Placetas pluton. To the east near Janey, increased dissection and the occurrence of microrelief produce a medium topographic texture. Lineament tectonics dominate landform development within Tavera Province to the north. This region of belted metamorphic rocks shows a strong grain in its topography (see Figure 4A). The Inoa Fault scarp at Pinalito and Guanajuma is sharply elongated and trends northwest- southeast. Faceted spurs along the scarp face and stream channel deflec- tions all reflect strong structural control. While the Inoa Fault scarp exhibits high slope and relief, the extreme northeastern portion is sub- maturely dissected (see Figure 4B). Here, local relief ranges from 60 to 80 meters. The drainage pattern is parallel, while stream development is subsequent. SOILs The association of soils found within Jagua-Bao reflects in large measure the rugged topography and composition of the Central Mountain Range's country rocks.4 Soils are characterized by their shallow depth to parent material and particularly by their low fertility. Where plutonic igneous rocks form the basement complex, parent material contains high but variable quantities of quartz and feldspar. Notwithstanding the parent material, however, it has been noted generally that shallow soil depth discourages high soil moisture retention and promotes a deficiency of soil moisture even during the rainy periods. On the metavolcanic uplands, surface drainage is good, but there is a high erosion risk due to the high relative relief. All in all, the soils that make up this association are those corresponding to the Auyamas, Baiguate, Hondo, and Jimenoa series. The first three are derived from plutonic igneous rocks with varying pro- portions of quartz and feldspar, while the Jimenoa Series is developed on the metavolcanics.. Soils in the Auyamas Series develop on the hornblende tonalite plutons that underlie Las Placetas and Janey. These soils have a coarse, sandy texture, shallow depth, and low fertility. Hilly topography with pronounced 4. Organization of American States, Reconocimiento y evaluacidn de los recursos naturales de la Repdblica Dominicana, 3 vols. (Washington: Pan American Union, Department of Economic Affairs, 1967), 2, Soil Association Map of the Dominican Republic, and ibid., 3:107-16. Physical Setting 15 structural control as shown by the rectangular drainage pattern, particu- larly on the Las Placetas pluton. Where this is found, first- and second- order stream development is subsequent along zones of weakness. The action of running water is still the dominant erosional agent. However, due to the more youthful landscape, with less area in slopes and conse- quently more land in broad interstream divides, the action of streams is more moderate. Topographic texture is coarse on the west central Las Placetas pluton. To the east near Janey, increased dissection and the occurrence of microrelief produce a medium topographic texture. Lineament tectonics dominate landform development within Tavera Province to the north. This region of belted metamorphic rocks shows a strong grain in its topography (see Figure 4A). The Inoa Fault scarp at Pinalito and Guanajuma is sharply elongated and trends northwest- southeast. Faceted spurs along the scarp face and stream channel deflec- tions all reflect strong structural control. While the Inoa Fault scarp exhibits high slope and relief, the extreme northeastern portion is sub- maturely dissected (see Figure 4B1). Here, local relief ranges from 60 to 80 meters. The drainage pattern is parallel, while stream development is subsequent. SOILs The association of soils found within Jagua-Bao reflects in large measure the rugged topography and composition of the Central Mountain Range's country rocks.4 Soils are characterized by their shallow depth to parent material and particularly by their low fertility. Where plutonic igneous rocks form the basement complex, parent material contains high but variable quantities of quartz and feldspar. Notwithstanding the parent material, however, it has been noted generally that shallow soil depth discourages high soil moisture retention and promotes a deficiency of soil moisture even during the rainy periods. On the metavolcanic uplands, surface drainage is good, but there is a high erosion risk due to the high relative relief. All in all, the soils that make up this association are those corresponding to the Auyamas, Baiguate, Hondo, and Jimenoa series. The first three are derived from plutonic igneous rocks with varying pro- portions of quartz and feldspar, while the Jimenoa Series is developed on the metavolcanics. Soils in the Auyamas Series develop on the hornblende tonalite plutons that underlie Las Placetas and Janey. These soils have a coarse, sandy texture, shallow depth, and low fertility. Hilly topography with pronounced 4. Organization of American States, Reconocimiento y evaluaci6n de los recursos naturales de la Republica Dominicana, 3 vols. (Washington: Pan American Union, Department of Economic Affairs, 1967), 2, Soil Association Map of the Dominican Republic, and ibid., 3:107-16. Physical Setting 15 structural control as shown by the rectangular drainage pattern, particu- larly on the Las Placetas pluton. Where this is found, first- and second- order stream development is subsequent along zones of weakness. The action of running water is still the dominant erosional agent. However, due to the more youthful landscape, with less area in slopes and conse- quently more land in broad interstream divides, the action of streams is more moderate. Topographic texture is coarse on the west central Las Placetas pluton. To the east near Janey, increased dissection and the occurrence of microrelief produce a medium topographic texture. Lineament tectonics dominate landform development within Tavera Province to the north. This region of belted metamorphic rocks shows a strong grain in its topography (see Figure 4A). The Inoa Fault scarp at Pinalito and Guanajuma is sharply elongated and trends northwest- southeast. Faceted spurs along the scarp face and stream channel deflec- tions all reflect strong structural control. While the Inca Fault scarp exhibits high slope and relief, the extreme northeastern portion is sub- maturely dissected (see Figure 4B). Here, local relief ranges from 60 to 80 meters. The drainage pattern is parallel, while stream development is subsequent. SOILS The association of soils found within Jagua-Bao reflects in large measure the rugged topography and composition of the Central Mountain Range's country rocksn Soils are characterized by their shallow depth to parent material and particularly by their low fertility. Where plutonic igneous rocks form the basement complex, parent material contains high but variable quantities of quartz and feldspar. Notwithstanding the parent material, however, it has been noted generally that shallow soil depth discourages high soil moisture retention and promotes a deficiency of soil moisture even during the rainy periods. On the metavolcanic uplands, surface drainage is good, but there is a high erosion risk due to the high relative relief. All in all, the soils that make up this association are those corresponding to the Auyamas, Baiguate, Hondo, and Jimenoa series. The first three are derived from plutonic igneous rocks with varying pro- portions of quartz and feldspar, while the Jimenoa Series is developed on the metavolcanics. Soils in the Auyamas Series develop on the hornblende tonalite plutons that underlie Las Placetas and Janey. These soils have a coarse, sandy texture, shallow depth, and low fertility. Hilly topography with pronounced 4. Organization of American States, Reconocimiento y evaluacidn de los recursos naturales de la Repdblica Dominicana, 3 vols. (Washington: Pan American Union, Department of Economic Affairs, 1967), 2, Soil Association Map of the Dominican Republic, and ibid., 3:107-16.  '1Olslpasdod Xq palpun! aq u -slpasdod q paeuu aq "1o slpasodod Aq palpunu aq 'punola)l-q "pmoiSllaeq u! pueldn a!uealoAElaw sauol!d so7 put punol8p!w w sewedny sE"j ql!m 1-tpnos u! putldn a!utalonelaw sauogj so-i put punol8p!w w sewtiny st7 ql!m lsamglnos malA 'aautzs!p w (Smo11E) 1lnEj WaAEj" glim gauall lElnlonlls kleluaw!paselayl! "d ma!A !a "is!p ui (smO t) lIntj E1aAEj" gllm gauall (tinlanlls favjuaw!paselayll 'V 4 P uol~lN V  Physical Setting 17 slope, generally more than 50 per cent, characterizes the physical setting of the area. Auyamas soils are susceptible to erosion, and runoff is facili- tated by the sandy texture and friable character of the soil. The Baiguate Series is formed on the quartz- and feldspar-rich dioritic country rock; soils are very shallow and have a clayey texture. Though depth of the solum is shallow, parent material is partially decomposed and saprolite is found to considerable depth. Baiguate develops on rugged topography with slopes varying from 50 to 70 per cent. Vegetation con- sists primarily of pine forest and pasture. Hondo soils are generally only 10 centimeters in depth; they have a clay loam texture, are graveliferous, and are very low in fertility. Rugged topography and steep slopes facilitate accelerated runoff and soil erosion. Because of the steep slopes and shallow soil depth, the water-holding capacity of these soils is limited. Excessive surface drainage further limits agricultural utilization and promotes the exploitation of pine forest re- sources. In some areas where topography and soil depth permit, sub- sistence agriculture is found. The Jimenoa Series develops on the mountainous topography of the metavolcanic country rocks. Soils are lithosols, shallow in depth; they have a clay loam texture and are low in fertility. Table 1 summarizes the salient features of Jagua-Bao soils, particularly their physical properties and erosional characteristics. Noteworthy is the fact that all soils within the region are typed as Class VII according to the U.S. Department of Agriculture (USDA) system. This indicates that the recommended use is for purposes other than cultivation. Implied by this classification is the need for conservation practices to protect and insure a rational use of the region's timber resources. CLIMATE The climatic regimen of Jagua-Bao is controlled by changes in the prevail- ing atmospheric pressure systems, topographic barriers, and land surface complexities. The dominant climatic control is the change in atmospheric circulation from high pressure during the winter season to low pressure during the summer months. In the winter, the region is dominated by the influence of the stable high-pressure system over the North American continent. During this period, winds blow forcefully and steadily from the northeast. Weak winter cyclones occasionally push polar continental air out into the Atlantic sufficiently far to affect the region. These northers produce prolonged light drizzle for several days through the winter months.t 5. Leo Alpert, "The Climate of Hispaniola" (Master's essay, Clark University, 1939), pp. 18-24. Physical Setting 17 slope, generally more than 50 per cent, characterizes the physical setting of the area. Auyamas soils are susceptible to erosion, and runoff is facili- tated by the sandy texture and friable character of the soil. The Baiguate Series is formed on the quartz- and feldspar-rich dioritic country rock; soils are very shallow and have a clayey texture. Though depth of the solum is shallow, parent material is partially decomposed and saprolite is found to considerable depth. Baiguate develops on rugged topography with slopes varying from 50 to 70 per cent. Vegetation con- sists primarily of pine forest and pasture. Hondo soils are generally only 10 centimeters in depth; they have a clay loam texture, are graveliferous, and are very low in fertility. Rugged topography and steep slopes facilitate accelerated runoff and soil erosion. Because of the steep slopes and shallow soil depth, the water-holding capacity of these soils is limited. Excessive surface drainage further limits agricultural utilization and promotes the exploitation of pine forest re- sources. In some areas where topography and soil depth permit, sub- sistence agriculture is found. The Jimenoa Series develops on the mountainous topography of the metavolcanic country rocks. Soils are lithosols, shallow in depth; they have a clay loam texture and are low in fertility. Table 1 summarizes the salient features of Jagua-Bao soils, particularly their physical properties and erosional characteristics. Noteworthy is the fact that all soils within the region are typed as Class VII according to the U.S. Department of Agriculture (USDA) system. This indicates that the recommended use is for purposes other than cultivation. Implied by this classification is the need for conservation practices to protect and insure a rational use of the region's timber resources. CLIMATE The climatic regimen of Jagua-Bao is controlled by changes in the prevail- ing atmospheric pressure systems, topographic barriers, and land surface complexities. The dominant climatic control is the change in atmospheric circulation from high pressure during the winter season to low pressure during the summer months. In the winter, the region is dominated by the influence of the stable high-pressure system over the North American continent. During this period, winds blow forcefully and steadily from the northeast. Weak winter cyclones occasionally push polar continental air out into the Atlantic sufficiently far to affect the region. These northers produce prolonged light drizzle for several days through the winter months.t 5. Leo Alpert, "The Climate of Hispaniola" (Master's essay, Clark University, 1939), pp. 18-24. Physical Setting 17 slope, generally more than 50 per cent, characterizes the physical setting of the area. Auyamas soils are susceptible to erosion, and runoff is facili- tated by the sandy texture and friable character of the soil. The Baiguate Series is formed on the quartz- and feldspar-rich dioritic country rock; soils are very shallow and have a clayey texture. Though depth of the solum is shallow, parent material is partially decomposed and saprolite is found to considerable depth. Baiguate develops on rugged topography with slopes varying from 50 to 70 per cent. Vegetation con- sists primarily of pine forest and pasture. Hondo soils are generally only 10 centimeters in depth; they have a clay loam texture, are graveliferous, and are very low in fertility. Rugged topography and steep slopes facilitate accelerated runoff and soil erosion. Because of the steep slopes and shallow soil depth, the water-holding capacity of these soils is limited. Excessive surface drainage further limits agricultural utilization and promotes the exploitation of pine forest re- sources. In some areas where topography and soil depth permit, sub- sistence agriculture is found. The Jimenoa Series develops on the mountainous topography of the metavolcanic country rocks. Soils are lithosols, shallow in depth; they have a clay loam texture and are low in fertility. Table 1 summarizes the salient features of Jagua-Bao soils, particularly their physical properties and erosional characteristics. Noteworthy is the fact that all soils within the region are typed as Class VII according to the U.S. Department of Agriculture (usDA) system. This indicates that the recommended use is for purposes other than cultivation. Implied by this classification is the need for conservation practices to protect and insure a rational use of the region's timber resources. CLIMATE The climatic regimen of Jagua-Bao is controlled by changes in the prevail- ing atmospheric pressure systems, topographic barriers, and land surface complexities. The dominant climatic control is the change in atmospheric circulation from high pressure during the winter season to low pressure during the summer months. In the winter, the region is dominated by the influence of the stable high-pressure system over the North American continent. During this period, winds blow forcefully and steadily from the northeast. Weak winter cyclones occasionally push polar continental air out into the Atlantic sufficiently far to affect the region. These northers produce prolonged light drizzle for several days through the winter months.' 5. Leo Alpert, "The Climate of Hispaniola" (Master's essay, Clark University, 1939), pp. 18-24.  TABLE 1 MAJOR CHARACTERISTICS OF JAGUA-13AO SOMS Landforms, Parent Physical Limiting Erosion Land Cap. Recommended Soil Series Series No. Material Slope (%) Characteristics Drainage Fertility Factors Risk Class Land Uses Auyamas 26 Plateaus; hilly topog- 30--60 Coarse, sandy- Excessive Low Topography, Severe VII Forestry raphy developed on textured soils; depth, hornblende tonalite shallow depth; fertility friable Baiguate 29 Plateaus; rugged 50-70 Clayey-tex- Excessive Medium Depth, severe VII Subsistence topography de- tured soils; fertility agriculture, veloped on diorites shallow depth forestry Hondo 27 Mountain crests; 25-45 Clayey loam Good Low Depth, Severe VII Forestry (pine), residual soils developed texture; stoniness subsistence on quartzitic rocks friable agriculture Jimenoa 31 Mountainous terrain; 15-45 Lithosols with Good Low Topography, Severe VII Forestry maturely dissected shallow depth; fertility uplands, developed clayey loam TABLET MAJOR CHARACTERISTICS OF JAGUA-13AO SOILS Landforms, Parent Physical Limiting Erosion Land Cap. Recommended Soil Series Series No. Material Slope (%) Characteristics Drainage Fertility Factors Risk Class Land Uses Auyamas 26 Plateaus; hilly topog- 30-60 Coarse, sandy- Excessive Low Topography, Severe VII Forestry raphy developed on textured soils; depth, hornblende tonality shallow depth; fertility friable Haiguate 29 Plateaus; rugged 50-70 Clayey-tex- Excessive Medium Depth, Severe VII Subsistence topography de. tured soils; fertility agriculture, veloped on diorites shallow depth forestry Hondo 27 Mountain crests; 25-15 Clayey loam Good Low Depth, Severe V11 Forestry (pine), residual soils developed texture; stoniness subsistence on quartzitic rocks friable agriculture Jimenoa 31 Mountainous terrain; 15-45 Lithosols with Good Low Topography, Severe VII Forestry maturely dissected shallow depth; fertility uplands, developed clayey loam on basnlts texturc TABLEI MAJOR CHARACTERISTICS OP JAGUA-BAO SOILS Landforms, Parent Physical Limiting Erosion Land Cap. Recommended Sell Series Series No. Material Slope (%) Characteristics Drainage Fertility Factors Risk Class Land Uses Auyamas 26 Plateaus; hilly topog- 30-60 Coarse, sandy- Excessive Low Topography, Severe Vll Forestry raphy developed on textured soils; depth, hornblende tonalite shallow depth; fertility friable Baiguate 29 Plateaus; rugged 50-70 Clayey-tex- Excessive Medium Depth, Severe Vll Subsistence topography de- tured soils; fertility agriculture, veloped on diorites shallow depth forestry Hondo 27 Mountain crests; 25-45 Clayey loam Good Low Depth, Severe VII Forestry (pine), residual soils developed texture; stoniness subsistence on quartzitic rocks friable agriculture Jimenoa 31 Mountainous terrain; 15-45 Lithosols with Good Low Topography, Severe V11 Forestry maturely dissected shallow depth; fertility uplands, developed clayey loam on basalts texture  Physical Setting 19 The equatorial low-pressure system dominates the scene during the summer months with winds from the southeast quadrant. This relatively unstable air mass is conducive to the formation of thunderstorms, which occur quite frequently during this season. It also influences the develop- ment of tropical hurricanes, occasionally producing torrential rains.6 The moisture-carrying capacity of air masses over the Jagua-Bao region is affected by topographic barriers. As winds come off the ocean and strike the north coast of the Dominican Republic, they encounter the Northern Mountain Range. This range is the major barrier to the trade winds. Moist air is cooled adiabatically on the north-facing mountain slope, and oro- graphic rainfall results. As air passes down the south slope, it is heated adiabatically and dry weather prevails. The map in Figure 5 illustrates the study region's location with respect to the barrier mountain range. It is evident that the northernmost strip is situated within the rain shadow of the east-west-trending mountains. Conversely, the southern fringe of the study region is located at a higher elevation along the northern flank of the Central Range. This southern zone thus receives considerably more rainfall due to orographic lifting. Precipitation varies greatly in the Jagua-Bao region, from 1,133 milli- meters at Pinalito to 1,873 millimeters at Mata Grande.r However, the annual range of temperature is small, extending from an average of 16.0' C (for the coldest station) in January to 25.7° C (for the warmest station) in July.8 Although temperature does not restrict the length of the growing season, its high value does directly influence moisture availability via water loss through evapotranspiration. Differences in precipitation at selected stations are shown in Figure 6.1 The graphs illustrate a bimodal precipitation regimen with the two wettest periods occurring during May- June and September-November. Notwithstanding these similarities, no- table variations do occur. Generally, the northern portion of the Jagua- Bao region is dry for at least six months of the year. Truly dry subtropical 6. Ibid., p. 20. 7. Computation of monthly mean temperature and precipitation for the 1951-70 period covers Jarabacoa, while stations at Tavera, Bao Bao, Pinalito, Guanaiuma, and Mata Grande have a 1966-70 record. Climatological data files, Division de Hidrologia, Instituto Nacional de Recursos Hidraulicos (INDnH), and Divisidn de Climatologia y Agroclimatologia, Secretaria de Agricultura, Santo Domingo. 8. Ibid. 9. Note that the water balance graphs in Figure 6 are based on the Holdridge moisture budget accounting method, which describes the relationship between actual and potential evapotranspiration and by doing so defines moisture deficiency and water surplus. For an explanation of the accounting method, see Joseph Tosi's statement "Clculo del balance hidrico," in J. J. Ewel, A. Madriz, and J. A. Tosi, Zonas de vida en Venezuela (Caracas: Ministerio de Agricultura y Cria, 1968), pp. 44-48. Physical Setting 19 The equatorial low-pressure system dominates the scene during the summer months with winds from the southeast quadrant. This relatively unstable air mass is conducive to the formation of thunderstorms, which occur quite frequently during this season. It also influences the develop- ment of tropical hurricanes, occasionally producing torrential rains. The moisture-carrying capacity of air masses over the Jagua-Bao region is affected by topographic barriers. As winds come off the ocean and strike the north coast of the Dominican Republic, they encounter the Northern Mountain Range. This range is the major barrier to the trade winds. Moist air is cooled adiabatically on the north-facing mountain slope, and oro- graphic rainfall results. As air passes down the south slope, it is heated adiabatically and dry weather prevails. The map in Figure 5 illustrates the study region's location with respect to the barrier mountain range. It is evident that the northernmost strip is situated within the rain shadow of the east-west-trending mountains. Conversely, the southern fringe of the study region is located at a higher elevation along the northern flank of the Central Range. This southern zone thus receives considerably more rainfall due to orographic lifting. Precipitation varies greatly in the Jagua-Bao region, from 1,133 milli- meters at Pinalito to 1,873 millimeters at Mata Grande.' However, the annual range of temperature is small, extending from an average of 16.0* C (for the coldest station) in January to 25.7' C (for the warmest station) in July.' Although temperature does not restrict the length of the growing season, its high value does directly influence moisture availability via water loss through evapotranspiration. Differences in precipitation at selected stations are shown in Figure 6.9 The graphs illustrate a bimodal precipitation regimen with the two wettest periods occurring during May- June and September-November. Notwithstanding these similarities, no- table variations do occur. Generally, the northern portion of the Jagua- Bao region is dry for at least six months of the year. Truly dry subtropical 6. Ibid., p. 20. 7. Computation of monthly mean temperature and precipitation for the 1951-70 period covers Jarabacoa, while stations at Tavera, Bao Ba, Pinalito, Guanajuma, and Mata Grande have a 1966-70 record. Climatological data files, Divisin de Hidrologia, Instituto Nacional de Recursos Hidraulicos (Isnr), and Divisidn de Climatologia y Agroclimatologia, Secretaria de Agricultura, Santo Domingo. 8. Ibid. 9. Note that the water balance graphs in Figure 6 are based on the Holdridge moisture budget accounting method, which describes the relationship between actual and potential evapotranspiration and by doing so defines moisture deficiency and water surplus. For an explanation of the accounting method, see Joseph Tosis statement "Calculo del balance hidrico," in J. J. Ewel, A. Madriz, and J. A. Tosi, Zonas de vida en Venezuela (Caracas: Ministerio de Agricultura y Cria, 1968), pp. 44-48. Physical Setting 19 The equatorial low-pressure system dominates the scene during the summer months with winds from the southeast quadrant. This relatively unstable air mass is conducive to the formation of thunderstorms, which occur quite frequently during this season. It also influences the develop- ment of tropical hurricanes, occasionally producing torrential rains.5 The moisture-carrying capacity of air masses over the Jagua-Bao region is affected by topographic barriers. As winds come off the ocean and strike the north coast of the Dominican Republic, they encounter the Northern Mountain Range. This range is the major barrier to the trade winds. Moist air is cooled adiabatically on the north-facing mountain slope, and oro- graphic rainfall results. As air passes down the south slope, it is heated adiabatically and dry weather prevails. The map in Figure 5 illustrates the study region's location with respect to the barrier mountain range. It is evident that the northernmost strip is situated within the rain shadow of the east-west-trending mountains. Conversely, the southern fringe of the study region is located at a higher elevation along the northern flank of the Central Range. This southern zone thus receives considerably more rainfall due to orographic lifting. Precipitation varies greatly in the Jagua-Bao region, from 1,133 milli- meters at Pinalito to 1,873 millimeters at Mata Grande. However, the annual range of temperature is small, extending from an average of 16.0' C (for the coldest station) in January to 25.7* C (for the warmest station) in July. Although temperature does not restrict the length of the growing season, its high value does directly influence moisture availability via water loss through evapotranspiration. Differences in precipitation at selected stations are shown in Figure 6.9 The graphs illustrate a bimodal precipitation regimen with the two wettest periods occurring during May- June and September-November. Notwithstanding these similarities, no- table variations do occur. Generally, the northern portion of the Jagua- Bao region is dry for at least six months of the year. Truly dry subtropical 6. Ibid., p. 20. 7. Computation of monthly mean temperature and precipitation for the 1951-70 period covers Jarabacoa, while stations at Tavera, Bao Bano, Pinalito, Guanaiuma, and Mata Grande have a 1966-70 record. Climatological data files, Divisin de Hidrologia, Instituto Nacional de Recursos Hidraulicos (INRu), and Divisidn de Climatologia y Agroclimatologfa, Secretaria de Agricultura, Santo Domingo. 8. Ibid. 9. Note that the water balance graphs in Figure 6 are based on the Holdridge moisture budget accounting method, which describes the relationship between actual and potential evapotranspiration and by doing so defines moisture deficiency and water surplus. For an explanation of the accounting method, see Joseph Tosi's statement "Cilculo del balance hidrico," in J. J. Ewel, A. Madriz, and J. A. Tosi, Zonas de vida en Venezuela (Caracas: Ministerio de Agricultura y Cria, 1968), pp. 44-48.  710 30' 71°00' 70°30' 70°00' y,1 iECxi r3. : ,,, a a4 Atlantic cean P'1 U YnVr a DAJA B DN 19 " / soda x 3d Al IPI:11 I.-I " . oS, N jk)s6 De GAS Ad.A I,%I NA(J A *SA'J PR CO ( 8 A-Han LA VFGA O ll ins: Slov«30%  Pinaito-1967-70~~~~~ ~ ~ ~ ~ ~ ~ ~ Ba-a-967 Gunjm-97-0 Tvr-96-0Pnlto16-0 Bo-a-967 Gaaua16-7 aea1677 iaio-977 a-Bo16-0 Gunjm-97-0 Iv FI N Xi F FI :®.1 MO MO i I t tI A S II A I I I 1 J J J J ] J J ]1 JJ 11 J 0 20 . o zoom.II I II M araI I Grande-1960-70 M anabao-1960-70 Jarabacoa-1951-70 I Mat.a Grande-1960-70 M anabao-1960 -70 Jarabacoa-1951-70 I Mato Grande-1960-70II Manabao-1960 -701 1 11Il I II I II II 1 I I I II II I 111111111 1 I I I II 111 Jarabacoa-1951-70II I I 1  22 Population and Energy conditions exist at Guanajuma and Pinalito, with constantly high tempera- tures causing evapotranspiration to exceed precipitation during most of the calendar year. However, even with this aridity, spring and fall rains are of sufficient intensity to produce soil moisture recharge, and runoff in May and June ranges from 18 to 108 millimeters0 Along the southern fringe of the region, adiabatic cooling caused by the higher elevations induces orographic precipitation, resulting in greater moisture. An exami- nation of the water balance graphs in the lower half of Figure 6 indicates that the southwestern area has the greatest water surplus. Indeed, unad- justed annual runoff totals 774 millimeters at Mata Grande, occurring over a nine-month period." The trend is one of decreasing surplus east- ward to Jarabacoa. Thus, an examination of the prevailing weather pat- terns points out high variability of precipitation; moisture deficiencies within the northern piedmont and moisture excesses along the southern mountainous perimeter are the prime climatological characteristics of this subtropical region. Indeed, it is the low montane forest upland in the southwest that provides the very source of Jagua-Bao's orographic pre- cipitation. HYDROLOGY While topography, parent material, soils, and climate are essential ingre- dients that make up the region's physical resource base, they are not isolated factors acting independently of each other. Rather, they form part of an interacting network, one component influencing the other in well-defined and often predictable ways. Changes in the hydrology of the soil zone are dependent upon variations in inputs to the water budget- precipitation, irrigation water, water coming from upward capillary move- ment from the water table-and soil water outputs, such as evapotranspi- ration, percolation to deeper strata and to the groundwater compartment, and runoffmr PRECIPITATION Rain is the only significant input to the water budget of the Dominican Republic. The intensity of rainfall is an important factor to note, since the force with which the first drops of a hard storm may hit the ground can greatly reduce the rate at which subsequent rain will infiltrate the surface layer of soil. A driving rain may have less impact on the soil 10. Ibid. 1t. Ibid. 12. J. H. Chang, Climate and Agriculture (Chicago: Aldine Publishing Co.. 1968). 22 Population and Energy conditions exist at Guanajuma and Pinalito, with constantly high tempera- tures causing evapotranspiration to exceed precipitation during most of the calendar year. However, even with this aridity, spring and fall rains are of sufficient intensity to produce soil moisture recharge, and runoff in May and June ranges from 18 to 108 millimeters.?5 Along the southern fringe of the region, adiabatic cooling caused by the higher elevations induces orographic precipitation, resulting in greater moisture. An exami- nation of the water balance graphs in the lower half of Figure 6 indicates that the southwestern area has the greatest water surplus. Indeed, unad- justed annual runoff totals 774 millimeters at Mata Grande, occurring over a nine-month period." The trend is one of decreasing surplus east- ward to Jarabacoa. Thus, an examination of the prevailing weather pat- terns points out high variability of precipitation; moisture deficiencies within the northern piedmont and moisture excesses along the southern mountainous perimeter are the prime climatological characteristics of this subtropical region. Indeed, it is the low montane forest upland in the southwest that provides the very source of Jagua-Bao's orographic pre- cipitation. HYDROLOGY While topography, parent material, soils, and climate are essential ingre- dients that make up the region's physical resource base, they are not isolated factors acting independently of each other. Rather, they form part of an interacting network, one component influencing the other in well-defined and often predictable ways. Changes in the hydrology of the soil zone are dependent upon variations in inputs to the water budget- precipitation, irrigation water, water coming from upward capillary move- ment from the water table-and soil water outputs, such as evapotranspi- ration, percolation to deeper strata and to the groundwater compartment, and runoff.'0 PRECIPITATION Rain is the only significant input to the water budget of the Dominican Republic. The intensity of rainfall is an important factor to note, since the force with which the first drops of a hard storm may hit the ground can greatly reduce the rate at which subsequent rain will infiltrate the surface layer of soil. A driving rain may have less impact on the soil 10. Ibid. 11. Ibid. 12. J. H. Chang, Climate and Agriculture (Chicago: Aldine Publishing Co., 1968). 22 Population and Energy conditions exist at Guanajuma and Pinalito, with constantly high tempera- tures causing evapotranspiration to exceed precipitation during most of the calendar year. However, even with this aridity, spring and fall rains are of sufficient intensity to produce soil moisture recharge, and runoff in May and June ranges from 18 to 108 millimeters?r Along the southern fringe of the region, adiabatic cooling caused by the higher elevations induces orographic precipitation, resulting in greater moisture. An exami- nation of the water balance graphs in the lower half of Figure 6 indicates that the southwestern area has the greatest water surplus. Indeed, unad- justed annual runoff totals 774 millimeters at Mata Grande, occurring over a nine-month period." The trend is one of decreasing surplus east- ward to Jarabacoa. Thus, an examination of the prevailing weather pat- terns points out high variability of precipitation; moisture deficiencies within the northern piedmont and moisture excesses along the southern mountainous perimeter are the prime climatological characteristics of this subtropical region. Indeed, it is the low montane forest upland in the southwest that provides the very source of Jagua-Bao's orographic pre- cipitation. HYDROLOGY While topography, parent material, soils, and climate are essential ingre- dients that make up the region's physical resource base, they are not isolated factors acting independently of each other. Rather, they form part of an interacting network, one component influencing the other in well-defined and often predictable ways. Changes in the hydrology of the soil zone are dependent upon variations in inputs to the water budget- precipitation, irrigation water, water coming from upward capillary move- ment from the water table-and soil water outputs, such as evapotranspi- ration, percolation to deeper strata and to the groundwater compartment, and runoff.'0 PRECIPITATION Rain is the only significant input to the water budget of the Dominican Republic. The intensity of rainfall is an important factor to note, since the force with which the first drops of a hard storm may hit the ground can greatly reduce the rate at which subsequent rain will infiltrate the surface layer of soil. A driving rain may have less impact on the soil 10. Ibid. 11. Ibid. 12. J. H. Chang, Climate and Agriculture (Chicago: Aldine Publishing Co, 1968).  Physical Setting 23 moisture compartment than a less intense rain, the latter delivering the same amount of water over a longer period of time. Light rainfalls are significant in that they may affect transpiration rates of the intercepting leaves even though they would scarcely be detected at ground level. Neither irrigation nor upward capillary movement are important inputs to the soil moisture compartment in the Jagua-Bao region, and hence will not be considered in this discussion. EVAPOTRANSPIRATION Water may leave the soil moisture compartment by direct evaporation from the soil surface or by transpiration through the plant community. Evaporation is affected mainly by humidity, solar radiation, and wind speed; the rate of transpiration is dependent on the difference between vapor pressures in the air and in the plant." When the vegetation in an ecosystem covers virtually all the soil surface (i.e., a leaf area index of at least 1), evaporation and transpiration are not always easily separated. Therefore, if one is interested primarily in changes in the soil moisture compartment, it is usually more convenient to combine the two as evapo- transpiration. A useful standard in measuring the effects of evapotranspiration is potential evapotranspiration, the rate at which water is transpired by vege- tation under optimum moisture conditions (species differences are gener- ally insignificant).4 Rates of evapotranspiration under less than optimum conditions-actual evapotranspiration-can thus be measured against a relatively consistent standard for a given area. Two important determinants of actual evapotranspiration are soil mois- ture and the nature of vegetative cover. Actual evapotranspiration appar- ently remains at its potential level as long as field capacity, the amount of moisture that a soil is capable of holding against gravity, is maintained. However, it drops off sharply-exponentially in some cases-at some level of soil moisture below field capacity.5 The amount of vegetation covering an area is of considerable importance in determining the rate of evapotranspiration. Work with wheat and safflower in Australia has dem- onstrated that beyond a certain amount of cover (a leaf area index of 4 in safflower), evapotranspiration remains nearly constant as long as soil 13. R. G. Barry, "Evaporation and Transpiration," Water, Earth and Man, ed. R. J. Chorley (London: Methuen & Co. Ltd., 1969), pp. 169-84. 14. H. L. Penman, "Evaporation: An Introductory Survey," Netherland Journal of Agricultural Science 4 (1956): 9-29. A discussion of factors affecting potential evapotranspiration is presented in Chang, Climate and Agriculture. 15. Chang, Climate and Agriculture. Physical Setting 23 moisture compartment than a less intense rain, the latter delivering the same amount of water over a longer period of time. Light rainfalls are significant in that they may affect transpiration rates of the intercepting leaves even though they would scarcely be detected at ground level. Neither irrigation nor upward capillary movement are important inputs to the soil moisture compartment in the Jagua-Bao region, and hence will not be considered in this discussion. EVAPOTRANSPIRATION Water may leave the soil moisture compartment by direct evaporation from the soil surface or by transpiration through the plant community. Evaporation is affected mainly by humidity, solar radiation, and wind speed; the rate of transpiration is dependent on the difference between vapor pressures in the air and in the plant.5 When the vegetation in an ecosystem covers virtually all the soil surface (i.e., a leaf area index of at least 1), evaporation and transpiration are not always easily separated. Therefore, if one is interested primarily in changes in the soil moisture compartment, it is usually more convenient to combine the two as evapo- transpiration. A useful standard in measuring the effects of evapotranspiration is potential evapotranspiration, the rate at which water is transpired by vege- tation under optimum moisture conditions (species differences are gener- ally insignificant).t1 Rates of evapotranspiration under less than optimum conditions-actual evapotranspiration-can thus be measured against a relatively consistent standard for a given area. Two important determinants of actual evapotranspiration are soil mois- ture and the nature of vegetative cover. Actual evapotranspiration appar- ently remains at its potential level as long as field capacity, the amount of moisture that a soil is capable of holding against gravity, is maintained. However, it drops off sharply-exponentially in some cases-at some level of soil moisture below field capacity." The amount of vegetation covering an area is of considerable importance in determining the rate of evapotranspiration. Work with wheat and safflower in Australia has dem- onstrated that beyond a certain amount of cover (a leaf area index of 4 in safflower), evapotranspiration remains nearly constant as long as soil 13. R. G. Barry, "Evaporation and Transpiration," Water, Earth and Man, ed. R. J. Chorley (London: Methuen & Co. Ltd., 1969), pp. 169-84. 14. H. L. Penman, "Evaporation: An Introductory Survey," Netherland Journal of Agricultural Science 4 (1956): 9-29. A discussion of factors affecting potential evapotranspiration is presented in Chang, Climate and Agriculture. 15. Chang, Climate and Agriculture. Physical Setting 23 moisture compartment than a less intense rain, the latter delivering the same amount of water over a longer period of time. Light rainfalls are significant in that they may affect transpiration rates of the intercepting leaves even though they would scarcely be detected at ground level. Neither irrigation nor upward capillary movement are important inputs to the soil moisture compartment in the Jagua-Bao region, and hence will not be considered in this discussion. EVAPOTRANSPIRATION Water may leave the soil moisture compartment by direct evaporation from the soil surface or by transpiration through the plant community. Evaporation is affected mainly by humidity, solar radiation, and wind speed; the rate of transpiration is dependent on the difference between vapor pressures in the air and in the plant.S When the vegetation in an ecosystem covers virtually all the soil surface (i.e., a leaf area index of at least 1), evaporation and transpiration are not always easily separated. Therefore, if one is interested primarily in changes in the soil moisture compartment, it is usually more convenient to combine the two as evapo- transpiration. A useful standard in measuring the effects of evapotranspiration is potential evapotranspiration, the rate at which water is transpired by vege- tation under optimum moisture conditions (species differences are gener- ally insignificant).50 Rates of evapotranspiration under less than optimum conditions-actual evapotranspiration-can thus be measured against a relatively consistent standard for a given area. Two important determinants of actual evapotranspiration are soil mois- ture and the nature of vegetative cover. Actual evapotranspiration appar- ently remains at its potential level as long as field capacity, the amount of moisture that a soil is capable of holding against gravity, is maintained. However, it drops off sharply-exponentially in some cases-at some level of soil moisture below field capacity." The amount of vegetation covering an area is of considerable importance in determining the rate of evapotranspiration. Work with wheat and safflower in Australia has dem- onstrated that beyond a certain amount of cover (a leaf area index of 4 in safflower), evapotranspiration remains nearly constant as long as soil 13. R. G. Barry, "Evaporation and Transpiration," Water, Earth and Man, ed. R. J. Chorley (London: Methuen & Co. Ltd., 1969), pp. 169-84. 14. H. L. Penman, "Evaporation: An Introductory Survey," Netherland Journal of Agricultural Science 4 (1956): 9-29. A discussion of factors affecting potential evapotranspiration is presented in Chang, Climate and Agriculture. 15. Chang, Climate and Agriculture.  24 Population and Energy moisture is maintained at field capacity.1t Evapotranspiration is therefore greater from a forested area than from a cultivated field. One representa- tive set of average annual evapotranspiration rates includes the following values: pine forest, 538 millimeters; deciduous hardwoods, 417 millime- ters; low vegetation, 448 millimeters; and bare soil, 195 millimeters. 1 RUNOFF When the soil moisture level exceeds field capacity, water may either percolate into deeper layers or travel across or through the ground to lower levels in the region. In areas of deeper soils, the capacities of two or more layers must be considered in an accounting of the soil moisture level. (In a model evaluating soil moisture conditions in Australia, for instance, both upper and lower soil stores were included in the simula- tione Transpiration of herbs drew upon the upper soil storage, and shrub transpiration depended on the layer with the higher moisture level.) Per- colation to deep ground water sources is generally ignored, however, being assumed to be of very small relative importance?5 Overland flow occurs when the intensity of rainfall exceeds the capacity of the soil to absorb it. Accordingly, both soil moisture storage and infil- tration capacity are important. The concept of overland flow is generally incorporated into the broadly defined term runoff, which is considered to be the primary cause of soil erosion.20 The percentage of precipitation reaching the earth which becomes runoff depends, however, on the mean annual rainfall, the nature and degree of vegetative cover, and the relief of the terrain, particularly where slopes are greater than 10 per cente Runoff is virtually unknown in humid areas with natural vegetative cover, even though the mean annual rainfall might be quite high. Variations in runoff from loess soils in Mississippi have ranged from 0.8 per cent in an 16. R. A. Fisher and G. D. Kohn, "The Relationship between Evapotranspiration and Growth in the Wheat Crop," Australian Journal of Agricultural Research 17 (1966): 255-67; W. R. Stern, "Evapotranspiration of Sallower at Three Densities of Sowing," Australian Journal of Agricultural Research 16 (1965): 961-71. 17. L. J. L. Deij, "The Lysimeter Station at Castricum (Holland)," Compte Rendus, Association International de Hydrologie 3 (1954): 203-4. 18. G. L. Swartzman and G. M. Van Dyne, "An Ecologically Based Simulation- Optimization Approach to Natural Resource Planning," Annual Review of Ecology and Systematics 3 (1972): 347-98. 19. R. J. More, "The Basin Hydrological Cycle," Water, Earth and Man, ed. R. J. Chorley (London: Methuen & Co., Ltd., 1969), pp. 67-76. 20. M. J. Kirkby, "Erosion by Water on Hill Slopes," Water, Earth and Man, ed. R. J. Charley (London: Methuen & Co., Ltd., 1969), pp. 229-38. 21. Farm Planners' Engineering Handbook for the Upper Mississippi Watershed (Milwaukee: U.S. Soil Conservation Service, 1953). 24 Population and Energy moisture is maintained at field capacity.10 Evapotranspiration is therefore greater from a forested area than from a cultivated field. One representa- tive set of average annual evapotranspiration rates includes the following values: pine forest, 538 millimeters; deciduous hardwoods, 417 millime- ters; low vegetation, 448 millimeters; and bare soil, 195 millimeters." RUNOFF When the soil moisture level exceeds field capacity, water may either percolate into deeper layers or travel across or through the ground to lower levels in the region. In areas of deeper soils, the capacities of two or more layers must be considered in an accounting of the soil moisture level. (In a model evaluating soil moisture conditions in Australia, for instance, both upper and lower soil stores were included in the simula- tion.tt Transpiration of herbs drew upon the upper soil storage, and shrub transpiration depended on the layer with the higher moisture level.) Per- colation to deep ground water sources is generally ignored, however, being assumed to be of very small relative importance.55 Overland flow occurs when the intensity of rainfall exceeds the capacity of the soil to absorb it. Accordingly, both soil moisture storage and infil- tration capacity are important. The concept of overland flow is generally incorporated into the broadly defined term runoff, which is considered to be the primary cause of soil erosion 20 The percentage of precipitation reaching the earth which becomes runoff depends, however, on the mean annual rainfall, the nature and degree of vegetative cover, and the relief of the terrain, particularly where slopes are greater than 10 per cent. Y Runoff is virtually unknown in humid areas with natural vegetative cover, even though the mean annual rainfall might be quite high. Variations in runoff from loess soils in Mississippi have ranged from 0.8 per cent in an 16. R. A. Fisher and G. D. Kohn, "The Relationship between Evapotranspiration and Growth in the Wheat Crop," Australian Journal of Agricultural Research 17 (1966): 255-67; W. R. Stern, "Evapotranspiration of Safltower at Three Densities of Sowing," Australian Journal of Agricultural Research 16 (1965): 961-71. 17. L. J. L. Deij, "The Lysimeter Station at Castricum (Holland)," Compte Rendus, Association International de Hydrologie 3 (1954): 203-4. 18. G. L. Swartzman and G. M. Van Dyne, "An Ecologically Based Simulation- Optimization Approach to Natural Resource Planning," Annual Review of Ecology and Systematics 3 (1972): 347-98. 19. R. J. More, "The Basin Hydrological Cycle," Water, Earth and Man, ed. R. J. Chorley (London: Methuen & Co., Ltd., 1969), pp. 67-76. 20. M. J. Kirkby, "Erosion by Water on Hill Slopes," Water, Earth and Man, ed. R. J. Chorley (London: Methuen & Co., Ltd., 1969), pp. 229-38. 21. Farm Planners' Engineering Handbook for the Upper Mississippi Watershed (Milwaukee: U.S. Soil Conservation Service, 1953). 24 Population and Energy moisture is maintained at field capacity.1 Evapotranspiration is therefore greater from a forested area than from a cultivated field. One representa- tive set of average annual evapotranspiration rates includes the following values: pine forest, 538 millimeters; deciduous hardwoods, 417 millime- ters; low vegetation, 448 millimeters; and bare soil, 195 millimeterssn RUNOFF When the soil moisture level exceeds field capacity, water may either percolate into deeper layers or travel across or through the ground to lower levels in the region. In areas of deeper soils, the capacities of two or more layers must be considered in an accounting of the soil moisture level. (In a model evaluating soil moisture conditions in Australia, for instance, both upper and lower soil stores were included in the simula- tion." Transpiration of herbs drew upon the upper soil storage, and shrub transpiration depended on the layer with the higher moisture level.) Per- colation to deep ground water sources is generally ignored, however, being assumed to be of very small relative importance.1 Overland flow occurs when the intensity of rainfall exceeds the capacity of the soil to absorb it. Accordingly, both soil moisture storage and infil- tration capacity are important. The concept of overland flow is generally incorporated into the broadly defined term runoff, which is considered to be the primary cause of soil erosion." The percentage of precipitation reaching the earth which becomes runoff depends, however, on the mean annual rainfall, the nature and degree of vegetative cover, and the relief of the terrain, particularly where slopes are greater than 10 per cent." Runoff is virtually unknown in humid areas with natural vegetative cover, even though the mean annual rainfall might be quite high. Variations in runoff from loess soils in Mississippi have ranged from 0.8 per cent in an 16. R. A. Fisher and G. D. Kohn, "The Relationship between Evapotranspiration and Growth in the Wheat Crop," Australian Journal of Agricultural Research 17 (1966): 255-67; W. R. Stern, "Evapotranspiration of Saffower at Three Densities of Sowing," Australian Journal of Agricultural Research 16 (1965): 961-71. 17. L. J. L. Deij, "The Lysimeter Station at Castricum (Holland)," Compte Rendus, Association International de Hydrologie 3 (1954): 203-4. 18. G. L. Swartzman and G. M. Van Dyne, "An Ecologically Based Simulation- Optimization Approach to Natural Resource Planning," Annual Review of Ecology and Systematics 3 (1972): 347-98. 19. R. J. More, "The Basin Hydrological Cycle," Water, Earth and Man, ed. R. J. Chorley (London: Methuen & Co., Ltd., 1969), pp. 67-76. 20. M. J. Kirkby, "Erosion by Water on Hill Slopes," Water, Earth and Man, ed. R. J. Chorley (London: Methuen & Co., Ltd., 1969), pp. 229-38. 21. Farm Planners' Engineering Handbook for the Upper Mississippi Watershed (Milwaukee: U.S. Soil Conservation Service, 1953).  Physical Setting 25 oak forest to 47 per cent in a contoured, cultivated plot and 58.2 per cent in a cultivated plot with the rows downslope." Mean annual rainfall has varied from 2,500 to 4,000 millimeters. Certain land-use patterns also affect the amount of runoff by altering the infiltration capacity of the soil. The infiltration capacity varies directly with the soil texture, being high for loamy sand and low for clay soilsat Experiments in North Carolina and Utah show that forest transformed into pasture has a much lower infiltration rate than do similar areas trans- formed to cornfields, because of the compacting effect of the cattle walking on the surface?2 Other studies suggest that these effects may be exagger- ated by overgrazing.25 EROSION The excessive removal of soil by runoff is a consequence to be avoided in watershed management. The degree of erosion caused by a given amount of runoff is proportional to the slope, the distance over which the runoff travels to the bottom of the watershed, the force of the rainfall, and the soil erodibility. The last variable is dependent on the depth and permeability of the soil as well as on the amount and kind of vegetation covering the soil during the peak rainfall periods?2t Relative erosion values for three sets of data in three different areas are shown in Table 2. In general, the trends shown by these data are similar to the pattern observed for runoff data. SOIL-WATER RELATIONSHIPS To assess the interactions of these factors and to determine underlying hydrological relationships, a base-line hydrological study was performed on the Jagua watershed within the Jagua-Bao region (see Figure 7). This 22. H. G. Meginnis, Effect of Cover on Surface Runoff and Erosion on the Loessial Uplands of Mississippi, U.S. Department of Agriculture Circular no. 347 (Washington, D.C.: U.S. Government Printing Office, 1935). 23. M. A. Morgan, "Overland Flow and Man," Water, Earth and Man, ed. R. J. Chorley (London: Methuen & Co., Ltd., 1969), pp. 239-55. 24. R. E. Dils, A Guide to the Coweeta Hydrologic Laboratory (Asheville, N.C.: Southeast Forest Experiment Station, U.S. Department of Agriculture Forest Service, 1957). 25. F. R. Dreibelbis and F. A. Post, "An Inventory of Soil Water Relationships on Woodland, Pasture and Cultivated Soils," Soil Science Society of America Pro- ceedings 6 (1941): 462-73; Watershed Research Aids Salt River Valley (South- western Forest and Range Experiment Station, 1947); and R. E. Dils, Influence of Forest Cutting and Mountain Farming on Some Vegetation, Surface Soil, and Surface Runoff Characteristics (Asheville, N.C.: Southeast Forest Experiment Sta- tion, U.S. Department of Agriculture, 1953). 26. Kirkby, "Erosion by Water on Hill Slopes." Physical Setting 25 oak forest to 47 per cent in a contoured, cultivated plot and 58.2 per cent in a cultivated plot with the rows downslope.e Mean annual rainfall has varied from 2,500 to 4,000 millimeters. Certain land-use patterns also affect the amount of runoff by altering the infiltration capacity of the soil. The infiltration capacity varies directly with the soil texture, being high for loamy sand and low for clay soils.nt Experiments in North Carolina and Utah show that forest transformed into pasture has a much lower infiltration rate than do similar areas trans- formed to cornfields, because of the compacting effect of the cattle walking on the surface. Other studies suggest that these effects may be exagger- ated by overgrazing5 EROSION The excessive removal of soil by runoff is a consequence to be avoided in watershed management. The degree of erosion caused by a given amount of runoff is proportional to the slope, the distance over which the runoff travels to the bottom of the watershed, the force of the rainfall, and the soil erodibility. The last variable is dependent on the depth and permeability of the soil as well as on the amount and kind of vegetation covering the soil during the peak rainfall periodst Relative erosion values for three sets of data in three different areas are shown in Table 2. In general, the trends shown by these data are similar to the pattern observed for runoff data. SOIL-WATER RELATIONSHIPS To assess the interactions of these factors and to determine underlying hydrological relationships, a base-line hydrological study was performed on the Jagua watershed within the Jagua-Bao region (see Figure 7). This 22. H. G. Meginnis, Effect of Cover on Surface Runoff and Erosion on the Loessial Uplands of Mississippi, U.S. Department of Agriculture Circular no. 347 (Washington, D.C.: U.S. Government Printing Office, 1935). 23. M. A. Morgan, "Overland Flow and Man," Water, Earth and Man, ed. R. J. Chorley (London: Methuen & Co., Ltd., 1969), pp. 239-55. 24. R. E. Dils, A Guide to the Coweeta Hydrologic Labtoatory (Asheville, N.C.: Southeast Forest Experiment Station, U.S. Department of Agriculture Forest Service, 1957). 25. F. R. Dreibelbis and F. A. Post, "An Inventory of Soil Water Relationships on Woodland, Pasture and Cultivated Soils," Soil Science Society of America Pro- ceedings 6 (1941): 462-73; Watershed Research Aids Salt River Valley (South- western Forest and Range Experiment Station, 1947); and R. E. Dils, dnfluence of Forest Cutting and Mountain Farming on Some Vegetation, Surface Soil, and Surface Runoff Characteristics (Asheville, N.C.: Southeast Forest Experiment Sta- tion, U.S. Department of Agriculture, 1953). 26. Kirkby, "Erosion by Water on Hill Slopes." Physical Setting 25 oak forest to 47 per cent in a contoured, cultivated plot and 58.2 per cent in a cultivated plot with the rows downslope."2 Mean annual rainfall has varied from 2,500 to 4,000 millimeters. Certain land-use patterns also affect the amount of runoff by altering the infiltration capacity of the soil. The infiltration capacity varies directly with the soil texture, being high for loamy sand and low for clay soils.w Experiments in North Carolina and Utah show that forest transformed into pasture has a much lower infiltration rate than do similar areas trans- formed to cornfields, because of the compacting effect of the cattle walking on the surface." Other studies suggest that these effects may be exagger- ated by overgrazing."t EROSION The excessive removal of soil by runoff is a consequence to be avoided in watershed management. The degree of erosion caused by a given amount of runoff is proportional to the slope, the distance over which the runoff travels to the bottom of the watershed, the force of the rainfall, and the soil erodibility. The last variable is dependent on the depth and permeability of the soil as well as on the amount and kind of vegetation covering the soil during the peak rainfall periodstt Relative erosion values for three sets of data in three different areas are shown in Table 2. In general, the trends shown by these data are similar to the pattern observed for runoff data. SOIL-WATER RELATIONSHIPS To assess the interactions of these factors and to determine underlying hydrological relationships, a base-line hydrological study was performed on the Jagua watershed within the Jagua-Bao region (see Figure 7). This 22. H. G. Meginnis, Effect of Cover on Surface Runoff and Erosion on the Loessial Uplands of Mississippi, U.S. Department of Agriculture Circular no. 347 (Washington, D.C.: U.S. Government Printing Office, 1935). 23. M. A. Morgan, "Overland Flow and Man," Water, Earth and Man, ed. R. J. Chorley (London: Methuen & Co., Ltd., 1969), pp. 239-55. 24. R. E. Dils, A Guide to the Coweeta Hydrologic Laboratory (Asheville, N.C.: Southeast Forest Experiment Station, U.S. Department of Agriculture Forest Service, 1957). 25. F. R. Dreibelbis and F. A. Post, "An Inventory of Soil Water Relationships on Woodland, Pasture and Cultivated Soils," Soil Science Society of America Pro- ceedings 6 (1941): 462-73; Watershed Research Aids Salt River Valley (South- western Forest and Range Experiment Station, 1947); and R. E. Dils, Influence of Forest Cutting and Mountain Farming on Some Vegetation, Surface Soil, and Surface Runoff Characteristics (Asheville, N.C.: Southeast Forest Experiment Sta- tion, U.S. Department of Agriculture, 1953). 26. Kirkby, "Erosion by Water on Hill Slopes." I _ yP Z i E  Physical Setting 27 TABLE 2 RELAVE ERSINe VALUSr FRo VARYING LANDa-USE PRACTIES elative Erosion Vales Lad Use Pacific Northweroar South Africa28 Pueto Ric029 Forest .01-1 1 1.02 Pastures in huamid regiees .01-1 1.15 Range or pans pasture 5-10 2 Orchardsswith cover crops 20 Orchards cteen-tilted 90 3.11 Row crops and fattow 100 3 5.43 watershed was selected because it has areas of each life zane located within it and is therefore represeutative of ecalogical conditions within the entice region (see Appendix A). In the analysis, a basic assamption was that the region was in an undisturbed state. While this premise reln- gated Jagtta-Bao to an "ideal" situation devoid of human influence, the relationships derived were nonetheless valid insofar as they explained the interacti~on of physical environmental parameters and as such peovided lbhe necessary base line for subsequent development of a culturally oei- ented, ecological land-use model. To evaluate hydrological relationships, climatological data weee grouped according to the Holdridge Life Zone Classificationn30 Mean monthly eainfall and temperature were calculated for the period of climatological record and, along with soils data, were used to generate average monthly and yearly waler balance-runoff figures for each station.rt Water balance 27. G.W. Msgrave, "Etimting LndEosio-Sheetronsion," Compte Redu, Association Internationat de Hydrologie 1 119541: 386-92. 21. a. A. Vorster, "Soil Erosion and Some Problems Carrested With Its Con- tsol," Proceedings of Institute of Civil Engiseers' Conference on Biological & Civil Engixeering (1949): 41-63. 29. J. a. Nail, The Silting of Cannillas Reservoir, Parto Riss, UtS. Department ot Agricxlture, Sail Consesation Service TP-119 (Washington, D.C.: U.S. ov- ernment Prirting Office, 1953). 30. L. R. Holdridge, Life Zone Ecology ( San Josi, Cotta Rica: Tropical Science Ceuter, 1964), pp. 13-19. 31. Reconnaissance-level information or soil series for the study region is pro- videdby the nASeport ofatrleesorces (Reconocisieotry evalacidef. Be- causeof theeploatory nalte of this information, it was reessary to nsr supplesentarey dale fram comparably desired her intensively studied Puerto Rican soils. Since both the Doseinican tRepublic and Poerno Rico wee sbjected to similar tectonic and morphalogical prartsres, it is postated that a Pareto Rican soil exhbiiting similas physical and chemical proprties cnn provide as appronimation of the Dominican Baiguate-Hondo-Auyamas-Jimeoa Association. The Las Piedras Soil SeriefounudinPuertoico washoen brcause of itsmrphoeetic simiarity to the abave-mentionrd ominican sails. Fos a detailed desription of Las Piedeas Physical Setting 27 TABLE 2 Roetive Erosiont Values Land Use PaificgNorchxeettr South Africa28 Purto Ric029 Forest .01-1 1 t.02 Pastures in humid regions .01-1 1.15 Rangor spar pature 5-10 2 Orchtardswith covrcrops 20 Orchards clear-tilled 90 3.11 Rowe crops end fallow. 100 3 5.43 watershed was selected because it has areas of each life zone located within it and is therefore representative of ecological conditions within the entire region (see Appendix A). In the analysis, a banic assumption was that the region was in an undisturbed state. While this premise rele- gated Jagua-Baa to an "ideal" situation devoid of human influence, the relationships derived were nonetheless valid insofar as they explained the interaclion of physical environmental parameters and an such provided lbhe recessary base lire for nubsequent development at a cultueally ori- ented, ecological lard-use model. To evaluate hydrological relationships, climatological data were grouped according 10 the Holdridge Life Zone Classificationat0 Mean monthly rainfall and temperature were calculated foe the period of climatological record and, along with sails data, ware used to generate average monthly and yearly water balance-runoff figures far each statior.31 Water balance 27. G3. W. Musgrae, "Ettiseating Land Erosion-Sheen Erosion," Coseete Rendus, Association International de Hydrologic 1 11954): 386-92. 28. E. A. Varstrr, "Soil Erosion and Somr Prohlrems Corrected With Its Con- trot," Proceedings of fnstitute of Civil Engineers' Confrence on Biological & Civil Ergineering (1949): 48-63. 29. J. J. Nall, The Silting of Caonillas Reservoir, Puerto Rico, U.S. Department oe Agricultre, tail Concration Serice TP-11t9 (Washingtnr, D.C.: U.S. Gov- ernment Printing Office, 1953). 30. L. R. Holtdridge, Life Zone Ecology (San fosi, Casto Rise, Tropicat Scirne Center, 1964), pp. 13-19. 31. Reonraissanor-level information or sail series foe the cindy rreion it pro- videdhbythe OAS report o atralcesores (Reconocimiento y ealacidn). Be- casse of the exploratory nature at this intormatio, it was necessary to ncr supplementary date erom comparably derived bet intencively studied Purto Rian soils. Since both thr Dominican Republic and Pueto Rica were subjected to similar tectonic red morphological processes, it is postulated that a Peertoa Ricer soil exhibiting similar physical and chemical propertirs ear proside an apprnximation og the Dominican Baiguate-Hondo-Auamas-timenoa Asscatioen. The Lee Piedras SoiiSeriesgfondinaPurrtoRicowas chosen because oftits mrphogonrticsimilrity to the aover-mentined Dominican soils. For a detailed description of Las Piedras Physical Sereing 27 TABLE 2 RELATIVE EROSION VALtS FRn VARYING LND-USr PRAsCTICES Relatise Erosion Values Laud Use retinac Nerthxrstts South Afria28c Perto Riceet Forest .01-1 1 1.02 Pastures in humid egions .01-1 1.15 Rangr as poor pasture 5-10 2 Orchardsxwith covreracrps 20 Orchards clean-tilred 90 3.11 Rose craps and fallow. 100 3 5.43 watershed was selected because it baa areas of each life zone located within it and in therefore representative of ecological conditions within the entire region (see Appendix A). In the analysis, a basic assumption was that the region wan in an undisturbed state. While this premise rele- gated Jagua-Bao to or "ideal" situation devoid of human influence, the relationships derived were nonetheless valid insofar as they explained the interaction of physical environmental parameters and as such provided the necessary base line for subsequent development of a cellar ally ori- ented, ecological lard-use model. To evaluate hydrological relationships, climatlogical data were grouped acording to the Holdridge Life Zone Classificationr30 Mean monthly rainfall and temperature were calculated for the period of climatological record and, along with sails data, were used to generate overage monthly and yearly water balance-runoff figures for each statios.31 Water balance 27. 13. W. Musgravr, "Estimating Lard Ersion-Sheet Erosion," Compe Rendus, Association Inernational de Hydrologie 1 (1954): 316-92. 29. J. A. Vorster, "Soil Erosion and Same Problems Connected With Its Cont- tot," Proceedinge of Institute of Civil Esgineerse Conference en Biological & Civl Engineering (1949): 46-63. 29. J. J. Nail, The Silting of Conillas Reserroir, Puerto Rico. U.S. Drpartmrnt of Agriculture, Soil Conserration Sersice TP-119 (Washington, D.C.: U.S. Goev- rnment Printing Oftice, 1933). 30. L. R. Holdride, Life Zone Ecology (See Jos, Caste Rica: Tropicl Scirence Cester, 1964), pp. 13-19. 31. Recennaissance-level information an toil series tor the study region is pro- videdhbythe OS report otfenatrlrsorcs (Reconocimietry ealarif). Br- cratse of thr exploatory ntrer at this intormation, it seas necessary is usr supplesentaery data from comparably derived hat intensively studied Puerto Riser soils. Since both the Domnican epublic end Poro Rice wert subjected to similar tectnic and morphlogical proeses, it is postulated that a Purto Ricer soil exhibiting similar physial and chemical properties can preside an approximati on at the Dominisc Baiguatr-Hondo-Auyameas-Jimnoa Associatio. Tho Let Piedras Soil Series foxed in Puerto Rica was chaser because of itt seorphogrneic similarity to lbs abosr-mentioned Domirican soiln. For s detailed description of Las Piedras  28 Population and Energy calculations were made for a soil depth assumed to be 300 millimeters, and also for 200- and 100-millimeter soil depths in order to examine the relationship between varying depth and runoff (see Appendix B).32 In calculating the water budgets, it was noted that the Mata Grande Station within the Lower Montane Wet Forest (wf-LM) was situated at this zone's lower attitudinal limit. To obtain a more representative life zone coverage for Mata Grande, two phantom stations were created at eleva- tions of 1,500 meters and 2,100 meters. Landsberg's formulas were used to compute temperature and rainfall data for these additional high-elevation stations 3 Since mean annual and mean monthly runoff figures were required to determine the relative amounts of runoff derived from each life zone, it was necessary to measure with a planimeter the total area within each life zone and then to weight each mean monthly runoff figure by the number of seconds in its corresponding month. These runoff figures were tallied to obtain both the total mean monthly runoff and the mean annual runoff in meters cubed per second for the Jagua watershed. The computer output from the runoff subroutine program is presented in Table 3 with two sets of data: the first is runoff calculated solely from the existing meteorologi- cal stations; the second is runoff including estimates of data for the two additional Mata Grande stations. The diagrams in Figures 8 and 9 are based on the latter calculations (Appendix C) and graphically show the amount and origin of runoff for each life zone in the Jagua watershed. Table 4 compares runoff from the Jagua River gauging station with the two sets of water balance calculations. soils, see M. A. Lugo-Lopez, Moisture Relationships of Puerto Rican Soils. Tech- nical Paper no. 9 (Rio Piedras: University of Puerto Rico, Agricultural Experiment Station, 1953), p. 91. Four important soil characteristics were used in these calcu- lations: field capacity (36 per cent); bulk density (1.36 g-cm.3); permanent wilting point (17 per cent); and average depth (30 centimeters). The first three soil para- meters were obtained from the Lugo-Lopez study, while the fourth parameter was estimated by the authors based upon their consideration of the minimum average root depth for a mature pine forest in the Lower Montane Wet Forest life zone (wf-LM). 32. An interactive terminal computer program for the ism 360 was designed by S. Gladin to facilitate water balance calculations and a subroutine was developed to calculate monthly runoff in cubic meters per second for each life zone. Appendix B contains both the computer program for the water balance calculations and the water budgets for representative life zones at 300-, 200-, and 100-millimeter soil depths. Appendix C gives the subroutine computer program and runoff calculations by life zone in cubic meters per second at 300-, 200-. and 100-millimeter soil depths. Both sets of data contain calculations for two additional altitudinal stations in the wf-LM life zone. 33. Helmut Landsberg, Physical Climatology (DuBois. Pa.: Gray Printing Co., 1968), pp. 161, 176. 28 Population and Energy calculations were made for a soil depth assumed to be 300 millimeters, and also for 200- and 100-millimeter soil depths in order to examine the relationship between varying depth and runoff (see Appendix B)3 In calculating the water budgets, it was noted that the Mata Grande Station within the Lower Montane Wet Forest (wf-LM) was situated at this zone's lower altitudinal limit. To obtain a more representative life zone coverage for Mata Grande, two phantom stations were created at eleva- tions of 1,500 meters and 2,100 meters. Landsberg's formulas were used to compute temperature and rainfall data for these additional high-elevation stations? Since mean annual and mean monthly runoff figures were required to determine the relative amounts of runoff derived from each life zone, it was necessary to measure with a planimeter the total area within each life zone and then to weight each mean monthly runoff figure by the number of seconds in its corresponding month. These runoff figures were tallied to obtain both the total mean monthly runoff and the mean annual runoff in meters cubed per second for the Jagua watershed. The computer output from the runoff subroutine program is presented in Table 3 with two sets of data: the first is runoff calculated solely from the existing meteorologi- cal stations; the second is runoff including estimates of data for the two additional Mata Grande stations. The diagrams in Figures 8 and 9 are based on the latter calculations (Appendix C) and graphically show the amount and origin of runoff for each life zone in the Jagua watershed. Table 4 compares runoff from the Jagua River gauging station with the two sets of water balance calculations. soils, see M. A. Lugo-Lopez, Moisture Relationships of Puerto Rican Soils, Tech- nical Paper no. 9 (Rio Piedras: University of Puerto Rico, Agricultural Experiment Station, 1953), p. 91. Four important soil characteristics were used in these calcu- lations: field capacity (36 per cent); bulk density (1.36 gm-3); permanent wilting point (17 per cent); and average depth (30 centimeters). The first three soil para- meters were obtained from the Lugo-Lopez study, while the fourth parameter was estimated by the authors based upon their consideration of the minimum average root depth for a mature pine forest in the Lower Montane Wet Forest life zone (wf-LM). 32. An interactive terminal computer program for the tem 360 was designed by S. Gladin to facilitate water balance calculations and a subroutine was developed to calculate monthly runoff in cubic meters per second for each life zone. Appendix B contains both the computer program for the water balance calculations and the water budgets for representative life zones at 300-, 200-, and 100-millimeter soil depths. Appendix C gives the subroutine computer program and runoff calculations by life zone in cubic meters per second at 300-. 200-, and 100-millimeter soil depths. Both sets of data contain calculations for two additional altitudinal stations in the wf-LM life zone. 33. Helmut Landsberg, Physical Climatology (DuBois. Pa.: Gray Printing Co.. 1968), pp. 161, 176. 28 Population and Energy calculations were made for a soil depth assumed to be 300 millimeters, and also for 200- and 100-millimeter soil depths in order to examine the relationship between varying depth and runoff (see Appendix B).tt In calculating the water budgets, it was noted that the Mata Grande Station within the Lower Montane Wet Forest (wf-LM) was situated at this zone's lower altitudinal limit. To obtain a more representative life zone coverage for Mata Grande, two phantom stations were created at eleva- tions of 1,500 meters and 2,100 meters. Landsberg's formulas were used to compute temperature and rainfall data for these additional high-elevation stations.3 Since mean annual and mean monthly runoff figures were required to determine the relative amounts of runoff derived from each life zone. it was necessary to measure with a planimeter the total area within each life zone and then to weight each mean monthly runoff figure by the number of seconds in its corresponding month. These runoff figures were tallied to obtain both the total mean monthly runoff and the mean annual runoff in meters cubed per second for the Jagua watershed. The computer output from the runoff subroutine program is presented in Table 3 with two sets of data: the first is runoff calculated solely from the existing meteorologi- cal stations; the second is runoff including estimates of data for the two additional Mata Grande stations. The diagrams in Figures 8 and 9 are based on the latter calculations (Appendix C) and graphically show the amount and origin of runoff for each life zone in the Jagua watershed. Table 4 compares runoff from the Jagua River gauging station with the two sets of water balance calculations. soils, see M. A. Lugo-Lopez, Moisture Relationships of Puerto Rican Soils, Tech- nical Paper no. 9 (Rio Piedras: University of Puerto Rico, Agricultural Experiment Station, 1953), p. 91. Four important soil characteristics were used in these calcu- lations: field capacity (36 per cent); bulk density (1.36 g-cm-); permanent wilting point (17 per cent); and average depth (30 centimeters). The first three soil para- meters were obtained from the Lugo-Lopez study, while the fourth parameter was estimated by the authors based upon their consideration of the minimum average root depth for a mature pine forest in the Lower Montane Wet Forest life zone (wf-LM). 32. An interactive terminal computer program for the BM 360 was designed by S. Gladin to facilitate water balance calculations and a subroutine was developed to calculate monthly runoff in cubic meters per second for each life zone. Appendix B contains both the computer program for the water balance calculations and the water budgets for representative life zones at 300-, 200-, and 100-millimeter soil depths. Appendix C gives the subroutine computer program and runoff calculations by life zone in cubic meters per second at 300-, 200-, and 100-millimeter soil depths. Both sets of data contain calculations for two additional altitudinal stations in the wf-LM life zone. 33. Helmut Landsberg, Physical Climatology (DuBois, Pa.: Gray Printing Co., 1968), pp. 161, 176.  Life Zone 300 mm % 200 mm % 100 rom % Set 1 df-S 0.08 0.3 0.13 0.4 0.22 0.6 mf-S 1.96 6.5 3.43 10.5 5.32 15.4 mf-LM 1.30 4.2 1.30 4.1 1.41 4.0 w&LM 27.08 89.0 27.08 85.0 27.29 80.0 Total 30.42 100.0 31.94 100.0 34.24 100.0 300 mm % 200 mm % 100 mm % 0.08 0.3 0.13 0.4 0.22 0.6 1.96 6.5 3.43 10.5 5.32 15.4 1.30 4.2 1.30 4.1 1.41 4.0 27.08 89.0 27.08 85.0 27.29 80.0 30.42 100.0 31.94 100.0 34.24 100.0 0.08 0.2 0.13 0.3 0.22 0.4 1.96 3.9 3.43 6.7 5.32 10.0 1.30 2.6 1.30 2.5 1.41 2.6 46.41 93.3 46.41 90.5 46.48 87.0 49.75 100.0 51.27 100.0 53.43 100.0  F = > z z z _C _ 33 r ut ', Al Hil[L Z .: r: a 7 a 7 m / a 9 . Han F a F z z N- = _ 7 1 - z a r a?- b z a a Enna F;'az-F = s o 3 3 N- 3= coc 2 =55 - 3 3 3  LIFE ZONES Soil depth I:,'i! lil; df-S m f-livt of 00mm To cal r noff m(-5 v(-LM 30.32 m3-sec ty- Q Hydrologic basin av rage LIEF ZONES Soil depth O df-S mf-1,M o{ 300mm Total naff ® mf-S -I'm 30.32 x- fy'f Q Hydrologic basin a rage LIFE ZONES Soil depth dF-S mf-LM 00.. Total runoff © f-S ,f-LM 30.32 m3sec' -y Hydrologic basin av rage SLPTEMBI I; OCTOBER 1OEMBER nr"cF.MSLR ' 0 1 2 3 4m3sec 5 6 7 8 SEPTEMBER Dc O13ER NOVEMBER DEC'F.MBER U , 1 2 3 4m3sec 1 $ 6 ] 8 I I I I I I I I I I I I I 1 I I SEPTEMBER OC'T'OBER N 0V EMB CR DECEMBER 0 I 2 3 4m3-sec 5 6 7 8  32 Population and Energy TABLE 4 COMPARISON OF DISCHARGE DATA FOR JAGUA RIvER BASIN Discharge in Discharge in Discharge in Wet Year Dry Year Average Year (m3sec-) (masec-) (ms-secI ) Pinalito Gauging Station 15.1 5.3 5.9 for Jagua River4 Estimated runoff from empirical data at - - 2.5 300 mm soil depth Estimated runoff from empirical data plus two phantom stations - - 4.1 in wf-LM life zone at 300 mm soil depth The evaluation of these data should take into account the following conditions. First, it was assumed that composite mean annual tempera- ture and rainfall statistics were the best approximation of climatological parameters within the respective ecological life zones. A comparison of these empirical meteorological statistics with those in the Holdridge life zone nomograph verified the assumption that the station data were repre- sentative of the life zone in which they were collected. Second, a further assumption was that the vegetation in each life zone was mature forest on zonal soils. This implied that the soil moisture status and runoff calcu- lations would appear relatively near their minimum or lower values, since the evapotranspiration of a mature forest proceeds at a greater rate than that of mixed farming or pasture at the same location. The foregoing assumptions should be kept in mind when viewing the soil moisture status matrix and maps (see Table 5 and Figures 10, 11, 12, and 13).5 As an example, Figure 10 shows soil moisture status for the December-January period and the data indicate that the Subtropical Moist Forest (mf-S) is relatively dry. If this zone were in pasture or crops, and therefore evapotranspiring at a lower rate than a mature pine forest, there would be more water available to recharge the soil. This additional mois- 34. Societ6 Grenobloise d'Etudes er d'Applications Hydrauliques (sOGREAH), Surveys for the Multipurpose Development of the Yaque del Norte and Yaque del Sur River Basins, report prepared for the government of the Dominican Republic (INDRHI) and the International Bank for Reconstruction and Development (man) acting as executing agency for the United Nations Development Program (Special Fund), 6 vols. (Grenoble, France: soGREAH, 1968). 5: 8, 10, 12. 35. L. R. Holdridge et al., Forest Environment and Tropical Life (Elmsford, N.Y.: Pergamon Press, Inc., 1971), pp. 48-58. 32 Population and Energy TABLE 4 COMPARISON OF DIsCHARGE DATA FOR JAGUA RIVER BASIN Discharge in Discharge in Discharge in Wet Year Dry Year Average Year (ms.secaI) (m3.sec-1) (ma-sec-1) Pinalito Gauging Station 15.1 5.3 5.9 for Jagua Rivera Estimated runoff from empirical data at - - 2.5 300 mm soil depth Estimated runoff from empirical data plus two phantom stations - - 4.1 in wf-LM life zone at 300 mm soil depth The evaluation of these data should take into account the following conditions. First, it was assumed that composite mean annual tempera- ture and rainfall statistics were the best approximation of climatological parameters within the respective ecological life zones. A comparison of these empirical meteorological statistics with those in the Holdridge life zone nomograph verified the assumption that the station data were repre- sentative of the life zone in which they were collected. Second, a further assumption was that the vegetation in each life zone was mature forest on zonal soils. This implied that the soil moisture status and runoff calcu- lations would appear relatively near their minimum or lower values, since the evapotranspiration of a mature forest proceeds at a greater rate than that of mixed farming or pasture at the same location. The foregoing assumptions should be kept in mind when viewing the soil moisture status matrix and maps (see Table 5 and Figures 10, 11, 12, and 13):35 As an example, Figure 10 shows soil moisture status for the December-January period and the data indicate that the Subtropical Moist Forest (mf-S) is relatively dry. If this zone were in pasture or crops, and therefore evapotranspiring at a lower rate than a mature pine forest, there would be more water available to recharge the soil. This additional mois- 34. Societs Grenobloise d'Etudes et d'Applications Hydrauliques (soGREAHl. Surveys for the Multipurpose Development of the Yaque del Norte and Yaque del Sur River Basins, report prepared for the government of the Dominican Republic (snea) and the International Bank for Reconstruction and Development (mRD) acting as executing agency for the United Nations Development Program (Special Fund), 6 vols. (Grenoble, France: SOGREAH, 1968), 5: 8, 10, 12. 35. L. R. Holdridge et al., Forest Environment and Tropical Life (Elmsford, N.Y.: Pergamon Press, Inc., 1971), pp. 48-58. 32 Population and Energy TABLE 4 COMPARISON OF DISCHARGE DATA FOR JAGUA RIvER BASIN Discharge in Discharge in Discharge in Wet Year Dry Year Average Year (m3-sec-1) (mr-sect) (m3+sec-) Pinalito Gauging Station 15.1 5.3 5.9 for Jausa River34 Estimated runoff from empirical data at - - 2.5 300 mm soil depth Estimated runoff from empirical data plus two phantom stations - - 4.1 in wf-LM life zone at 300 mm soil depth The evaluation of these data should take into account the following conditions. First, it was assumed that composite mean annual tempera- ture and rainfall statistics were the best approximation of climatological parameters within the respective ecological life zones. A comparison of these empirical meteorological statistics with those in the Holdridge life zone nomograph verified the assumption that the station data were repre- sentative of the life zone in which they were collected. Second, a further assumption was that the vegetation in each life zone was mature forest on zonal soils. This implied that the soil moisture status and runoff calcu- lations would appear relatively near their minimum or lower values, since the evapotranspiration of a mature forest proceeds at a greater rate than that of mixed farming or pasture at the same location. The foregoing assumptions should be kept in mind when viewing the soil moisture status matrix and maps (see Table 5 and Figures 10, 11, 12, and 13).3a As an example, Figure 10 shows soil moisture status for the December-January period and the data indicate that the Subtropical Moist Forest (mf-S) is relatively dry. If this zone were in pasture or crops, and therefore evapotranspiring at a lower rate than a mature pine forest, there would be more water available to recharge the soil. This additional mois- 34. Soci6t6 Grenobloise d'Etudes et d'Applications Hydrauliques (sOGREAH, Surveys for the Multipurpose Development of the Yaque del Norte and Yaque del Sur River Basins, report prepared for the government of the Dominican Republic (mm) and the International Bank for Reconstruction and Development (mRD) acting as executing agency for the United Nations Development Program (Special Fund), 6 vols. (Grenoble, France: SOGREAH, 1968). 5: 8, 10, 12. 35. L. R. Holdridge et al., Forest Environment and Tropical Life (Elmsford, N.Y.: Pergamon Press, Inc., 1971), pp. 48-58.  Physical Setting 33 TABLE 5 COMPOsITE MEDIAN MoISTURE STATUS BY LIFE ZONES AND SEASONs Life Zone Dec.-Jan. Feb.-Mar. Apr.-Jul. Aug.-Nov. df-S Moist Dry Moist Drought mf-S Dry Drought Dry Drought mf-LM Moist Drought Moist Wet wf-LM Moist Moist Wet Excessively wet ture could lengthen the actual growing season. Altering evapotranspiration rates by changing vegetation types is, therefore, analogous to decreasing or increasing rainfall within certain limits. The difference here is that evapotranspiration is dependent upon the amount of soil moisture in situ available to plants, while precipitation is relatively independent of soil moisture. A similar effect can be seen by increasing or decreasing soil depth. In Table 3 it is evident that, as soil depth is decreased, the per- centage of runoff contributed by the Subtropical Dry Forest (df-S) and the Subtropical Moist Forest (mf-S) life zones is increased. It will be recalled from the discussion of regional climatology that the df-S life zone is located on the piedmont flanking the Central Mountain Range. In con- trast, the Lower Montane Moist Forest (mf-LM) life zone is on the lower northern slopes of the Central Range, while the Lower Montane Wet Forest (wf-LM) life zone lies near the summit of that range. Both the mf-LM and wf-LM life zones are recipients of orographic precipitation. In this case, the net effect of changing soil depth is to lower the field capacity of the soil and, therefore, to allow the soil to recharge at a faster rate while incoming precipitation is held constant. In those areas where the soil is perennially at or near its field capacity, little change in the amount of runoff would be noticed. But in soils where field capacity is reached infrequently, considerable changes in runoff are discernible be- cause of the faster recharge rate and lower water-holding capacity. Thus, one would expect that with decreasing soil depth, the drier life zones would contribute an increasing percentage of the total runoff, while the wetter life zones would show a declining contribution. Table 4 compares the volume of discharge of the Jagua River at the Pinalito Gauging Station for wet, dry, and average years with the water balance calculations under both sets of assumptions. It is readily apparent that the estimated runoff from the first set of calculations grossly under- estimates the actual measured discharge. The second set, based on adjust- ments within the wf-LM life zone, provides a reasonable approximation of the measured discharges for both dry and wet years. The latter compu- Physical Setting 33 TABLE 5 COMPOSITE MEDIAN MOIsTURE STATUs er LIFE ZONES AND SEASONs Life Zone Dec-Jan. Feb.-Mar. Apr.-Jul. Aug.-Nov. df-S Moist Dry Moist Drought mf-S Dry Drought Dry Drought mf-LM Moist Drought Moist Wet wf-LM Moist Moist Wet Excessively wet lure could lengthen the actual growing season. Altering evapotranspiration rates by changing vegetation types is, therefore, analogous to decreasing or increasing rainfall within certain limits. The difference here is that evapotranspiration is dependent upon the amount of soil moisture in situ available to plants, while precipitation is relatively independent of soil moisture. A similar effect can be seen by increasing or decreasing soil depth. In Table 3 it is evident that, as soil depth is decreased, the per- centage of runoff contributed by the Subtropical Dry Forest (df-S) and the Subtropical Moist Forest (mf-S) life zones is increased. It will be recalled from the discussion of regional climatology that the df-S life zone is located on the piedmont flanking the Central Mountain Range. In con- trast, the Lower Montane Moist Forest (mf-LM) life zone is on the lower northern slopes of the Central Range, while the Lower Montane Wet Forest (wf-LM) life zone lies near the summit of that range. Both the mf-LM and wf-LM life zones are recipients of orographic precipitation. In this case, the net effect of changing soil depth is to lower the field capacity of the soil and, therefore, to allow the soil to recharge at a faster rate while incoming precipitation is held constant. In those areas where the soil is perennially at or near its field capacity, little change in the amount of runoff would be noticed. But in soils where field capacity is reached infrequently, considerable changes in runoff are discernible be- cause of the faster recharge rate and lower water-holding capacity. Thus, one would expect that with decreasing soil depth, the drier life zones would contribute an increasing percentage of the total runoff, while the wetter life zones would show a declining contribution. Table 4 compares the volume of discharge of the Jagua River at the Pinalito Gauging Station for wet, dry, and average years with the water balance calculations under both sets of assumptions. It is readily apparent that the estimated runoff from the first set of calculations grossly under- estimates the actual measured discharge. The second set, based on adjust- ments within the wf-LM life zone, provides a reasonable approximation of the measured discharges for both dry and wet years. The latter compu- Physical Setting 33 TABLE 5 COMPOSITE MEDIAN MOISTURE STATUs BY LIFE ZONEs AND SEASONS Life Zone Dec.-Jan. Feb.-Mar. Apr-Jul. Aug-Nov. df-S Moist Dry Moist Drought mf-S Dry Drought Dry Drought mf-LM Moist Drought Moist Wet wf-LM Moist Moist Wet Excessively wet ture could lengthen the actual growing season. Altering evapotranspiration rates by changing vegetation types is, therefore, analogous to decreasing or increasing rainfall within certain limits. The difference here is that evapotranspiration is dependent upon the amount of soil moisture in situ available to plants, while precipitation is relatively independent of soil moisture. A similar effect can be seen by increasing or decreasing soil depth. In Table 3 it is evident that, as soil depth is decreased, the per- centage of runoff contributed by the Subtropical Dry Forest (df-S) and the Subtropical Moist Forest (mf-S) life zones is increased. It will be recalled from the discussion of regional climatology that the df-S life zone is located on the piedmont flanking the Central Mountain Range. In con- trast, the Lower Montane Moist Forest (mf-LM) life zone is on the lower northern slopes of the Central Range, while the Lower Montane Wet Forest (wf-LM) life zone lies near the summit of that range. Both the mf-LM and wf-LM life zones are recipients of orographic precipitation. In this case, the net effect of changing soil depth is to lower the field capacity of the soil and, therefore, to allow the soil to recharge at a faster rate while incoming precipitation is held constant. In those areas where the soil is perennially at or near its field capacity, little change in the amount of runoff would be noticed. But in soils where field capacity is reached infrequently, considerable changes in runoff are discernible be- cause of the faster recharge rate and lower water-holding capacity. Thus, one would expect that with decreasing soil depth, the drier life zones would contribute an increasing percentage of the total runoff, while the wetter life zones would show a declining contribution. Table 4 compares the volume of discharge of the Jagua River at the Pinalito Gauging Station for wet, dry, and average years with the water balance calculations under both sets of assumptions. It is readily apparent that the estimated runoff from the first set of calculations grossly under- estimates the actual measured discharge. The second set, based on adjust- ments within the wf-LM life zone, provides a reasonable approximation of the measured discharges for both dry and wet years. The latter compu-  - - - - -------- - ----- I - a v , ,, m  --- - ---- -------  't el _ ' '" l/, ;o Oho ...3 Y i y x "L _ - $c I ' / ;3O F la l^v"VC l V y 3 c y .... _ ; ; ; ° Ys . I1 \ J s y ....  38 Population and Energy tations provide the best approximation of actual discharge. In analyzing these data, it should be remembered always that the water balance calcu- lations were based upon the assumption that all the life zones were in mature forest on zonal soils. In fact, this is not the case. As will be pointed out, much of the study region is in pasture and mixed farming, especially the moist and dry life zones. Therefore, it could be hypothesized that the discrepancy between the calculated discharge figure obtained by using the second set of conditions and the actual measured discharge for dry and average years is due to the lower evapotranspiration rate of the pas- ture and mixed farming areas. This base-line analysis of the physical environment indicates that the hydrological potential of the Jagua watershed-and, in an extended fash- ion, of the Jagua Bao region-is vested in the Lower Montane Wet Forest (wf-LM) life zone. Particular attention therefore should be directed to- ward maintaining this life zone in its natural canopy. As will be seen, it is this particular zone that has been subjected to flagrant deforestation. 38 Population and Energy tations provide the best approximation of actual discharge. In analyzing these data, it should be remembered always that the water balance calcu- lations were based upon the assumption that all the life zones were in mature forest on zonal soils. In fact, this is not the case. As will be pointed out, much of the study region is in pasture and mixed farming, especially the moist and dry life zones. Therefore, it could be hypothesized that the discrepancy between the calculated discharge figure obtained by using the second set of conditions and the actual measured discharge for dry and average years is due to the lower evapotranspiration rate of the pas- ture and mixed farming areas. This base-line analysis of the physical environment indicates that the hydrological potential of the Jagua watershed-and, in an extended fash- ion, of the Jagua Bao region-is vested in the Lower Montane Wet Forest (wf-LM) life zone. Particular attention therefore should be directed to- ward maintaining this life zone in its natural canopy. As will be seen, it is this particular zone that has been subjected to flagrant deforestation. 38 Population and Energy tations provide the best approximation of actual discharge. In analyzing these data, it should be remembered always that the water balance calcu- lations were based upon the assumption that all the life zones were in mature forest on zonal soils. In fact, this is not the case. As will be pointed out, much of the study region is in pasture and mixed farming, especially the moist and dry life zones. Therefore, it could be hypothesized that the discrepancy between the calculated discharge figure obtained by using the second set of conditions and the actual measured discharge for dry and average years is due to the lower evapotranspiration rate of the pas- ture and mixed farming areas. This base-line analysis of the physical environment indicates that the hydrological potential of the Jagua watershed-and, in an extended fash- ion, of the Jagua Bao region-is vested in the Lower Montane Wet Forest (wf-LM) life zone. Particular attention therefore should be directed to- ward maintaining this life zone in its natural canopy. As will be seen, it is this particular zone that has been subjected to flagrant deforestation.  3. Cultural Background F IFTY YEARS AGO, Durland described the geography of the Domini- can Republic as the least known among the Greater Antilles and the least changed since pre-Columbian times. With the vast majority of the land in forest vegetation, the mountain ranges were almost completely covered with a canopy of forest growth.t However, over the past half- century, the amount of land remaining in forest vegetation has rapidly diminished. In 1967, it was estimated that only a fraction of the republic could be classified as forested? Those scientists acquainted with the prob- lems of deforestation in the Dominican Republic identify the principal causes as population increases with concomitant extensions of slash-and- burn agriculture and extensive grazing.3 Field studies substantiate the importance of these factors as landscape determinants in the Jagua-Bao region. 1. W. D. Ourland, "The Forests of the Dominican Republic," Geographical Review 12 (April 1922): 206-10. 2. Organization of American States, Reconocimiento y evaluacidn de los recursos naturales de la Repdblica Dominicana, 3 vols. (Washington, D.C.: Pan American Union, Department of Economic Affairs, 1967), 1: 172. 3. The writings of Carlos Chardon demonstrate public awareness of the de- forestation problem based on scientific observations as far back as 1937. For a detailed explanation, see Chardon's Reconocimiento de los recursos naturales de la Repablica Dominicana, Report to President Rafael L. Trujillo Molina (Ciudad Trujillo [Santo Domingo], 1937), pp. 364-69. A more definitive ecological discussion 39 3. Cultural Background F IFTY YEARS AGo, Durland described the geography of the Domini- can Republic as the least known among the Greater Antilles and the least changed since pre-Columbian times. With the vast majority of the land in forest vegetation, the mountain ranges were almost completely covered with a canopy of forest growth.' However, over the past half- century, the amount of land remaining in forest vegetation has rapidly diminished. In 1967, it was estimated that only a fraction of the republic could be classified as forested? Those scientists acquainted with the prob- lems of deforestation in the Dominican Republic identify the principal causes as population increases with concomitant extensions of slash-and- burn agriculture and extensive grazing.t Field studies substantiate the importance of these factors as landscape determinants in the Jagua-Bao region. 1. W. D. Durland, "The Forests of the Dominican Republic," Geographical Review 12 (April 1922): 206-10. 2. Organization of American States, Reconocimiento y evaluaciod de los recursos naturales de la Repdblica Dominican, 3 vols. (Washington, D.C.: Pan American Union, Department of Economic Affairs, 1967), is 172. 3. The writings of Carlos Chardon demonstrate public awareness of the de- forestation problem based on scientific observations as far back as 1937. For a detailed explanation, see Chardon's Reconocimiento de [os recursos naturales de la Repdblica Dominicana, Report to President Rafael L. Trujillo Molina (Ciudad Trujillo [Santo Domingo], 1937), pp. 364-69. A more definitive ecological discussion 39 3. Cultural Background FIFTY YEARS AGO, Durland described the geography of the Domini- can Republic as the least known among the Greater Antilles and the least changed since pre-Columbian times. With the vast majority of the land in forest vegetation, the mountain ranges were almost completely covered with a canopy of forest growth.t However, over the past half- century, the amount of land remaining in forest vegetation has rapidly diminished. In 1967, it was estimated that only a fraction of the republic could be classified as forested.2 Those scientists acquainted with the prob- lems of deforestation in the Dominican Republic identify the principal causes as population increases with concomitant extensions of slash-and- burn agriculture and extensive grazing. Field studies substantiate the importance of these factors as landscape determinants in the Jagua-Bao region. 1. W. D. Durland, "The Forests of the Dominican Republic," Geographical Review 12 (April 1922): 206-10. 2. Organization of American States, Reconocimiento y evaluacidn de los recursos naturales de la Repdblica Dominicana, 3 vols. (Washington, D.C.: Pan American Union, Department of Economic Affairs, 1967), 1: 172. 3. The writings of Carlos Chardon demonstrate public awareness of the de- forestation problem based on scientific observations as far back as 1937. For a detailed explanation, me Chardon's Reconocimiento de los recursos naturales de la Republica Dominicana, Report to President Rafael L. Trujillo Molina (Ciudad Trujillo [Santo Domingo], 1937), pp. 364-69. A more definitive ecological discussion  40 Population and Energy Settlement patterns in the Dominican Republic show periods of contrac- tion and expansion over two centuries. The carves in Pigure 14 illusteate population growth for selected communities in Jagua-Bao and the entire region and nation daring the 1935-70 period. National population data have hero included for comparative purposesa The notional population curve reflects most clearly the demographic fluctuations over the pass two centuries. In the republic, population de- creased at an alarmoing rate between 1790 and 1020 in response to the repeated invasions and occupation by adjoining Haiti. By 1844, Santo Domingo had recovered its losses and population equaled the 1790 level. Post-1844 fluctuations were negligible. In general, aver the 1820-1970 period, population in the republic grew as the average annual rate of 2.0 per cent, one of the high est rates of increase in the world. The demographic trend for the Jagua-Boo region closely approximated the national trend from 1935 to 1961, hat since then increases have de- clined (Figure 14). Three communities within the region have demon- strated wide variations in growth performance. Population in Juncalito is found in Chaedon's "Lot pinares tie In Reptublica Dominicana," Caribbean, Feore- ter 2 (April 1941): 120-30. Recently, the Food and Agricultural Orgnaotion at the United Nations presided technical assistance to the Dominicas goverement is training foresters fee extension sevice. An prt at this serrice, a number at base- line studies base been prformed which snhstantiate the rmlationship between pepa- lation growth and defornstation. See United Nations, Inentariaridn y fomnes dr tos recursos forrestalr- Reptiblica Domninae, Waring Document no. 1 (Santo Domingo: Programs de las Naciones Usidas paea el Desaemtllo, 19711, pp. 2-3, 8-13. 4. OttoSchenrich, Santo Domingo: A Country wcith a Future (New York: Macmsillan Compauy, 1910), pp. 165-68; Dominican Republic, Primer censo no- rional, ed. D. C. Leon and S. Aybar y Nusfiez (Santo Domineo, 19201. p. 157: U.S., Congress, Senate, Repsort of the Commission ef dnquiry to Santo Deminga, 42nd Cong., let lss., 1871, Es. Dec. no. 9, pp. 181-82; Pedr6n, "Menonia descrip- ties de In pante espaiola tie Sante Domingo, to00," La eta tie Frauncia en Santo Domingo: contribucidin a su etadio, eti. E. Rodrigueo Demorizi (Ciuad Truillo [Santo Domingo]; Editors tint Cadhbe, 1955). p. 190; M. A. Amsiama, "La pohlaci6n tie Santo Domingo," Cet 27 (Joly-December 1959): 116-34; William Waton. Preent State of the Spaniel Colonires; fncludinc a Particular Report of Hiepaniolo, 2 vets. (London: Losgan, Hurest, Rees, Drer aend Brown, 1010), 1: 132; Domini- ean Republic, Poblacidie tieo Republica Dominicana (Ciudad Trujillo [Santo Do- mingo]: Seccitin tie Publicaciones, 19461. p. 17; Domniican Republic, Diwrcitn Geeral tie tEstadistic, Terer renso notional tie poblaeidn; restimen general (Ciu- dad Tmujillo [Santo Domingo]: Secai6n tin Publicaciones, 1953); Dominican Re- public, Oficina Nacional tie Estadistica, Cao reese nacional tie poblaciin: e odmen eneral (Sno Domingo: Divisitin tie Ceaseotin Poblacidn y Hahisecido, 1966), p. 23; and Dominican Republic, Oficina Nagional tie tEstadistica, Repuiblica Dominianuenifras SatoDomigo: Seceaiado Taico de IsPresiencia, 1970), p. 3. 40 Population and Energy Settlement patterns in the Dominican Republic show periods of contrac- tion and expansion over two centuries. The curves in Figure 14 illustrate population growth for selected communities in Jagua-Bao and the entire region and nation during the 1935-70 period. Natienal population data have been included for comparative purposes. The national population curve refleets most clearly the demographic fluctuations over the pant two centuries. In the republic, population de- creased 01 an alarming rate between 1790 aed 1820 in response to the repeated invasions and occupation by adjoining Haiti. By 1844, Santo Domingo had recovered its losses and population equaled the 1790 level. Post-1844 fluctuations were negligible. In general, over the 1820-1970 period, population in the republic grew at the average annual rate of 2.8 per cent, gune of the highest rates of increase in thr world. The demographic trend for the Jagua-Bao region closely approximated the national trend from 1935 to 1961, has since then increases have de- clined (Figure 14). Three communities within the region have demon- strated wide variations in growth performance. Population in Juncalito is fund in Chaerdon's "Las piares tie Is Reptiblica Dominicans," Caribbean Fores- tee 2 (April 1941); 120-30. Recently, the Food and Agricultueal Organizatieon et the UnitediNtionstpoideitechicaltassistancstoehe Domnican goemnment in teaining foestees tee extension seevice. As pat ee this servica, a number or base- line studies have been perfeemedi which nubstantiate the rmlationship betuween pops- Ilin geowth anti deformstation. See United Nations, Incentariacids y foeeno tie lee recuresos forestales: Repuiblico Domisicana, Woering Documnt so. I (Santo Domsingo: Programa tie tas Naciones Unidans paea el Desaremllo, 19711. pp. 2-3. 8-13. 4.Otto Schoenrich, Sant Doming: ACountry with aeFutre (New York: Macmillan Comany, 19181, pp. 165-68; Dominican Republic Prim er cenc na- cional, edi. D. C. Leon anti S. Ayhae p Nuez (Sato Dominge, 19201. p. 157; U.S., Congress, Senate, Report of the Commission of tInquiry to Santo Dominga, 42nd Cang., tl nest., 1871, Es. Doc. no. 9, pp. 181-82; Pedretn, °Memutia desncrip- lien tie Ia pane espafiola tie Santa Dcmingo, 1800,. Lo era tie Francia en Santos Demingso: contribuciin a so esudio, edi. E. Rodeiguee Demorizi (Ciudadt Tmuiillo [Sno Domingo]; tEditsoein Caribe, 19555), p. 190; M. A. Amniama, "La poblacitin tie Sante Demingo," csso 27 (July-Decemher 1959); 116-34; William Walton Preent Slate cf the Spanish Colonie; Includiing a Particular Rleeces of Hispaniola, 2 sets. (Leaden: Longman, Hurt, Rees, Orme, anti Browe, 1010). 1: 132; Domini- can Republic, Poblaciin tie la Repsublise Dominicana (Ciuatid Trajillc [Sante Do- minao]: Seccite tie Publicaciones, 1946), p. 17; Dominican Republic, Dimasiin General tin Estadistica, Teecer ceso national tie poblacide: reedwes ogeneral (Cia- tied Tmuillo [Santo Damingo]: Seccitin tie Publicacioesn 1953); Dominian Re- public, Oficia Nacioal tie Etadistica, Cartoecensonaiowal tie poblaciin: re- edwin general (Snto Domino: Dieisitu tie Censo tie Poblacitin y Hubitaciin 1966), p. 23; and Dominican Republic, Oficina Nacioeal tie Essadistica, Republica ominicanas en cifrus (Snto Damingo: Secretneiado Tticnico tie Ia Peesidencia, 1978), p. 3. 40 Population and Energy Settlement patterns in the Dominican Republic show periods of contrac- tion and expansion aver Iwo centuries. The curves in Figure 14 illustrate population growth for selected communities in Jagua-Bao and the entire region and nation during the 1935-70 period. National population data have been included for comparative purposes' The national population curve reflects most clearly the demographic fluctuations over the past two centuries. In the republic, population de- creased at an alarming rate between 1790 and 1820 in response to the repeated invasions and occupation by adjoining Haiti. By 1844, Santo Domingo had recovered its losses and population equaled the 1790 level. Post-1844 fluctuations were negligible. In general, over the 1820-1970 period, population in the republic grew at the average nnual rate of 2.8 per cent, one of the highest rules of increase in the world. The demographic trend for the Jagua-Bao region closely approximated the natinal treed from 1935 to 1961, but since lbhen incr eases have den- clined (Figure Id). Three communities within the regioe have demon- strated wide variations in growth performance. Population in Juncalito in tund in Chaerdon's "Len pinares tie Ia Reptiblica Dominicas," Caribbeun Poes- tee 2 (April 1941): 120-30. Recently, the Peed nd Agricultural Organiztion of she United Nations perided technical assistance In tbe Dominian govrenmt is training foresterstfor estension sersice. At pat of this terrie, a number oftbase- tine studies burr bees peefoned whicb substantiate the rmlationship between popu- lation growth nd deforestation. See United Nations, Ins-ensueriacidn y fomento tie loe recusos forestales: Repuiblica Domsinicana, Weeding Docusnt no. 1 (Santo Domingo; Peogenma tie las Naciones Unidias para el Desareoll, 1971), pp. 2-3, 8-13. 4. Otto Schoenric, SanoDomingo ACuntywit aFuture(NewYork: Macmillan Company, 19181. pp. 165-68; Dsminican Republic Primer cense a cionnl, edi. D. C. Lean anti S. Aybar y Nsnez (Sante Domingo, 1920). p. 157; U.S., Congress, Senate, Report of the Comemieeion of fnquiry te Santo Dominge. 42nd Cong, 1st sees., 1071, Ps. Dec. as. 9, pp. 181-02; Pedrdn, "Memouda desatip- dva tie In pate espafoela tie Santo Domng, lone," La era tie Francia en Santa Domingo: contribuctin a so restio, ed. E. Rodeiguez Demarizi (Ciuatid Trujillo [Snto Domingo]; tEditora del Caribr, 1955), p. 190; M. A. Amuiam, "La poblacitin tie Santo Domingo," Mo~ 27 (July-December 1959); 116-34; William Waltoe, Present State of the Spanish Coteries; Including a Particular Report of Hispaniola, 2 vols. (Leaden; Longmcn, Hurst, Rees, Drme and Brown, 1010). 1: 132; Domini- an Rtpublic, Poblaiin tie la Reptiblica Dominicana (Ciudand Trujillo (Sassa Do- mingo]: Seccitx tie Publicaciones, 1946). p. 17; Dominicn Republic Dimccitie Deeas tie nstadinsic, Tercer eso eaoal tie poblacitis: reedmen general (Cia- dadt Truillo [Sno Domingo]: Seccida tie Pabliacionts, 1953); Dominican Re- public, Oficina Nacional tie Estadistica, Cuaorto censocoal tie poblacidn: re- otimen generel (Santo Domiugo: Division tie Ceno tie Peblucitin y llabitnaiie, 1066), p. 23; nd Daminican Republic, ODicina Nacioal tie tEstadistica, Reptiblica Dominicana en rifrae (Santa Dominuo: Seretariado Tfcnico tie Ia Presidencia, 1970), p. 3.  Cultural Background 41 Cultural Background 41 Cultural Background 41 5,000 - ...... Dominican Republic -- - Jagua.-Bao Study Region . I --- - Las Placeta Seio . -u ..u .rJuncalito Abajo Section .*/ 1,000 - Pialit Section .u - co Time FIGURE 14. Population growth for selected communities and the nation, 1790-1970. Abajo has declined sharply since 1961 due to emigration. Pinalito, a community in the extreme northeastern portion of the study region, has provided an interesting contrast of steadily increasing population over the past twenty-five years. Las Placetas, the third community, has experienced a moderate population decrease since 1961 due to emigration, limitations on access to land formerly controlled by lumber mills, and the vagaries of an interrupted market structure during the 1965-66 OAS intervention. Within Jagua-Bao, emigration is definitely a post-Trujillo (post-1961) phenomenon that reached a peak between 1962 and 1965, and has been associated principally with the attractiveness of opportunities in New York 5,000 - ....... Dominican Republic - - -Jagua-Bao Study Region ---- Las Placetas Section ------- Juncelito Abajo Section ./ A ,000 pinalito Section .u 100 - * .- 100100100 Time FIGURE 14. Population growth for selected communities and the nation, 1790-1970. Abajo has declined sharply since 1961 due to emigration. Pinalito, a community in the extreme northeastern portion of the study region, has provided an interesting contrast of steadily increasing population over the past twenty-five years. Las Placetas, the third community, has experienced a moderate population decrease since 1961 due to emigration, limitations on access to land formerly controlled by lumber mills, and the vagaries of an interrupted market structure during the 1965-66 OAs intervention. Within Jagua-Bao, emigration is definitely a post-Trujillo (post-1961) phenomenon that reached a peak between 1962 and 1965, and has been associated principally with the attractiveness of opportunities in New York 5,000- ......Dominican Republic ---- Jagua-Bao Study Region .* --- Las Placetas Section . e ----- Juncalito Abajo Section lTim Feneene 14. Poulton grmwth for selected coemunities and the nation, 1790-1970. Ahajo has declined sharply since 1961 due to emigration. Pinuito, a community in the extreme northeastern portion of the study region, has provided an interesting contrast of steadily increasing population ever the past twenty-five years. Las Placetas, the third community, has experienced a moderate population decrease since 1961 due to emigration, limitations en access to land formerly controlled by lumber mitts, and the vagaries of an interrupted market structure daring the 1965-66 OAS intervention. Within Jagua-Bao, emigration is definitely a post-Trajillo (post-1961) phenomenon that reached a peak hetween 1962 and 1965, and has heen associated principally with the attractiveness of opportunities in New York  42 Population and Energy City.t Jobs are the major inducement. The exodus has reached such pro- portions in communities such as Juncalito Abajo that the young adult male population has been visibly reduced. Within such communities, even though a husband or father may leave his family behind, the majority of migrants consider the separation temporary and most send home monthly checks averaging between $RD 30 and $RD 100 to cover family living expenses. Money is also saved in order to reunite the entire family at the earliest possible time. Settlement expansion in Jagua-Bao has taken place within the past century. Travelers in the area prior to 1870 described a pristine forest upland, very sparsely settled by a few hardy mountaineer families.' By 1900, settlements had been introduced along three principal corridors: from San Jos6 de las Matas via Palero, Cejita, and Las Carreras to Los Limones B along the western perimeter; from Janico via Pinalito (Las Auyamas), Los Pilones, El Papayo, and Bejucal on the trail to Jumunucu in the central area; and from Sabana Iglesia via El Aguacate, La Guama, and Llano del Higo (Los Limones A) to Jarabacoa (see map in Figure 15).7 At that time, major trails connected these settlements with the surrounding countryside. By 1927, Juncalito Abajo (El Juncalito) had been founded and a trail broken through to Guanajuma and Janico.t All in all, the settlement process since 1900 can be characterized first by growth along the major trails resulting in peripheral line settlements, and later by extension from this periphery toward the central upland. Population distribution for 1968 is given in Plate L While the map indicates a somewhat even population distribution pattern for the entire Jagua-Bao region, several features are discernible. First, the historical 5. N. L. Gonzlez, "Peasants' Progress: Dominicans in New York," Caribbean Studies 10 (October 1970): 154-71. 6. W. M. Gabb, "On the Topography and Geology of Santo Domingo," Trans- actions of the American Philosophical Society, New Series, 15 (1881): 114-18. 7. C. N. de Moya, Mapa de to isla de Santo Domingo y Haiti (New York: Rand McNally & Co., 1906). There are two sections in the region with identical names; the larger of these, Los Limones B, is located in San Jos6 de las Matas Municipality; Los Limones A is located in Janico Municipality. 8. Santo Domingo & San Juan Map, West Indies, provisional ed. N.E.-10 (New York: American Geographical Society, 1927). 9. From preliminary 1970 census data obtained from the Dominican Republic, Oficina Nacional de Estadistica, an annual growth rate of 2.0 per cent per year has been calculated. Based on this rate, the 1968 population in the study region is estimated to be 20,061. The 1950 national census reported an average occupancy of 3.16 people per occupied structure in Janico Municipality. A count of mapped structures on a 1958 field-checked Army Topographic Command map was 4,716. Although these structures are obviously not all occupied homes, it is the authors' contention that their spatial distribution approximates the population dispersion as of that date. By multiplying each dot by a factor of 4, one may visualize a rough population distribution for the study region as of 1968. 42 Population and Energy City.t Jobs are the major inducement. The exodus has reached such pro- portions in communities such as Juncalito Abajo that the young adult male population has been visibly reduced. Within such communities, even though a husband or father may leave his family behind, the majority of migrants consider the separation temporary and most send home monthly checks averaging between $RD 30 and $RD 100 to cover family living expenses. Money is also saved in order to reunite the entire family at the earliest possible time. Settlement expansion in Jagua-Bao has taken place within the past century. Travelers in the area prior to 1870 described a pristine forest upland, very sparsely settled by a few hardy mountaineer families. By 1900, settlements had been introduced along three principal corridors: from San Jos6 de las Matas via Palero, Cejita, and Las Carreras to Los Limones B along the western perimeter; from Janico via Pinalito (Las Auyamas), Los Pilones, El Papayo, and Bejucal on the trail to Jumunucu in the central area; and from Sabana Iglesia via El Aguacate, La Guama, and Llano del Higo (Los Limones A) to Jarabacoa (see map in Figure 15).7 At that time, major trails connected these settlements with the surrounding countryside. By 1927, Juncalito Abajo (El Juncalito) had been founded and a trail broken through to Guanajuma and Janico 8 All in all, the settlement process since 1900 can be characterized first by growth along the major trails resulting in peripheral line settlements, and later by extension from this periphery toward the central upland. Population distribution for 1968 is given in Plate 11 While the map indicates a somewhat even population distribution pattern for the entire Jagua-Bao region, several features are discernible. First, the historical 5. N. L. Gonzalez, "Peasants' Progress: Dominicans in New York," Caribbean Studies 10 (October 1970): 154-71. 6. W. M. Gabb, "On the Topography and Geology of Santo Domingo," Trans- actions of the American Philosophical Society, New Series, 15 (1881): 114-18. 7. C. N. de Moya, Mapa de la isla de Santo Domingo y Haiti (New York: Rand McNally & Co., 1906). There are two sections in the region with identical names; the larger of these, Los Limones B, is located in San Jose de las Matas Municipality; Los Limones A is located in Janico Municipality. 8. Santo Domingo & San Juan Map, West Indies, provisional ed. N.E.-10 (New York: American Geographical Society, 1927). 9. From preliminary 1970 census data obtained from -the Dominican Republic, Oficina Naional de Estadistica, an annual growth rate of 2.0 per cent per year has been calculated. Based on this rate, the 1968 population in the study region is estimated to be 20,061. The 1950 national census reported an average occupancy of 3.16 people per occupied structure in Janico Municipality. A count of mapped structures on a 1958 field-checked Army Topographic Command map was 4,716. Although these structures are obviously not all occupied homes, it is the authors' contention that their spatial distribution approximates the population dispersion as of that date. By multiplying each dot by a factor of 4, one may visualize a rough population distribution for the study region as of 1968. 42 Population and Energy City.t Jobs are the major inducement. The exodus has reached such pro- portions in communities such as Juncalito Abajo that the young adult male population has been visibly reduced. Within such communities, even though a husband or father may leave his family behind, the majority of migrants consider the separation temporary and most send home monthly checks averaging between $RD 30 and $RD 100 to cover family living expenses. Money is also saved in order to reunite the entire family at the earliest possible time. Settlement expansion in Jagua-Bao has taken place within the past century. Travelers in the area prior to 1870 described a pristine forest upland, very sparsely settled by a few hardy mountaineer families. By 1900, settlements had been introduced along three principal corridors: from San Jos6 de las Matas via Palero, Cejita, and Las Carreras to Los Limones B along the western perimeter; from Janico via Pinalito (Las Auyamas), Los Pilones, El Papayo, and Bejucal on the trail to Jumunucu in the central area; and from Sabana Iglesia via El Aguacate, La Guama, and Llano del Higo (Los Limones A) to Jarabacoa (see map in Figure 15).7 At that time, major trails connected these settlements with the surrounding countryside. By 1927, Juncalito Abajo (El Juncalito) had been founded and a trail broken through to Guanajuma and Janico.t All in all, the settlement process since 1900 can be characterized first by growth along the major trails resulting in peripheral line settlements, and later by extension from this periphery toward the central upland. Population distribution for 1968 is given in Plate I. While the map indicates a somewhat even population distribution pattern for the entire Jagua-Bao region, several features are discernible. First, the historical 5. N. L. Gonzalez, "Peasants' Progress: Dominicans in New York." Caribbean Studies 10 (October 1970): 154-71. 6. W. M. Gabb, "On the Topography and Geology of Santo Domingo," Trans- actions of the American Philosophical Society, New Series, 15 (1881): 114-18. 7. C. N. de Moya, Mapa de to isla de Santo Domingo y Haiti (New York: Rand McNally & Co., 1906). There are two sections in the region with identical names; the larger of these, Los Limones B, is located in San Jose de las Matas Municipality; Los Limones A is located in Janico Municipality. 8. Santo Domingo & San Juan Map, West Indies, provisional ed. NP-10 (New York: American Geographical Society, 1927). 9. From preliminary 1970 census data obtained from -the Dominican Republic, Oficina Nacional de Estadistica, an annual growth rate of 2.0 per cent per year has been calculated. Based on this rate, the 1968 population in the study region is estimated to be 20,061. The 1950 national census reported an average occupancy of 3.16 people per occupied structure in Janico Municipality. A count of mapped structures on a 1958 field-checked Army Topographic Command map was 4,716. Although these structures are obviously not all occupied homes, it is the authors' contention that their spatial distribution approximates the population dispersion as of that date. By multiplying each dot by a factor of 4, one may visualize a rough population distribution for the study region as of 1968.  7o5s I0°50' 70°45' Wto' \=jae. f.a a .. D. River iu Ce6;eve's 6 I'al ro ;." P "o. Bohi. vie 'Cej Gnu .. ° Loa '~ya "" IS' Pij s 15nn Rancho -4--"- z Lie EI "Aguacace 00 Lan Ce reraa "."EI Jui calilo ".EI b yo ~ Pawyo ia'Guama 7ee a 1 i dd Hi- ...... .o un Y o'To ),. 10 Lim .AY To 1"" t ( C o nSd ° r _ o M N 3 Population in hundreds of persons Population in hundreds of persons Population in hundreds of persons Land in hundreds of hectares Land in hundreds of hec Land in hundreds of hectares is I t I r 1 I 1 1 i 1 1 1 I t I I I I I I I a - b r i t m r vY, i i Y G > n Y r r o nS o p M y N 3 Population in hundreds of per Population in hundreds of per Population in hundreds of per Land in hundreds of hectares Land in hundreds of hectares Land in hundreds of hectares i _zc; t is,. i i i i 11 is I 1 I I I; I _ 1 I I i I Y b r ter i Y % Y i l n a > o n w v 0 o M - y y 9  Las Placetas 97 unrealistic. Still, by offering a diversity of simulated conditions, the rela- tionships among the variables may be shown more dramatically. Las Placetas is experiencing already the regeneration of cut-over forest land. Assuming that the law prohibiting cutting continues indefinitely, Figure 25 reveals that the stabilization of the amount of land in forest over the next fifty years will eventually lead to a concurrent stabilization in the amount of land in pasture. Crop land will shrink in area. However, there will be a less precipitous decline in population than there has been in the period since 1948, presumably due to continued income subsidies from emigrants. Mixed farming and forest land would decrease in area if forest cutting were to be resumed in 1975. As shown in Figure 26, pasture would in- crease considerably. Figure 27 shows that if the rate of change to pasture were to rise more, population growth would quickly recover after an initial slight decrease, and both mixed farm and forest land would decrease in area. What seems to be obvious is that large increases in pasture do not stimulate rapid population growth. The relationship between population and pasture land use emphasizes the relatively low efficiency of grazing activities. If the amount of land in mixed farming were allowed to accumulate in successive years, without reverting to other land-use types, the results as shown in Figure 28 would be noteworthy. Rapid population growth would occur beyond what has been sustained in the past. Given present agricul- tural practices, however, this is an unrealistic assumption. It is the sort of changing relationship that might be expected under modem farming conditions. The simulation of retention of land in farming is instructive, however, to the point of illustrating that, with technological innovations, more population could be absorbed into the section's economy. An additional alternative to present conditions is a possible increase in the current rates of both emigration and money subsidy. At twice the 1962-75 rate of emigration (see Figure 29), all land uses tend to level off quickly, and population size decreases somewhat before stabilizing. Mixed farmland does not drop so low as when present trends are con- tinued. At four times the 1962-75 emigration rate (see Figure 30), changes are more apparent. Forest now increases, and total land in pas- ture drops farther while crop land only slightly decreases. Finally, Figure 31 shows the probable future impact on population and land use as a result of a tenfold increase in the money subsidy to the Las Placetas system. Because the conversion of forest to other land uses is restricted by law, the increase in the subsidy would provide a boost to population size. The results obtained from simulations of the land-use model for Las Las Placetas 97 unrealistic. Still, by offering a diversity of simulated conditions, the rela- tionships among the variables may be shown more dramatically. Las Placetas is experiencing already the regeneration of cut-over forest land. Assuming that the law prohibiting cutting continues indefinitely, Figure 25 reveals that the stabilization of the amount of land in forest over the next fifty years will eventually lead to a concurrent stabilization in the amount of land in pasture. Crop land will shrink in area. However, there will be a less precipitous decline in population than there has been in the period since 1948, presumably due to continued income subsidies from emigrants. Mixed farming and forest land would decrease in area if forest cutting were to be resumed in 1975. As shown in Figure 26, pasture would in- crease considerably. Figure 27 shows that if the rate of change to pasture were to rise more, population growth would quickly recover after an initial slight decrease, and both mixed farm and forest land would decrease in area. What seems to be obvious is that large increases in pasture do not stimulate rapid population growth. The relationship between population and pasture land use emphasizes the relatively low efficiency of grazing activities. If the amount of land in mixed farming were allowed to accumulate in successive years, without reverting to other land-use types, the results as shown in Figure 28 would be noteworthy. Rapid population growth would occur beyond what has been sustained in the past. Given present agricul- tural practices, however, this is an unrealistic assumption. It is the sort of changing relationship that might be expected under modem farming conditions. The simulation of retention of land in farming is instructive, however, to the point of illustrating that, with technological innovations, more population could be absorbed into the section's economy. An additional alternative to present conditions is a possible increase in the current rates of both emigration and money subsidy. At twice the 1962-75 rate of emigration (see Figure 29), all land uses tend to level off quickly, and population size decreases somewhat before stabilizing. Mixed farmland does not drop so low as when present trends are con- tinued. At four times the 1962-75 emigration rate (see Figure 30), changes are more apparent. Forest now increases, and total land in pas- ture drops farther while crop land only slightly decreases. Finally, Figure 31 shows the probable future impact on population and land use as a result of a tenfold increase in the money subsidy to the Las Placetas system. Because the conversion of forest to other land uses is restricted by law, the increase in the subsidy would provide a boost to population size. The results obtained from simulations of the land-use model for Las Las Placetas 97 unrealistic. Still, by offering a diversity of simulated conditions, the rela- tionships among the variables may be shown more dramatically. Las Placetas is experiencing already the regeneration of cut-over forest land. Assuming that the law prohibiting cutting continues indefinitely, Figure 25 reveals that the stabilization of the amount of land in forest over the next fifty years will eventually lead to a concurrent stabilization in the amount of land in pasture. Crop land will shrink in area. However, there will be a less precipitous decline in population than there has been in the period since 1948, presumably due to continued income subsidies from emigrants. Mixed farming and forest land would decrease in area if forest cutting were to be resumed in 1975. As shown in Figure 26, pasture would in- crease considerably. Figure 27 shows that if the rate of change to pasture were to rise more, population growth would quickly recover after an initial slight decrease, and both mixed farm and forest land would decrease in area. What seems to be obvious is that large increases in pasture do not stimulate rapid population growth. The relationship between population and pasture land use emphasizes the relatively low efficiency of grazing activities. If the amount of land in mixed farming were allowed to accumulate in successive years, without reverting to other land-use types, the results as shown in Figure 28 would be noteworthy. Rapid population growth would occur beyond what has been sustained in the past. Given present agricul- tural practices, however, this is an unrealistic assumption. It is the sort of changing relationship that might be expected under modern farming conditions. The simulation of retention of land in farming is instructive, however, to the point of illustrating that, with technological innovations, more population could be absorbed into the section's economy. An additional alternative to present conditions is a possible increase in the current rates of both emigration and money subsidy. At twice the 1962-75 rate of emigration (see Figure 29), all land uses tend to level off quickly, and population size decreases somewhat before stabilizing. Mixed farmland does not drop so low as when present trends are con- tinued. At four times the 1962-75 emigration rate (see Figure 30), changes are more apparent. Forest now increases, and total land in pas- ture drops farther while crop land only slightly decreases. Finally, Figure 31 shows the probable future impact on population and land use as a result of a tenfold increase in the money subsidy to the Las Placetas system. Because the conversion of forest to other land uses is restricted by law, the increase in the subsidy would provide a boost to population size. The results obtained from simulations of the land-use model for Las  PC° Fig 25 v 35 - Pocar fg2 Fig 27ear~m Foo ;Stootofodootd" ooiohot 30 F ~ oto~rtooott 195oti3otttgttoooi 1979. 01 FOOOO27 Stoloto o fod tooo ppooooohoottioLo Pooto oio otghoootfttofottooftotpttt too 5.5~r Fi-gtt po-6o Fig 27z,. Fg2 Footttoo5Sitooftootto --odoMixtdpoooithot farmioottototto thot ~ ~ 3 oodtFt io pio o14 0pto of odiotofto Fooot 2. itolttot f oo ot odpopfoiotooootitoLo Pooot oio -tih to-i foot otto to ttoo t 95 Foottog 27 Siotofott t ofo ot otdppffo ho ttoLt loto oih togh ooo itooooootoooofootioopttotooto.Sooto posot Pe"' _ s5 - Pas°rr Fig 25 --- nnxed f-mg - 30 roae u 20 = = 1s 10 19ss 198s 201; - P-P!, - Pae ea Fig 26 Mixed farming 30 F°as. - 0 IS 0 195 193s >ou - Pe°gle Fi 27 i-' --- Al xedrfarming v 30 .. F v 25 FIGURE 25. Simutoionoffland-useand popultion chantges in Las Pott, assumingf thot onditiotts owhioh opplied to f949-70 period willI hold intt he fotoro. FIotURt 26. Sitmtlftion of laod-ote ottd popolotion chatnget it Lot Pbotot wthich mttghtoccurtif forttttintg weretresttedit 1975. FIGttRE 27. Simtulftion of food-ott oand popolotioo chaoges int Lot Platato wohich mitght occur if rttoof coonversionoof foresttintopature weret 5.5 pertceot portyeor.  Fig 30 H Fig 30 _ ro . Fang _ 21 Fig 28 Fig 28 Fig 28 59 Fig 29 _ Fig 31 Fig 29 _ Fig 31 Fig 29 _ Fig 31 21 z .,777 ---- - - - - - - - - - - - - ------------ -------------- ------------- FlouaE 28. Simulation of land-use and population changes in Las Placetas which might occur if land could be converted to farmland FIGURE 28. Simulation of land-use and population changes in Las Placetas which might occur if land could be converted to farmland FIGURE 28. Simulation of land-use and population changes in Las Placetas which might occur if land could be cone more readily. mom readily. more readily. FIGURE 29. Simulation of land-use and population changes in Las Placetas which might occur if rate of emigration observed from 1962 FIGURE 29. Simulation of land-use and population changes in Las Placetas which might occur if rate of emigration observed from 1962 FIGURE 29. Simulation of land-use and population changes in Las Placetas which might occur if rate of emigration oM to 1975 were to double in 1975. to 1975 were to double in 1975. to 1975 were to double in 1975. FIGURE 30. Simulation of land-use and population changes in Las Placetas which might occur if rate of emigration observed from FIGURE 30. Simulation of land-use and population changes in Las Placetas which might occur if rate of emigration observed from FIGURE 30. Simulation of land-use and population changes in Las Placetas which might occur if rate of emigratioot 1962 to 1975 were to quadruple in 1975. 1962 to 1975 were to quadruple in 1975. 1962 to 1975 were to quadruple in 1975. FIGURE 31. Simulation of land-use and population changes in Las Placetas which might occur if rate of money inflow to the area were FIGURE 31. Simulation of land-use and population changes in Las Placetas which might occur if rate of money inflow to the area were FIGURE 31. Simulation of land-use and population changes in Las Placetas which might occur if rate of money inflow to double or quadruple in 1975. to double or quadruple in 1975. to double or quadruple in 1975.  100 Population and Energy Placetas, as well as for Juncalito Abajo and Pinalito, strongly suggest that the model can duplicate known values of land-use patterns and population size. In addition, reasonable predictions of future patterns of land-use change and population growth seem possible. Because of the encouraging results attained in working with these three test cases, it would seem worthwhile to extend the model to cover the entire Jagua-Bao region. 100 Population and Energy Placetas, as well as for Juncalito Abajo and Pinalito, strongly suggest that the model can duplicate known values of land-use patterns and population size. In addition, reasonable predictions of future patterns of land-use change and population growth seem possible. Because of the encouraging results attained in working with these three test cases, it would seem worthwhile to extend the model to cover the entire Jagua-Bao region. 100 Population and Energy Placetas, as well as for Juncalito Abajo and Pinalito, strongly suggest that the model can duplicate known values of land-use patterns and population size. In addition, reasonable predictions of future patterns of land-use change and population growth seem possible. Because of the encouraging results attained in working with these three test cases, it would seem worthwhile to extend the model to cover the entire Jagua-Bao region.  6. Integrated Land Use- Water Balance Modeling T HE PRIMARY GOAL in watershed management is to obtain the greatest water yield possible with the least erosion of soil in the basin and subsequent siltation of the reservoir. To evaluate the effects of various land-use activities in the Jagua-Bao region on the siltation rate in the projected reservoir, the pattern of change of the major land-use activities for the entire region was examined, using procedures developed in the Las Placetas case study. A possible relationship between the land- use patterns and total erosion in the region was derived. In constructing and simulating a model of the soil moisture changes in the Jagua-Bao region, both available data from the area and information from the litera- ture were utilized. From this, and from the model describing projected land-use practices in the region, it was possible to make predictions of relative erosion rates under several land-management conditions. WATER BALANCE DETERMINATIONS The water balance model shown in Figure 32 uses the same energy flow symbols discussed earlier for the land-use model. In this case, however, the flows are of water and silt; they are not flows of energy. The equations describing the changes in soil moisture and in the sediment load of the reservoir are: dS/dt = = k15R - k21LST - k22S dCs/dt = = k23SF + k24SC + k25SP + k26SM 101 6. Integrated Land Use- Water Balance Modeling THE PRIMARY GOAL in watershed management is to obtain the greatest water yield possible with the least erosion of soil in the basin and subsequent siltation of the reservoir. To evaluate the effects of various land-use activities in the Jagua-Bao region on the siltation rate in the projected reservoir, the pattern of change of the major land-use activities for the entire region was examined, using procedures developed in the Las Placetas case study. A possible relationship between the land- use patterns and total erosion in the region was derived. In constructing and simulating a model of the soil moisture changes in the Jagua-Bao region, both available data from the area and information from the litera- ture were utilized. From this, and from the model describing projected land-use practices in the region, it was possible to make predictions of relative erosion rates under several land-management conditions. WATER BALANCE DETERMINATIONs The water balance model shown in Figure 32 uses the same energy flow symbols discussed earlier for the land-use model. In this case, however, the flows are of water and silt; they are not flows of energy. The equations describing the changes in soil moisture and in the sediment load of the reservoir are: dS/dt = = kaoR - k5LST - keeS dCs/dt = = k2SF + k24SC + k25SP + k26SM 101 6. Integrated Land Use- Water Balance Modeling THE PRIMARY GOAL in watershed management is to obtain the greatest water yield possible with the least erosion of soil in the basin and subsequent siltation of the reservoir. To evaluate the effects of various land-use activities in the Jagua-Bao region on the siltation rate in the projected reservoir, the pattern of change of the major land-use activities for the entire region was examined, using procedures developed in the Las Placetas case study. A possible relationship between the land- use patterns and total erosion in the region was derived. In constructing and simulating a model of the soil moisture changes in the Jagua-Bao region, both available data from the area and information from the litera- ture were utilized. From this, and from the model describing projected land-use practices in the region, it was possible to make predictions of relative erosion rates under several land-management conditions. WATER BALANCE DETERMINATIONs The water balance model shown in Figure 32 uses the same energy flow symbols discussed earlier for the land-use model. In this case, however, the flows are of water and silt; they are not flows of energy. The equations describing the changes in soil moisture and in the sediment load of the reservoir are: dS/dt = = keeR - k1LST - k22S dCs/dt = = k23SF + k24SC + k2ISP + k26SM  IF- T F t and Forest land R r lost through Rainfall ol:rans pimt- Oueput Pascur from the _ Y - land e land use model M N M. far L land Arnim ula tcd cdin ci tli it 4irv  Land Use-Water Balance Modeling 103 The principal variable in the model is soil moisture, which is shown to be replenished by rainfall and drained by evapotranspiration and runoff. The amount of water lost through evapotranspiration depends on available water as well as the temperature (T) and the amount of land in forest and coffee (L), these vegetation types having significantly higher rates of transpiration than are found in pasture or mixed farming. The effect of the pattern of land use on the reservoir is manifested in the rate of accumulation of sediments. Erosion coefficients were estab- lished, as will be described; relative sediment accumulation rates for each of the land-use categories are calculated by multiplying the total amount of runoff by the amount of land in each category and the corresponding erosion coefficient. The four results are summed to indicate the total rate of accumulation of sediments in the Jagua-Bao region. PRECIPITATION Rainfall in the Jagua-Bao region varies considerably over the watershed. By using the life zone map of the Dominican Republic, the estimated mean annual value for precipitation within the region was calculated to be about 1,550 mm-yr'.1 There are peaks of rainfall twice each year, one in the late spring and a lesser one in the fall. In order to simulate rainfall as the sole input to the available soil moisture in the region, a truncated sine function was programmed with two cycles per year. This function is shown in Figure 33, along with actual data from one of the climatological stations. In spite of the lack of a complete match between the two curves, it should be noted that the simulated values seldom differ by more than 10 per cent from the empirical data. EVAPOTRANSPIRATION As shown in the model, the rate of evapotranspiration is increased by temperature and by leaf area index, or the number of layers of leaves over a given area of ground. Because the area in forest would have the highest rate of evapotranspiration of the four land-use types, and because seasonal changes in transpiration in the pine forest or in a coffee planta- tion would be minimal, leaf area in the model was made a function of the amount of area in forest and in coffee. The simulated yearly change in evapotranspiration, with temperature data from one of the climato- logical stations, is shown in Figure 33. 1. Organization of American States, Reconocimiento y evaluacidn de los recursos naturales de la Repdblica Dominicana, 3 vols. (Washington, D.C.: Pan American Union, Department of Economic Affairs, 1967), 2: Ecological Map of Dominican Republic. Land Use-Water Balance Modeling 103 The principal variable in the model is soil moisture, which is shown to be replenished by rainfall and drained by evapotranspiration and runoff. The amount of water lost through evapotranspiration depends on available water as well as the temperature (T) and the amount of land in forest and coffee (L), these vegetation types having significantly higher rates of transpiration than are found in pasture or mixed farming. The effect of the pattern of land use on the reservoir is manifested in the rate of accumulation of sediments. Erosion coefficients were estab- lished, as will be described; relative sediment accumulation rates for each of the land-use categories are calculated by multiplying the total amount of runoff by the amount of land in each category and the corresponding erosion coefficient. The four results are summed to indicate the total rate of accumulation of sediments in the Jagua-Bao region. PRECIPITATION Rainfall in the Jagua-Bao region varies considerably over the watershed. By using the life zone map of the Dominican Republic, the estimated mean annual value for precipitation within the region was calculated to be about 1,550 mm yr1.1 There are peaks of rainfall twice each year, one in the late spring and a lesser one in the fall. In order to simulate rainfall as the sole input to the available soil moisture in the region, a truncated sine function was programmed with two cycles per year. This function is shown in Figure 33, along with actual data from one of the climatological stations. In spite of the lack of a complete match between the two curves, it should be noted that the simulated values seldom differ by more than 10 per cent from the empirical data. EVAPOTRANSPIRATION As shown in the model, the rate of evapotranspiration is increased by temperature and by leaf area index, or the number of layers of leaves over a given area of ground. Because the area in forest would have the highest rate of evapotranspiration of the four land-use types, and because seasonal changes in transpiration in the pine forest or in a coffee planta- tion would be minimal, leaf area in the model was made a function of the amount of area in forest and in coffee. The simulated yearly change in evapotranspiration, with temperature data from one of the climato- logical stations, is shown in Figure 33. 1. Organization of American States, Reconocimiento y evaluacidn de los recursos naturales de la Repdblica Dominicana, 3 vols. (Washington, D.C.: Pan American Union, Department of Economic Affairs, 1967), 2: Ecological Map of Dominican Republic. Land Use-Water Balance Modeling 103 The principal variable in the model is soil moisture, which is shown to be replenished by rainfall and drained by evapotranspiration and runoff. The amount of water lost through evapotranspiration depends on available water as well as the temperature (T) and the amount of land in forest and coffee (L), these vegetation types having significantly higher rates of transpiration than are found in pasture or mixed farming. The effect of the pattern of land use on the reservoir is manifested in the rate of accumulation of sediments. Erosion coefficients were estab- lished, as will be described; relative sediment accumulation rates for each of the land-use categories are calculated by multiplying the total amount of runoff by the amount of land in each category and the corresponding erosion coefficient. The four results are summed to indicate the total rate of accumulation of sediments in the Jagua-Bao region. PRECIPITATION Rainfall in the Jagua-Bao region varies considerably over the watershed. By using the life zone map of the Dominican Republic, the estimated mean annual value for precipitation within the region was calculated to be about 1,550 mm-yr'.1 There are peaks of rainfall twice each year, one in the late spring and a lesser one in the fall. In order to simulate rainfall as the sole input to the available soil moisture in the region, a truncated sine function was programmed with two cycles per year. This function is shown in Figure 33, along with actual data from one of the climatological stations. In spite of the lack of a complete match between the two curves, it should be noted that the simulated values seldom differ by more than 10 per cent from the empirical data. EVAPOTRANSPIRATION As shown in the model, the rate of evapotranspiration is increased by temperature and by leaf area index, or the number of layers of leaves over a given area of ground. Because the area in forest would have the highest rate of evapotranspiration of the four land-use types, and because seasonal changes in transpiration in the pine forest or in a coffee planta- tion would be minimal, leaf area in the model was made a function of the amount of area in forest and in coffee. The simulated yearly change in evapotranspiration, with temperature data from one of the climato- logical stations, is shown in Figure 33. 1. Organization of American States, Reconocimiento y evaluacidn de los recuros naturales de la Repdblica Dominicana, 3 vols. (Washington, D.C.: Pan American Union, Department of Economic Affairs, 1967), 2: Ecological Map of Dominican Republic.  35 135 135 FIGuRe 33. Simuation outputs of wae aac model fo on er Fmua 33. Simulation otputs of wae baac model for on er FIGURE 33. SimulIation oupt of wae baac model for on er  Land Use-Water Balance Modeling 105 TEMPERATURE Mean annual temperature for the region was calculated with the life zone map to be about 22*C. It is often necessary to correct temperature data for differences between air temperature and biotemperature; however, above elevations of about 250 meters at the latitude of the Dominican Republic, air temperature can be taken as approximately equivalent to biotemperature 2 Like rainfall, temperature was programmed as a curve imitating as closely as possible the temperature regime in the study region. Tempera- ture was expressed as a cosine function, such that the temperature would be at a minimum in January and December and at a maximum in July and August. The simulated temperature curve for one of the climatological stations in the region is presented in Figure 33. RUNOFF Erosion is expected to be greatest in cultivated areas, least in forests, and intermediate in pastures and coffee plantations. The degree of overgrazing of a pasture is a significant factor, since the resultant change in the rate at which water infiltrates the soil appears to offset the benefit derived from having a continuous vegetative cover. In selecting a set of coefficients with which to simulate the differential rates of erosion that exist for each of the four kinds of land use, there was reason to adopt those coefficients shown in Table 2 which were extracted from a study of the Caonillas watershed in Puerto Rico a However, there are several major differences between the sites that made this approach inadvisable. The major dissimilarities between the two watersheds are found in the quality of the soils. Virtually all the soils in Jagua-Bao are classified as Class VII, not suited for cultivation and best left in woodland. Roughly 85 per cent of the soils in the Caonillas watershed are of Types I-IV, however, indicating a greater range in soil type than is present in Jagua- Bao. Since runoff appears to be less on stony soils, erosion may actually present a greater problem in the Puerto Rican site than at Jagua-Bao.4 Moreover, the regional differences between rates of erosion from similar land uses on differing soil types may result in important differences in the overall coefficients. Finally, differences in land-use practices between the Puerto Rican and Dominican regions seemed to be sufficiently great to be 2. Ibid. 3. J. J. Noll, The Silting of Caonillas Reservoir, Puerto Rico, U.S. Department of Agriculture, Soil Conservation Service TP-119 (Washington: U.S. Government Printing Office, 1953). 4. B. Maran and O. LohaI, "Surface Runoff in Forests and Unforested Areas," Sbornik Ceskoslovenske Akademie Zemed. 27-B (1949): 349-78. Land Use-Water Balance Modeling 105 TEMPERATURE Mean annual temperature for the region was calculated with the life zone map to be about 22*C. It is often necessary to correct temperature data for differences between air temperature and biotemperature; however, above elevations of about 250 meters at the latitude of the Dominican Republic, air temperature can be taken as approximately equivalent to biotemperature.? Like rainfall, temperature was programmed as a curve imitating as closely as possible the temperature regime in the study region. Tempera- ture was expressed as a cosine function, such that the temperature would be at a minimum in January and December and at a maximum in July and August. The simulated temperature curve for one of the climatological stations in the region is presented in Figure 33. RUNOFF Erosion is expected to be greatest in cultivated areas, least in forests, and intermediate in pastures and coffee plantations. The degree of overgrazing of a pasture is a significant factor, since the resultant change in the rate at which water infiltrates the soil appears to offset the benefit derived from having a continuous vegetative cover. In selecting a set of coefficients with which to simulate the differential rates of erosion that exist for each of the four kinds of land use, there was reason to adopt those coefficients shown in Table 2 which were extracted from a study of the Caonillas watershed in Puerto Rico.t However, there are several major differences between the sites that made this approach inadvisable. The major dissimilarities between the two watersheds are found in the quality of the soils. Virtually all the soils in Jagua-Bao are classified as Class VII, not suited for cultivation and best left in woodland. Roughly 85 per cent of the soils in the Caonillas watershed are of Types I-IV, however, indicating a greater range in soil type than is present in Jagua- Bao. Since runoff appears to be less on stony soils, erosion may actually present a greater problem in the Puerto Rican site than at Jagua-Bao.' Moreover, the regional differences between rates of erosion from similar land uses on differing soil types may result in important differences in the overall coefficients. Finally, differences in land-use practices between the Puerto Rican and Dominican regions seemed to be sufficiently great to be 2. Ibid. 3. J. J. Noll, The Silting of Caonillas Reservoir, Puerto Rico, U.S. Department of Agriculture, Soil Conservation Service TP-119 (Washington: U.S. Government Printing Office, 1953). 4. B. Maran and O. LoaI, "Surface Runoff in Forests and Unforested Areas," Sbornik Ceskoslovenske Akademie Zemed. 27-B (1949): 349-78. Land Use-Water Balance Modeling 105 TEMPERATURE Mean annual temperature for the region was calculated with the life zone map to be about 22*C. It is often necessary to correct temperature data for differences between air temperature and biotemperature; however, above elevations of about 250 meters at the latitude of the Dominican Republic, air temperature can be taken as approximately equivalent to biotemperature? Like rainfall, temperature was programmed as a curve imitating as closely as possible the temperature regime in the study region. Tempera- ture was expressed as a cosine function, such that the temperature would be at a minimum in January and December and at a maximum in July and August. The simulated temperature curve for one of the climatological stations in the region is presented in Figure 33. RUNOFF Erosion is expected to be greatest in cultivated areas, least in forests, and intermediate in pastures and coffee plantations. The degree of overgrazing of a pasture is a significant factor, since the resultant change in the rate at which water infiltrates the soil appears to offset the benefit derived from having a continuous vegetative cover. In selecting a set of coefficients with which to simulate the differential rates of erosion that exist for each of the four kinds of land use, there was reason to adopt those coefficients shown in Table 2 which were extracted from a study of the Caonillas watershed in Puerto Rico.t However, there are several major differences between the sites that made this approach inadvisable. The major dissimilarities between the two watersheds are found in the quality of the soils. Virtually all the soils in Jagua-Bao are classified as Class VII, not suited for cultivation and best left in woodland. Roughly 85 per cent of the soils in the Caonillas watershed are of Types I-IV, however, indicating a greater range in soil type than is present in Jagua- Bao. Since runoff appears to be less on stony soils, erosion may actually present a greater problem in the Puerto Rican site than at Jagua-Bao.4 Moreover, the regional differences between rates of erosion from similar land uses on differing soil types may result in important differences in the overall coefficients. Finally, differences in land-use practices between the Puerto Rican and Dominican regions seemed to be sufficiently great to be 2. Ibid. 3. J. J. Noll, The Silting of Caonillas Reservoir, Puerto Rico, U.S. Department of Agriculture, Soil Conservation Service TP-119 (Washington: U.S. Government Printing Office, 1953). 4. B. Maran and O. Lohta, "Surface Runoff in Forests and Unforested Areas," Sbornik' Ceskoslovenski Akademie Zemed. 27-B (1949): 349-78.  106 Population and Energy taken into account, particularly the method of coffee cultivation. Consid- erable erosion has undoubtedly been prevented in Jagua-Bao by planting subsistence crops and other vegetation beneath the coffee trees, a practice recommended in the Puerto Rican study but not in effect at that time. Furthermore, the grasslands apparently have not been so heavily grazed in Puerto Rico as in Jagua-Bao. It is clear from the values listed in Table 2 that the nonforested areas will have greater erosion problems than the forested areas, and that the forest itself will have considerably less erosion than any cultivated areas. Erosion in a coffee plantation is therefore set at a level five times greater than erosion in the forest; erosion from land in mixed farming produces four times more than land in coffee, with the value for pasture intermediate between them (Table 15). The relative sediment load contributed by each of the land-use categories was deter- mined by the appropriate coefficient multiplied by the area of land and by the total runoff. TABLE 15 RELATIvE EROSION COEFFICIENTs SELECTED FOR UsE IN JAGUA-BAo REGION Land Use Coefficient Forest 01 Coffee .05 Pasture .10 Mixed farming .20 CHANGES IN SOIL MOISTURE The environmental factors presented above describe those forces which cause variations in the amount of soil moisture present over time. An additional parameter of considerable importance is the water-holding capacity of the soil. Based on the known parent material, topography, and geomorphology of the study region, physical characteristics of the Las Piedras Puerto Rican Soil Series were chosen for estimating the soil moisture properties, since this series seemed to be most similar to the principal soils found within the Jagua-Bao region. The field capacity of the soil was calculated to be 147 millimeters, assuming an effective depth of 1 meter.' Beyond this value, additional inputs to the soil moisture com- 5. The value selected for field capacity is quite important. Differences between results from the same model using higher and lower values for the field capacity are demonstrated in the chapter by G. A. Antonini, K. C. Ewel, and JJ.J Ewe, "Eco- logical Modelling of a Tropical Watershed: A Guide to Regional Planning," in Spatial Aspects of Development, ed. B. S. Hoyle (London: John Wiley & Sons, Inc., 1974). 106 Population and Energy taken into account, particularly the method of coffee cultivation. Consid- erable erosion has undoubtedly been prevented in Jagua-Bao by planting subsistence crops and other vegetation beneath the coffee trees, a practice recommended in the Puerto Rican study but not in effect at that time. Furthermore, the grasslands apparently have not been so heavily grazed in Puerto Rico as in Jagua-Bao. It is clear from the values listed in Table 2 that the nonforested areas will have greater erosion problems than the forested areas, and that the forest itself will have considerably less erosion than any cultivated areas. Erosion in a coffee plantation is therefore set at a level five times greater than erosion in the forest; erosion from land in mixed farming produces four times more than land in coffee, with the value for pasture intermediate between them (Table 15). The relative sediment load contributed by each of the land-use categories was deter- mined by the appropriate coefficient multiplied by the area of land and by the total runoff. TABLE 15 RELATIVE ERoSIoN COEFFICIENTS SELECTED FOR UsE IN JAGUA-BAo REGION Land Use Coefficient Forest .01 Coffee .05 Pasture .10 Mixed farming .20 CHANGES IN SOIL MOISTURE The environmental factors presented above describe those forces which cause variations in the amount of soil moisture present over time. An additional parameter of considerable importance is the water-holding capacity of the soil. Based on the known parent material, topography, and geomorphology of the study region, physical characteristics of the Las Piedras Puerto Rican Soil Series were chosen for estimating the soil moisture properties, since this series seemed to be most similar to the principal soils found within the Jagua-Bao region. The field capacity of the soil was calculated to be 147 millimeters, assuming an effective depth of 1 meter? Beyond this value, additional inputs to the soil moisture com- 5. The value selected for field capacity is quite important. Differences between results from the same model using higher and lower values for the field capacity are demonstrated in the chapter by G. A. Antonini, K. C. Ewel, and J. J. Ewel, "Eco- logical Modelling' of a Tropical Watershed: A Guide to Regional Planning," in Spatial Aspects of Development, ed. B. S. Hoyle (London: John Wiley & Sons, Inc., 1974). 106 Population and Energy taken into account, particularly the method of coffee cultivation. Consid- erable erosion has undoubtedly been prevented in Jagua-Bao by planting subsistence crops and other vegetation beneath the coffee trees, a practice recommended in the Puerto Rican study but not in effect at that time. Furthermore, the grasslands apparently have not been so heavily grazed in Puerto Rico as in Jagua-Bao. It is clear from the values listed in Table 2 that the nonforested areas will have greater erosion problems than the forested areas, and that the forest itself will have considerably less erosion than any cultivated areas. Erosion in a coffee plantation is therefore set at a level five times greater than erosion in the forest; erosion from land in mixed farming produces four times more than land in coffee, with the value for pasture intermediate between them (Table 15). The relative sediment load contributed by each of the land-use categories was deter- mined by the appropriate coefficient multiplied by the area of land and by the total runoff. TABLE 15 RELATIvE EROsION COEFFICIENTS SELECTED FOR UsE IN JAGUA-BAO REGION Land Use Coefficient Forest .01 Coffee .05 Pasture .10 Mixed farming .20 CHANGES IN SOIL MOISTURE The environmental factors presented above describe those forces which cause variations in the amount of soil moisture present over time. An additional parameter of considerable importance is the water-holding capacity of the soil. Based on the known parent material, topography, and geomorphology of the study region, physical characteristics of the Las Piedras Puerto Rican Soil Series were chosen for estimating the soil moisture properties, since this series seemed to be most similar to the principal soils found within the Jagua-Bao region. The field capacity of the soil was calculated to be 147 millimeters, assuming an effective depth of 1 meter.5 Beyond this value, additional inputs to the soil moisture com- 5. The value selected for field capacity is quite important. Differences between results from the same model using higher and lower values for the field capacity are demonstrated in the chapter by G. A. Antonini, K. C. Ewel, and J. J. Ewel, Eco- logical Modelling' of a Tropical Watershed: A Guide to Regional Planning," in Spatial Aspects of Development, ed. B. S. Hoyle (London: John Wiley & Sons, Inc., 1974).  Land Use-Water Balance Modeling 107 partment are unlikely to percolate deeper, due to the shallowness of the soil, and consequently would become runoff. Annual changes in the soil moisture compartment calculated for the area adjoining one of the climatological stations under the above assump- tions are shown in Figure 33. Also shown in this figure are yearly varia- tions in total runoff. As expected, soil moisture recharge lags behind rainfall, as does runoff, which does not appear until after field capacity has been reached and evapotranspiration demands have been met. SIMULATIONs OF LAND-USE CHANGE IN THE JAGUA-BAO REGION In order to examine the effect of land-use change in Jagua-Bao, the rates of population growth, land-use change, and energy expenditures were calculated for the entire region in the same fashion as for Las Placetas, Pinalito, and Juncalito Abajo, described in chapter 5. The techniques used to evaluate the land-use changes on a regional scale were similar to those used in the Las Placetas case study. The rates of energy flow are shown in Table 16. As described earlier, the constants were calculated by equat- ing the rate of a flow at any particular time with the expression describing that pathway. The coefficient derived in this way remained constant, while the variables changed. Most of the coefficients were assumed to have re- mained constant throughout the twenty-two-year study period; other path- ways, specifically those associated with emigration, changed significantly after 1961. These can be changed on the analog computer by actually switching the pathway from one coefficient to another. There is considerable variation in crop productivity within the study region: Juncalito Arriba produces significantly more per hectare than the other sections, such as Jagua Abajo and Bejucal, both of which produce less than Juncalito Arriba by an order of magnitude. The prin- cipal crops in Jagua-Bao are bananas, grown in sixteen sections; plan- tains and chick peas, grown in only twelve and nine sections, respectively; and the ubiquitous maize, sweet potatoes, and beans, common to the entire region. Poultry is also included in the farm category, since chickens, turkeys, and occasionally ducks are raised in and around the farm. Pasture land provides a yield that is smaller by an order of magni- tude. Cattle are by far the main food source obtained from this type of land; other commonly raised animals are mules, horses, and occasionally sheep and goats. A small amount of honey is harvested regularly from bee hives. Finally, coffee plantations are found in sixteen sections. The yield is again an order of magnitude less than that of pasture, the value deter- mined by the purchase price of coffee at market rather than by its caloric value. It should be added that in calculating the yield of each of the Land Use-Water Balance Modeling 107 partment are unlikely to percolate deeper, due to the shallowness of the soil, and consequently would become runoff. Annual changes in the soil moisture compartment calculated for the area adjoining one of the climatological stations under the above assump- tions are shown in Figure 33. Also shown in this figure are yearly varia- tions in total runoff. As expected, soil moisture recharge lags behind rainfall, as does runoff, which does not appear until after field capacity has been reached and evapotranspiration demands have been met. SIMULATIONS OF LAND-USE CHANGE IN THE JAGUA-BAo REGION In order to examine the effect of land-use change in Jagua-Bao, the rates of population growth, land-use change, and energy expenditures were calculated for the entire region in the same fashion as for Las Placetas, Pinalito, and Juncalito Abajo, described in chapter 5. The techniques used to evaluate the land-use changes on a regional scale were similar to those used in the Las Placetas case study. The rates of energy flow are shown in Table 16. As described earlier, the constants were calculated by equat- ing the rate of a flow at any particular time with the expression describing that pathway. The coefficient derived in this way remained constant, while the variables changed. Most of the coefficients were assumed to have re- mained constant throughout the twenty-two-year study period; other path- ways, specifically those associated with emigration, changed significantly after 1961. These can be changed on the analog computer by actually switching the pathway from one coefficient to another. There is considerable variation in crop productivity within the study region: Juncalito Arriba produces significantly more per hectare than the other sections, such as Jagua Abajo and Bejucal, both of which produce less than Juncalito Arriba by an order of magnitude. The prin- cipal crops in Jagua-Bao are bananas, grown in sixteen sections; plan- tains and chick peas, grown in only twelve and nine sections, respectively; and the ubiquitous maize, sweet potatoes, and beans, common to the entire region. Poultry is also included in the farm category, since chickens, turkeys, and occasionally ducks are raised in and around the farm. Pasture land provides a yield that is smaller by an order of magni- tude. Cattle are by far the main food source obtained from this type of land; other commonly raised animals are mules, horses, and occasionally sheep and goats. A small amount of honey is harvested regularly from bee hives. Finally, coffee plantations are found in sixteen sections. The yield is again an order of magnitude less than that of pasture, the value deter- mined by the purchase price of coffee at market rather than by its caloric value. It should be added that in calculating the yield of each of the Land Use-Water Balance Modeling 107 partment are unlikely to percolate deeper, due to the shallowness of the soil, and consequently would become runoff. Annual changes in the soil moisture compartment calculated for the area adjoining one of the climatological stations under the above assump- tions are shown in Figure 33. Also shown in this figure are yearly varia- tions in total runoff. As expected, soil moisture recharge lags behind rainfall, as does runoff, which does not appear until after field capacity has been reached and evapotranspiration demands have been met. SIMULATIONS OF LAND-USE CHANGE IN THE JAGUA-BAO REGION In order to examine the effect of land-use change in Jagua-Bao, the rates of population growth, land-use change, and energy expenditures were calculated for the entire region in the same fashion as for Las Placetas, Pinalito, and Juncalito Abajo, described in chapter 5. The techniques used to evaluate the land-use changes on a regional scale were similar to those used in the Las Placetas case study. The rates of energy flow are shown in Table 16. As described earlier, the constants were calculated by equat- ing the rate of a flow at any particular time with the expression describing that pathway. The coefficient derived in this way remained constant, while the variables changed. Most of the coefficients were assumed to have re- mained constant throughout the twenty-two-year study period; other path- ways, specifically those associated with emigration, changed significantly after 1961. These can be changed on the analog computer by actually switching the pathway from one coefficient to another. There is considerable variation in crop productivity within the study region: Juncalito Arriba produces significantly more per hectare than the other sections, such as Jagua Abajo and Bejucal, both of which produce less than Juncalito Arriba by an order of magnitude. The prin- cipal crops in Jagua-Bao are bananas, grown in sixteen sections; plan- tains and chick peas, grown in only twelve and nine sections, respectively; and the ubiquitous maize, sweet potatoes, and beans, common to the entire region. Poultry is also included in the farm category, since chickens, turkeys, and occasionally ducks are raised in and around the farm. Pasture land provides a yield that is smaller by an order of magni- tude. Cattle are by far the main food source obtained from this type of land; other commonly raised animals are mules, horses, and occasionally sheep and goats. A small amount of honey is harvested regularly from bee hives. Finally, coffee plantations are found in sixteen sections. The yield is again an order of magnitude less than that of pasture, the value deter- mined by the purchase price of coffee at market rather than by its caloric value. It should be added that in calculating the yield of each of the  TABLE 16 TABLE l6 TABLE 16 RATES OF ENERGY FLOW AND LAND-USE CONVERSION AFFECTING RATES OF ENERGY FLOW AND LANG-USE CONVERSION AFFECTING RATES OF ENERGY FLOW AND LANG-USE CONVEE910N AFFECTING JAGGA-BAO REGION J---BAO REGION JAGOA-BAO REGION k,(P}C}M)H 3.30 x 109kcal"yr-1 kaH2 5.51 z 1010kcal-yr-7 k7M 110 ha"yr-r keP 250 ha"yr-r kaC 49 ha-yr-r k70FH 8.12 x 101ha-yr-1 k11FH 82 ha"yr-r k,,M 94 ha"yr-r kr,1P 66 ha"yr-r krgC 193 ha"yr-r kraFH 520 ha"yr-r k7aM 310 ha"yr] k17C 76 ha"yr-i k] HP 586 ha"yr r Designation Rate of Flow or Value of Constant Flows of Energy in Equation Change in 1948 of Coefficient and Land Energy obtained: k1MH 5.34 x 10'Okcalyr-1 k1-2.22 x 10-3ha-1.yr-1 from mixed farming k2PH 7.91 x 109kcal"yr-t k2=1.71 x 10-4ha-1.yr-1 from pasture k3CH 8.23 x 108kcal"yr-1 k3= 8.29 x 10-sha-1-yr-1 from coffee k4H2 3.10 x 107k-1-yr-r k4-8.22 x 10-21kcal-2 from outside subsidy 1970: 6.92 x 109kcal-yr-l k481t.=1.84 x 1048kcal-2 Energy expended: in agricultural ks(P}C}.M)H 3.30 x 109kcal"yr-t k5 =4.81 x 10-5ha-1-yr-1 activity in other activities, kaH2 5.51 x 10r6kcal"yr-1 k8=3.80 x 10-9kcal-1-yr-1 emigration, death Land converted from: k7M 110 ha-y'-r k,1=1.8 x 10-2yr-I mixed farming to forest k8P 250 ba"yr-1 k8= 2.55 x 10-2yr-I pasture to forest kaC 49 ha"yr-t ka=2.20 x 10-2"yr-t coffee to forest krnF'H 8.12 x 103h."yr-1 kro=9.39 x 10-11kcal-r"yrt forest to other uses k11FH 82 ha"yr-1 kr1=9.48 x 10-13kcal-t.yr-1 forest to coffee k12M 94 h."yr-1 k12=1.6 x 10-2yr-I mixed farming to coffee k13P 66 ha"yr-1 k13=6.73 x 10-3yr-t pasture to coffee 1,14C 193 ha-yr-1 k =8.80 x 10-2yr-I coffee to other uses k16FH 520 ha-yr-1 krn =6.01 x 10-12kcal-1"yr4 forest to pasture k16M 310 ha-y, r k1u = 5.20 x 10-2yr-r mixed farming to pasture k1,1C 76 h."yr-t kt,1=3.5 x 10 2yr-r coffee to pasture k1NP 586 Im-y, -t kls=5.98 x 10-2yrr pasture to other us c ka(P}C}M)H 3.30 x 109kcal"yr-1 k6H2 5.51 x 1010kcal"yr-1 k7M 110 ha-Y,1 kaP 250 ha"yr-1 kaC 49 ha"yr-1 k7aFH 8.12 x 103ha"yr-1 k11FH 82 ha"yr-1 k1ZM 94 ha"yr l k1,IP 66 ha"yr-1 k14C 193 ha"yr-1 k14FH 520 ha"yr4 kOM 310 ha"yrr k17C 76 h.-y. -1 k1xP 586 ha"yr1  Land Use-Water Balance Modeling 109 main categories, no distinction was made between subsistence crops and those products used for trading, buying, and selling. It was assumed that whenever a crop or animal was offered for sale, the quantity of money exchanged for it had a buying power of similar caloric value. Conse- quently, a steer sold at market would return enough money for its owner to purchase an equivalent amount of energy, perhaps in flour or other staples. To determine energy expenditures in the food production process, it was assumed as before that one-third of the population is actively engaged in agricultural work: 76 to 80 per cent of the energy is spent on crops, 8 per cent on coffee, and 20 per cent on pasture. The category of other losses from the human population encompasses the work of women and children necessary to support the laborers, as well as death, which of course reduces the pool of potential energy. Emigration was insignificant until after the end of the Trujillo regime in 1961. Large numbers of people have left Jagua-Bao since then, pushed out by the lack of good farmland and drawn to better jobs in the larger cities in the Dominican Republic and in New York City. The quantifi- cation of their loss represents not only the decrease in actual numbers, but the decrease in energy which could have been devoted to labor as well. Many of these people left families behind, however, and send back enough money to make up a significant proportion of the income in at least three sections. Because of the difficulty encountered in quantifying both emigration and other losses, these values were adjusted during simulation to achieve a population growth curve consistent with the known data points. A simulated projection of population changes and land-use changes from 1948 to 2025, assuming the continuance of present conditions, is shown in Figure 34. Data points are shown for known values of land areas and of population levels through 1970. The rapid population growth prior to 1962 has been slowed by increased emigration, as well as by restrictions on land use. The passing of a law in 1967 prohibiting forest cutting is assumed to have been effective, thereby reducing the rate at which forest is converted to farmland. The amount of land in pasture continues to increase; however, the amount of land in coffee remains relatively stable, and the amount of land in mixed farming de- creases. In terms of population, the net effect is a slower rate of increase. In Figure 35 are shown the changes in land use and population size that might occur if the law on forest cutting were ineffective. In this case, with forest continuing to be transformed into pasture, coffee, and particularly mixed farming, considerably more rapid population growth Land Use-Water Balance Modeling 109 main categories, no distinction was made between subsistence crops and those products used for trading, buying, and selling. It was assumed that whenever a crop or animal was offered for sale, the quantity of money exchanged for it had a buying power of similar caloric value. Conse- quently, a steer sold at market would return enough money for its owner to purchase an equivalent amount of energy, perhaps in flour or other staples. To determine energy expenditures in the food production process, it was assumed as before that one-third of the population is actively engaged in agricultural work: 76 to 80 per cent of the energy is spent on crops, 8 per cent on coffee, and 20 per cent on pasture. The category of other losses from the human population encompasses the work of women and children necessary to support the laborers, as well as death, which of course reduces the pool of potential energy. Emigration was insignificant until after the end of the Trujillo regime in 1961. Large numbers of people have left Jagua-Bao since then, pushed out by the lack of good farmland and drawn to better jobs in the larger cities in the Dominican Republic and in New York City. The quantifi- cation of their loss represents not only the decrease in actual numbers, but the decrease in energy which could have been devoted to labor as well. Many of these people left families behind, however, and send back enough money to make up a significant proportion of the income in at least three sections. Because of the difficulty encountered in quantifying both emigration and other losses, these values were adjusted during simulation to achieve a population growth curve consistent with the known data points. A simulated projection of population changes and land-use changes from 1948 to 2025, assuming the continuance of present conditions, is shown in Figure 34. Data points are shown for known values of land areas and of population levels through 1970. The rapid population growth prior to 1962 has been slowed by increased emigration, as well as by restrictions on land use. The passing of a law in 1967 prohibiting forest cutting is assumed to have been effective, thereby reducing the rate at which forest is converted to farmland. The amount of land in pasture continues to increase; however, the amount of land in coffee remains relatively stable, and the amount of land in mixed farming de- creases. In terms of population, the net effect is a slower rate of increase. In Figure 35 are shown the changes in land use and population size that might occur if the law on forest cutting were ineffective. In this case, with forest continuing to be transformed into pasture, coffee, and particularly mixed farming, considerably more rapid population growth Land Use-Water Balance Modeling 109 main categories, no distinction was made between subsistence crops and those products used for trading, buying, and selling. It was assumed that whenever a crop or animal was offered for sale, the quantity of money exchanged for it had a buying power of similar caloric value. Conse- quently, a steer sold at market would return enough money for its owner to purchase an equivalent amount of energy, perhaps in flour or other staples. To determine energy expenditures in the food production process, it was assumed as before that one-third of the population is actively engaged in agricultural work: 76 to 80 per cent of the energy is spent on crops, 8 per cent on coffee, and 20 per cent on pasture. The category of other losses from the human population encompasses the work of women and children necessary to support the laborers, as well as death, which of course reduces the pool of potential energy. Emigration was insignificant until after the end of the Trujillo regime in 1961. Large numbers of people have left Jagua-Bao since then, pushed out by the lack of good farmland and drawn to better jobs in the larger cities in the Dominican Republic and in New York City. The quantifi- cation of their loss represents not only the decrease in actual numbers, but the decrease in energy which could have been devoted to labor as well. Many of these people left families behind, however, and send back enough money to make up a significant proportion of the income in at least three sections. Because of the difficulty encountered in quantifying both emigration and other losses, these values were adjusted during simulation to achieve a population growth curve consistent with the known data points. A simulated projection of population changes and land-use changes from 1948 to 2025, assuming the continuance of present conditions, is shown in Figure 34. Data points are shown for known values of land areas and of population levels through 1970. The rapid population growth prior to 1962 has been slowed by increased emigration, as well as by restrictions on land use. The passing of a law in 1967 prohibiting forest cutting is assumed to have been effective, thereby reducing the rate at which forest is converted to farmland. The amount of land in pasture continues to increase; however, the amount of land in coffee remains relatively stable, and the amount of land in mixed farming de- creases. In terms of population, the net effect is a slower rate of increase. In Figure 35 are shown the changes in land use and population size that might occur if the law on forest cutting were ineffective. In this case, with forest continuing to be transformed into pasture, coffee, and particularly mixed farming, considerably more rapid population growth  .4 .3 ; .2 .4 "3 0 .1 -25 20 '15 .10 Fig 34 Mixed farming 1955 1985 2015 -4 -3 -2 .4 -2 Fig 34 Mixed farming - . Coffee 1955 1985 2015 Fig 35 Mixed faring ------ Cofe - . 1955 1985 2515 a x c 0 a 0 4 -3. -2 -1 -25 .20 -15 -10 O_ k G 0 7 a -25 -20 -15 -10 -5 -25 -20 -15 -10 "5 * Fig 34 People Mixed faring 1955 1985 2015 * Fig 35 Mixed fig ~~~__-- -- Coffee . ' . . . . . 1955 1985 2015 Fatua 34. Smulatd changes in land use and populationiei Jagua-Bao region from 1948to 2025,bae don otinutionof penttrends. FiruRE 35. Simulted changes in land usean population sz in Jagua Ba region, from 1048 to~ 2025, assuming foretuing c~ontiue in spite of 1907 legislation. Fmuao 34. Simulated changes in land usad population size in Jaga-Hao rgion FGUR 35. Simulated changes in land use and population size in Jaguao region from, 1948 to 2025, assumig f oest cutig coninues in, spite of 1967 legislation. FIGoRE 34. Simulated changes in land uso and population size in Jagoa-Hao region from,1948to 2025,basd on a, contiuaionof preset tend. FtGoR 35. Simulated changes in land uso and populaion siz in Jagua Ha region from, 1948 to 2025, assuming forestcuting continue in spite of 1967 legislation.  Land Use-Water Balance Modeling 111 would be predicted after 1975. The projected filling of the reservoir in 1975 would have no visible influence when viewed from the perspective of the region as a whole, since the land which is to be inundated repre- sents only a small proportion of Jagua-Bao. It may seem as if the loss of this land might actually be for the better, as fish populations would become established in the reservoir and provide a new energy source for the inhabitants of the area. However, since most edible fish are at the second, and often third and fourth, trophic levels, their productivity is of necessity at least two orders of magnitude less than that of crop land. EFFECTS OF SIMULATED LAND USE AND POPULATION CHANGES ON SEDIMENTATION RATES The water balance model described in Figure 32 was run simultaneously with the land-use change model; the simulations of the two models were linked according to the diagrams in Figures 22 and 32 in order to calcu- late the effects of land use on runoff and erosion. Changes in the pattern of land use over time, as brought about by public policy or by natural causes, affect the rate of accumulation of sediments in the reservoir, particularly as forests are cut over or allowed to regenerate. Comparison of the rates of accumulation resulting from each of several projections of land use and population change are in Figure 36. Action taken by the government, to assure protection of the forest when the dam is filled in 1975, could retard considerably the siltation rate of the dam. Conversely, lack of action could result in several strate- gies being adopted locally to extract more food from the land and thereby increase the siltation rate. During simulation, sediments were allowed to accumulate over a period of fifty years, from 1975 to 2025; courses of action were investigated to determine their impact on the reservoir. The results of these policy changes-or lack of them-and their effects on both the population and the pattern of land-use changes are shown in Figures 37-44, while the relative rates of sediment accumulation are plotted in Figure 36. CONTINUATION OF PRESENT TRENDS Two possible results of a policy allowing continuation of present trends have already been discussed and are shown in Figures 34 and 35. A third possibility is shown in Figure 37. It was assumed that cutting has been prevented since 1967 and, furthermore, that stricter laws will be imposed to prohibit any cutting of forest at all, allowing a slow regrowth of forest from exhausted pasture and farmland. Under these conditions, the population would drop slightly below the 1975 level, the amount of Land Use-Water Balance Modeling 111 would be predicted after 1975. The projected filling of the reservoir in 1975 would have no visible influence when viewed from the perspective of the region as a whole, since the land which is to be inundated repre- sents only a small proportion of Jagua-Bao. It may seem as if the loss of this land might actually be for the better, as fish populations would become established in the reservoir and provide a new energy source for the inhabitants of the area. However, since most edible fish are at the second, and often third and fourth, trophic levels, their productivity is of necessity at least two orders of magnitude less than that of crop land. EFFECTS OF SIMULATED LAND USE AND POPULATION CHANGEs ON SEDIMENTATION RATES The water balance model described in Figure 32 was run simultaneously with the land-use change model; the simulations of the two models were linked according to the diagrams in Figures 22 and 32 in order to calcu- late the effects of land use on runoff and erosion. Changes in the pattern of land use over time, as brought about by public policy or by natural causes, affect the rate of accumulation of sediments in the reservoir, particularly as forests are cut over or allowed to regenerate. Comparison of the rates of accumulation resulting from each of several projections of land use and population change are in Figure 36. Action taken by the government, to assure protection of the forest when the dam is filled in 1975, could retard considerably the siltation rate of the dam. Conversely, lack of action could result in several strate- gies being adopted locally to extract more food from the land and thereby increase the siltation rate. During simulation, sediments were allowed to accumulate over a period of fifty years, from 1975 to 2025; courses of action were investigated to determine their impact on the reservoir. The results of these policy changes-or lack of them-and their effects on both the population and the pattern of land-use changes are shown in Figures 37-44, while the relative rates of sediment accumulation are plotted in Figure 36. CONTINUATION OF PRESENT TRENDS Two possible results of a policy allowing continuation of present trends have already been discussed and are shown in Figures 34 and 35. A third possibility is shown in Figure 37. It was assumed that cutting has been prevented since 1967 and, furthermore, that stricter laws will be imposed to prohibit any cutting of forest at all, allowing a slow regrowth of forest from exhausted pasture and farmland. Under these conditions, the population would drop slightly below the 1975 level, the amount of Land Use-Water Balance Modeling 111 would be predicted after 1975. The projected filling of the reservoir in 1975 would have no visible influence when viewed from the perspective of the region as a whole, since the land which is to be inundated repre- sents only a small proportion of Jagua-Bao. It may seem as if the loss of this land might actually be for the better, as fish populations would become established in the reservoir and provide a new energy source for the inhabitants of the area. However, since most edible fish are at the second, and often third and fourth, trophic levels, their productivity is of necessity at least two orders of magnitude less than that of crop land. EFFECTS OF SIMULATED LAND USE AND POPULATION CHANGES ON SEDIMENTATION RATES The water balance model described in Figure 32 was run simultaneously with the land-use change model; the simulations of the two models were linked according to the diagrams in Figures 22 and 32 in order to calcu- late the effects of land use on runoff and erosion. Changes in the pattern of land use over time, as brought about by public policy or by natural causes, affect the rate of accumulation of sediments in the reservoir, particularly as forests are cut over or allowed to regenerate. Comparison of the rates of accumulation resulting from each of several projections of land use and population change are in Figure 36. Action taken by the government, to assure protection of the forest when the dam is filled in 1975, could retard considerably the siltation rate of the dam. Conversely, lack of action could result in several strate- gies being adopted locally to extract more food from the land and thereby increase the siltation rate. During simulation, sediments were allowed to accumulate over a period of fifty years, from 1975 to 2025; courses of action were investigated to determine their impact on the reservoir. The results of these policy changes-or lack of them-and their effects on both the population and the pattern of land-use changes are shown in Figures 37-44, while the relative rates of sediment accumulation are plotted in Figure 36. CONTINUATION OF PRESENT TRENDS Two possible results of a policy allowing continuation of present trends have already been discussed and are shown in Figures 34 and 35. A third possibility is shown in Figure 37. It was assumed that cutting has been prevented since 1967 and, furthermore, that stricter laws will be imposed to prohibit any cutting of forest at all, allowing a slow regrowth of forest from exhausted pasture and farmland. Under these conditions, the population would drop slightly below the 1975 level, the amount of  Fig.- Number Lad Use Poli63y -5Fores u9prord. ut~idy. 2 -35 Law ignored, 333F33g Fooumd -34 Current tred ontinud - 43 Foes p 2ece. 33P3F3>3 qudrupled -37 La3efeci, foret ro Figooo N 46e LF3 U-~ Pobodod ooo nras3 foe330 pacr 46 Forest up3 td~ susdy2 -43 Foreot uprod eigrotooo qoodooplod Figooo Nube] - d UsePod c 'is 2025 1975 'BS '95 '05 Years FIGURE 36. Relative accumula0tion of sedimenrt from Jagua-Bao re0io9 as simulated from 1975 through 2025 for twe1ve diffetrt land-use policies. FIGURE 36. Relativr accumulaion4 of srdimernt from Jagua-Bao region as simulated from 1 975 through 2025 for twelve different laod-ose policies. FIGURE 36. Rlative accumultion of sediment from Jagua-Bao r00i00 as simulated from 1975 through 2025 for twe19e diffrernt lood-use policies.  a as Fig 37 0 15 < 2 ^ Ple 19 2 t 1955 1985 2015 FIGURE 37. Simulated changes in land used population siz i JauaR-Bao region fromt 1948 to 2025, assuing that foes tting is prohibited in, 1967 and that fret FIGURE 38. S iuted chanlges in land used poptuation size in Jagua-Bao regiont fr194t 202,assig tataut s of landin eh ategyare hed constan at their 1975 leels. FIGURE 39. Simulate~d changes in land use, and poplation size int Jagua-Bao region from 194 t202, assu ig tht retttgcontisthrogh967ad tht a 25 Fig 39 Ut tti 197 -1- FIGURE 39. Simte~Gtd changes in lantd used population size in Jagua-Bao regionl fErm 1948 to 2025, assuinR~g thtfstctting UIisU prhiited intGI 1967 d t oet from 1948REIG to 2025, asu ig tattd amut~ of lad iahctgoyaehldcntn FIGURE 37. SimuteId chanlges it lantd use and Jpulation sie in, Jaua-RBao region fromtt 1948 to 2025, assumtintg that forst cutting is prothibited int 1967 tttd that foest is permIittedto regrow after 1975. FIGURE 38. SimlateId chantges in, land GIG and po~pulation size in, Jagua-Bao egion fErm 1948 to 2025, assuminGgU tht amounts of land in eac~h category are held consItnt at their 1975 levelst. FIGURE 39. SimlaUtd chanlges in land use and poGulation sie in Jagu-Bao rgEion fromt 1949 to 2025, assumtin~g that forest cutting continues through 1967 and thUG rateUofUconvrstion of foestItoIixd farintg i dubled.  4 zs Fig 40 Fo 41 Fig 42 Fttoo 40 jottdoogt obO odppt ot otgoBoog tttott94tto2O25ottogth~oot te ottoooootot7 it 20bt tit pot 107 t FtKt 41 ittoo hoo obOotod oooooto otgoOotgt ftot 148to205 tttoogtht togtoo -ttotot195 t oototh pt-92 Ett 42 2it oo nhoo o o t o oooio to otpoBtogo ftto 148t 22, totlo ho ottt t otiott ot otit 96 ogtott otttt~~~~~ ~~~~~ -to tot of -titto oto 197 it dobi tt pt-t7 - t Fig 40 Fo 41 Pag4 Ftoo 40. 20tttd oogto od Otod pooottto otoo o too Itot 190tP07oeooototoo too-opo toto oototoo17 ott tottot t ~ogttioootto195 it 8 d 20o h pt195 tto Fig 40 Fo 41 Fi- 4 boo 198 t 205 otooototho too19 too 198 2f0o195 o obottpt17 Ftoo 42. Fiottd o o gti tO Oto o ooig t 4 it o ooO o t go to-ott ~ ~ ~ ~ 2 198tP05 totiooo otoi ooooot o.Otit 97Itooit ot htto f tgtt o tt tOStdob htp-97 to.  Fig 43 H Fig 43 Fig 45 1S Fig 43 Fig 45 u 1 o ts ------- ------ a Fig 44 Fig 46 Is { Fig 44 H Fig 44 -4 4 20 2 2 5 5', - - - - - - - -- ------ - ----- 2.1n 77 A, after 1975 is quadruple the pre-1975 rate. after 1975 is quadruple the pre-1975 rate. after 1975 is quadruple the pre-1975 rate. FIGURE 43. Simulated changes in land use and population size in Jagua-Boo region from 1948 to 2025, assuming that emigration rate FIGURE 43. Simulated changes in land use and population size in Jagua-Boo region from 1948 to 2025, assuming that emigration rite FIGURE 43. Simulated changes in land use and population size in Jagua-Sao region from 1948 to 2025, assuming tha to be cut and that emigration rate quadruples after 1975. to be cut and that emigration rate quadruples after 1975. to be cut and that emigration rate quadruples after 1975. FIGURE 44. Simulated changes in land use and population size in Jagua-Boo region from 1948 to 2025, assuming that forest continues FIGURE 44. Simulated changes in land use and population size in Jagua-Boo region from 1948 to 2025, assuming that forest continues FIGURE 44. Simulated changes in land use and population size in Jagua-Boo region from 1948 to 2025, assuming that rate at which money is supplied to residents. rate at which money is supplied to residents. rate at which money is supplied to residents. FIGURE. 45. Simulated changes in land use and population size in Jagua-Boo region from 1948 to 2025, assuming a doubling of the FIGURE 45, Simulated changes in land use and population size in Jagua-Boo region from 1948 to 2025, assuming a doubling of the FIGURE 45. Simulated changes in land use and population size in Jagua-Boo region from 1948 to 2025, assuming a cutting and a doubling of the rate at which money is provided. cutting and a doubling of the rate at which money is provided. cutting and a doubling of the rate at which money is provided. FIGURE 46. Simulated changes in land use and population size in Jagua-Boo region from 1948 to 2025, assuming both continued forest FIGURE 46. Simulated changes in land use and population size in Jagua-Boo region from 1948 to 2025, assuming both continued forest FIGURE 46. Simulated changes in land use and population site in Jagua-Boo region from 1948 to 2025, assuming both  116 Population and Energy land in mixed farmland and coffee would stay fairly constant, and the amount of pasture would decrease precipitously. Any of these three situa- tions is a likely occurrence; the results are compared in Figure 36. The more desirable course of action is the third, which would result in con- siderably less sediment accumulation over fifty years. The shape of the curve indicates an actual decrease in the rate of sediment accumulation, whereas the rates of accumulation for the other two alternatives seem to be constant. A fourth possibility, that the forest cutting law would be relaxed in 1975 after having been effective for eight years, was tested. The results of the land-use changes are similar to the curves produced by the simu- lation in which the law was never effective, and so are not shown; the sedimentation curve falls only slightly below the curve describing ac- cumulation that would result from failure to enforce the law. The few years of protection do not prove to be significant in the light of fifty subsequent years of steady clearing. A fifth possibility, perhaps somewhat more difficult to implement, would be the maintenance of constant ratios of land-use types, equivalent to the conditions present in 1975 (see Figure 38). The population would continue to rise slowly to a level slightly above that predicted if present trends were to continue, while the sedimentation rate would be lower, presumably because of the stabilizing effect of pasture on the sediment load. If no policy were implemented, rising population pressures might force the inhabitants of the region not only to continue cutting the forest, but also to increase the rate of conversion of forest to mixed farming. Such a possibility is shown in Figure 39, in which the coefficient determining the rate of conversion of forest to mixed farming from 1948 to 1975 is doubled after 1975, and the assumption is made that forest cutting has continued since 1967. The subsequent increase in erosion sends sediment accumulation soaring to the second highest level of any of the possi- bilities tested. The highest level is reached when the rate of conversion of forest to pasture is similarly doubled (see Figure 40). Since land can remain in pasture for a considerably longer time than in mixed farming, increasing the amount of pasture land could have a more serious effect in the long run. Seven possible courses of action have been explored that describe the range of results which could be obtained by implement- ing either basic land-management policies or no policy at all. ALTERING POPULATION PREssURE ON THE LAND More drastic measures would involve resettlement plans that would re- move large numbers of people from the region. The effects of instituting 116 Population and Energy land in mixed farmland and coffee would stay fairly constant, and the amount of pasture would decrease precipitously. Any of these three situa- tions is a likely occurrence; the results are compared in Figure 36. The more desirable course of action is the third, which would result in con- siderably less sediment accumulation over fifty years. The shape of the curve indicates an actual decrease in the rate of sediment accumulation, whereas the rates of accumulation for the other two alternatives seem to be constant. A fourth possibility, that the forest cutting law would be relaxed in 1975 after having been effective for eight years, was tested. The results of the land-use changes are similar to the curves produced by the simu- lation in which the law was never effective, and so are not shown; the sedimentation curve falls only slightly below the curve describing ac- cumulation that would result from failure to enforce the law. The few years of protection do not prove to be significant in the light of fifty subsequent years of steady clearing. A fifth possibility, perhaps somewhat more difficult to implement, would be the maintenance of constant ratios of land-use types, equivalent to the conditions present in 1975 (see Figure 38). The population would continue to rise slowly to a level slightly above that predicted if present trends were to continue, while the sedimentation rate would be lower, presumably because of the stabilizing effect of pasture on the sediment load. If no policy were implemented, rising population pressures might force the inhabitants of the region not only to continue cutting the forest, but also to increase the rate of conversion of forest to mixed farming. Such a possibility is shown in Figure 39, in which the coefficient determining the rate of conversion of forest to mixed farming from 1948 to 1975 is doubled after 1975, and the assumption is made that forest cutting has continued since 1967. The subsequent increase in erosion sends sediment accumulation soaring to the second highest level of any of the possi- bilities tested. The highest level is reached when the rate of conversion of forest to pasture is similarly doubled (see Figure 40). Since land can remain in pasture for a considerably longer time than in mixed farming, increasing the amount of pasture land could have a more serious effect in the long run. Seven possible courses of action have been explored that describe the range of results which could be obtained by implement- ing either basic land-management policies or no policy at all. ALTERING POPULATION PRESSURE ON THE LAND More drastic measures would involve resettlement plans that would re- move large numbers of people from the region. The effects of instituting 116 Population and Energy land in mixed farmland and coffee would stay fairly constant, and the amount of pasture would decrease precipitously. Any of these three situa- tions is a likely occurrence; the results are compared in Figure 36. The more desirable course of action is the third, which would result in con- siderably less sediment accumulation over fifty years. The shape of the curve indicates an actual decrease in the rate of sediment accumulation, whereas the rates of accumulation for the other two alternatives seem to be constant. A fourth possibility, that the forest cutting law would be relaxed in 1975 after having been effective for eight years, was tested. The results of the land-use changes are similar to the curves produced by the simu- lation in which the law was never effective, and so are not shown; the sedimentation curve falls only slightly below the curve describing ac- cumulation that would result from failure to enforce the law. The few years of protection do not prove to be significant in the light of fifty subsequent years of steady clearing. A fifth possibility, perhaps somewhat more difficult to implement, would be the maintenance of constant ratios of land-use types, equivalent to the conditions present in 1975 (see Figure 38). The population would continue to rise slowly to a level slightly above that predicted if present trends were to continue, while the sedimentation rate would be lower, presumably because of the stabilizing effect of pasture on the sediment load. If no policy were implemented, rising population pressures might force the inhabitants of the region not only to continue cutting the forest, but also to increase the rate of conversion of forest to mixed farming. Such a possibility is shown in Figure 39, in which the coefficient determining the rate of conversion of forest to mixed farming from 1948 to 1975 is doubled after 1975, and the assumption is made that forest cutting has continued since 1967. The subsequent increase in erosion sends sediment accumulation soaring to the second highest level of any of the possi- bilities tested. The highest level is reached when the rate of conversion of forest to pasture is similarly doubled (see Figure 40). Since land can remain in pasture for a considerably longer time than in mixed farming, increasing the amount of pasture land could have a more serious effect in the long run. Seven possible courses of action have been explored that describe the range of results which could be obtained by implement- ing either basic land-management policies or no policy at all. ALTERING POPULATION PRESSURE ON THE LAND More drastic measures would involve resettlement plans that would re- move large numbers of people from the region. The effects of instituting  Land Use-Water Balance Modeling 117 several population policies were achieved experimentally by first doubling and then quadrupling the rate of emigration from the region. Once again, the coefficient calculated from the 1962-70 rate was doubled for 1975 to achieve this rate. In the first instance (Figure 41), population would eventually be reduced to two-thirds of its level in 1975, assuming that forest cutting had been prohibited since 1967. If cutting had continued, however (Figure 42), the initial decrease would soon be compensated for as increased food supplies (primarily from mixed farming) were grown on land previously in forest. The effects of these two possibilities on the sedimentation load would be significantly different, the latter producing considerably more sediments as additional land was turned into farms. Quadrupling the 1962-70 emigration rate would effectively reduce the population by one-half if the forest area were held constant (Figure 43). Even if forest cutting were to continue, the population would be reduced by one-third (Figure 44); the same effect could be achieved by doubling the emigration rate while maintaining a constant amount of forest. However, the increase in farmland generally results in a higher sedimentation load when cutting is allowed to continue. The most radical policy that could be imposed on the Jagua-Bao region would be to remove all inhabitants. This would allow subsequent regrowth of the vegetation. The results of such a policy are shown only as they affect the sedimentation rate, reducing the load to a very low level that is only slightly above the level resulting from the reversion of forest as indicated earlier. One additional set of possibilities, considerably more humanitarian, was considered. In recognition of the relative poverty of the people in Jagua-Bao, the national government might extend a large, continuing subsidy to the inhabitants of the region (Figure 45). Population size and the amount of land in pasture would increase considerably, the people presumably receiving the bulk of their support from goods pur- chased with the money. If forest cutting were simultaneously permitted (Figure 46), the subsidy still would underwrite population growth, but both mixed farming and pasture would increase. The consequence would be large sedimentation loads. It is possible to simulate the effects of several other policies, but most represent changes that would be similar to, or at least predictable from, the results presented here. For instance, the effects of the removal of people from particular sections could be inferred from the tests which doubled and quadrupled the removal rates from the entire region. Comparison of these simulations is facilitated by the graph in Figure 36, which presents the same results as those in Figures 34, 35, and 37-46, but in a slightly different form. As mentioned earlier, the rates of sedi- Land Use-Water Balance Modeling 117 several population policies were achieved experimentally by first doubling and then quadrupling the rate of emigration from the region. Once again, the coefficient calculated from the 1962-70 rate was doubled for 1975 to achieve this rate. In the first instance (Figure 41), population would eventually be reduced to two-thirds of its level in 1975, assuming that forest cutting had been prohibited since 1967. If cutting had continued, however (Figure 42), the initial decrease would soon be compensated for as increased food supplies (primarily from mixed farming) were grown on land previously in forest. The effects of these two possibilities on the sedimentation load would be significantly different, the latter producing considerably more sediments as additional land was turned into farms. Quadrupling the 1962-70 emigration rate would effectively reduce the population by one-half if the forest area were held constant (Figure 43). Even if forest cutting were to continue, the population would be reduced by one-third (Figure 44); the same effect could be achieved by doubling the emigration rate while maintaining a constant amount of forest. However, the increase in farmland generally results in a higher sedimentation load when cutting is allowed to continue. The most radical policy that could be imposed on the Jagua-Bao region would be to remove all inhabitants. This would allow subsequent regrowth of the vegetation. The results of such a policy are shown only as they affect the sedimentation rate, reducing the load to a very low level that is only slightly above the level resulting from the reversion of forest as indicated earlier. One additional set of possibilities, considerably more humanitarian, was considered. In recognition of the relative poverty of the people in Jagua-Bao, the national government might extend a large, continuing subsidy to the inhabitants of the region (Figure 45). Population size and the amount of land in pasture would increase considerably, the people presumably receiving the bulk of their support from goods pur- chased with the money. If forest cutting were simultaneously permitted (Figure 46), the subsidy still would underwrite population growth, but both mixed farming and pasture would increase. The consequence would be large sedimentation loads. It is possible to simulate the effects of several other policies, but most represent changes that would be similar to, or at least predictable from, the results presented here. For instance, the effects of the removal of people from particular sections could be inferred from the tests which doubled and quadrupled the removal rates from the entire region. Comparison of these simulations is facilitated by the graph in Figure 36, which presents the same results as those in Figures 34, 35, and 37-46, but in a slightly different form. As mentioned earlier, the rates of sedi- Land Use-Water Balance Modeling 117 several population policies were achieved experimentally by first doubling and then quadrupling the rate of emigration from the region. Once again, the coefficient calculated from the 1962-70 rate was doubled for 1975 to achieve this rate. In the first instance (Figure 41), population would eventually be reduced to two-thirds of its level in 1975, assuming that forest cutting had been prohibited since 1967. If cutting had continued, however (Figure 42), the initial decrease would soon be compensated for as increased food supplies (primarily from mixed farming) were grown on land previously in forest. The effects of these two possibilities on the sedimentation load would be significantly different, the latter producing considerably more sediments as additional land was turned into farms. Quadrupling the 1962-70 emigration rate would effectively reduce the population by one-half if the forest area were held constant (Figure 43). Even if forest cutting were to continue, the population would be reduced by one-third (Figure 44); the same effect could be achieved by doubling the emigration rate while maintaining a constant amount of forest. However, the increase in farmland generally results in a higher sedimentation load when cutting is allowed to continue. The most radical policy that could be imposed on the Jagua-Bao region would be to remove all inhabitants. This would allow subsequent regrowth of the vegetation. The results of such a policy are shown only as they affect the sedimentation rate, reducing the load to a very low level that is only slightly above the level resulting from the reversion of forest as indicated earlier. One additional set of possibilities, considerably more humanitarian, was considered. In recognition of the relative poverty of the people in Jagua-Bao, the national government might extend a large, continuing subsidy to the inhabitants of the region (Figure 45). Population size and the amount of land in pasture would increase considerably, the people presumably receiving the bulk of their support from goods pur- chased with the money. If forest cutting were simultaneously permitted (Figure 46), the subsidy still would underwrite population growth, but both mixed farming and pasture would increase. The consequence would be large sedimentation loads. It is possible to simulate the effects of several other policies, but most represent changes that would be similar to, or at least predictable from, the results presented heere. For instance, the effects of the removal of people from particular sections could be inferred from the tests which doubled and quadrupled the removal rates from the entire region. Comparison of these simulations is facilitated by the graph in Figure 36, which presents the same results as those in Figures 34, 35, and 37-46, but in a slightly different form. As mentioned earlier, the rates of sedi-  118 Population and Energy ment accumulation are relative, since actual soil loss from the region is unknown. If the sedimentation rate that results from a continuation of present trends is viewed as a standard, Figure 36 presents the relative advantages and disadvantages of the other policies as they speed or slow the time required to accumulate the same load. Presumably, more ac- curate runoff and erosion data would enable one to indicate actual num- bers of years for each prediction rather than the relative rates presented here. 118 Population and Energy ment accumulation are relative, since actual soil loss from the region is unknown. If the sedimentation rate that results from a continuation of present trends is viewed as a standard, Figure 36 presents the relative advantages and disadvantages of the other policies as they speed or slow the time required to accumulate the same load. Presumably, more ac- curate runoff and erosion data would enable one to indicate actual num- bers of years for each prediction rather than the relative rates presented here. 118 Population and Energy ment accumulation are relative, since actual soil loss from the region is unknown. If the sedimentation rate that results from a continuation of present trends is viewed as a standard, Figure 36 presents the relative advantages and disadvantages of the other policies as they speed or slow the time required to accumulate the same load. Presumably, more ac- curate runoff and erosion data would enable one to indicate actual num- bers of years for each prediction rather than the relative rates presented here.  7. Ecological Factors In Development T HE PAST TWO DECADES have witnessed the rapid expansion of international development projects in Latin America. Most of these projects, related to physical improvement of the region's resource base, have received high priority from lending institutions. Roads, dams, reservoirs, irrigation works, and potable water supplies have led the proj- ect list because planners and politicians alike recognize the existence of a strong infrastructural base to be a prime prerequisite for local, regional, and national economic growth. While local leaders have been responsive to the undertaking of such development, they have been slow to realize that the viable, long-term, stable operations of such projects depend directly upon the rational use of the resource base. Furthermore, because infrastructural development in Latin America has been accompanied by exploitation of natural re- sources, many environmental problems have emerged. Too little has been done by either the international development agencies or the national governments to cope with these problems. The reasons for inaction on this environmental issue lie both in the political arena and in technical fields. Conflicting land tenure claims often discourage the rational use of natural resources at the local level. Inadequate environmental legislation and the lack of technical personnel 119 7. Ecological Factors In Development THE PAST TWO DECADES have witnessed the rapid expansion of international development projects in Latin America. Most of these projects, related to physical improvement of the region's resource base, have received high priority from lending institutions. Roads, dams, reservoirs, irrigation works, and potable water supplies have led the proj- ect list because planners and politicians alike recognize the existence of a strong infrastructural base to be a prime prerequisite for local, regional, and national economic growth. While local leaders have been responsive to the undertaking of such development, they have been slow to realize that the viable, long-term, stable operations of such projects depend directly upon the rational use of the resource base. Furthermore, because infrastructural development in Latin America has been accompanied by exploitation of natural re- sources, many environmental problems have emerged. Too little has been done by either the international development agencies or the national governments to cope with these problems. The reasons for inaction on this environmental issue lie both in the political arena and in technical fields. Conflicting land tenure claims often discourage the rational use of natural resources at the local level. Inadequate environmental legislation and the lack of technical personnel 119 7. Ecological Factors In Development T HE PAST TWO DECADES have witnessed the rapid expansion of international development projects in Latin America. Most of these projects, related to physical improvement of the region's resource base, have received high priority from lending institutions. Roads, dams, reservoirs, irrigation works, and potable water supplies have led the proj- ect list because planners and politicians alike recognize the existence of a strong infrastructural base to be a prime prerequisite for local, regional, and national economic growth. While local leaders have been responsive to the undertaking of such development, they have been slow to realize that the viable, long-term, stable operations of such projects depend directly upon the rational use of the resource base. Furthermore, because infrastructural development in Latin America has been accompanied by exploitation of natural re- sources, many environmental problems have emerged. Too little has been done by either the international development agencies or the national governments to cope with these problems. The reasons for inaction on this environmental issue lie both in the political arena and in technical fields. Conflicting land tenure claims often discourage the rational use of natural resources at the local level. Inadequate environmental legislation and the lack of technical personnel  120 Population and Energy to enforce the legislation, juxtaposed with poorly defined conservation programs and land management policies, explain government inaction at the national level. Technical assistance from international agencies in the conservation of natural resources has been in short supply. On the one hand, these agen- cies realize that additional development-oriented programs could be financed and implemented by adding conservation measures to irrigation or other infrastructural projects. To date, the agencies have lacked the necessary ecological techniques and methods to evaluate environmental impact in cultural as well as ecological terms. What quantitative worth has a soil erosion study or a reforestation project? What is the value of preserving scenic beauty? What investment in ecological surveys is warranted in the developing countries of this hemisphere? In the face of rapid exploitation of the region's resources, these and other questions concerning human impact on the landscape deserve singular attention. This ecological study specifically focuses on one aspect of this impact, namely, the measurement of cumulative effects of land-use change on the long-term future availability of natural re- sources. It demonstrates how ecological modeling techniques can be refined and applied to evaluate quantitatively the ecological impact of human activities on downstream dams and reservoirs. The case of sediment control in the Jagua-Bao region of the Domin- ican Republic has been presented as a microcosm of Latin American regional development. In common with other Latin American countries, the Dominican Republic is faced with the need to accelerate the develop- ment of the country's natural resources in a rational manner that will extend their use through future generations. The republic's ever-increasing demands for power and its relatively rich natural-resource base and large agricultural-labor pool, juxtaposed with a strategic geographical location among its food-scarce Caribbean neighbors, has prompted the government to place great stress on regional plans that utilize the country's hydraulic resources and diversify its agri- cultural base. These plans imply a tremendous fiscal expenditure and public commitment to the theory of whole-basin development. Intrinsic to the plans is the understanding that one must take into account the need to conserve all key resources for the benefit of future populations. The analysis and computer simulations which have been presented show the linkages between population and natural resources and dem- onstrate the impact of changing land-use activities on a downstream reservoir. The results are a small but decisive step toward placing the theory of whole-basin development within a culturally oriented ecological framework. 120 Population and Energy to enforce the legislation, juxtaposed with poorly defined conservation programs and land management policies, explain government inaction at the national level. Technical assistance from international agencies in the conservation of natural resources has been in short supply. On the one hand, these agen- cies realize that additional development-oriented programs could be financed and implemented by adding conservation measures to irrigation or other infrastructural projects. To date, the agencies have lacked the necessary ecological techniques and methods to evaluate environmental impact in cultural as well as ecological terms. What quantitative worth has a soil erosion study or a reforestation project? What is the value of preserving scenic beauty? What investment in ecological surveys is warranted in the developing countries of this hemisphere? In the face of rapid exploitation of the region's resources, these and other questions concerning human impact on the landscape deserve singular attention. This ecological study specifically focuses on one aspect of this impact, namely, the measurement of cumulative effects of land-use change on the long-term future availability of natural re- sources. It demonstrates how ecological modeling techniques can be refined and applied to evaluate quantitatively the ecological impact of human activities on downstream dams and reservoirs. The case of sediment control in the Jagua-Bao region of the Domin- ican Republic has been presented as a microcosm of Latin American regional development. In common with other Latin American countries, the Dominican Republic is faced with the need to accelerate the develop- ment of the country's natural resources in a rational manner that will extend their use through future generations. The republic's ever-increasing demands for power and its relatively rich natural-resource base and large agricultural-labor pool, juxtaposed with a strategic geographical location among its food-scarce Caribbean neighbors, has prompted the government to place great stress on regional plans that utilize the country's hydraulic resources and diversify its agri- cultural base. These plans imply a tremendous fiscal expenditure and public commitment to the theory of whole-basin development. Intrinsic to the plans is the understanding that one must take into account the need to conserve all key resources for the benefit of future populations. The analysis and computer simulations which have been presented show the linkages between population and natural resources and dem- onstrate the impact of changing land-use activities on a downstream reservoir. The results are a small but decisive step toward placing the theory of whole-basin development within a culturally oriented ecological framework. 120 Population and Energy to enforce the legislation, juxtaposed with poorly defined conservation programs and land management policies, explain government inaction at the national level. Technical assistance from international agencies in the conservation of natural resources has been in short supply. On the one hand, these agen- cies realize that additional development-oriented programs could be financed and implemented by adding conservation measures to irrigation or other infrastructural projects. To date, the agencies have lacked the necessary ecological techniques and methods to evaluate environmental impact in cultural as well as ecological terms. What quantitative worth has a soil erosion study or a reforestation project? What is the value of preserving scenic beauty? What investment in ecological surveys is warranted in the developing countries of this hemisphere? In the face of rapid exploitation of the region's resources, these and other questions concerning human impact on the landscape deserve singular attention. This ecological study specifically focuses on one aspect of this impact, namely, the measurement of cumulative effects of land-use change on the long-term future availability of natural re- sources. It demonstrates how ecological modeling techniques can be refined and applied to evaluate quantitatively the ecological impact of human activities on downstream dams and reservoirs. The case of sediment control in the Jagua-Bao region of the Domin- ican Republic has been presented as a microcosm of Latin American regional development. In common with other Latin American countries, the Dominican Republic is faced with the need to accelerate the develop- ment of the country's natural resources in a rational manner that will extend their use through future generations. The republic's ever-increasing demands for power and its relatively rich natural-resource base and large agricultural-labor pool, juxtaposed with a strategic geographical location among its food-scarce Caribbean neighbors, has prompted the government to place great stress on regional plans that utilize the country's hydraulic resources and diversify its agri- cultural base. These plans imply a tremendous fiscal expenditure and public commitment to the theory of whole-basin development. Intrinsic to the plans is the understanding that one must take into account the need to conserve all key resources for the benefit of future populations. The analysis and computer simulations which have been presented show the linkages between population and natural resources and dem- onstrate the impact of changing land-use activities on a downstream reservoir. The results are a small but decisive step toward placing the theory of whole-basin development within a culturally oriented ecological framework.  Ecological Factors in Development 121 It is clear that land management policies or the lack of them in catch- ment areas will affect, for better or worse, conditions downstream at a reservoir site. The absence of such policies, an all-too-frequent occur- rence, has resulted in the failure of many projects crucial to the im- provement of conditions in developing areas.' In the specific case of Jagua-Bao, should the government of the Dominican Republic wish to utilize to the fullest its investment in this hydroelectric facility and ex- tend the reservoir's life expectancy, policy makers must establish con- servation-oriented plans for the use of upstream land resources. To assist planners in reaching such development decisions, Figure 47 is presented. It summarizes in graphic form the relative amounts of sedi- ment that would accumulate in the reservoir under twelve land-manage- ment conditions. The vertical dashed line in the center of the graph indicates the relative sediment load that will be produced if present trends are continued over the next fifty years; this line therefore repre- sents a standard for comparison of the results of other policies. The relative positions of the other bars indicate the amount of time it would take Jagua-Bao under each distinct land-management policy-from re- growth of the forest to dominance of pasture land-to achieve the same total amount of siltation as would be achieved by the standard land use in the year 2025, fifty years after the installation of the reservoir. Bars shorter than the mid-bar indicate more rapid rates of sediment accumu- lation, while the longer bars portray slower rates of sedimentation. Over the wide range of land-use policies presented, the time required for each public policy to reach the same sediment load differs by more than thirty years. In relative terms, the increased conversion of forest to pasture results in a decrease of more than a decade in time required to reach the standard sediment load. In contrast, a stringent forest protection policy increases the time to reach that sediment load by nearly twenty years. Because of the conservative relative-erosion rates assigned to each of the land-use categories in the integrated model, Figure 47 represents minimal differences to be expected as a result of instituting one of a variety of population and land management decisions upstream from the proposed Jagua-Bao reservoir. As in the case of data presented from the previous chapters, the summary does not purport to make or recommend policy decisions. Rather, it provides analysis of data upon which rational 1. Last-minute intervention in the Anchicaya hydroelectric project in Colombia eetrieved the project from failure, primarily because of the lack of compensation for sedimentation. This project is discussed in detail by R. N. Allen, "The Anchicaya Hydroelectric Project in Colombia: Design and Sedimentation Problems," in The Careless Technology: Ecology and International Development, ed. M. Taghi Farvar and J. P. Milton (Garden City, N. Y.: Natural History Press, 1972), pp. 318-48. Ecological Factors in Development 121 It is clear that land management policies or the lack of them in catch- ment areas will affect, for better or worse, conditions downstream at a reservoir site. The absence of such policies, an all-too-frequent occur- rence, has resulted in the failure of many projects crucial to the im- provement of conditions in developing areas? In the specific case of Jagua-Bao, should the government of the Dominican Republic wish to utilize to the fullest its investment in this hydroelectric facility and ex- tend the reservoir's life expectancy, policy makers must establish con- servation-oriented plans for the use of upstream land resources. To assist planners in reaching such development decisions, Figure 47 is presented. It summarizes in graphic form the relative amounts of sedi- ment that would accumulate in the reservoir under twelve land-manage- ment conditions. The vertical dashed line in the center of the graph indicates the relative sediment load that will be produced if present trends are continued over the next fifty years; this line therefore repre- sents a standard for comparison of the results of other policies. The relative positions of the other bars indicate the amount of time it would take Jagua-Bao under each distinct land-management policy-from re- growth of the forest to dominance of pasture land-to achieve the same total amount of siltation as would be achieved by the standard land use in the year 2025, fifty years after the installation of the reservoir. Bars shorter than the mid-bar indicate more rapid rates of sediment accumu- lation, while the longer bars portray slower rates of sedimentation. Over the wide range of land-use policies presented, the time required for each public policy to reach the same sediment load differs by more than thirty years. In relative terms, the increased conversion of forest to pasture results in a decrease of more than a decade in time required to reach the standard sediment load. In contrast, a stringent forest protection policy increases the time to reach that sediment load by nearly twenty years. Because of the conservative relative-erosion rates assigned to each of the land-use categories in the integrated model, Figure 47 represents minimal differences to be expected as a result of instituting one of a variety of population and land management decisions upstream from the proposed Jagua-Bao reservoir. As in the case of data presented from the previous chapters, the summary does not purport to make or recommend policy decisions. Rather, it provides analysis of data upon which rational 1. Last-minute intervention in the Anchicaya hydroelectric project in Colombia retrieved the project from failure, primarily because of the lack of compensation for sedimentation. This project is discussed in detail by R. N. Allen, "The Anchicaya Hydroelectric Poject in Colombia: Design and Sedimentation Problems," in The Careless Technology: Ecology and International Development, ed. M. Taghi Farvar and J. P. Milton (Garden City, N. Y.: Natural History Press, 1972), pp. 318-48. Ecological Factors in Development 121 It is clear that land management policies or the lack of them in catch- ment areas will affect, for better or worse, conditions downstream at a reservoir site. The absence of such policies, an all-too-frequent occur- rence, has resulted in the failure of many projects crucial to the im- provement of conditions in developing areas.' In the specific case of Jagua-Bao, should the government of the Dominican Republic wish to utilize to the fullest its investment in this hydroelectric facility and ex- tend the reservoir's life expectancy, policy makers must establish con- servation-oriented plans for the use of upstream land resources. To assist planners in reaching such development decisions, Figure 47 is presented. It summarizes in graphic form the relative amounts of sedi- ment that would accumulate in the reservoir under twelve land-manage- ment conditions. The vertical dashed line in the center of the graph indicates the relative sediment load that will be produced if present trends are continued over the next fifty years; this line therefore repre- sents a standard for comparison of the results of other policies. The relative positions of the other bars indicate the amount of time it would take Jagua-Bao under each distinct land-management policy-from re- growth of the forest to dominance of pasture land-to achieve the same total amount of siltation as would be achieved by the standard land use in the year 2025, fifty years after the installation of the reservoir. Bars shorter than the mid-bar indicate more rapid rates of sediment accumu- lation, while the longer bars portray slower rates of sedimentation. Over the wide range of land-use policies presented, the time required for each public policy to reach the same sediment load differs by more than thirty years. In relative terms, the increased conversion of forest to pasture results in a decrease of more than a decade in time required to reach the standard sediment load. In contrast, a stringent forest protection policy increases the time to reach that sediment load by nearly twenty years. Because of the conservative relative-erosion rates assigned to each of the land-use categories in the integrated model, Figure 47 represents minimal differences to be expected as a result of instituting one of a variety of population and land management decisions upstream from the proposed Jagua-Bao reservoir. As in the case of data presented from the previous chapters, the summary does not purport to make or recommend policy decisions. Rather, it provides analysis of data upon which rational 1. Last-minute intervention in the Anchicaya hydroelectric project in Colombia retrieved the project from failure, primarily because of the lack of compensation for sedimentation. This project is discussed in detail by R. N. Allen, "The Anchicaya Hydroelectric Project in Colombia: Design and Sedimentation Problems," in The Careless Technology: Ecology and International Development, ed. M. Taghi Farvar and J. P. Milton (Garden City, N. Y.: Natural History Press, 1972), pp. 318-48.  _= r 9 0 3 c 3 c A = o a - - - - - - - - - - - - - -- = r' 3 9 0 A N I o. - 0 3 f a.. 3 . _ 1  Ecological Factors in Development 123 decisions can be made. The final selection of a particular policy is left to those responsible for national planning. While this study has uncovered much information on the relationships between changing land use and resource utilization in the tropics, it is not a definitive answer to the question of what the total amounts of sediment are that can be expected to accumulate in the reservoir under various land-management policies over the next fifty years. What is pro- vided, however, is a framework of relative environmental costs and benefits-stated in terms of decreasing or increasing the life expectancy of the reservoir-that should prove useful in guiding further watershed planning. From a theoretical standpoint, success was achieved in reproducing population trends and land-use patterns with the land-use model. The predictive capability of the model makes it a useful tool, although it must be remembered that errors in interpretation increase considerably as pro- jections are carried much farther into the future. It should be noted that projected population trends produced by this model differ somewhat from those produced by an earlier model as a result of simulation of an in- crease of emigration in the 1960s and effective enforcement of the 1967 law prohibiting forest cutting. The results indicate that further changes in the near future could bring about an entirely different solution to the problem of resource depletion in Jagua-Bao. The approach presented here represents the refinement of several re- search procedures which should be of considerable use to future workers in the fields of settlement geography, tropical ecology, and resource de- velopment. The land-use model is a simplistic but very useful method of evaluating the basic land-resource requirements of a small rural popula- tion. The simulation of changes in land use as a function of the amount of energy that people utilize from their environment imparts a spatial as well as a temporal dimension to changes in the population. A more detailed model of the relationship between people and the land would include an expansion of the demographic variables to account for the lag in population response to changing environmental conditions. Notwith- standing this future refinement, the model has served well in reproducing the land-use changes that have been observed in the past. The development of a quantitative mapping technique to assess both natural and harvested-yield power density has proven to be extremely useful in spatially portraying the magnitude of both ecologic and eco- nomic change within the region. In spite of the drawback of not having an empirical data base, and having to rely on estimates from the litera- ture, it is evident that this mapping technique demonstrates in quantifiable Ecological Factors in Development 123 decisions can be made. The final selection of a particular policy is left to those responsible for national planning. While this study has uncovered much information on the relationships between changing land use and resource utilization in the tropics, it is not a definitive answer to the question of what the total amounts of sediment are that can be expected to accumulate in the reservoir under various land-management policies over the next fifty years. What is pro- vided, however, is a framework of relative environmental costs and benefits-stated in terms of decreasing or increasing the life expectancy of the reservoir-that should prove useful in guiding further watershed planning. From a theoretical standpoint, success was achieved in reproducing population trends and land-use patterns with the land-use model. The predictive capability of the model makes it a useful tool, although it must be remembered that errors in interpretation increase considerably as pro- jections are carried much farther into the future. It should be noted that projected population trends produced by this model differ somewhat from those produced by an earlier model as a result of simulation of an in- crease of emigration in the 1960s and effective enforcement of the 1967 law prohibiting forest cutting. The results indicate that further changes in the near future could bring about an entirely different solution to the problem of resource depletion in Jagua-Bao. The approach presented here represents the refinement of several re- search procedures which should be of considerable use to future workers in the fields of settlement geography, tropical ecology, and resource de- velopment. The land-use model is a simplistic but very useful method of evaluating the basic land-resource requirements of a small rural popula- tion. The simulation of changes in land use as a function of the amount of energy that people utilize from their environment imparts a spatial as well as a temporal dimension to changes in the population. A more detailed model of the relationship between people and the land would include an expansion of the demographic variables to account for the lag in population response to changing environmental conditions. Notwith- standing this future refinement, the model has served well in reproducing the land-use changes that have been observed in the past. The development of a quantitative mapping technique to assess both natural and harvested-yield power density has proven to be extremely useful in spatially portraying the magnitude of both ecologic and eco- nomic change within the region. In spite of the drawback of not having an empirical data base, and having to rely on estimates from the litera- ture, it is evident that this mapping technique demonstrates in quantifiable Ecological Factors in Development 123 decisions can be made. The final selection of a particular policy is left to those responsible for national planning. While this study has uncovered much information on the relationships between changing land use and resource utilization in the tropics, it is not a definitive answer to the question of what the total amounts of sediment are that can be expected to accumulate in the reservoir under various land-management policies over the next fifty years. What is pro- vided, however, is a framework of relative environmental costs and benefits-stated in terms of decreasing or increasing the life expectancy of the reservoir-that should prove useful in guiding further watershed planning. From a theoretical standpoint, success was achieved in reproducing population trends and land-use patterns with the land-use model. The predictive capability of the model makes it a useful tool, although it must be remembered that errors in interpretation increase considerably as pro- jections are carried much farther into the future. It should be noted that projected population trends produced by this model differ somewhat from those produced by an earlier model as a result of simulation of an in- crease of emigration in the 1960s and effective enforcement of the 1967 law prohibiting forest cutting. The results indicate that further changes in the near future could bring about an entirely different solution to the problem of resource depletion in Jagua-Bao. The approach presented here represents the refinement of several re- search procedures which should be of considerable use to future workers in the fields of settlement geography, tropical ecology, and resource de- velopment. The land-use model is a simplistic but very useful method of evaluating the basic land-resource requirements of a small rural popula- tion. The simulation of changes in land use as a function of the amount of energy that people utilize from their environment imparts a spatial as well as a temporal dimension to changes in the population. A more detailed model of the relationship between people and the land would include an expansion of the demographic variables to account for the lag in population response to changing environmental conditions. Notwith- standing this future refinement, the model has served well in reproducing the land-use changes that have been observed in the past. The development of a quantitative mapping technique to assess both natural and harvested-yield power density has proven to be extremely useful in spatially portraying the magnitude of both ecologic and eco- nomic change within the region. In spite of the drawback of not having an empirical data base, and having to rely on estimates from the litera- ture, it is evident that this mapping technique demonstrates in quantifiable  124 Population and Energy terms the degree of the ecological impact resulting from the changing use of the land. A significant feature of the study has been the use of energy units to evaluate and compare land-use patterns. Energy flow modeling permits a direct assessment of the land-use activities and facilitates the compari- son of inputs and outputs in terms of gains and losses of energy. By working with units of energy, it is possible to evaluate the land-use changes graphically, simply by determining the magnitudes of yields and the energy spent by people within the region. The energy flow language is particularly useful in this kind of analysis, because interactions between flows of energy, information, and matter can be demonstrated without invoking different kinds of symbols for basically similar units and pro- cesses. Moreover, no flows are hidden in this language. The energy flow diagrams obey the Laws of Thermodynamics by indicating that each interaction of flows and each change in the form of energy being used is accompanied by dispersal of heat. More important, perhaps, is the fact that the energy flow diagram represents a mathematical statement which can be readily translated into equations for solution on a computer. While these equations might well be arrived at by other means, the process of diagramming the entire system first allows both the modeler and the observer to visualize and perhaps to modify the system before simulation. In the final analysis, an understanding of the far-reaching effects that a successful river-basin development program may have for a nation like the Dominican Republic requires that the dynamic nature of resource management be placed within the total context of relationships between people and the land. Failure to do so leaves planning for human well- being on a level of guesswork that cannot be justified today. 124 Population and Energy terms the degree of the ecological impact resulting from the changing use of the land. A significant feature of the study has been the use of energy units to evaluate and compare land-use patterns. Energy flow modeling permits a direct assessment of the land-use activities and facilitates the compari- son of inputs and outputs in terms of gains and losses of energy. By working with units of energy, it is possible to evaluate the land-use changes graphically, simply by determining the magnitudes of yields and the energy spent by people within the region. The energy flow language is particularly useful in this kind of analysis, because interactions between flows of energy, information, and matter can be demonstrated without invoking different kinds of symbols for basically similar units and pro- cesses. Moreover, no flows are hidden in this language. The energy flow diagrams obey the Laws of Thermodynamics by indicating that each interaction of flows and each change in the form of energy being used is accompanied by dispersal of heat. More important, perhaps, is the fact that the energy flow diagram represents a mathematical statement which can be readily translated into equations for solution on a computer. While these equations might well be arrived at by other means, the process of diagramming the entire system first allows both the modeler and the observer to visualize and perhaps to modify the system before simulation. In the final analysis, an understanding of the far-reaching effects that a successful river-basin development program may have for a nation like the Dominican Republic requires that the dynamic nature of resource management be placed within the total context of relationships between people and the land. Failure to do so leaves planning for human well- being on a level of guesswork that cannot be justified today. 124 Population and Energy terms the degree of the ecological impact resulting from the changing use of the land. A significant feature of the study has been the use of energy units to evaluate and compare land-use patterns. Energy flow modeling permits a direct assessment of the land-use activities and facilitates the compari- son of inputs and outputs in terms of gains and losses of energy. By working with units of energy, it is possible to evaluate the land-use changes graphically, simply by determining the magnitudes of yields and the energy spent by people within the region. The energy flow language is particularly useful in this kind of analysis, because interactions between flows of energy, information, and matter can be demonstrated without invoking different kinds of symbols for basically similar units and pro- cesses. Moreover, no flows are hidden in this language. The energy flow diagrams obey the Laws of Thermodynamics by indicating that each interaction of flows and each change in the form of energy being used is accompanied by dispersal of heat. More important, perhaps, is the fact that the energy flow diagram represents a mathematical statement which can be readily translated into equations for solution on a computer. While these equations might well be arrived at by other means, the process of diagramming the entire system first allows both the modeler and the observer to visualize and perhaps to modify the system before simulation. In the final analysis, an understanding of the far-reaching effects that a successful river-basin development program may have for a nation like the Dominican Republic requires that the dynamic nature of resource management be placed within the total context of relationships between people and the land. Failure to do so leaves planning for human well- being on a level of guesswork that cannot be justified today.  Appendix A HYDROLOGICAL CHARACTERISTICS OF JAGUA RIVER DRAINAGE BASING A. TOPOGRAPHIC CHARACTERISTICS Area 5=394 km2 Average width=I=S/L=8.4 km Length L=47 km Ratio I/L=0.18 Max. height Zmax=1,840 Lit Average basin slope (Zmax-Zo)/L=0.034 Height of river at station Zo=240 m Massiveness coefficient=h2-C-I=1,104 B. HYDRAULIC CHARACTERISTICS-STREAM PLOW REGIME Jan. Feb. Mar. Apr. May June Representative data for the year Discharge 3.10 3.00 2.60 5.40 13.70 5.90 Rainfall, mm=1,488 Average Rainfall, hm3 21.52 22.98 33.74 53.31 92.43 60.64 Flow deficit (losses), mm=798 year Runoff, hens 11.23 9.68 9.36 20.47 55.13 22.38 Runoff coefficient= 0.46 Extreme flows, m3-see-1 3.50 20.60 Specific runoff, I-sec-l.km-2=22 Dry Discharge 2.10 1.55 1.41 1.76 11.62 14.36 Rainfall, man= 1,085 year Rainfall, hm3 18.76 9.28 4.28 14.21 89.03 49.97 Flow deficit (losses), mm=505 (1947) Runoff, hm3 7.72 5.12 5.14 6.22 42.50 50.86 Runoff coefficient=0.53 Extreme flows, m3"sec-1 1.90 Specific runoff, I"sec-l-km-2=18 Wet Discharge 8.4 10.60 40.10 17.70 15.20 8.40 Rainfall, mm_2,496 year Rainfall, hm3 53.83 60.99 172.91 90.52 92.17 66.51 Flow deficit (losses), mm =842 (1960) Runoff, hm3 29.62 35.51 149.15 62.81 54.26 28.92 Runoff coefficient =0.67 Extreme flows, m3"sec-I 54.50 Specific runoff, I-seo-I"km-2=52 Continued Appendix A HYDROLOGICAL CHARACTERLSTICS OF JAGUA RIVER DRAINAGE BASING A. TOPOGRAPHIC CHARACTERISTICS Area S=394 km2 Average width= 1 =S/L=8.4 kin Length L=47 km Ratio 1/L=0.18 Max. height Zmax=1,840 m Average basin slope (Zmax-Zo)/L=0.034 Height of river at station Zo=240 m Massiveness coefficient=h2"sec-1=1,104 B. HYDRAULIC CHARACTERISTICS-STREAM FLOW REGIME Jan. Feb. Mar. Apr. May June Representative data for the year Discharge 3.10 3,00 2.60 5.40 13.70 5.90 Rainfall, mm=1,488 Average Rainfall, hm3 21.52 22.98 33.74 53.31 92.43 60.64 Flow deficit (losses), mm=798 year Runoff, hm3 11.23 9.68 9.36 20.47 55.13 22.38 Runoff coefficient=0.46 Extreme flows, m2 sec-I 3.50 20,60 Specific runoff, I-sec-l-km-2=22 Dry Discharge 2.10 1.55 1,48 1.76 11.62 14.36 Rainfall, mm=1,085 year Rainfall, hma 18.76 9.28 4.28 14.21 89.03 49.97 Flow deficit (losses), mm=505 (1947) Runoff, hens 7.72 5.12 5.14 6.22 42,50 50.86 Runoff coefficient= 0.53 Extreme flows, m3"sec-I 1.90 Specific runoff, I"see 1.km-2=18 Discharge 8.40 10.60 40.10 17.70 15.20 8.40 Rainfall, mm=2,496 year Rai.1.11, hm3 53.83 60.99 172.91 90.52 92,17 66.51 Flow deficit (losses), mm=842 (1960) Runoff, hm3 29.62 35.51 149.15 62.81 54.26 28.92 Runoff coefficient=0.67 Extreme flows, m3"sec-1 54.50 Specific runoff, I-Acc-l-km-2=52 Continued Appendix A HYDROLOGICAL CHARACTERISTICS OF JAGHA Mena DRAINAGE BASINa A. TOPOGRAPHIC CHARACTERISTICS Area 5=394 km2 Average width =l=S/L=8.4 km Length L=47 km Ratio 1/L=0.18 Max. height Zmax=1,840 m Average basin slope (Zmax-Zo)/L=0.034 Height of river at station Zo=240 m Massiveness coefficient=h2"sec-I=1,104 B. HYDRAULIC CHARACTERISTICS-STREAM FLOW REGIME Jan. Feb. Mar. Apr. May June Representative data for the year Discharge 3.10 3.00 2.60 5.40 13.70 5.90 Rainfall, mm=1,488 Average Rainfall, hms 21.52 22.98 33.74 53.31 92.43 60.64 Flow deficit (losses), mm=798 year Runoff, turns 11.23 9.68 9.36 20.47 55.13 2238 Runoff coefficient -0.46 Extreme flows, .3.sec-I 3.50 20.60 Specific runoff, I-sec-l.km-2=22 Dry Discharge 2.10 1.55 1.41 1.76 11.62 14.36 Rainfall, mm=1,085 yem Rainfall, hms 18.76 9.28 4.28 14.21 89.03 49.97 Flow deficit (losses), mm=505 (1947 Runoff, hms 7.72 5.12 5.14 6.22 42.50 50.86 Runoff coefficient=0.53 Extreme flows, m3-sec-I 1.90 Specific runoff, 1"sec-l.km-2=18 wet Discharge 8.40 10.60 40.10 17.70 15.20 840 Rainfall, mm=2,496 year Raifall, hms 53.83 60.99 172.91 90.52 92.17 66.51 Flow deficit (losses), mm=842 (1960) Runoff, hms 29.62 35.51 149.15 62.81 54.26 28.92 Runoff coefficient -0.67 Extreme flows, m3-sec-I 54.50 Specific runoff, I-sec I"km-2=52 Continued  B. HYDRAULICCHARACTERISTics--Continued B. HYDRAULIC CHARACTERISTICS--COndnued R. HYDRAULIC CHARACTERISTICS-Continued July Aug. Sept. Oct. Nov. Dec. Representative data for the year July Aug. Sept. Oct, Nov. Dec. Representative data for the year July Aug. Sept. Oct. Nov. Dec. Representative t Discharge 3.50 4.90 8.20 9.10 6.40 4.50 Rainfall, mm-1,488 Discharge 3.50 4.90 8.20 9.10 6.40 4.50 Rainfall, mm=1,488 Discharge 7.50 4.90 8.20 9.10 6.40 4.50 Rainfll, mm= Average Rainfall, hms 31.79 47.97 66.02 70.42 52.73 3725 Flow deficit (losses), usm=798 Average Rainfall, hms 31.79 47,93 66,02 70.42 52.33 33.25 Flow deficit (losses), mm=798 Average 1I( Rainfall, hms 71.79 47.93 66.02 10.42 52.33 33.25 Flow adeficit (to year Runoff, buss 12.85 19.58 31.39 36.63 24.60 1820 Runoff coeffcent-0.A6 year Runoff, hms 12.85 19.58 31.59 36.63 24-b0 16,20 Runoff coefficient=0.46 year ( Runoff, buss 12.85 19.58 31.59 36.63 24.W 18.20 Runoff eoefBaei l Extreme flaws, M3.Seo-1 Specific runoff, I"secl"km-R=22 Extreme flows, M3.Sec-1 Specific runoff, I-sect"km-2=22 Extreme flows, m3-secI Specific runoff, Discharge 2.11 2.88 9.05 13.24 1.41 1.84 Rainfall , mm-1,085 Discharge 2,11 2.88 9.05 13.24 1.41 1.84 Rainfall, mm=1,085 Discharge 2.11 2.88 9.05 13.24 1.41 1.84 Rainfall, In- Dry I( Rainfall, hms 15.09 37.25 90.43 73,19 5.76 19.28 Flow deficit (losses), ruse=505 Dry Rainfall, hms 15.09 77.25 90.43 73.19 5.76 19.28 Flow deficit (losses), mm_505 Dry Rainfall, hms 15.09 37.25 90.47 73.19 5.76 19.28 Flaw deficit (lo(1947) J Runoff, hms 7.72 10 y at l Extreme flows, ms-sect 18.10 1.90 Specific noff, l-See Lk-2=18 Extreme flows, m3aec-1 18.10 1.90 Specific runoff, I-see-l"km-2=18 Extreme flows, ms-see-1 18.10 1.90 Specific runoff, Discharge 5.40 2.30 20.60 21.70 3.90 25.10 Rainfall, mm=2,496 Discharge 5,40 2.50 20.60 21.70 3.90 25,10 Rainfall, m- 2,496 Discharge 5,40 2.50 20.60 21.70 3.90 25.10 Rainfall, mm='. Wet Rainfall, hms 58.84 17.12 109.32 113.70 31.44 115.89 Flow deficit (losses), mm= 942 Wet Rainfall, hms 58.84 17.12 109.32 117.70 31.44 115.89 Flow deficit (losses), m- 842 Wet Rainfall, hurt 58.84 17.12 109.32 113.70 31.44 115,89 Flow deficit (to year year year (1960) Runoff, hms 19.02 9.80 72.57 79.62 15.50 94.87 Runoff coefficient= 0.67 (1960) Runoff, hms 19.02 9.80 72.57 79.62 15.50 94.87 Runoff coefficient= 0.67 (1960) Runoff, hms 19.02 9.80 72.57 79.62 15.50 94.87 Runoff coeflicie, Extreme flaws, .3-S-1 3.70 Specific runoff, I-sert"km.R=52 Extreme flows, net-e-1 3.70 Specific runoff, laec1.koT2=52 Exveme flows, ms sere 3.70 Specific runoff, C. PROJECT DESIGN FLOOD C. EROJECT DESIGN T-on C. FROJFCT DESIGN FLOOD Morphological flood (greater than 1,000-year flood) in M3.Sec.1 . 3,100 Morphological flood (greater than 1,000-year flood) in ms.sec-t = 3,100 Morphological flood (greater than 1,000-year flood) in ml-sec 1 = 3,100 D. MEAN ANNUAL .SEDIMENT LOAD D. MOAN ANNUAL SEDIMENT LOAD D. MEAN ANNUAL SEDIMENT LOAD Specific degradation (DS = 1,240 tons" m yr Specific degradation Hiss) =1,240 tonskm-2-yr-1 Specific degradation (DS)=1,240 tonskm-2"yr-T Suspended load=500,000 tons"yr-1 Suspended load=500,000 tonsyr-I Suspender) load-500,000 tonsyr-1 Bed load=6,300 tons-yrl Bed load_6,300 wns-yrl tied 1oad=6,300 tons-yI a. Adapted from S-eys for the Multipurpose Development of the Yaque del Norte and Yaque del Sur River Basins, 6 vols. (Grenoble: SOGREAH, e. Adapted from Surveys for the Multipurpose Development o) the Yaque del Norte and Yaque del Sur River Basins, 6 vols. (Grenoble: socR"H, a. Adapted from Surveys for the Multipurpwe Develupnuent of the Yaque del None and Yaque del Sur River Basins, 6 vols. (( 1968), 5:8,10, 12, and 2:ftem 2.226, Table 2. 1968), 5:8, 10, 12, and 2:item 2 226, "fable 2. 1968), 5:8,10, 12, and 2:item 2226, Table 2.  Appendix B Appendix B Appendix B COMPUTERo PROGRMAN WATERl BALANCE CALCULAIONS OREPSNTIE LIFE ZONE AT 300-, 200-, AND 100-MILLoIETER SOIL DEPTH 0001 DIMENSION TEMP( 12),PRECIP(12),C( 12),DEF( 12),WAT(12) 0002 DIMENSION EVAP(12),DEPL(12),RUN( 12),RECHRG(12), $SUR) 12) 0003 COMPLEXI16 LOCATN 0004 C(1)=C()C(5))=C7)=C(8)=C10)=C(12)=. 0005 C(2)'=4.56 0006 C(4)=C(6)=C(9)=C(11)=4.84 0007 5 READ,LOCATN,SOILDP,BLKDEN,FLDCAP,WILTPT 0008 READ ,TEMP 0009 READ PRECIP 0010 WRITE (6,15) LOCATN 0011 15 FORMAT(///2A8) 0012 WRITE (6.16) SOILDP,BLKDEN 0013 16 FORMAT ('LOCATIONAL PARAMETERS: SOIL DEPTH 0014 $=',F6.1,' MM, SULK DENSITY=',FS.2,' GM/CU CC') 0015 WRITE (6,17) FLDCAP, WILTPT 0016 17 FORMAT(T24,'PERCENT FIELD CAPACITY ='F52' 0017 $PERCENT PERMANENT WILTING POINT =',F5.2) 0018 SOILDP=SOILDP*BLKDEN 0019 FLDCAP=FLDCAP*SOILDP 0020 WILTPT=WILTPT*SOILDP COMPUTE PR0ORA AN WATER BALANCE CALCLAToIONS FR REPRSENTATIE LIFE ZOE AT 300-, 200-, AD100-MILLIM0EE S0IL DEPTHS 0001 DIMENSION TEMP)12),PRECIP) 12),C) 12),DEF) 12).WAT)12) 0002 DIMENSION EVAP(12),DEPL)12),RUN(I2),RECHRG)12), $SUR)12) 0003 COMPLEX-16 LOCATN 0004 C())=C(3)=C(5) =C(7)=~C()= C(10) =C)12)=5. 0005 C(2)=4.56 0006 C(4)=C(6)=C) )C(11)=4.84 0007 5 READ,LOCATN,SOILDP,BLKDEN,FLDCAP,WILTPT 0008 READ ,TEMP 0009 READ PRECIP 0010 WRITE (6,15) LOCATN 0011 15 FORMAT(///2A8) 0012 WRITE (6,16) SOILDP,BLKDEN 0013 16 FORMAT ('LOCATIONAL PARAMETERS: SOIL DEPTH 0014 $=',F6.1,' MM, BULK DENSITY =',F5.2,' GM/CU CC') 0015 WRITE (6,17) FLDCAP, WILTPT 0016 17 FORMAT)T24,'PERCENT FIELD CAPACITY =' 1P5.2,', 0017 $PERCENT PERMANENT WILTING POINT =',F5.2) 0018 SOILDP=SOILDP*BLKDEN 0010 FLDCAP=FLDCAP*SOILDP 0020 WILTPT=WILTPT*SOILDP ConinuedO COMPUER PROGRAMAN WATER BALANCE CALCLTONS FORl REPREENTAIE LIFE ZONES AT 300-, 200-, AND 100-MILLIMETER SOIL 0DEP11S 0001 DIMENSION TEMP) 12),PRECIP)12),C(),75F)12),WAT)12) 0002 DIMENSION EVAP)(12),DEPL) 12),RUN) 12).RECPIRO)12) ISUR) 12) 0003 COMPLEX-16 LOCATN 0004 C())=C(3)=C(5) =C(7)=C())=C)10)=C12)=5. 0005 C(2) =4.56 0006 C(4)=~C(6)=C()=)C(11)=4.84 0007 5 READ,LOCATN,SOILDP,BLKDEN,FLDCAP,WILTPT 0008 READ ,TEMP 0009 READ PRECIP 0010 WRITE (6,15) LOCATN 0011 15 FORMAT(///2A8) 0012 WRITE (6,16) SOILDP,BLKDEN 0013 16 FORMAT ('LOCATIONAL PARAMETERS: SOIL DEPTH 0014 $=',F6.1,' MM, BULK DENSITY =',F5.2,' GM/CU CC') 0015 WRITE (6,17) FLDCAP, WILTPT 0016 17 FORMAT)T24,'PERCENT FIELD CAPACITY =' ,52 0017 $PERCENT PERMANENT WILTING POINT =',1F5.2) 0018 SOILDP=SOILDP*BLKDEN 0019 FLDCAP=FLDCAP*SOILDP 0020 WILTPT=WILTPT*SILDP Continued 127 127  128 Population and Energy APPENDIX B-Cninued 0821 SOILDP=FLDCAP-WILTPT 8822 WRITE(6,25) FLDCAP,WILTPT,SOILDP 8823 25 FORMAT(T24, 'FIELD CAPACITY =',F6.1,' MM, n024 $PERMANENT WILTING POINT ,' _' ,F6.1, 'MM, AVAIL $SOIL MOISTURE =',F6.1,'MM') 8025 WRITE (6,27) 8026 27 FORMAT(T33,JAN FEB MAR APR MAY 8827 $JUN JUL AUG SEP OCT NOV DEC $ YEAR') 0028 SUM=0. 0029 DO 30I=1,12 003n 30 SUM=SUM+TEMP (I) on31 SUM=SUM/12. 8832 WRITE(6,40) TEMPSUM 0033 48 FORMAT(' MEAN AIR TEMPERATURE' ,8X,13F7.1) 8834 WRITE(6,50) TEMPSUM 0035 50 FORMAT)' MEAN BIOTEMPERATURE' ,9X,13F7.1) 0036 SUM=0. 0037 TOT=0. 0030 DO 60 1=1,12 0039 TEMP(I)=TEMP(I)*C(I) 0048 SUM=SUM+TEMP(I) 0841 60 TOT=TOT+PRECIP(I) 0042 WRITE(6,70) TEMP,SUM 0043 70 FORMAT)' POTENTIAL EVAPOTRANSPIRATION',13F7.i) 0044 FAC=TOT/SUM 0045 IF(FAC-1.) 90,90,80 0046 80 FAC=1. 0047 90 DO01001I=1,12 0048 100 TEMP(I)=TEMP(I)*FAC 0049 SUM=SUM*FAC 0050 WRITE(6,110) TEMPSUM 0051 110 FORMAT)' POT. EVAP. ADJ. DRY CLIMIATE ',13F7.1) 0052 WRITE)6,120) PRECIPTOT 0053 120 FORMAT)' PRECIPITATION' ,ISX,13F7.1) 0034 FAC=FLDCAP 0055 DO 190 J=1,3 0056 DO 190 I=1,12 0057 SUM=PRECIP)I) -TEMP (I) 0058 IF(SUM) 160,130,130 0059 130 SUR(I)=SUM 0060 DEF)I)=0. 0061 EVAP(I) =TEMP(I) 0862 DEPL(I) =0. 0063 TOT=SUM+FAC 0064 IF(TOT-FLDCAP) 150,150,140 065 140 TOT=FLDCAP 0066 150 WAT(I) =TOT 0067 RECHRG(I) =TOT-FAC 0868 RUN())=SUM-REC8RO)I) 0069 FAC=TOT 078 00 TO 190 0071 160 RUN(I)=0. 8072 SUR(I)=0. 128 Population and Energy APPENDIX B-Continued 0821 SOILDP=FLDCAP-WILTPT 0822 WRITE)6,25) FLDCAP,WILTPT,SOILDP 0823 25 FORMAT)T24, 'FIELD CAPACITY =',F6.1,' MM, 0024 $PERMANENT WILTING POINT ,' _' ,F6.1, 'MM, AVAIL $SOIL MOISTURE =',F6.1,'MM') 0025 WRITE (6,27) 0826 27 FORMAT)T33,JAN FEB MAR APR MAY 0027 $JUN JUL AUG SEP OCT NOV DEC $YEAR') 08 SUM=0. 0829 DO 300=1,12 0030 30 SUM=SUM+TEMP (I) 0031 SUM-SUM/12. 0832 WIJTE)6,40) TEMP,SUM 0033 40 FORMAT)' MEAN AIR TEMPERATURE' ,8X, 13F7.1) 0834 WRITE(6,50) TEMP,SUM 0033 50 FORMAT)' MEAN BIOTEMPERATURE' ,9X,13F7.1) 0836 SUM=O. 0037 TOT=O. 0038 00 60 1=1,12 0039 TEMP(I) =TEMP(I)*C(I) 0048 SUM=SUM+TEMP(I) 8041 60 TOT=TOT+PRECIP)I) 0042 WRITE)6,70) TEMPSUM 0043 70 FORMAT)' POTENTIAL EVAPOTRANSPIRATION',13F7.1) 0044 FAC=TOT/SUM 0043 IF(FAC-1.) 90,90,0 0046 80 FAC=1. 0847 90 DO 100 1=1,12 0048 100 TEMP(I)=TEMP()*PFAC 0049 SUM=SUM*FAC 0850 WRITE(6,1lO) TEMPSUM 0091 110 FORMAT)' POT. EVAP. ADJ. DRY CLIMATE ',I13F7.1) 0052 WRITE(6,120) PRECIPTOT 0033 120 FORMAT)' PRECIPITATION 15SX,13F 7.1) 0854 FAC=FLDCAP 0055 DO 190 3=1,3 0836 DO 190 I=1,12 0037 SUM=PRECIP)I) -TEMP(I) 0038 IF(SUM) 160,130,130 0059 130 SUR(I) =SUM 0060 DEF)I)=0. 0061 EVAP(I)=TEMP()1 0062 DEPL)I)=0. 0063 TOT=SUM+FAC 0864 IF(TOT-FLDCAP) 150,150,140 0863 140 TOT=FLDCAP 0066 150 WAT(I)=TOT 0062 RECH8RG(I) =TOT-FAC 0868 RUN(I)=SUM-REC4RO)I) 0869 FAC=TOT 0870 00 TO 190 0821 160 RUN(4))=0. 0872 SUR(I)=0. 128 Population and Energy APPENDIX B--Connued 0821 SOILDP=FLDCAP-WILTPT 0022 WRITE)6,25) FLDCAP,WILTPT,SOILDP 0823 25 FORMAT)T24, 'FIELD CAPACITY =',F6.1,' MM, 0024 $PERMANENT WILTING POINT ,' _' ,F6.1, 'MM, AVAIL $SOIL MOISTURE =',F6.1,'MM') 0023 WRITE (6,27) 0026 27 FORMAT)T33,JAN FEB MAR APR MAY 0027 $JUN JUL AUG SEP OCT NOV DEC $ YEAR') 0828 SUM=0. 0829 DO030I=1,12 0030 30 SUM=SUM+)TEMP (I) 0031 SUM=SUM/12. 0032 WRITE)6,40) TEMPSUM 0833 40 FORMAT)' MEAN AIR TEMPERATURE' ,8X,13F7.I) 0834 WRITE)6,50) TEMP,SUM 0033 50 FORMAT)' MEAN BIOTEMFERATURE' ,9X,13F7.1) 0036 SUM=0. 0037 TOT=O. 0038 DO 601I=1,12 0839 TEMP(I)=TEMP(I)rC1) 0040 SUM=SUM+TEMP(I) 0841 60 TOT=TOT+PRECIP)I) 0042 WRITE)6,70) TEMP,SUM 0043 70 FORMAT)' POTENTIAL EVAPOTRANSPIRATION'.13F7-1) 0044 FAC=TOT/SUM 8043 IF(FAC-1.) 90,90,80 0046 80 FAC=1. 0047 90 DO01001I=112 0048 100 TEMP(I)=TEMP(I)*FAC 0049 SUM=SUM*FAC 0830 WRITE)6,110) TEMP,SUM 0031 110 FORMAT)' POT. EVAP. ADJ. DRY CLIMATE ',13F7.1) 0032 WRITE)6,120) PRECIPTOT 0033 120 FORMAT)' PRECIPITATION' ,15X,13F7.1) 0034 FAC=FLDCAP 0033 00 190 1=1,3 0836 DO01901I=1,12 0037 SUM=PRECIP)I) -TEMP(I) 0858 IF(SUM) 163,130,130 0039 130 SUR(I)=SUM 0089 DEF(I)=0. 0061 EVAP(I)=TEMP(I) 0062 DEPL(I)=0. 0863 TOT=SUM+FAC 0864 IF(TOT-FLDCAP) 150,130,140 8063 140 TOT=FLDCAP 0066 130 WAT(I)=TOT 0062 RECHRG(I) =TOT-FAC 0868 RUN())=SUM-RECHRO)I) 0069 FAC=TOT 8679 00 TO 190 0871 160 RUN)I) =0. 0872 SUR(I)=O.  Appendix B 129 APPENDIX B-Coninued 0073 RECHRG(I)=0. 0074 DEF(I)=-SUM 0075 FAC=FAC-.5 0076 SUM=.SUM+FAC 0077 IPF(SUM) 170,170,10 0070 170 EVAP(I)=PRECIP(I)+FAC 0079 DEPL(I) =FAC 0080 G0 TO 185 0081 180 EVAP(I) =TEMOP(I) 0082 DEPL(I) =FAC-SUM 0083 FAC=SUM+FAC 0084 185 WAT(I) =FAC 0085 190 CONTINUE 0086 SUM=0. 0007 TOT=O. 0088 DO 999 =1,12 0089 TOT=TOT+EVAP(I) 0000 999 SUM=SUM+RUN(I) 0091 WRITE(6,998) EVAPTOT 0002 998 FORMAT(' ACTUAL EVAPOTRANSPIRATION ',13F7.1) 0093 WRITE(6,200) SUR 0094 200 FORMAT(' WATER SURPLUS' ,15X,12F7.1) 0095 WRITE(6,210) RECHRG 0096 210 FORMAT(' SOIL MOISTURE RECHARGE' ,6X,12F7.1) 0097 WITE(6,220) DEPL 0098 220 FORMAT(' SOIL MOISTURE DEPLETION' ,5X,12F7.1) 0099 WRITE(6,230) WAT 0100 230 FORMAT(' AVAILABLE SOIL MOISTURE EMO' ,IX,12F7.1) 0101 WRITE(6,240) RUNSUM 0102 240 FORMAT(' ALL RUNOFF' ,18X,13F7.1) 0103 DO 250 8=1,12 0100 DEPL(I) =FLDCAP-WAT(I) 0105 250 RUN(I)=DEPL(I)+DEF(I) 0106 WRITE(6,260) DEPL 0107 260 FORMAT(' SOIL MOISTURE DEFICIT' ,7X,12F7.1) 0108 WRITE(6,270) DEE 0109 270 FORMAT(' PRECIPITATION DEPICIr ,7X,12F7.1) 0110 WRITE(6,280) RUN 0111 280 FORMAT(' TOTAL MOISTURE DEFICIT' ,6X,12F7.1////) 0112 GO TO 5 0113 END Appendix B 129 APPENDIX B,-Cntnu~ed 0073 RECHORG(I)=0. 0074 DEF(I)=-SUM 0075 FAC=FAC-.5 0076 SUM=SUM+FAC 0077 IF(SUM) 170,170,180 0078 170 EVAP(I)=PRECIP(I)+F-AC 0079 DEPL(I)=FAC 0080 00 TO 183 0081 180 EVAP(I) =TEMP(I) 0082 DEPL(I)=FAC-SUM 0083 FAC=SUM+FAC 0084 185 WAT(I)=FAC 0083 190 CONTINUE 0086 SUM=O. 0087 TOT'=O. 0088 00999 =1,12 0089 TOT=TOT+EVAP(I) 0090 999 SUM=SUM+RUN(I) 0091 WRITE(6,998) EVAPTOT 0002 998 FORMAT(' ACTUAL EVAPOTRANSPIRATION ',13F7.1) 0093 WRITE(6,200) OUR 0094 200 FORMAT(' WATER SURPLUS' ,15X, 12F7.1) 0093 WRITE(6,210) RECHRG 0000 210 FORMAT(' SOIL MOISTURE RECHARGE' ,6X,12F7.1) 0097 WRITE(6,220) DEPL 0098 220 FORMAT(' SOIL MOISTURE DEPLETION' ,SX,12F7.1) 0099 WRITE(6,230) WAT 0100 230 FORMAT(' AVAILABLE SOIL MOISTURE EMO' ,1X,12P7.1) 0101 WRITE(6,240) RUNSUM 0102 240 FORMAT(' ALL RUNOFF' ,18X,13F7.1) 0103 DO 250 I=1,12 0100 DEPL(I)=FLDCAP-WAT)I) 0103 250 RUN(I)=DEPL(I)+DEF(I) 0106 WRITE(6,260) DEPL 0107 260 FORMAT)' SOIL MOISTURE DEFICIT' ,7X,12P7.1) 0108 WRITE(6,270) DEE 0109 270 FORMAT(' PRECIPITATION DEFICIT' ,7X,12F7.1) 0110 WITE(6,280) RUN 0111 280 FORMAT)' TOTAL MOISTURE DEFICIT' ,6X,12F7.1////) 0112 GO TO 5 0113 END Appendix B 129 APPENDIX B-Cninued 0073 0075 0076 0077 0078 0079 0080 0081 0082 0083 0084 0085 0086 0007 0088 0089 0090 0091 0092 0093 0094 0095 0096 0097 0098 0100 0102 0104 0105 0106 0108 0109 0110 0111 0112 170 180 185 190 999 200 210 226 240 250 270 280 RECIORO(I) =0. DEF(I) = -SUM FAC=FACO.5 SUM =SUM +FAC IF(SUM) 170,170,180 EVAP(I) =PRECIP)I) +FAC DEPL(I) =FAC 00 TO 185 EVAP(I) =TEMP(I) DEPL(I) =FAC-SUM FAC=SUM+FAC WAT(I) =FAC CONTINUE SUM= 0. TOT=O. 00 999 =1,12 TOT=TOT+EVAP(I) SUM=SUM+RUN(I) WRITE(6,998) EVAPTOT FORMAT(' ACTUAL EVAPOTRANSPIRATION4 ',13F7.1) WRITE(6,200) SUR FORMAT(' WATER SURPLUS' ,15X,12F7.1) WRITE(6,210) RECHORG FORMAT(' SOIL MOISTURE RECIOAROS' ,6X,12F7.1) WRITE(6,220) DEPL FORMAT)' SOIL MOISTURE DEPLETION' ,5X,12F7.1) WRITE(6,230) WAT FORMAT(' AVAILABLE SOIL MOISTURE EMO' ,IX,12F7.1) WRITE(6,240) RUNSUM FORMAT)' ALL RUNOFF' ,I8X,13F7.1) DO 250 8=1,12 DEPL(I) =FLDCAP- WAT(I) RUN(I) =DEPL(I) +DEF)I) WRITE(6,260) DEPL FORMAT)' SOIL MOISTURE DEFICIT' ,7X,12F7.1) WRITE(6,270) DEF FORMAT(' PRECIPITATION DEFICIT' ,7X,12F7.1) WRITE(6,280) RUN FORMAT(' TOTAL MOISTURE DEFICIT' ,6X,12F7.1////) 00 TO 5 END  WATER BALANCE DATA Guanajuma Station: 19' 16'30" N., 70°44' 40" W.; 560 m elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 19.5 19.5 20.5 22.0 23.0 23.5 23.5 24.0 24.0 23.0 21.5 20.0 22.0 Mean biotemperature 19.5 19.5 20.5 22.0 23.0 23.5 23.5 24.0 24.0 23.0 21.5 20.0 22.0 Potential evapotranspiration 97.5 88.9 102,5 106.5 115.0 113.7 117.5 120.0 116.2 115.0 104.1 100.0 1,296.9 Pot, evap. adj, dry climate 95.2 86.8 100.1 103.9 112.3 111.0 114.7 117.1 113.4 112.3 101.6 97.6 1,266.0 Precipitation 80.0 99.0 64.0 128.0 178.0 124.0 79.0 56.0 54.0 86.0 124.0 194.0 1,266.0 Actual evapotranspiration 95.2 86.8 100.1 103.9 112.3 111.0 114.7 111.6 81.8 99.9 101.6 97.6 1,216.5 Water surplus 0.0 12.2 0.0 24.1 65.7 13.0 0.0 0.0 0.0 0.0 22.4 96.4 Soil moisture recharge 0.0 12.2 0.0 24.1 29.2 0.0 0.0 0.0 0.0 0.0 22.4 96.4 Soil moisture depletion 15.2 0.0 36.1 0.0 0.0 0.0 35.7 55.6 27.8 139 0.0 0.0 Available soil moisture emoa 117.5 129.7 93.6 117.7 146.9 146.9 111.2 55.6 27.8 13.9 36.3 132.7 All runoff 0.0 0.0 0.0 0.0 36.6 13.0 0.0 0.0 0.0 0.0 0.0 0.0 49.5 Soil moisture deficit 29.4 17.2 53.2 29.2 0.0 0.0 35.7 91.3 119.1 133.0 110.6 14.2 Precipitation deficit 15.2 0.0 36.1 0.0 0.0 0.0 35.7 61.1 59.4 26.3 0.0 0.0 Total moisture deficit 44.5 17.2 89.3 29.2 0.0 0.0 71.4 152.4 178.5 159.2 110.6 14.2 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g"cm-a; per cent field capacity = 0.36; per cent permanent willing point = 0.17; field capacity = 97.9 mm; permanent witting point = 46.2 mm; available soil moisture = 51.7 one. Jan. Feb. Mar. At,.. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 19.5 19.5 20.5 22.0 23.0 23.5 23.5 24.0 24.0 23.0 21.5 20.0 22.11 Mean biotemperature 19.5 19.5 20.5 22.0 23.0 23.5 23.5 24.0 24.0 23.0 21.5 20.0 22.0 PDtential evapotranspiration 97.5 88.9 102.5 106,5 115.0 113.7 117.5 12f1.0 116.2 115.0 104.1 100.0 1,296.9 Pot. evap, adj, dry climate 95.2 R6.8 100.1 103.9 112.3 111.0 114.7 117.1 113.4 112.3 101.6 97.6 1,266.0 Precipitation 80.0 99.0 64,0 128.0 178.0 124.0 79.11 56.0 54.0 86.0 124.0 194.0 1,266.0 Actual evapotranspiration 95.2 86.8 100.1 103.9 112.3 111.0 114.7 87.1 69.6 93.8 101.6 97.6 1,173.6 Water surplus 0.0 112 0.0 24.1 65.7 13.0 0.0 0 .0 00 0.0 22.4 96.4 WATER BALANCE nATA Guanajuma Station: 19° 16' 30" N, 70° 44' 40" W.; 560 in elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-a; per cent field capacity - 0.36; per cent permanent wilting point = 0.17; field capacity = 146.9 man; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 19.5 19.5 20.5 22.0 23.0 23.5 23.5 24.0 24.0 23.0 21.5 20.0 22.0 Mean biotemperature 19.5 19.5 20.5 22.0 23.0 23.5 23.5 24.0 24.0 23.0 21.5 20.0 22.0 Potential evapotranspiration 97.5 88.9 102.5 106.5 115.0 113.7 117.5 120.0 116.2 115.0 104.1 100.0 1,296.9 Pot. evap. adj. dry climate 95.2 86.8 100.1 103.9 112.3 111.0 114.7 117.1 113.4 112.3 101.6 97.6 1,266.0 Precipitation 80.0 99.0 64.0 128.0 178.0 124.0 79.0 56.0 54.0 86.0 124.0 194.0 1,266.0 Actual evapotranspiration 95.2 86.8 100.1 103.9 112.3 111.0 114.7 111.6 81.8 99.9 101.6 97.6 1,216.5 Water surplus 0.0 12.2 0.0 24.1 65.7 13.0 0.0 0.0 0.0 0.0 22.4 96.4 Soil moisture recharge 0.0 12.2 0.0 24.1 29.2 0.0 0.0 0.0 0.0 0.0 22.4 96.4 Soil moisture depletion 15.2 0.0 36.1 0.0 0.0 0.0 35.7 55.6 27.8 13.9 0.0 0.0 Available soil moisture emoa 117.5 129.7 93.6 117.7 146.9 146.9 111.2 55.6 27.8 13.9 36.3 132.7 All runoff 0.0 0.0 0.0 0.0 36.6 13.0 0.0 0.0 0.0 0.0 0.0 0.0 49.5 Soil moisture deficit 29.4 17.2 53.2 29.2 0.0 0.0 35.7 91.3 119.1 133.0 110.6 142 Precipitation deficit 15.2 0.0 36.1 0.0 0.0 OA 35.7 61.1 59.4 26.3 0.0 0.0 Total moisture deficit 44.5 17.2 89.3 29.2 0.0 0.0 71.4 152.4 178.5 159.2 110.6 14.2 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g"cm-g; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 97.9 min; permanent wilting paint = 46.2 mm; available soil moisture = 51.7 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 19.5 9.5 20.5 22.0 23.0 23.5 23.5 14.il 24.0 23.0 21.5 20.0 22.0 Mean biotemperm a 19.5 1 19.5 20.5 22.0 23.0 23.5 23..5 24.0 24.0 23.0 21.5 20.0 22.0 Potential evapotranspiration 97.5 88.9 102.5 106.5 115.0 113.7 117.5 120.0 116.2 11.5.0 104.1 100.0 1,296.9 Pot. evap, adl. dry climate 95.2 86.8 100.1 103.9 112.3 111.0 1147 117.1 113.4 112.3 101.6 97.6 1,266.0 Precipitation 80.11 99.0 64.0 128.0 178.0 124.0 79.0 56.0 54.0 86.0 124.0 194.0 1,266.0 Actual evapotranspiration 95.2 86.8 100.1 103.9 112.3 111.0 114.7 87,1 69b 93.8 101.6 97.6 1,173.6 Water surplus 0.0 12.2 0.0 24.1 65.7 13.0 0.0 0,0 0.0 0.0 22.4 96.4 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity _ 0.36; 1 capacity = 97.9 men; permanent witting point = 46.2 mm; available soil moisture = 51.7 mm. Jan. Feb. Mar. Apr. May June July Aug. Mean air temperature 19.5 19.5 2t1.5 22.0 23.0 2},5 23.5 24.0 Mean biotemperature 19.5 19.5 20.5 22.0 21.0 23.5 23.5 24.0 Potential evapotranspiration 97.5 88.9 102.5 106.5 115.0 113.1 117.5 120.0 Pol. evap. adj. dry climalc 95.2 86.8 100.1 103.9 112.3 I I I.U I t4.7 117.1 Precipitation 80.0 99.0 64.0 12R.0 ]78.0 124.0 79.0 56.0 Actual evalwfrunspiration 9.5 .2 86.8 lOO.l 103.9 112.3 111.0 114.7 87.1 Water surplus 0.0 12.2 0.0 24.1 65.7 13A 0.11 0.0  Soil moisture recharge 010 122 0.0 24.1 15.0 0.0 0.0 0.0 010 0.0 22.4 6T7 Soil moisture recharge 0.0 12.2 0.0 24.1 15.0 0.0 0.0 0.0 0.0 0.0 22.4 67.7 Soil moisture recharge 0.0 12.2 0.0 24.1 15.0 0.0 0.0 0.0 0.0 0.0 22.4 Soil moisture depletion 15.2 0.0 36.1 0.0 0.0 0.0 35.7 31.1 15.6 7.8 0.0 0.0 Soil moisture depletion 15.2 0.0 36.1 0.0 0.0 0.0 35.7 31.1 15.6 7.8 0.0 0.0 Soil moisture depletion 152 0.0 36.1 0.0 0.0 0.0 35.7 31.1 15.6 7.8 0.0 Available soil moisture emo 82.7 94.9 58.9 82.9 97.9 97.9 622 31.1 15.6 7.8 30.2 97.9 Available soil moisture emo 82.7 94.9 589 829 97.9 979 62.2 31.1 15.6 7.8 30.2 97.9 Available soil moisture emo 82.7 94.9 58.9 82.9 97.9 97.9 62.2 31.1 15.6 7.8 302 All runoff 0.0 0.0 0.0 0.0 50.7 13.0 0.0 0.0 0.0 0.0 0.0 28.7 92.4 All runofl 0.0 0.0 0.0 0.0 50.7 13.0 0.0 0.0 0.0 0.0 0.0 28.7 92.4 All runoff 0.0 0.0 0.0 0.0 50.7 13.0 0.0 0.0 0.0 0.0 0.0 Soil moisture deficit 15.2 3.0 39.0 15.0 0.0 0.0 35.7 66.8 82.4 90.1 67.7 0.0 Soil moisture deficit 15.2 3.0 39.0 15.0 0.0 0.0 353 66.8 82.4 90.1 67.7 0.0 Soil moisture deficit 152 3.0 39.0 15.0 0.0 0.0 35.7 66.8 82.4 90.1 67.7 Precipitation deficit 15.2 0.0 361 0.0 0.0 0.0 35.7 61.1 59.4 26.3 0.0 0.0 Precipitation deficit 15.2 0.0 36.1 0.0 0.0 0.0 35.7 61.1 59.4 26.3 0.0 0.0 Precipitation deficit 15.2 0.0 36.1 0.0 0.0 0.0 35.7 61.1 59.4 26.3 0.0 Total moisture deficit 30.4 3.0 75.1 15.0 0.0 0.0 71.4 128.0 141.8 116.4 67.7 0.0 Total moisture deficit 30.4 3.0 75.1 15.0 0.0 0.0 71.4 128.0 141.8 116.4 67.7 0.0 Total moisture deficit 30.4 3.0 75.1 15.0 0.0 0.0 71.4 128.0 141.8 116.4 67.7 Soil parameters: soil depth = 100.0 mm; bulk density = 1.36 g-cm-3; per cent field capacity capacity = 49.0 mm; permanent wilting point = 23.1 mm; available soil moisture = 25.8 mm. Jan. Feb. Mar. Apr. May June July Mean air temperature 19.5 19.5 20.5 22.0 23.0 23.5 23.5 Mean biotemperature 19.5 19.5 20.5 22.0 23.0 23.5 23.5 Potential evapotranspiration 97.5 88.9 102.5 106.5 115.0 113.7 117.5 Pot. evap. adj. dry climate 95.2 86.8 100.1 103.9 112.3 111.0 114.7 Precipitation 80.0 99.0 64.0 128.0 178.0 124.0 79.0 Actual evapotranspiration 95.2 86.8 87.0 103.9 112.3 111.0 103.5 Water surplus 0.0 12.2 0.0 24.1 65.7 13.0 0.0 Soil moisture recharge 0.0 12.2 0.0 24.1 1.9 0.0 0.0 Soil moisture depletion 15.2 0.0 23.0 0.0 0.0 0.0 24.5 Available soil moisture earn 33.8 46.0 23.0 47.0 49.0 49.0 24.5 All runoff 0.0 0.0 0.0 0.0 63.8 13.0 0.0 Soil moisture deficit 15.2 3.0 26.0 1.9 0.0 0.0 24.5 Precipitation deficit 15.2 0.0 36.1 0.0 0.0 0.0 35.7 Total moisture deficit 30.4 3.0 62.0 1.9 0.0 0.0 60.2 a. Earn = end of month. Soil parameters: soil depth - 100.0 mm; In capacity - 49.0 mm; permanent wilting point Jan. Feb. Mean air temperature 19.5 19.5 Mean biotemperature 19.5 19.5 Potential evapotranspiration 97.5 88.9 Pot. evap. adj. dry climate 95.2 86.8 Precipitation 80.0 99.0 Actual evapotranspiration 95.2 86.8 Water surplus 0.0 12.2 Soil moisture recharge 0.0 12.2 Soil moisture depletion 15.2 0.0 Available soil moisture emo 33.8 46.0 All runoff 0.0 0.0 Soil moisture deficit 15.2 3.0 Precipitation deficit 15.2 0.0 Total moisture deficit 30.4 3.0 a. Emo - end of month. ilk density = 1.36 g.cm-3; per cent field capacity = 23.1 mm; available soil moisture = 25.8 mm. Mar. Apr. May June July 20.5 22.0 23.0 23.5 23.5 20.5 22.0 23.0 23.5 23.5 102.5 106.5 115.0 113.7 117.5 100.1 103.9 112.3 111.0 114.7 64.0 128.0 178.0 124.0 79.0 87.0 103.9 112.3 111.0 103.5 0.0 24.1 65.7 13.0 0.0 0.0 24.1 1.9 0.0 0.0 23.0 0.0 0.0 0.0 24.5 23.0 47.0 49.0 49.0 24.5 0.0 0.0 63.8 13.0 0.0 26.0 1.9 0.0 0.0 24.5 36.1 0.0 0.0 0.0 35.7 62.0 1.9 0.0 0.0 60.2 Soil parameters: soil depth - 100.0 mm; bulk density capacity = 49.0 mm; permanent wilting point = 23.1 m Jan. Feb. Mar. Mean air temperature 19.5 19.5 20.5 Mean biotemperature 19.5 19.5 20.5 Potential evapotranspiration 97.5 88.9 1025 Pot. evap, adj. dry climate 95.2 86.8 100.1 Precipitation 80.0 99.0 64.0 Actual evapotranspiration 95.2 86.8 87.0 Water surplus 0.0 12.2 0.0 Soil moisture recharge 0.0 12.2 0.0 Soil moisture depletion 15.2 0.0 23.0 Available soil moisture emo 33.8 46.0 23.0 All runoff 0.0 0.0 0.0 Soil moisture deficit 15.2 3.0 26.0 Precipitation deficit 15.2 0.0 36.1 Total moisture deficit 30.4 3.0 62.0 a. Emo - end of month. = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field m; available soil moisture = 25.8 mm. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year 22.0 21 21 23.5 24.0 24.0 23.0 21.5 20.0 22.0 22.0 23.0 23.5 23.5 24.0 24.0 23.0 21.5 20.0 22.0 106.5 115.0 113.7 117.5 120.0 116.2 115.0 104.1 100.0 1,296.9 103.9 112.3 111.0 114.7 117.1 113.4 112.3 101.6 97.6 1,266.0 128.0 178.0 124.0 79.0 56.0 54.0 86.0 124.0 194.0 1,266.0 103.9 112.3 111.0 103.5 68.2 60.1 89.1 101.6 97.6 1,116.3 24.1 65.7 13.0 0.0 0.0 0.0 0.0 22.4 96.4 24.1 1.9 0.0 0.0 0.0 0.0 0.0 22.4 23.5 0.0 0.0 0.0 24.5 12.2 6.1 3.1 0.0 0.0 47.0 49.0 49.0 24.5 12.2 6.1 3.1 25.5 49.0 0.0 63.8 13.0 0.0 0.0 0.0 0.0 0.0 72.9 149.7 1.9 0.0 0.0 24.5 36.7 42.8 45.9 23.5 0.0 0.0 0.0 0.0 35.7 61.1 59.4 26.3 0.0 0.0 1.9 0.0 0.0 60.2 97.9 102.2 72.2 23.5 0.0  P6ralito Station; 190 17'50' N., 70' 48120" W.; 480 in elevation Pinalito Station: 1717' 50" N., 70'48' 10" W.; 480 in elevation Prnalito Station: 1717' 50" N, 70'48'20" W.; 480 m elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field Soil parameters: soil depth = 300.0 mm; bulk density = 136 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting. capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. capacity = 146.9 mm; permanent wilting point = 69,4 mm; available soil moisture = 77.5 mm. Jan, Feb. Mar. Apr, May June July Aug Sept. Oct. Nov. Dec. Year Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Mean air temperature 19.3 19.8 20.6 22,0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean air temperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean air temperature 19.3 19.8 20.6 22.0 22,6 23.6 23.6 24.4 23.8 23.4 21.9 Mean biotemperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean biotemperature 19.3 19,8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean biotemperature 19.3 19.8 20.6 22,0 22,6 23.6 23.6 24.4 23.8 23.4 21.9 Potential evapotranspiration 96.5 90.3 103.0 106,5 113.0 114,2 118.0 1220 115.2 117.0 106.0 100.5 1,302.2 Potential evapotranspiration 96.5 90.3 103.0 106.5 113.0 1142 118.0 122.0 115.2 117.0 106.0 100.5 1,302.2 Potential evapotranspiration 96.5 90.3 103.0 106.5 113.0 114.2 118.0 122.0 115.2 117.0 106.0 Pot. evap. adj. dry climate 84.0 78.6 89.6 92.6 98.3 99.4 102.7 106.1 1002 101.8 92.2 87.4 1,133.0 Pot. evap. adj. dry climate 84.0 78.6 89.6 92.6 98.3 99.4 102.7 106.1 100.2 101.8 92.2 87.4 1,133.0 Pot, evap. adj. dry climate 84.0 78.6 89.6 92.6 98.3 99.4 102.7 106.1 100.2 101.8 92.2 Precipitation 55.0 46.0 36.0 114,0 288.0 116.0 49.0 48.0 40.0 60,0 125.0 156.0 1,133.0 Precipitation 55.0 46.0 36.0 114.0 288.0 116.0 49.0 48.0 40.0 60.0 125.0 156.0 1,133.0 Precipitation 55.0 46.0 36.0 114.0 288.0 116.0 49.0 48,0 40.0 60.0 125.0 Actual evapotranspiration 84.0 78.6 61.7 92.6 983 99.4 102.7 94.6 63.3 71.7 92.2 87,4 1,026.5 Actual evapotranspiration 84.0 78.6 61.7 92.6 98.3 99.4 1027 94.6 63.3 71.7 92.2 87.4 1,026.5 Actual evapotranspiration 84.0 78.6 61,1 92.6 98.3 99.4 102,7 94.6 63.3 71.7 92.2 Water surplus 0.0 0.0 0.0 21.4 189.7 16.6 0.0 0.0 0.0 0.0 32.8 68.6 Water surplus 0.0 0.0 0.0 21.4 189.7 16.6 0.0 0.0 0.0 0.0 328 68.6 Water surplus 0.0 0.0 0.0 21,4 189.7 16.6 0.0 0.0 0.0 0.0 32.8 Soil moisture recharge 0.0 0.0 0.0 21.4 99.8 0.0 0.0 0.0 0.0 0.0 32.8 68.6 Sal moisture recharge 0.0 0.0 OA 21.4 99.8 0.0 0.0 0,0 0.0 0.0 32.8 68.6 Sal moisture recharge 0.0 0.0 0.0 21.4 99.8 0.0 0.0 0,0 0.0 0.0 328 Soil moisture depletion 29.0 326 25.7 0.0 0.0 0.0 53.7 46.6 23.3 11.7 0.0 0.0 Soil moisture depletion 29.0 32.6 25.7 QO 0.0 0.0 53.7 46.6 233 11.7 0.0 0.0 Soil moisture depletion 29.0 32.6 25.7 0.0 0.0 0.0 53.7 46.6 23.3 11.7 0.0 Available soil moisture emo 84.0 51.5 25.7 47.1 146.9 146.9 932 46.6 23.3 11.7 "A 113.0 Available soil moisture emo 84.0 51.5 25.7 47.1 146.9 1469 93.2 46.6 23.3 11.7 44.4 113.0 Available soil moisture emo 84.0 51.5 25.7 47.1 146.9 146.9 912 46,6 23.3 11.7 44.4 All runoff 0.0 0.0 0.0 0,0 89.9 16.6 0.0 0.0 0.0 0.0 0.0 0.0 106.5 All runoff 0.0 0.0 0.0 0.0 89,9 16.6 0,0 0.0 0.0 0.0 0.0 0,0 106.5 All runoff 0.0 0.0 0.0 0.0 89.9 16.6 0.0 0.0 0.0 0.0 0.0 Sod moisture deficit 62.9 95.4 121.1 99.8 0.0 0.0 53.7 100.3 123,6 135.2 1025 33.9 Soil moisture deficit 62.9 95.4 121.1 99.8 0.0 0.0 53.7 100.3 123.6 1352 102,5 33.9 Soil moisture deficit 629 95.4 121.1 99.8 0.0 0.0 53.7 100.3 123.6 135.2 102.5 Precipitation deficit 29.0 32.6 53.6 0.0 0.0 0,0 53.7 58.1 60.2 41.8 0.0 0.0 Precipitation deficit 29.0 32.6 53.6 0.0 0.0 0.0 53.7 58.1 60.2 41.8 0.0 0,0 Precipitation deficit 29.0 316 53.6 0.0 0.0 0.0 53.7 58.1 60.2 41.8 0.0 Total moisture deficit 91.8 128.0 174.8 99.8 0.0 0.0 107.3 158.4 183.8 117.0 102.5 33.9 Total moisture deficit 91.8 128.0 174,8 99.8 0.0 0.0 107.3 158.4 183.8 177.0 102.5 33.9 Total moisture deficit 91.8 128,0 174.8 99.8 0.0 0.0 107.3 158.4 183.8 177.0 102.5 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g"cm-a; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 97.9 mm; permanent wilting point = 46.2 mm; available soil moisture = 51.7 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean biotemperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Potential evapotranspiration 96.5 90.3 103.0 106.5 113,0 114.2 118.0 122.0 115.2 117.0 106.0 100.5 1,302.2 Pot. cvap. adj. dry climate 84.0 78,6 89.6 92.6 98.3 99.4 102.7 106.1 100.2 101.8 92.2 87.4 1,133.0 Precipitation 55.0 46.0 36.0 114.0 288.0 116.0 49.0 41.0 40.0 60.0 125.0 156.0 1,133.0 Actual evapotranspiration 84.0 78.6 54.2 92.6 98.3 99.4 98.0 72.5 52.2 66.1 92,2 87.4 975.5 Water surplus 0.0 0 .0 0.0 21.4 189.7 16.6 0.0 0.0 0.0 0.0 32.8 68.6 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g"cm-a; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 97.9 mm; permanent wilting point = 46.2 mm; available soil moisture = 51.7 mm. Jan. Fab. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean biotemperature 193 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Potential evapotranspiration 96.5 90.3 103.0 106.5 113.0 114.2 118.0 122.0 115.2 117.0 106.0 100.5 1,302.2 Pot. evap, adj. dry climate 84.0 78.6 89.6 92.6 98.3 99.4 102.7 106.1 100.2 101.8 92.2 87.4 1,133.0 Precipitation 55.0 46.0 36.0 114.0 288.0 116.0 49.0 48,0 40.0 60.0 125.0 156.0 1,133.0 Actual evapotranspiration 84.0 78.6 541 92.6 98.3 99.4 98.0 72.5 52.2 66.1 92.2 87.4 975.5 Water surplus 0.0 0.0 0.0 21A 189.7 16.6 0.0 0.0 0.0 0.0 32.8 68.6 Soil parameters: soil depth = 200,0 mm; bulk density = 1.36 g"cm-a; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 97.9 mm; permanent wilting point = 46.2 mm; available soil moisture = 51.7 mm. Jan. Feb. Mar, Apr, May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20,1 22.1 Mean bimemperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24,4 23,8 23.4 21.9 201 22.1 Potential evapotranspiration 96.5 903 103.0 106.5 113.0 114.2 118.0 122.0 115.2 117.0 106.0 100.5 1,302.2 Pot. evap. adj. dry climate 84.0 78.6 89.6 92.6 98.3 99.4 102.7 106.1 100.2 101.8 92.2 87.4 1,133.0 Precipitation 55.0 46,0 36,0 114,0 288.0 116.0 49,0 48.0 40.0 60.0 125.0 156.0 1,133.0 Actual evapotranspiration 84.0 78.6 54.2 92.6 983 99.4 98.0 72,5 52.2 66.1 92.2 87.4 975.5 Water surplus 0.0 0.0 0.0 21A 189.7 16.6 OA 0.0 0.0 0,0 32.8 68.6  Soil moisture recharge 0.0 0.0 0.0 21.4 58.4 0.0 0.0 0.0 0.0 0.0 32.8 59.0 Soil moisture recharge 0.0 0.0 0.0 21.4 58.4 0.0 0.0 0.0 0.0 0.0 32.8 59.0 Soil moisture recharge 0.0 0.0 0.0 21.4 58.4 0.0 0.0 0.0 0.0 0.0 32.8 Soil moisture depletion 29.0 32.6 18.2 0.0 0.0 0.0 49.0 24.5 12.2 6.1 U 0.0 Sod moisture depletion 29.0 326 181 0.0 0.0 0,0 49.0 24.5 12.2 6.1 0.0 0.0 Soil moisture depletion 29.0 32.6 18.2 0.0 0.0 0.0 49.0 24.5 12.2 6.1 0.0 Available soil moisture emo 69.0 36.4 18.2 39.6 97.9 979 49.0 24,5 122 61 389 97.9 Available soil moisture emo 69.0 36.4 181 39.6 97.9 97.9 49.0 245 12.2 6.1 38.9 97.9 Available soil moisture emo 69.0 36.4 18.2 39.6 97.9 97.9 49.0 24.5 122 6.1 389 All runoff 0.0 0.0 0.0 0.0 131.3 16.6 0.0 0.0 0.0 0.0 0.0 9.5 157.5 All runoff 0.0 0,0 0.0 0.0 131.3 16.6 0.0 0.0 0.0 0.0 0.0 9.5 157.5 All runoff 0.0 0.0 0.0 0.0 131.3 16.6 0.0 0.0 0.0 0.0 0.0 Sod moisture deficit 29.0 61.5 79.7 58,4 0.0 0.0 49.0 73.4 85.7 91.8 59.0 0.0 Soil moisture deficit 29.0 61.5 79.7 58.4 0.0 0.0 49.0 73.4 85.7 91.8 59.0 0.0 Soil moisture deficit 29.0 61.5 79.7 58.4 010 0.0 49.0 73.4 85.7 91.8 59.0 Precipitation deficit 29.0 32.6 53.6 0.0 0.0 0.0 53.7 58.1 601 41,8 0.0 0.0 Precipitation deficit 29.0 32.6 53.6 0.0 0.0 0.0 53.7 58.1 60.2 41.8 0.0 0.0 Precipitation deficit 29.0 32.6 53.6 0.0 0.0 0.0 53.7 58.1 60.2 41.8 0.0 Total moisture deficit 57.9 94,1 133.3 58.4 0.0 0.0 102.6 131.6 145.9 133.6 59.0 0.0 Total moisture deficit 57.9 94.1 133.3 58.4 0.0 0.0 102.6 131.6 145.9 133.6 59.0 0.0 Total moisture deficit 57.9 94.1 133.3 58.4 0.0 0.0 502.6 131.6 145.9 133.6 59.0 Soil parameters: soil depth = 100.0 mm; bulk density = 1.36 g-cm-3; per cent field capacity = 0.36; per cent permanentwilting point = 0.17; field Soil parameters: sod depth = 100.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field Soil parameters; soil depth = 100.0 mm; bulk density = 176 g"rvm3; per cent field capacity = 0.36; per cent permanent viltig capacity = 49.0 mm; permanent wilting point = 23.1 mm; available soil moisture = 25.8 nom. capacity = 49,0 mm; permanent wilting point = 23.1 rim; available sod moisture = 25.8 mm. capacity = 49.0 mm; permanent wdting point = 23.1 mm; available soil moisture = 25.8 mm. Jan. Feb. Met. Apr. May June July Aug. Sept. Oct. Nov. Dec. Yea Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Mean air temperature 19.3 19.8 20.6 22.0 22,6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean air temperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 219 20.1 22.1 Mean air temperature 19.3 19.8 20.6 22.0 226 23.6 23.6 24,4 23.8 23.4 21.9 Mean biotemperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24,4 23.8 23.4 21.9 20.1 22.1 Mean biotemperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24,4 23.8 23.4 21.9 20,1 22.1 Mean biotemperature 19.3 19.8 20.6 22.0 226 23.6 23.6 24.4 23.8 23.4 21,9 Potential evapotranspiration 96.5 90.3 103.0 1065 113.0 114.2 118.0 122.0 1152 117.0 106.0 1005 1,702.2 Potential evapotranspiration 965 90.3 1010 106.5 113.0 114.2 118.0 122.0 115.2 117.0 106.0 100.5 1,302.2 Potential evapotranspiration 96.5 90.3 103.0 106.5 113.0 114.2 118.0 1220 115.2 117.0 106.0 Pot. evap. adj. dry climate 84.0 78.6 89.6 92.6 98.3 99.4 102.7 106.1 1002 101.8 92.2 87.4 1,133.0 Pot. evap. adj. dry climate 84.0 78.6 89.6 92.6 98.3 99.4 102.7 106.1 100.2 101.8 92.2 87.4 1,133.0 Pot. evap. adj. dry climate 84.0 78.6 89.6 92.6 98.3 99.4 102.7 1061 100.2 101.8 92.2 Precipitation 55.0 46.0 36.0 114.0 288.0 116.0 49.0 480 40.0 60.0 125.0 156.0 1,133.0 Precipitation 55.0 46.0 36.0 114.0 288.0 116.0 49.0 48.0 40.0 60.0 125.0 1560 1,133.0 Precipitation 55.0 46.0 36.0 114.0 288.0 116.0 49.0 48.0 40.0 60.0 125.0 Actual evapotranspiration 79.5 582 42.1 92.6 98.3 99.4 73.5 60.2 46.1 63.1 92.2 87.4 892.9 Actual evapotranspiration 79.5 58.2 42.1 92.6 983 99.4 735 601 46.1 63.1 922 87.4 892.8 Actual evapotranspiration 79.5 58.2 42.1 92.6 98.3 99.4 73.5 60.2 46.1 63.1 92.2 Water surplus 0.0 0.0 0.0 21.4 189.7 16.6 0.0 0.0 0.0 0.0 32,8 68.6 Water surplus 0.0 0.0 0.0 21.4 189.7 16.6 0.0 0.0 0.0 0.0 32.8 68.6 Water surplus 0.0 0.0 0.0 21.4 189.7 16.6 0.0 0.0 0.0 0.0 32.8 Sail moisture recharge 0.0 0.0 0.0 21.4 21.5 0.0 0.0 0.0 0.0 0.0 32.8 13.1 Sod moisture recharge 0.0 0.0 0.0 21.4 215 0.0 0.0 0.0 0.0 0.0 32,8 13.1 Soil moisture recharge 0.0 0,0 0.0 21.4 21.5 0.0 0.0 0.0 0.0 0.0 32.8 Soil moisture depletion 24.5 122 6.1 0.0 0.0 0.0 24,5 12.2 6.1 3.1 0.0 0.0 Sod moisture depletion 24.5 122 6.1 0.0 0.0 0.0 21.5 12.2 6.1 3.1 0.0 0.0 Soil moisture depletion 24.5 12.2 6.1 0.0 0.0 0.0 24.5 12,2 6.1 3.1 0.0 Available soil moisture emo 24.5 122 6.1 27.5 49.0 49,0 24.5 122 6.1 3.1 35.8 49.0 Available soil moisture emo 24.5 12,2 6.1 27.5 49.0 49.0 24.5 12.2 6.1 3.1 35.8 49.0 Available soil moisture emo 24.5 12.2 6.1 27.5 49.0 49.0 24.5 12.2 6.1 3.1 35.8 All runoff 0.0 0.0 0.0 0.0 168.2 166 0.0 0.0 0.0 0.0 0.0 55.4 240.2 All runoff 0,0 0.0 0.0 0.0 1682 16.6 0.0 0.0 0.0 0.0 0.0 55.4 240.2 All runoff 0.0 0.0 0.0 0.0 168.2 16.6 0.0 0.0 0.0 0.0 0.0 Soil moisture deficit 24.5 36.7 42.8 21.5 010 0.0 24,5 36.7 42.8 45.9 13.1 0.0 Sod moisture deficit 24.5 36.7 42.8 21.5 0.0 0.0 24.5 36.7 42,8 45.9 13.1 010 Soil moisture deficit 24.5 36.7 42.8 21.5 0.0 0.0 24.5 36.7 42.8 45.9 13.1 Precipitation deficit 29.0 32.6 53,6 0.0 0.0 0.0 53.7 58.1 60.2 41.8 0.0 0.0 Precipitation deficit 29.0 32.6 53.6 0.0 0.0 0.0 53.7 58.1 60.2 41.8 0.0 0.0 Precipitation deficit 29.0 32.6 53.6 0.0 0.0 01) 53.7 58.1 602 41.8 0.0 Total moisture deficit 53.4 69.3 96.5 21.5 0.0 0.0 78.1 94.9 103.1 87,7 13.1 0.0 Total moisture deficit 53.4 69.3 96.5 21.5 0.0 0.0 78.1 949 103.1 87.7 13.1 0.0 Total moisture deficit 53.4 69.3 96.5 21.5 0.0 0.0 78.1 94.9 103.1 87.7 13.1  Bao Bao Station: 1778' 20" N, 70° 47' 50" W.; 540 in elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 25.5 25.0 24.5 23.0 21.0 23.0 Mean biotemperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 25.5 25.0 24.5 23.0 21.0 23.0 Potential evapotranspiration 97.5 91.2 105.0 111.3 120.0 121.0 122.5 127.5 121.0 122.5 111.3 105.0 1,355.8 Pot. evap. adj. dry climate 89.6 83.8 96.5 102.3 110.3 111.2 112.6 117.2 111.2 112.6 102.3 96.5 1,246.0 Precipitation 82.0 69.0 100.0 143.0 228.0 82.0 50.0 59.0 54.0 110.0 133.0 136.0 1,246.0 Actual evapotranspiration 89.6 83.8 96.5 102.3 110.3 111.2 108.8 88.4 68.7 112.6 102.3 96.5 1,171.0 Water surplus 0.0 0.0 3.5 40.7 117.7 0.0 0.0 0.0 0.0 0.0 30.7 39.5 Soil moisture recharge 0.0 0.0 3.5 40.7 42.7 0.0 0.0 0.0 0.0 0.0 30.7 39.5 Soil moisture depletion 7.6 14.8 0.0 0.0 0.0 29.2 58.8 29.4 14.7 2.6 0.0 0.0 Available soil moisture emo 74.7 59.9 63.4 104.1 146.9 117.7 58.8 29.4 14.7 12.1 42.8 82.3 All runoff 0.0 0.0 0.0 0.0 75.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 75.0 Soil moisture deficit 72.1 87.0 83.4 42.7 0.0 29.2 88.0 117.5 132.2 134.7 104.0 64.5 Precipitation deficit 7.6 14.8 0.0 0.0 0.0 29.2 62.6 582 57.2 2.6 0.0 0.0 Total moisture deficit 793 101.8 83.4 42.7 0.0 58.4 150.6 175.6 189.4 137.3 104.0 64.5 Soil parameters: .it depth = 200.0 mm; bulk density = 1.36 g"em-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 97.9 mm; permanent wilting point = 46.2 mm; available soil moisture = 51.7 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 25.5 25.0 24.5 23.0 21.0 23.0 Mean biotemperature 19.5 20.0 21,0 23.0 24.0 25.0 24.5 25.5 25.0 24.5 23.0 21.0 23.0 Potential evapotranspiration 97.5 91.2 105.0 111.3 120.0 121.0 122.5 127.5 121.0 122.5 111.3 105.0 1,355.8 Par evap. adj. dry climate 89.6 83.8 96.5 102.3 110.3 111.2 112,6 117.2 111.2 112.0 102.3 96.5 1,246.0 Precipitation 82.0 69.0 100.0 143,0 228.0 82.0 "50.0 59.0 54.0 110.0 133,0 136.0 1,246.0 Actual-al fauspiration 89.6 83.8 96.5 102.3 1103 111.2 84.4 762 62.6 112.6 102.3 96.5 1,128.2 Water surplus 0.0 0.0 3,5 40.7 1t7.7 0.0 0.0 0.0 0.0 0.0 30.7 39.5 Ban Ban Station: 19' 18'20" N, 700 47'50" W.; 540 at elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; per cent field capacit; capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. Jan. Feb. Mar. Apr. May June July Mean air temperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 Mean biotemperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 Potential evapotranspiration 97.5 91.2 105.0 111.3 120.0 121.0 122.5 Pot. evap. adj. dry climate 89.6 83.8 96.5 102.3 110.3 111.2 112.6 Precipitation 82.0 69.0 100.0 143.0 228.0 82.0 50.0 Actual evapotranspiration 89.6 83.8 96.5 102.3 110.3 111.2 108.8 Water surplus 0.0 0.0 3.5 40.7 117.7 0.0 0.0 Soil moisture recharge 0.0 0.0 3.5 40.7 42.7 0.0 0.0 Soil moisture depletion 7.6 14.8 0.0 0.0 0.0 29.2 58.8 Available soil moisture emo 74.7 59.9 63.4 104.1 146.9 117.7 58.8 All runoff 0.0 0.0 0.0 0.0 75.0 0.0 0.0 Soil moisture deficit 72.1 87.0 83.4 42.7 0.0 29.2 88.0 Precipitation deficit 7.6 14.8 0.0 0.0 0.0 29.2 62.6 Total moisture deficit 79.7 101.8 83.4 42.7 0.0 58.4 150.6 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g"cm-s; per cent field capacit; capacity = 97.9 mm; permanent wilting point = 46.2 mm; available soil moisture = 51.7 mm. Jan. Feb. Mar. Apr. May June July Mean air temperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 Mean biotemperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 Potential evapotranspirntion 97.5 91.2 105.0 1113 (20.0 121.0 122.5 Pot. evap. adj, dry climate 89.6 83.8 96.5 102.3 110.3 111.2 112.6 Precipitation 82.0 69.0 1001) 143.0 228.0 82.0 '50.0 Actual evapouanspiratlon 89.6 83.8 96.5 102.3 110.3 111.2 84.4 Water surplus 0.0 OA 3.5 40.7 117.7 0.0 0.0 r = 0.36; per cent permanent wilting point = 0.17; field Aug. Sept. Oct. Nov. Dec. Year 25.5 25.0 24.5 23.0 21.0 23.0 25.5 25.0 24.5 23.0 21.0 23.0 127.5 121.0 122.5 111.3 105.0 1,355.8 117.2 111.2 112.6 102.3 96.5 1,246.0 59.0 54.0 110.0 133.0 136.0 1,246.0 88.4 68,7 112.6 102.3 96.5 1,171.0 0.0 0.0 0.0 30.7 39.5 0.0 0.0 0.0 30.7 39.5 29.4 14.7 2.6 0.0 0.0 29.4 14.7 12.] 42.8 82.3 0.0 0.0 0.0 0.0 0.0 75.0 117.5 132.2 134.7 104.0 64.5 58.2 57.2 2.6 0.0 0.0 175.6 189.4 137.3 104.0 64.5 r = 0.36; per cent permanent wilting point = 0.17; field Aug. Sept. Oct. Nov. Dec. Year 5 25.0 24.5 23.0 21.0 23.0 25.5 25.0 24.5 23,0 21.0 23,0 127.5 121,0 122.5 111,3 L050 1,355.8 117.2 111.2 112,6 102.3 96..5 1,246.0 59.0 54.0 110A 133.0 136.0 1,246.0 76.2 62.6 112,6 102.3 96.5 1,728,2 0.0 0.0 0.0 30.7 39.5 Bao Ban Station.- 19' 18'20" N., 70' 47' 50" W.; 540 m elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-a; per cent field capacity = 0.36; per cent permanent willing point = 0.17; field capacity = 146.9 mm; permanent witting point = 69.4 mm; available soil moisture = 77.5 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 25.5 25.0 24.5 23.0 21.0 23.0 Mean biotemperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 25.5 25.0 24.5 23.0 21.0 23.0 Potential evapotranspiration 97.5 91.2 105.0 111.3 120.0 121.0 122.5 127.5 121.0 122.5 111.3 105.0 1,355.8 Pot. evap. adj. dry climate 89.6 83.8 96.5 102.3 110.3 111.2 112.6 117.2 111.2 112.6 102.3 96.5 1,246.0 Precipitation 82.0 69.0 100.0 143.0 228.0 82.0 50.0 59.0 54.0 110.0 133.0 136.0 1,246.0 Actual evapotranspiration 89.6 83.8 96.5 102.3 110.3 111.2 108.8 88.4 68.7 112.6 1023 96.5 1,171.0 Water surplus 0.0 0.0 3.5 40.7 117.7 0.0 0.0 0.0 0.0 0.0 30.7 39.5 Soil moisture recharge 0.0 0.0 3.5 40.7 42.7 0.0 0.0 0.0 0.0 0.0 30.7 39.5 Soil moisture depletion 7.6 14.8 0.0 0.0 0.0 29.2 58.8 29.4 14.7 2.6 0.0 0.0 Available soil moisture emo 74.7 59.9 63.4 104.1 146.9 117.7 58.8 29.4 14.7 12.1 42.8 82.3 All runoff 0.0 0.0 0.0 0.0 75.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 75.0 Soil moisture deficit 72.1 87.0 83.4 42.7 0.0 292 98.0 117.5 132.2 134.7 104.0 64.5 Precipitation deficit 7.6 14.8 0.0 0.0 0.0 29.2 62.6 58.2 57.2 2.6 0.0 0.0 Total moisture deficit 79.7 101.8 83.4 42.7 0.0 58.4 150.6 175.6 189.4 137.3 104.0 64.5 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 97.9 min; permanent witting point = 46.2 mm; available soil moisture = 51.7 mm. Jan. Feb. Mar. Apr, May June Judy Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 25.5 25.0 24.5 23.0 21.0 23.0 Mean biotemperat ire 19.5 20.0 21.0 23.0 24.0 25.0 24.5 25.5 25.(1 24.5 23.0 21.0 23.0 Potential evapotranspiration 97.5 91.2 105.0 111.3 120.0 121.0 122.5 127.3 121.0 122.5 111.3 105.0 1,355.8 Put. evap. adi. dry cliruate 89.6 83,8 96.5 102.3 110.3 111.2 112.6 117.2 Il l,2 112.6 102.3 96.5 1,246.0 Precipimuon H2.0 G9.0 100.0 ]43.0 228.0 82.0 511,0 59.11 54.0 110.0 133.0 136.0 1,246.0 Actual cvapoua-piration 89.6 83.8 96.5 102.3 110.3 111.2 R4.4 76.2 62.6 112.6 102.3 96.5 1,128.2 Water surplus 0.0 0.0 3.5 40.7 117.7 d.0 0.0 0.0 0.0 0.0 30.7 39.5  Soil moisture recharge 0.0 0.0 3.5 40.6 0.0 0.0 0.0 0.0 0.0 010 30.7 39.5 Soil moisture depletion 7.6 14.8 0.0 0.0 0.0 29.2 34.4 17.2 8.6 2.6 0.0 0.0 Available soil moisture 68.6 53.8 57.3 97.9 97.9 68.7 34.4 17.2 8.6 6.0 36.7 76.2 All runoff 0.0 0.0 0.0 0.1 117.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 117.8 Soil moisture deficit 29.3 44.1 40.6 0.0 0.0 29.2 63.6 80.7 89.3 91.9 61.2 21.7 Precipitation deficit 7.6 14.8 0.0 0.0 0.0 29.2 62.6 58.2 57.2 2.6 0.0 0.0 Total moisture deficit 36.9 58.9 40.6 0.0 0.0 58.4 126.1 138.9 146.5 94.5 61.2 21.7 Soil parameters: soil depth = 100.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 49.0 mm; permanent willing point = 23.1 mm; available soil moisture = 25.8 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct Nov. Dec. Year Mean air temperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 25.5 25.0 24.5 23.0 21.0 23.0 Mean biotemperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 25.5 25.0 24.5 23.0 21.0 23.0 Potential evapotranspiration 97.5 91.2 105.0 111.3 120.0 121.0 122.5 127.5 121.0 122.5 111.3 105.0 1,355.8 Pot. evap. adj. dry climate 89.6 83.8 96.5 102.3 110.3 111.2 112.6 117.2 111.2 112.6 102.3 96.5 1,246.0 Precipitation 82.0 69.0 100.0 143.0 228.0 82.0 50.0 59.0 54.0 110.0 133.0 136.0 1,246.0 Actual evapotranspiration 89.6 83.8 96.5 102.3 110.3 106.5 62.2 65.1 57.1 111.5 102.3 96.5 1,083.7 Water surplus 0.0 0.0 3.5 40.7 117.7 0.0 0.0 0.0 0.0 0.0 30.7 39.5 Soil moisture recharge 0.0 0.0 3.5 18.9 0.0 0.0 0.0 0.0 0.0 0.0 303 16.7 Soil moisture depletion 7.6 14.8 0.0 0.0 0.0 24.5 12.2 6.1 3.1 1.5 0.0 0.0 Available soil moisture emo 41.4 26.5 30.1 49.0 49.0 24.5 12.2 6.1 3.1 1.5 32.2 49.0 All runoff 0.0 0.0 0.0 21.8 117.7 0.0 0.0 0.0 0.0 0.0 0.0 22.8 162.3 Soil moisture deficit 7.6 22.4 18.9 0.0 0.0 24.5 36.7 42.8 45.9 47.4 16.7 0.0 Precipitation deficit 7.6 14.8 0.0 0.0 010 29.2 62.6 58.2 57.2 2.6 0.0 0.0 Total deficit 15.2 372 18.9 0.0 0.0 53.7 99.3 101.0 103.1 50.0 163 0.0 Soil moisture recharge 0.0 0.0 3.5 40.6 0.0 0.0 0.0 0.0 0.0 0.0 30.7 39.5 Soil moisture depletion 7.6 14.8 0.0 0.0 0.0 29.2 34.4 17.2 8.6 2.6 0.0 0.0 Available soil moisture 68.6 53.8 57.3 97.9 97.9 68.7 34.4 17.2 8.6 6.0 36.7 76.2 All runoff 0.0 0.0 0.0 0.1 117.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 117.8 Soil moisture deficit 29.3 44.1 40.6 0.0 0.0 29.2 63.6 80.7 89.3 91.9 61.2 21.7 Precipitation deficit 7.6 14.8 0.0 0.0 0.0 29.2 62.6 58.2 57.2 2.6 0.0 0.0 Total moisture deficit 36.9 58.9 40.6 0.0 0.0 58.4 126.1 138.9 146.5 94.5 61.2 21.7 Soil parameters: soil depth = 100.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 49.0 mm; permanent wilting point = 23.1 mm; available soil moisture = 25.8 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Yea Mean air temperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 25.5 25.0 24.5 23.0 21.0 23.0 Mean biotemperature 19.5 20.0 21.0 23.0 24.0 25.0 24.5 25.5 25.0 24.5 23.0 21.0 23.0 Potential evapotranspiration 97.5 91.2 105.0 111.3 120.0 121.0 122.5 127.5 121.0 122.5 111.3 105.0 1,355.8 Pot. evap. adj. dry climate 89.6 83.8 96.5 102.3 110.3 111.2 112.6 117.2 111.2 112.6 102.3 96.5 1,246.0 Precipitation 82.0 69.0 100.0 143.0 228.0 82.0 50.0 59.0 54.0 110.0 133.0 136.0 1,246.0 Actual evapotranspiration 89.6 83.8 96.5 102.3 110.3 106.5 62.2 65.1 57.1 111.5 102.3 96.5 1,083.7 Water surplus 0.0 0.0 3.5 40.7 117.7 0.0 0.0 0.0 0.0 0.0 30.7 39.5 Soil moisture recharge 0.0 0.0 3.5 18.9 0.0 0.0 0.0 0.0 0.0 0.0 30.7 16.7 Soil moisture depletion 7.6 14.8 0.0 0.0 0.0 24.5 12.2 6.1 3.1 1.5 010 0.0 Available soil moisture emo 41.4 26.5 30.1 49.0 49.0 24.5 12.2 61 31 1.5 32.2 49.0 All runoff 0.0 0.0 0.0 21.8 117.7 0.0 0.0 0.0 0.0 0.0 0.0 22.8 162.3 Soil moisture deficit 7.6 22.4 18.9 0.0 0.0 24.5 36.7 42.8 45.9 47.4 16.7 0.0 Precipitation deficit 7.6 14.8 0.0 0.0 0.0 29.2 62.6 58.2 572 2.6 0.0 0.0 Total deficit 15.2 37.2 18.9 0.0 0.0 53.7 99.3 101.0 103.1 50.0 16.7 0.0 Soil moisture recharge 0.0 0.0 3.5 Soil moisture depletion 7.6 14.8 0.0 Available soil moisture 68.6 53.8 57.3 All runoff 0.0 0.0 010 Soil moisture deficit 29.3 44.1 40.6 Precipitation deficit 7.6 14.8 0.0 Total moisture deficit 36.9 58.9 40.6 Soil parameters: soil depth = 100.0 mm; bulk density capacity = 49.0 mm; permanent wilting point = 23.1 to Jan. Feb. Mar. Mean air temperature 19.5 20.0 21.0 Mean bimemperature 19.5 20.0 21.0 Potential evapotranspiration 97.5 91.2 105.0 Pot. evap. adj. dry climate 89.6 83.8 96.5 Precipitation 82.0 69.0 100.0 Actual evapotranspiration 89.6 83.8 96.5 Water surplus 0.0 0.0 3.5 Soil moisture recharge 0.0 0.0 3.5 Soil moisture depletion 7.6 14.8 0.0 Available soil moisture emo 41.4 26.5 30.1 All runoff 0.0 0.0 0.0 Soil moisture deficit 7.6 22.4 18.9 Precipitation deficit 7.6 14.8 0.0 Total deficit 15.2 37.2 18.9 0.0 0.0 0.0 30.7 39.5 17.2 8.6 2.6 0.0 0.0 17.2 8.6 6.0 36.7 76.2 0.0 0.0 0.0 0.0 0.0 117.8 80.7 89.3 91.9 61.2 21.7 58.2 57.2 2.6 0.0 0.0 138.9 146.5 94.5 61.2 21.7 t = 0.36; per cent permanent wilting point = 0.17; field Aug. Sept. Oct. Nov. Dec. Year 25.5 25.0 24.5 23.0 21.0 23.0 25.5 25.0 24.5 23.0 21.0 23.0 127.5 121.0 122.5 111.3 105.0 1,355.8 117.2 111.2 112.6 102.3 96.5 1,246.0 59.0 54.0 110.0 133.0 136.0 1,246.0 65.1 57.1 111.5 102.3 96.5 1,083.7 0.0 0.0 0.0 30.7 39.5 0.0 0.0 0.0 30.7 16.7 6.1 3.1 1.5 0.0 0.0 6.1 3.1 1.5 32.2 49.0 0.0 0.0 0.0 0.0 22.8 162.3 42.8 45.9 4714 16.7 0.0 58.2 57.2 2.6 0.0 0.0 101.0 103.1 50.0 16.7 0.0  Jarabacoa Station: 19.07' 00" N., 70.38' 00" W.; 480 m elevation Jarabacca Station: 17 07' 00" N, 70.38' 00" W.; 480 m elevation Jarabacoa Station: 19' 07' 00" N., 70° 38' 00" W.; 480 or elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cma; per cent field capacity = 0.36; per cent permanent willing point = 0.17; fold Soil parametes: sod depth = 300.0 mm; bulk density = 1.36 gam-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field Sod parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm, capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Jan. Feb. Mar. Apr. May June July Aug, Sept. Oct. Nov. Dec. Year Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Mean air temperature 19.3 19.8 20.6 22.0 22.6 21.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean air temperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean air temperature 19.3 19.8 20.6 22.0 22.6 216 23.6 24.4 23.8 23.4 21.9 Mean biotemperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean biotemperature 19.3 19.8 20.6 220 216 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean bimemperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 Potential evapotranspiration 96.5 90.3 103.0 106.5 113.0 114.2 118.0 122.0 115.2 117.0 106.0 100.5 1,302.2 Potential evapotranspiration 96.5 90.3 103.0 106.5 113.0 114.2 118.0 122.0 1152 117.0 106.0 100.5 1,302.2 Potential evapotranspiration 96.5 90.3 103.0 106.5 113.0 114.2 118.0 122.0 115.2 117.0 106.0 Pot. evap. adj. dry climate 96.5 90.3 103.0 106.5 113.0 114.2 118.0 1220 115.2 117.0 106.0 100.5 1,302.2 Pot, evap, adj, dry climate 96.5 90.3 103.0 106.5 113.0 114.2 118.0 122.0 115.2 117.0 106.0 100.5 1,3022 Pot. evap. adj. dry climate 96.5 90.3 103.0 106.5 113.0 114.2 118.0 122.0 115.2 117.0 106.0 Precipitation 92.0 96.0 91.0 143.0 186.0 93.0 96.0 79.0 87.0 142.0 162.0 135.0 1,402.0 Precipitation 92.0 96.0 91.0 143.0 186.0 93.0 96.0 79.0 87.0 142.0 162.0 135.0 1,402.0 Precipitation 92.0 96.0 91.0 143.0 186.0 93.0 96.0 79.0 87.0 142.0 162.0 Actual evapotranspiration 96.5 90.3 103.0 106.5 113.0 114.2 118.0 122.0 1152 117.0 106.0 100.5 1,302.2 Actual evapotranspiration 96.5 90.3 103.0 106.5 113.0 1142 118.0 122.0 115.2 117.0 106.0 100.5 1,302.2 Actual evapotranspiration 96.5 903 103.0 106.5 113.0 1142 118.0 122.0 115.2 117.0 106.0 Water surplus 0.0 5.7 0.0 36.5 73.0 0.0 0.0 0.0 0.0 25.0 56.0 34.5 Water surplus 0.0 5.7 0.0 36.5 73.0 0.0 0.0 0.0 0.0 25.0 56.0 34.5 Water surplus 0.0 5.7 0.0 36.5 73.0 0.0 0.0 0.0 0.0 25.0 56.0 Soil moisture recharge 0.0 4.5 0.0 12.0 0.0 0.0 0.0 0.0 0.0 25.0 56.0 33.4 Soil moisture recharge 0.0 4.5 0.0 12.0 0.0 0.0 0.0 0.0 0.0 25.0 56.0 33.4 Soil moisture recharge 0.0 45 0.0 12.0 0.0 0.0 0.0 0.0 010 25.0 56.0 Soil moisture depletion 4.5 0.0 12.0 0.0 0.0 21.2 22.0 43.0 28.2 0.0 0.0 0.0 Sal moisture depletion 4.5 0.0 12.0 0.0 0.0 212 22.0 43.0 282 0.0 0.0 0.0 Soil moisture depletion 4.5 0.0 12.0 0.0 0.0 21.2 22.0 43.0 28.2 0.0 0.0 Available sod moisture emo 142,4 1469 134.9 1469 146.9 125.7 103.7 60.7 32.5 57.5 113.5 146.9 Available soil moisture emo 142.4 146.9 134.9 146.9 1469 125.7 103.7 60.7 32.5 57.5 113.5 146.9 Available soil moisture coin 142.4 146.9 134.9 146.9 146.9 125.7 103.7 60.7 32.5 57.5 113.5 All runoff 0.0 1.2 0.0 24.5 73.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1 99.8 All runoff 0.0 1.2 0.0 24.5 73.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1 99.8 All runoff 0.0 1.2 0.0 24.5 73.0 0.0 0.0 0.0 0.0 0.0 0.0 Soil moisture deficit 45 0.0 12.0 0.0 0.0 21.2 43.2 862 114.4 89.4 33.4 0.0 Soil moisture deficit 4.5 0.0 12.0 0.0 0.0 212 412 86.2 114.4 89.4 33.4 0.0 Sell moisture deficit 4.5 0.0 12.0 0.0 0.0 21.2 43.2 86.2 114.4 89.4 33.4 Precipitation deficit 45 0.0 12.0 0.0 0.0 21.2 22.0 43.0 28.2 0.0 0.0 0.0 Precipitation deficit 4.5 0.0 12.0 0.0 0.0 212 22.0 43.0 28.2 0.0 0.0 0.0 Precipitation deficit 4.5 0.0 12.0 0.0 0.0 21.2 22.0 43.0 28.2 0.0 0.0 Total moisture deficit 9.0 0.0 24.0 0.0 0.0 42.4 65.2 129.2 142.6 89.4 33.4 0.0 Total moisture deficit 9.0 0.0 24.0 0.0 0.0 42.4 652 1291 142.6 89.4 33.4 0.0 Total moisture deficit 9.0 0.0 24.0 0.0 0.0 42.4 65.2 1292 142.6 89.4 33.4 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g"em-3; per cent fold capacity = 0.36; per cent permanent willing point = 0.17; fold Soil parameters: sal depth = 200.0 mm; bulk density = 1.36 g"cma; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field Soil parameters: soil depth = 200.0 men; bulk density = 1.36 g-cma; per cent field capacity = 0.36; per cent permanent waling capacity = 97.9 men; permanent wilting point = 46.2 mm; available soil moisture = 51.7 von, capacity = 97.9 mm; permanent wilting point = 46.2 mm; available soil moisture = 51.7 mm. capacity = 97.9 mm; permanent wilting point = 46.2 mm; available sod moisture = 51.7 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec Year Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Mean air temperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23A 21.9 20.1 22.1 Mean air temperature 197 19.8 20.6 22.0 22.6 23.6 23.6 244 23.8 23.4 21.9 20.1 22.1 Mean air temperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 Mean bimemperature 193 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean blotemperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean biotemperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 Polemia evapotranspiration 96.5 90.3 103.0 106.5 113.0 1142 118.0 122.0 115.2 117.0 106.0 100.5 1,302.2 Potential evapotranspiration 965 90.3 103.0 106.5 113.0 114.2 118.0 122.0 115.2 117.0 1040 100.5 1,3022 Potential evapotranspiration 96.5 90.3 103.0 106.5 113.0 114.2 118.0 122,0 115.2 117.0 106.0 Put evap, adj. dry climate 96.5 90.3 103.0 106.5 113.0 1142 118.0 122.0 115.2 117.0 106.0 100.5 1,302.2 Put map, adi. dry climate 96.5 903 103.0 106.5 113.0 1142 118.0 122.0 115.2 117.0 106.0 100.5 1,3022 Po, evap. adi. dry climate 96.5 90.3 103.0 1065 113.0 114.2 118.0 122,0 1152 117.0 106.0 Precipitation 92.0 96.0 91.0 143.0 186.0 93.0 96.0 79.0 87.0 142.0 162.0 135.0 1,402.0 Precipitation 92.0 96.0 91.0 143.0 186.0 93.0 96.0 79.0 87.0 142.0 162.0 135.0 1,402.0 Precipitation 92.0 96.0 91.0 143,0 186.0 93.0 96.0 79.0 87.0 142.0 162.0 Aeu I evapotranspiration 96.5 90.7 107,0 106.5 113.0 114.2 118.0 106.3 100.7 117,0 106.0 100.5 1,272.0 Actual evapotranspiration 96.5 90.3 103.0 106,5 113,0 114.2 118.0 106.3 100.7 117.0 106.0 100.5 1,272.0 Actual evapotranspiration 96.5 903 103.0 106.5 113,0 114.2 118.0 1069 IW.7 117.0 106.0 Wale, surplus 0.0 5.7 0.0 36.5 73.0 0.0 0,0 0.0 0.0 25.0 56.0 34.5 Water surplus 0.0 5.7 0.0 36.5 73.0 0.0 0.0 0.0 0.0 25.0 56.0 34.5 Water surplus 0.0 5.7 0.0 36.5 73.0 0.0 0.0 0.0 0.0 25.0 56.0  Soil moisture recharge 0.0 4.5 0.0 12.0 0.0 0.0 0.0 0.0 0.0 25.0 560 32 Soil moisture recharge 0.0 4.5 0.0 12.0 0.0 0.0 0.0 0.0 0.0 25.0 56.0 3.2 Soil moisture recharge 0.0 4.5 0.0 12.0 0.0 0.0 0.0 0.0 0.0 25.0 56.0 Soil moisture depletion 4.5 0.0 12.0 0.0 OA 21.2 22.0 27.3 17.7 0.0 0.0 0.0 Soil moisture depletion 4.5 0.0 12.0 0.0 0.0 21.2 22.0 27.3 13.7 0.0 0.0 0.0 Soil moisture depletion 4.5 0.0 12.0 0.0 0.0 212 220 27.3 13.7 0.0 0.0 Available soil moisture emo 93.4 97.9 85.9 979 979 76.7 54.7 27.3 13.7 38.7 94.7 97.9 Available soil moisture amo 93.4 97.9 85.9 97.9 97.9 76.7 54.7 27.3 13.7 38.7 94.7 97.9 Available sod moisture emo 93.4 97.9 85.9 97.9 97.9 76.7 54.7 279 13.7 38.7 94.7 All runoff 0.0 1.2 0.0 24.5 73.0 0.0 0.0 0.0 0.0 0.0 0.0 31.3 130.0 All runoff 0.0 1.2 0.0 24.5 73.0 0.0 0.0 0.0 010 0.0 0.0 31.3 130.0 All runoff 0.0 1.2 0.0 24.5 77.0 0.0 0.0 0.0 0.0 0.0 0.0 Soil moisture deficit 4.5 0.0 12.0 0.0 0.0 21.2 43.2 70.6 84.2 59.2 3.2 0.0 Sail moisture deficit 4.5 0.0 12.0 0.0 0.0 21.2 43.2 70.6 842 59.2 3.2 0.0 Soil moisture deficit 4.5 0.0 12.0 0.0 0.0 21.2 43.2 70.6 84.2 59.2 3.2 Precipitation deficit 4.5 0.0 12.0 0.0 0.0 21.2 22.0 43.0 28.2 0.0 0.0 0.0 Precipitation deficit 4.5 0.0 12.0 0.0 0.0 21.2 22.0 43.0 28.2 0.0 0.0 0.0 Precipitation deficit 4,5 0.0 12.0 0.0 0.0 21.2 22.0 43.0 28.2 0.0 0.0 Total moisture deficit 9.0 0.0 24.0 0.0 0.0 42.4 652 113.6 112.4 591 3.2 0.0 Total moisture deficit 90 0.0 24.0 0.0 0.0 42.4 65.2 113.6 112.4 59.2 3.2 OA Total moisture deficit 9.0 0.0 24.0 OA 0.0 42.4 65.2 113.6 112.4 59.2 3.2 Sod parameters: soil depth = 100.0 mm; bulk density = 1.36 g-cm-a; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field Sod parameters: soil depth = 100.0 mm; bulk density = 1.36 g"am-s; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field Sod parameters: soil depth = 100.0 mm; bulk density = 1.36 g-cm-s; per cent field capacity = 0.36; per cent permanent wilting capacity = 49.0 mm; permanent wilting point = 23.1 mm; available soil moisture = 25.8 mm, capacity = 49.0 mm; permanent wilting point = 23.1 mm; available soil moisture = 25.8 mm. capacity = 49.0 mm; permanent wilting point = 23.1 mm; available soil moisture = 25.8 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept Oct. Nov. Dec. Year Jan. Feb. Mar. Apr. May June July Aug. Sept Oct. Nov, Dec. Year Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Mean air temperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean air temperature 19.3 19.8 20.6 22.0 226 23.6 23.6 24.4 23.8 23.4 219 20.1 22.1 Mean air temperature 199 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 Mean biotemperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23A 21.9 20.1 22.1 Mean Notemperature 19.3 19.8 20.6 220 22.6 23.6 23.6 24.4 23.8 23.4 21.9 20.1 22.1 Mean biotemperature 19.3 19.8 20.6 22.0 22.6 23.6 23.6 24.4 23.8 23.4 21.9 Potential evapotranspiration 965 90.3 103.0 106.5 113.0 114.2 118.0 122.0 115.2 117.0 106.0 100.5 1,3022 Potential evapotranspiration %.5 90.3 103.0 106.5 113.0 114.2 118.0 122.0 1151 117.0 106.0 100.5 1,302.2 Potential evapotranspiration 96.5 90.3 103.0 106.5 113.0 114.2 118.0 122.0 1151 117.0 106.0 Pot, evap. adj, dry climate 965 90.3 103.0 1065 113.0 1142 118.0 122.0 115.2 117.0 106.0 100.5 1,302.2 Pot. evap. adj. dry climate 961 90.3 103.0 106.5 113.0 1142 118.0 1220 115.2 117.0 106.0 100.5 1,3022 Pot. evap, adj. dry climate 965 909 103.0 106.5 113.0 114.2 118.0 122.0 1152 117.0 106.0 Precipitation 92.0 96.0 91.0 143.0 186.0 93.0 96.0 79.0 87.0 142.0 162.0 135.0 1,402.0 Precipitation 92.0 96.0 91.0 143.0 186.0 93.0 96.0 79.0 87.0 142.0 162.0 135.0 1,402.0 Precipitation 92.0 96.0 91.0 143.0 186.0 93.0 96.0 79.0 87.0 142.0 162.0 Actual evapotranspiration 96.5 90.3 103.0 1065 113.0 114.2 109.9 85.9 90.5 117.0 106.0 100.5 1,233.3 Actual evapotranspiration 96.5 90.3 103.0 106.5 113.0 114.2 109.9 85.9 90.5 117.0 106.0 100.5 1,2339 Actual evapotranspiration 96.5 90.3 103.0 106.5 113.0 114.2 109.9 85.9 905 117.0 106.0 Water surplus 0.0 5.7 0.0 365 73.0 0.0 0.0 0.0 0.0 25.0 56.0 34.5 Water surplus 0.0 5.7 0.0 365 73.0 0.0 0.0 0.0 0.0 25.0 56.0 34.5 Water surplus 0.0 53 0.0 36.5 73.0 0.0 0.0 0.0 0.0 25.0 56.0 Soil moisture recharge 0.0 4.5 0.0 12.0 0.0 0.0 0.0 0.0 0.0 25.0 20.5 0.0 Soil moisture recharge 0.0 4.5 0.0 12.0 0.0 0.0 0.0 0.0 0.0 25.0 20.5 0.0 Soil moisture recharge 0.0 4.5 0.0 12.0 0.0 0.0 0.0 0.0 0.0 25.0 20.5 Soil moisture depletion 4.5 0.0 12.0 OA 0.0 21.2 139 69 3.5 0.0 0.0 0.0 Soil moisture depletion 4.5 0.0 12.0 0.0 0.0 21.2 13.9 6.9 3.5 0.0 0.0 0.0 Soil moisture depletion 4.5 0.0 12.0 0.0 0.0 21.2 13.9 6.9 3.5 0.0 0.0 Available sod moisture emo 44.5 49.0 37.0 49.0 49.0 27.7 139 69 3.5 28.5 49.0 49.0 Available soil moisture emo 44.5 49.0 37.0 49.0 49.0 27.7 13.9 6.9 3.5 28.5 49.0 49.0 Available soil moisture ems 44.5 49.0 37.0 49.0 49.0 27.7 13.9 6.9 3.5 28.5 49.0 All runoff 0.0 1.2 0.0 245 73. Precipitation deficit 4.5 0.0 12.0 0.0 0.0 21.2 22.0 47.0 28.2 0.0 OA 0.0 Precipitation deficit 4.5 0.0 12.0 0.0 0.0 212 22.0 43.0 28.2 0.0 0.0 0.0 Precipitation deficit 4.5 0.0 12.0 0.0 0.0 21.2 22.0 43.0 28.2 0.0 0.0 Total moisture deficit 9.0 0.0 24.0 0.0  Tavera Station; 19' 16' 40" N., 70° 42' 50" W.; 300 to elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 7 Jan. Feb. Mar. Apr. May June Mean air temperature 22.3 22.3 23.0 23.7 25.7 26.3 Mean biotemperature 22.3 22.3 23.0 23.7 25.7 26.3 Potential evapotranspiration 111.5 101.7 115.0 114.7 128.5 127.3 Pot. evap. adj. dry climate 108.9 99.3 112.3 112.0 125.5 124.3 Precipitation 74.0 115.0 49.0 115.0 238.0 120.0 Actual evapotranspiration 108.9 99.3 99.0 112.0 125.5 124.3 Water surplus 0.0 15.7 0.0 3.0 112.5 0.0 Soil moisture recharge 0.0 15.7 0.0 3.0 93.8 0.0 Soil moisture depletion 34.9 0.0 50.0 0.0 0.0 4.3 Available soil moisture emo 84.3 100.1 50.0 53.0 146.9 142.6 All runoff 0.0 0.0 0.0 0.0 18.7 0.0 Soil moisture deficit 62.5 46.8 96.8 93.8 0.0 4.3 Precipitation deficit 34.9 0.0 63.3 0.0 0.0 4.3 Total moisture deficit 97.4 46.8 160.1 93.8 0.0 8.6 Id capacity = 0.36; per cent permanent wilting point - 0.17; field 77.5 mm. July Aug. Sept. Oct. Nov. Dec. Year 25.7 25.7 26.3 25.8 24.3 22.5 24.5 25.7 25.7 26.3 25.8 24.3 22.5 24.5 128.5 128.5 127.3 129.0 117.6 112.5 1,442.1 125.5 125.5 124.3 126.0 114.8 109.8 1,408.0 92.0 100.0 77.0 151.0 133.0 144.0 1,408.0 125.5 125.5 118.8 126.0 114.8 109.8 1,389.3 0.0 0.0 0.0 25.0 18.2 34.2 0.0 0.0 0.0 25.0 18.2 34.2 33.5 25.5 41.8 0.0 0.0 0.0 109.1 83.7 41.8 66.9 85.1 119.2 0.0 0.0 0.0 0.0 0.0 0.0 18.7 37.7 63.2 105.0 80.0 61.8 27.7 33.5 25.5 47.3 0.0 0.0 0.0 71.2 88.7 152.3 80.0 61.8 27.7 Tavera Station: 19' 16' 40" N., 70° 42' 50" W.; 300 in elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity capacity - 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. Jan. Feb. Mar. Apr. May June July Mean air temperature 22.3 22.3 23.0 23.7 25.7 26.3 25.7 Mean biotemperature 22.3 22.3 23.0 23.7 25.7 26.3 25.7 Potential evapotranspiration 111.5 101.7 115.0 114.7 128.5 127.3 128.5 Pot. evap. adj. dry climate 108.9 99.3 112.3 112.0 125.5 124.3 125.5 Precipitation 74.0 115.0 49.0 115.0 238.0 120.0 92.0 Actual evapotranspiration 108.9 99.3 99.0 112.0 125.5 124.3 125.5 Water surplus 0.0 15.7 0.0 3.0 112.5 0.0 0.0 Soil moisture recharge 0.0 15.7 0.0 3.0 93.8 0.0 0.0 Soil moisture depletion 34.9 0.0 50.0 0.0 0.0 4.3 33.5 Available soil moisture emo 84.3 100.1 50.0 53.0 146.9 142.6 109.1 All runoff 0.0 0.0 0.0 0.0 18.7 0.0 0.0 Soil moisture deficit 62.5 46.8 96.8 93.8 0.0 4.3 37.7 Precipitation deficit 34.9 010 63.3 0.0 0.0 4.3 33.5 Total moisture deficit 97.4 46.8 160.1 93.8 0.0 8.6 71.2 per cent permanent wilting point = 0.17; field Sept. Oct. Nov. Dec. Y- 26.3 25 .8 243 22.5 24.5 26.3 25.8 243 22.5 24.5 127.3 129.0 117.6 112.5 1,442.1 124.3 126.0 114.8 109.8 1,408.0 77.0 151.0 133.0 144.0 1,408.0 118.8 126.0 114.8 109.8 1,389.3 0.0 25.0 18.2 34.2 0.0 25.0 18.2 34.2 41.8 0.0 0.0 0.0 41.8 66.9 85.1 119.2 0.0 0.0 0.0 0.0 18.7 105.0 80.0 61.8 27.7 47.3 0.0 0.0 0.0 152.3 80.0 61.8 27.7 Mean air temperature 22.3 Mean biotemperature 22.3 Potential evapotranspiration 111.5 Pot. evap. adj. dry climate 108.9 Precipitation 74.0 Actual evapotranspiration 108.9 Water surplus 0.0 Sail moisture recharge 0.0 Soil moisture depletion 34.9 Available soil moisture can, 84.3 All runoff 0.0 Soil moisture deficit 62.5 Precipitation deficit 34.9 Total moisture deficit 97.4 26.3 25 .8 24.3 22.5 24.5 26.3 25.8 24.3 22,5 24.5 127.3 129.0 117.6 112.5 1,442.1 124.3 126.0 114.8 109.8 1,408.0 77.0 151.0 133.0 144.0 1,408.0 118.8 126.0 114.8 109.8 1,3 89.3 0.0 25.0 18.2 34.2 0.0 25.0 18.2 34.2 41.8 0.0 0.0 0.0 41.8 66.9 85.1 119.2 0.0 0.0 0.0 0.0 18.7 105.0 80.0 61.8 27.7 47.3 0.0 0.0 0.0 152.3 80.0 61.8 27.7 Soil parameters: soil depth = 200.0 min; bt capacity = 97.9 min; permanent wilting point Jan. Feb. Mean air temperature 22.3 22.3 Mean biotempcraturc 22.7 22.3 Potential evapotranspiration 111.5 101.7 Pot. -ap. adj. dry elimate 108.9 99.3 Precipitation 74.0 115.0 Actual ovapotranspiration 108.9 99.3 Water surplus 0.0 t5.7 ilk density = 1.36 g"cm-a; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field - 46.2 mm; available soil moisture = 51.7 mm. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year 23.0 23-7 25.7 26.3 25.7 25.7 26.3 25.8 24.3 22.5 24.5 23.0 23.7 25.7 26.3 25,7 25.7 26.3 25.8 24.3 22.5 24.5 115.0 114.7 128.5 127.7 12 R.5 128.5 127.3 129.0 117.6 112.5 1,442.1 D 2.3 112-0 125.5 124.3 125.5 125.5 124.3 126.0 114.8 109.8 1,408.0 49.0 115.0 238.0 120.0 92.0 100.0 77.0 15(.0 133.0 144.0 1,40R.0 86.8 112.0 125.5 124.3 125.5 125.5 94.4 126.0 114.8 109.8 1,352.6 0.0 3.0 112.5 OA 0.0 0.0 0.0 25.0 18.2 34.2 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g"em-a; per cent field capacity = 0.36; per cent pCnnanent wilting point = 0.17; field capacity = 97.9 rmn: permanent wilting point = 46.2 mm; available soil moisture - 51.7 mm. Jan. Feb. Mar. Al- May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 22.3 22.3 23.0 23.7 25.7 26.3 25.7 25.7 26.3 25.8 24,1 22.5 24.5 Mean biotempernture 22.3 22.3 23.0 23.7 25.7 26.3 25.7 25.7 26.3 25.8 24,3 22.5 24, putentlnlc-patra-piration 111.5 101.7 115.0 ]14.7 128.5 127.3 128.5 128.5 127.3 129.0 117.6 112.5 1,442.1 t. evap. adj. dy climate 108.9 99.3 112.3 112.0 125.5 124.3 125.5 125.5 124.3 126.0 114.8 109,8 1,408.0 Precipitation 74.0 115.0 49.0 115.0 238.0 12fi.0 92.0 100.0 77.0 151.0 133.0 144.0 1,408.0 Actual -apon-spiraticn 108.9 99.3 86.8 112.0 125.5 124.3 125,5 125.5 94.4 126.0 114.8 109.8 1,352.6 Water -plus 0.0 15.7 OA 30 112.5 0.0 0.0 0.0 0.0 25.0 18.2 34.2 Soil parameters; soil depth = 200.0 ni bulk density = 1.36 g"cm-a; per cent field capacity = 0.36; per cent permanent wilting point -_ 0.17; field capacity - 97.9 mm; permanent wilting point = 46.2 mm; available soil moisture = 51.7 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 223 22.3 23.0 23.7 253 26.3 25.7 25.7 26.3 25.8 24.3 22.5 24.5 Mean biotemperature 223 22.3 23.0 23.7 25.7 26.3 25.7 25.7 26.3 25.9 24.3 22.5 24.5 Potential evapotranspiration 111.5 101.7 115.0 114.7 128.5 127.3 128.5 128.5 127.3 129.0 117.6 112.5 1.442.1 Pot, evap. adj. dry climate 108.9 99.3 112.3 I12A 125.5 124.3 125.5 125.5 724.3 126.0 114.8 109.8 1,408.0 Necipimtiou 74.0 115.0 49.0 115.0 23 8.0 120A 92.0 100.0 77.0 IS t.o 133.0 144.0 1,408.0 Actual evapotrunspiration 108.9 99.3 86.8 112.0 125.5 124.3 125.5 123.3 94,4 126.0 114.8 109.8 1;352.6 Water surplus 0.0 15.7 0.0 3.0 112.5 0.0 0.0 0.0 0.0 25.0 18.2 34.2  Soil moisture recharge 0.0 15.7 0.0 3.0 57.1 0.0 0.0 0.0 0.0 25.0 18.2 34.2 Soil moisture depletion 34.9 0.0 37.8 0.0 0.0 4.3 33.5 25.5 17.4 0.0 0.0 0.0 Available soil moisture emo 59.9 75.6 37.8 40.8 97.9 93.6 60.2 34.7 17.4 42.4 60.6 94.7 All runoff 0.0 0.0 0.0 0.0 55.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 55.4 .it moisture deficit 38.1 22.3 60.1 57.1 0.0 4.3 37.7 63.2 80.6 55.5 37.3 3.2 Precipitation deficit 34.9 0.0 63.3 0.0 0.0 4.3 33.5 25.5 47.3 0.0 0.0 0.0 Total moisture deficit 72.9 22.3 123.4 57.1 0.0 8.6 71.2 88.7 127.8 55.5 37.3 3.2 Soil parameters: soil depth = 100.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 49.0 mm; permanent wilting point = 23.1 mm; available soil moisture - 25.8 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 22.3 22.3 23.0 23.7 25.7 26.3 25.7 25.7 26.3 25.8 24.3 22.5 24.5 Mean bimemperature 22.3 22.3 23.0 23.7 25.7 26.3 25.7 25.7 26.3 25.8 24.3 22.5 24.5 Potential evapotranspiration 111.5 101.7 115.0 114.7 128.5 127.3 128.5 128.5 127.3 129.0 117.6 112.5 1,442.1 Pot. evap. adj. dry climate 108.9 99.3 112.3 112.0 125.5 124.3 125.5 125.5 124.3 126.0 114.8 109.8 1,408.0 Precipitation 74.0 115.0 49.0 115.0 238.0 120.0 92.0 100.0 77.0 151.0 133.0 144.0 1,408.0 Actual evapotranspiration 98.5 99.3 69.1 112.0 125.5 124.3 114.3 111.2 82.6 126.0 114.8 109.8 1,287.3 Water surplus 0.0 15.7 0.0 3.0 112.5 0.0 0.0 0.0 0.0 25.0 18.2 34.2 Soil moisture recharge 0.0 15.7 0.0 3.0 25.9 0.0 0.0 0.0 0.0 25.0 18.2 0.2 Soil moisture depletion 24.5 0.0 20.1 0,0 0.0 4.3 22.3 11.2 5.6 0.0 0.0 0.0 Available soil moisture emo 24.5 40.2 20.1 23.1 49.0 44.7 22.3 11.2 5.6 30.6 48.8 49.0 All runoff 0.0 0.0 0.0 0.0 86.7 0.0 0.0 0.0 0.0 0.0 0.0 34.0 120.7 Soil moisture deficit 24.5 8.8 28.9 25,9 0.0 4.3 266 37.8 43.4 18.3 0.2 0.0 Precipitation deficit 34.9 0.0 63.3 0.0 0.0 4.3 33..5 25.5 47.3 0.0 0.0 0.0 Total moisture deficit 59.3 8.8 92.1 25.9 010 8.6 60.1 63.3 90.7 18.3 0,2 0.0 Soil moisture recharge 0.0 15.7 0.0 3.0 57.1 0.0 0.0 0.0 0.0 25.0 18.2 34.2 Soil moisture depletion 34.9 0.0 37.8 0.0 0.0 4.3 33.5 25.5 17.4 0.0 0.0 0.0 Available soil moisture emo 59.9 75.6 37.8 40.8 97.9 93.6 60.2 34.7 17.4 42.4 60.6 94.7 All runoff 0.0 0.0 0.0 0.0 55.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 55.4 Soil moisture deficit 38.1 22.3 60.1 57.1 0.0 4.3 37.7 63.2 80.6 55.5 37.3 3.2 Precipitation deficit 34.9 0.0 63.3 0.0 0.0 4.3 33.5 25.5 47.3 0.0 0.0 0.0 Total moisture deficit 72.9 22,3 123.4 57.1 0.0 8.6 71.2 883 127.8 55.5 37.3 3.2 Soil parameters: soil depth = 100.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 49.0 mm; permanent wilting point = 23.1 mm; available soil moisture = 25.8 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 22.3 22.3 23.0 23.7 25.7 26.3 25.7 25.7 26.3 25.8 24.3 22.5 24.5 Mean biotemperature 22.3 22.3 23.0 23.7 25.7 26.3 25.7 25.7 26.3 25.8 24.3 22.5 24.5 Potential evapotranspiration 111.5 101.7 115.0 114.7 128.5 127.3 128.5 128.5 127.3 129.0 117.6 112.5 1,442.1 Pot. evap. adj. dry climate 108.9 99.3 112.3 112.0 125.5 124.3 125.5 125.5 124.3 126.0 114.8 109.8 1,408.0 Precipitation 74.0 115.0 49.0 115.0 238.0 120.0 92.0 100.0 77.0 151.0 133.0 144.0 1,408.0 Actual evapotranspiration 98.5 99.3 69.1 112.0 125.5 124.3 114.3 111.2 82.6 126.0 114.8 109.8 1,287.3 urplus 0.0 15.7 0.0 3.0 112.5 0.0 0.0 0.0 0.0 25.0 18.2 34.2 Soil moisture recharge 0.0 15.7 0.0 3.0 25.9 0.0 0.0 0.0 0.0 25.0 18.2 0.2 Soil moisture depletion 24.5 0.0 20.1 0.0 0.0 4.3 22.3 11.2 5.6 0.0 0.0 0.0 Available soil moisture emo 24.5 40.2 20.1 23.1 49.0 44.7 22.3 11.2 5.6 30.6 48.8 49.0 All runoff 0.0 0.0 0.0 0.0 86.7 0.0 0.0 0.0 0.0 0.0 0.0 34.0 120.7 Soit moisture deficit 24.5 8.8 28.9 25.9 0.0 4.3 26.6 37.6 43.4 18.3 0.2 0.0 Precipitation deficit 34.9 0.0 63.3 0.0 0.0 4.3 33.5 25.5 47.3 0.0 0.0 0.0 Total moisture deficit 59.3 8.8 92.1 25.9 0.0 8.6 60.1 63.3 90.7 18.3 0.2 0.0 pth = 100.0 mm; bulk density = 1.36 g-cm-3; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field nment wilting point = 23.1 mm; available soil moisture = 25.8 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year 22.3 22.3 23.0 23.7 25.7 26.3 25.7 25.7 26.3 25.8 24.3 22.5 24.5 22.3 22.3 23.0 23.7 25.7 26.3 25.7 25.7 26.3 25.8 24.3 22.5 24.5 n 111.5 101-7 115.0 114.7 128.5 127.3 128.5 128.5 127.3 129.0 117.6 112.5 1,442.1 108.9 99.3 112.3 112.0 125.5 124.3 125.5 125.5 124.3 126.0 114.8 109.8 1,408.0 74.0 115.0 49.0 115.0 238.0 120.0 92.0 100.0 77.0 151.0 133.0 144.0 1,408.0 98.5 99.3 69.1 112.0 125.5 124.3 114.3 111.2 82.6 126.0 114.8 109.8 1,287.3 0.0 15.7 0.0 3.0 112.5 0.0 0.0 0.0 0.0 25.0 18.2 34.2 0.0 15.7 0.0 3.0 25.9 0.0 0.0 0.0 0.0 25.0 18.2 0.2 24.5 0.0 20.1 0.0 0.0 4.3 22.3 11.2 5.6 0.0 0.0 0.0 0 24.5 40.2 20.1 23.1 49.0 44.7 22.3 11.2 5.6 30.6 48.8 49.0 0.0 0.0 0.0 0.0 86.7 0.0 0.0 0.0 0.0 0.0 0.0 34.0 120.7 24.5 8.8 28.9 253 0.0 4.3 26.6 37.8 43.4 18.3 0.2 0.0 34.9 0.0 63.3 0.0 0.0 4.3 33.5 25.5 47.3 0.0 0.0 0.0 59.3 8.8 92.1 25.9 0.0 8.6 60.1 63.3 90.7 183 0.2 0.0  Mambao Station: 19° 04'20" N., 70° 48' 40" W.; 960 m elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. Jan. Feb. Mar. Apr. May June July Mean air temperature 16.0 16.5 18.5 18.5 19.5 20.0 20.0 Mean biotemperature 16.0 16.5 18.5 18.5 19.5 20.0 20.0 Potential evapotranspiration 80.0 75.2 92.5 89.5 97.5 96.8 100.0 Pot, evap. adj. dry climate 80.0 75.2 92.5 89.5 97.5 96.8 100.0 Precipitation 80.0 75.0 93.0 90.0 98.0 97.0 100.0 Actual evapotranspiration 80.0 75.2 92.5 89.5 97.5 96.8 100.0 Water surplus 0.0 0.0 0.5 0.5 0.5 0.2 0.0 Soil moisture recharge 0.0 0.0 0.2. 0.0 0.0 0.0 0.0 Soil moisture depletion 0.0 0.2 0.0 0.0 0.0 0.0 0.0 Available soil moisture emo 146.9 146.6 146.9 146.9 146.9 146.9 146.9 All runoff 0.0 0.0 0.3 0.5 0.5 0.2 0.0 Soil moisture deficit 0.0 0.2 0.0 0.0 0.0 0.0 0.0 Precipitation deficit 0.0 0.2 0.0 0,0 0.0 0.0 0.0 Total moisture deficit OA 0.5 0.0 0.0 0.0 0.0 0.0 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g"em-3; per cent field capacity capacity = 97.9 mm; permanent wilting point = 46.2 mm; available soil moisture = 51.7 mm. Jan. Feb. Mar. Apr. May June July Mean air temperature 16.0 16.5 18.5 18.5 19.5 20.0 20.0 Mean biotemperature 16.0 16.5 18.5 18.5 19.5 20.0 211.0 Potential evapotranspiration 80.0 75.2 92.5 x9.5 97.5 96.8 100.0 Pot. evap. adj, dry climate 80.0 75.2 92.5 89.5 97.5 96.8 100.0 Prccipimtion 80.0 75.0 93.0 90.0 98.0 97.0 100.0 Actual evapotranspiration 80.0 752 92.5 89.5 97.5 96.8 100.0 Water surplus OA 0.0 0.5 0.5 0.5 0.2 0.0 Manabao Station: 19. 04'20- N., 70' 48' 40" W.; 960 m elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; pei capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil mo. Jan. Feb. Mar. Apr. May Mean it temperature 16.0 16.5 18.5 18.5 19.5 Mean biotemperature 16.0 16.5 18.5 18.5 19.5 Potential evapotranspiration 80.0 75.2 92.5 89.5 97.5 Pot. evap. adj. dry climate 80.0 75.2 92.5 89.5 97.5 Precipitation 80.0 75.0 93.0 90.0 98.0 Actual evapotranspiration 80.0 75.2 92.5 89.5 97.5 Water surplus 0.0 0.0 0.5 0.5 0.5 Soil moisture recharge 0.0 0.0 0.2 0.0 0.0 Soil moisture depletion 0.0 0.2 0.0 0.0 0.0 Available soil moisture emo 146.9 146.6 146.9 146.9 146.9 All runoff 0.0 0.0 0.3 0.5 0.5 Soil moisture deficit 0.0 0.2 0.0 0.0 0.0 Precipitation deficit 0.0 0.2 0.0 0.0 0.0 Total moisture deficit 010 0.5 0.0 0.0 0.0 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g-cm-3; pe. capacity = 97.9 mm; permanent wilting point = 46.2 mm; available soil moi Jan. Feb. Mar. Apr. May Mean air temperature 16.0 16.5 18.5 18.5 19.5 Men. biotempcratttre 16.0 16.5 18.5 18.5 19.5 Potential evapotranspiration 80.0 75.2 92.5 89.5 97.5 Pot. evap. adj. dry climate 80.0 75.2 92.5 89.5 97.5 Precipitation 80.0 75.0 93.0 90.0 98.0 Actual evapotranspiration 80.0 752 92.5 89.5 97.5 Water surplus 0.0 0.0 0.5 0.5 0.5 er cent field capacity = 0.36; per cent permanent wilting point = 0.17; field oisture = 77.5 mm. June July Aug. Sept. Oct. Nov. Dec. Year 20.0 20.0 20.5 20.5 20.0 18.5 17.0 18.8 20.0 20.0 20.5 20.5 20.0 18.5 17.0 18.8 96.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 96.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 97.0 100.0 10310 99.0 100.0 90.0 85.0 1,110.0 96.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 0.2 0.0 0.5 0.0 0.0 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 146.9 146.9 146.9 146.7 146.7 146.9 146.9 0.2 0.0 0.5 0.0 0.0 0.2 0.0 2.2 0.0 0.0 0.0 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.2 0.0 0.0 per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field isture = 51.7 mm. June July Aug. Sept. Oct. Nov. Dec. Year 20.0 20.0 20.5 20.5 20.0 18.5 17.0 18.8 20.0 20.o zo.s zo.s 20.0 le.s 17.0 ls.e 96.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 96.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 97.0 100.0 103.0 99.0 100.0 90.0 85.0 1,110.0 96.8 IM) 102.5 99.2 100.0 89.5 85.0 1,107.8 0.2 OA 0.5 0.0 0.0 0.5 0.0 A1anabao Station: 19' 04'20" N., 70°48' 40" W.; 960 m elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = Jan. Feb. Mar. Apr. May June Mean air temperature 16.0 16.5 18.5 18.5 19.5 20.0 Mean biotemperature 16.0 16.5 18.5 18.5 19.5 20.0 Potential evapotranspiration 80.0 75.2 92.5 89.5 97.5 96.8 Pot. evap. adj. dry climate 80.0 75.2 92.5 89.5 97.5 96.8 Precipitation 80.0 75.0 93.0 90.0 98.0 97.0 Actual evapotranspiration 80.0 75.2 92.5 89.5 97.5 96.8 Water surplus 0.0 0.0 0.5 0.5 0.5 0.2 Soil moisture recharge 0.0 0.0 0.2 0.0 0.0 0.0 Soil moisture depletion 0.0 0.2 0.0 0.0 0.0 0.0 Available soil moisture emo 146.9 146.6 146.9 146.9 146.9 146.9 All runoff 0.0 0.0 0.3 (15 0.5 0.2 Soil moisture deficit 0.0 0.2 0.0 0.0 0.0 0.0 Precipitation deficit 0.0 0.2 0.0 0.0 0.0 0.0 Total moisture deficit 010 0.5 0.0 0.0 0.0 0.0 capacity = 0.36; per cent permanent willing point = 0.17; field '7.5 mm. July Aug. Sept. Oct. Nov. Dec. Y- 20.0 20.5 20.5 20.0 18.5 17.0 18.8 20.0 20.5 20.5 20.0 18.5 17.0 18.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 100,0 102.5 992 100.0 89.5 85.0 1,107.8 100.0 103.0 99.0 100.0 90.0 85.0 1,110.0 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 0.0 0.5 0.0 0.0 0.5 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.2 0.0 0.0 0.0 146.9 146.9 146.7 146.7 146.9 146.9 0.0 0.5 0.0 0.0 0.2 0.0 2.2 0.0 0.0 0.2 R2 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.4 0.2 0.0 0.0 Soil parameters: soil depth = 200.0 mm; bulk densit7 capacity = 97.9 mm; permanent wilting point = 46.2 mr Jan. Feb. Mar. Mean air temperature 16.0 16.5 18.5 Mean biotemperatnre 16.0 16.5 18.5 Potential evapotranspiration 80.0 75.2 92.5 Pot. evap. adj. dry climate 80.0 75.2 92.5 Precipilmm 80.0 75.0 93.0 Actnal evapotranspiration 80.0 75.2 92.5 water surplus 0.0 0.0 0.5 ty = 1.36 g"cm-a; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field im; available soil moisture = 51.7 mm. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year 18.5 19.5 20.U 20.0 20.5 20.5 20.0 I8.5 17.0 18.8 18.5 19.5 20.0 20.0 20.5 20.5 20.0 18.5 17.0 l8,8 89.5 97.5 96.8 100.0 1025 99.2 100.0 89.5 85.0 1,107.8 89,5 97.5 96.8 If10.0 102,5 99.2 100.0 89.5 85.0 1,107.8 90.0 98.0 97.0 100.0 103.0 99.0 100.0 90A 85.0 1,110.0 89,5 97.5 96.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 0.5 0.5 02 11.0 0.5 0.0 0,0 0.5 0.0  Soil moisture recharge 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0,0 0.0 0,0 02 0.0 Soil moisture recharge 0.0 0.0 0.2 0.0 0,0 0.0 0.0 0.0 0.0 0.0 01 0.0 Soil moisture recharge 0.0 0.0 01 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 Soil moisture depletion 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 Soil moisture depletion 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 Soil moisture depletion 0.0 02 0.0 0.0 0.0 0.0 0.0 0.0 01 0.0 0.0 Available soil moisture emo 97.9 97.7 97.9 97,9 97.9 97.9 97,9 97.9 97.7 97.7 979 97.9 Available soil moisture emo 97.9 97.7 97.9 979 97.9 91,9 97.9 97.9 97.7 97.7 97.9 97,9 Available soil moisture ems, 97.9 97.7 97.9 97.9 97,9 979 97.9 97.9 97.7 97.7 97.9 All runoff 0.0 0.0 0.3 0.5 0.5 0.2 0.0 0.5 0.0 OA 0.2 0.0 2.2 All runoff 0.0 0.0 0.3 0.5 0.5 01 0.0 0.5 0.0 0,0 0.2 0.0 2.2 All runoff 0.0 0.0 0.3 0.5 OS 0.2 0.0 0.5 0.0 0.0 0.2 Soil moisture deficit 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.2 0.0 0.0 Soil moisture deficit 0.0 02 0.0 0.0 0.0 0.0 0.0 0.0 0.2 01 0.0 0.0 Soil moisture deficit 0.0 '02 0.0 0.0 0.0 0.0 0.0 0.0 0.2 02 0.0 Precipitation deficit 0.0 02 0.0 0,0 0,0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 Precipitation deficit 0,0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 02 0.0 0.0 0.0 Precipitation deficit 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 Total moisture deficit 0,0 0,5 0.0 0,0 0.0 0.0 0.0 0.0 0.4 02 0.0 0.0 Total moisture deficit 0.0 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.2 0.0 0.0 Total moisture deficit 0.0 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.2 0,0 Soil parameters; soil depth = 100.0 mm; bulk density = 1.36 g-cm-a; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field Soil parameters: soil depth = 100.0 mm; bulk density = 1.36 gams; per cent field capacity = 0,36; per cent permanent wilting point = 0.17; field Soil parameters: soil depth = 100.0 man; bulk density = 1.36 g"cm-8; per cent field capacity = 0.36; per cent permanent wilting capacity = 49.0 mm; permanent wilting point . 231 mm; available soil moisture = 25.8 mm. capacity = 49.0 mm; permanent wilting point = 23.1 nun; available soil moisture = 25.8 mm. capacity = 49.0 mm; permanent wilting point = 23.1 mm; available soil moisture = 25.8 mm, Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Jan. Feb, Mar. Apr. May June July Aug. Sept. Oct. Nov, Dec. Year Jan. Feb. Mar. Apr. May June July Aug. Sept, Oct. Nov. Mean air temperature 16.0 165 18.5 18.5 19.5 20.0 20.0 20.5 20.5 20.0 18.5 17.0 18.8 Mean air temperature 16.0 16.5 18.5 18.5 195 20.0 20.0 20.5 20.5 20.0 18.5 17.0 18.8 Mean air temperature 16.0 16.5 18.5 18.5 19.5 20.0 20.0 20.5 20,5 20.0 18.5 Mean biotemperature 16,0 16,5 18,5 18.5 19.5 20.0 20.0 20.5 20.5 20.0 18.5 17.0 18,8 Mean biotemperature 16.0 16.5 18.5 18.5 195 20.0 20.0 20.5 20.5 200 18.5 17.0 18.8 Mean biotemperalure 16.0 16.5 18.5 18.5 19.5 20.0 20.0 20.5 20.5 20.0 18.5 Potential evapotranspiration 80.0 752 92.5 89.5 97,5 96.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 Potential evapotranspiration 80.0 75.2 92.5 89.5 97.5 96.8 100.0 102.5 992 100.0 89.5 85.0 1,107.8 Potential evapotranspiration 80.0 75.2 92.5 89.5 97.5 96.8 100.0 102,5 99.2 100.0 89.5 Pot. evap. adj. dry climate 80.0 752 92.5 89.5 97.5 96.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 Pot. evap. adj. dry climate 80.0 75.2 92.5 89.5 97.5 96.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 Pol. evap. adj. dry climate 80.0 75.2 92.5 89.5 97.5 96,8 100.0 102.5 991 100.0 89.5 Precipitation 80.0 75.0 93.0 90.0 98.0 97.0 100.0 103.0 99.0 100.0 900 85.0 1,110.0 Precipitation 80.0 75.0 93.0 90.0 98.0 97.0 100.0 103.0 99.0 100,0 90.0 85.0 1,110.0 Precipitation 80.0 75.0 93.0 90.0 98.0 97.0 100.0 103.0 99.0 100.0 90.0 Actual evapotranspiration 80.0 75.2 92.5 89.5 97,5 96.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 Actual evapotranspiration 80.0 752 92,5 89.5 97,5 96.8 100.0 102.5 99.2 100.0 89.5 85.0 1,107.8 Actual evapotranspiration 80.0 75.2 92.5 89.5 97.5 96.8 100.0 102.5 99.2 100,0 89.5 Water surplus 0,0 0.0 0.5 0.5 0,5 0.2 0.0 0.5 0.0 0.0 0.5 0.0 Water surplus 0.0 0.0 0,5 0.5 0.5 0.2 0.0 0.5 0.0 0.0 0.5 0.0 Water surplus 0.0 0.0 0.5 0.5 0.5 02 0.0 0.5 00 0.0 0,5 Soil moisture recharge 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 02 0.0 Soil moisture recharge 0.0 0.0 01 0.0 0.0 0.0 0.0 0.0 0,0 0.0 0.2 0,0 Soil moisture recharge 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 Soil moisture depletion 0.0 02 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 Soil moisture depletion 0,0 01 0,0 0.0 OA 0.0 0.0 0.0 0.2 0.0 0.0 0.0 Soil moisture depletion 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0,0 0.0 Available soil moisture emo 49.0 48.7 49.0 49,0 49.0 49.0 49.0 49,0 48.7 48.7 49.0 49.0 Available soil moisture emo 49.0 48.7 490 49.0 49.0 49.0 49.0 49.0 48,7 48.7 49.0 49.0 Available soil moisture ens, 49.0 48.7 49.0 49.0 49.0 49.0 49.0 49.0 48.7 48.7 49,0 All runoff 0,0 0.0 0.3 0.5 0.5 0.2 0.0 0.5 0.0 0.0 01 0.0 2.2 All runoff 0.0 0.0 0.3 0.5 0.5 0.2 0.0 0.5 0.0 0.0 0.2 0.0 21 All runoff 0.0 0.0 OJ 0.5 0.5 0.2 0.0 0.5 0.0 0.0 0.2 Sail moisture deficit 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.2 0.0 0.0 Soil moisture deficit 0.0 0.2 0.0 0.0 0.0 0,0 0.0 0.0 01 0.2 0,0 0.0 Soil moisture deficit 0.0 0.2 0.0 0,0 0.0 0.0 0.0 0.0 02 0.2 0.0 Precipitation deficit 0.0 02 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 Precipitation deficit 0.0 0.2 0,0 0.0 0.0 0.0 0.0 0.0 02 0.0 0.0 0.0 Precipitation deficit 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0,0 Total moisture deficit 0.0 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.2 0.0 0.0 Total moisture deficit 0.0 05 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.2 0.0 0.0 Total moisture deficit 0.0 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.2 0.0  Mato Grande Station: 19° 13' 10" N., 70' 58,50" W.; 1,000 m eleva Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g capacity = 146.9 mm; permanent wilting point = 69.4 mm; availab ]an. Feb. Mar. Apr. Mean air temperature 16.0 16.0 18.5 18.5 Mean bimemperature 16.0 16.0 18.5 18.5 Potential evapotranspiration 80.0 73.0 92.5 89.5 Pot. evap. adj. dry climate 80.0 73.0 92.5 89.5 Precipitation 77.0 44.0 102.0 144.0 Actual evapotranspiration 80.0 73.0 92.5 89.5 Water surplus 0.0 0.0 9.5 54.5 Soil moisture recharge 0.0 0.0 9.5 22.5 Soil moisture depletion 3.0 29.0 0.0 0.0 Available soil moisture emo 1439 114.9 124.4 146.9 All runoff 0.0 0.0 0.0 32.0 Soil moisture deficit 3.0 32.0 22.5 0.0 Precipitation deficit 3.0 29.0 0.0 0.0 Total moisture deficit 6.0 60.9 22.5 0.0 per cent permanent wilting point = 0.17; field Sept. Oct. Nov. Dec. Year 20.0 19.5 18.0 16.5 18.6 20.0 19.5 18.0 16.5 18.6 96.8 97.5 87.1 82.5 1,095.7 96.8 97.5 87.1 82.5 1,095.7 232.0 237.0 209.0 128.0 1,873.0 96.8 97.5 87.1 82.5 1,095.7 135.2 139.5 121.9 45.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1469 146.9 146.9 146.9 135.2 139.5 121.9 45.5 777.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 per cent permanent wilting point = 0.17; field Sept. Oct. Nov. Dec. Year 20 19.5 18.0 16.5 18.6 20.0 19.5 18.0 16.5 18.6 96.8 97.5 87.1 82.5 1,095.7 96.8 97.5 87.1 82.5 1,095.7 232( 237.0 209.0 128.0 1,873.0 96.8 97.5 87.1 82.5 1,095.7 1 ]5.2 119.5 121.9 45.5 Mara Grande Station: 19' 13' 10" N, 700 58'50" W.; 1,000 or elevation Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-3; per cent field capacity capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. Jan. Feb. Mar. Apr. May June July Mean air temperature 16.0 16.0 18.5 18.5 19.5 20.0 20.0 Mean biotemperature 16.0 16.0 18.5 18.5 19.5 20.0 20.0 Potential evapotranspiration 80.0 73.0 915 89.5 97.5 96.8 100.0 Pot. evap. adj. dry climate 80.0 73.0 92.5 89.5 97.5 96.8 100.0 Precipitation 77.0 44.0 102.0 144.0 239.0 204.0 123.0 Actual evapotranspiration 80.0 73.0 92.5 89.5 97.5 96.8 100.0 Water surplus 0.0 0.0 9.5 54.5 141.5 107.2 23.0 Soil moisture recharge 0.0 0.0 9.5 22.5 0.0 0.0 0.0 Soil moisture depletion 3.0 29.0 0.0 0.0 0.0 0.0 0.0 Available soil moisture emo 143.9 114.9 124.4 146.9 146.9 146.9 146.9 All runoff 0.0 0.0 0.0 32.0 141.5 107.2 23.0 Soil moisture deficit 3.0 32.0 22.5 0.0 0.0 0.0 0.0 Precipitation deficit 3.0 29.0 0.0 0.0 0.0 0.0 0.0 Total moisture deficit 6.0 60.9 22.5 0.0 0.0 0.0 0.0 Mata Grande Station: 19. 13' 10" N., 70° 58'50" W.; 1,000 in elevation r = 0.36; per cent permanent wilting point = 0.17; field Soil parameters: soil depth = 300.0 mm; bulk density = 1.36 g"cm-a; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 146.9 mm; permanent wilting point = 69.4 mm; available soil moisture = 77.5 mm. Aug. Sept. Oct. Nov. Dec. Year Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year 20.5 20.0 19.5 18.0 16.5 18.6 Mean air temperature 16.0 16.0 18.5 18.5 19.5 20.0 20.0 20.5 20.0 19.5 18.0 16.5 18.6 20.5 20.0 19.5 18.0 16.5 18.6 Mean biotemperature 16.0 16.0 18.5 18.5 19.5 20.0 20.0 20.5 20.0 19.5 18.0 16.5 18.6 102.5 96.8 97.5 87.1 82.5 1,095.7 Potential evapotranspiration 80.0 73.0 92.5 89.5 97.5 96.8 100.0 102.5 96.8 97.5 87.1 82.5 1,095.7 102.5 96.8 97.5 87.1 82.5 1,095.7 Pot. evap. adj. dry climate 80.0 73.0 92.5 89.5 97.5 96.8 100.0 102.5 96.8 97.5 87.1 82.5 1,095.7 134.0 232.0 237.0 209.0 128.0 1,873.0 Precipitation 77.0 44.0 102.0 144.0 239.0 204.0 123.0 134.0 232.0 237.0 209.0 128.0 1,873.0 102.5 96.8 97.5 87.1 82.5 1,095.7 Actual evapotranspiration 80.0 73.0 92.5 89.5 97.5 96.8 100.0 102.5 96.8 97.5 87.1 82.5 1,095.7 31.5 135.2 139.5 121.9 45.5 Water surplus 0.0 0.0 9.5 54.5 141.5 107.2 23.0 31.5 135.2 139.5 121.9 45.5 0.0 0.0 0.0 0.0 0.0 Soil moisture recharge 0.0 0.0 9.5 22.5 0.0 0.0 0.0 0.0 0.0 0.0 0,0 0.0 0.0 0.0 0.0 0.0 0.0 Soil moisture depletion 3.0 29.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 146.9 146.9 146.9 146.9 146.9 Available soil moisture emo 143.9 114.9 124.4 146.9 146.9 146.9 146.9 146.9 146.9 146.9 146.9 146.9 31.5 135.2 139.5 121.9 45.5 777.3 All runoff 0.0 0.0 0.0 32.0 141.5 107.2 23.0 31.5 135.2 139.5 121.9 45.5 7773 0.0 0.0 0.0 0.0 0.0 Soil moisture deficit 3.0 32.0 22.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Precipitation deficit 3.0 29.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Total moisture deficit 6.0 60.9 22.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Soil parameters: soil depth = 200.0 mm; bulk density capacity = 97.9 mm; permanent wilting point = 46.2 mn )an. Feb. Mar. Mean air temperature 16.0 16.0 18.5 Mean biolemperature 16.0 16.0 18.5 Potential evapotranspiration 80.0 73.0 92.5 Pot. evap. adj. dry climate 80.0 73.0 92.5 Prreipiialiun 77.0 44.0 102.0 Actnal evapotranspiration R0.0 73.0 92.5 Water surpins OA no 9.5 c = 1.36 g"cm-t; per cent field capacity = 0.36; 1 m; available soil moisture = 51.7 mm. Apr. May luac July Aug. 18.5 19.5 20.0 20.0 20.5 t 8.5 19.5 20.0 20.0 20.5 89.5 97.4 96.g 100.0 102.5 89.5 97.5 96.8 WOO 1112.5 144.0 239.0 204.0 123.0 134.0 89.5 97.5 96,8 100.0 102.5 54.5 141.5 107.2 23.0 31.5 Soil parameters: soil depth = 200.0 mm; bulk density = 1.36 g"em-a; per cent field capacity = 0.36; per cent permanent wilting point = 0.17; field capacity = 97.9 mm; permanent wilting point = 46.2 mm; available soil moisture = 51.7 mm. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Year Mean air temperature 16.0 16.0 18.5 18.5 19.5 20.0 20.0 20.5 20.0 19.5 18.0 16.5 18.6 Mean biotemperature 16.0 16.0 18.5 18.5 19.5 20.0 20.0 20.5 20.0 ]9.5 18.0 16.5 18.6 Potential evapob.ansPiration 80.0 73.0 92.5 89.5 97.5 96.8 100.0 102.5 96.8 97.5 87.1 82.5 1,095.7 Pol. evap. A. dry donate 80.0 71,0 92.5 89.5 97.5 96.8 100.0 102.5 96.8 97.5 87.1 82.5 1,095.7 Precipitation 77.0 44.0 102.0 144.0 219.0 204.0 123.0 134.0 2:12.0 237.0 209.0 128.0 1,873.0 Aetna[ evapotranspiration 80.0 73.0 92.5 89.5 97,5 96.8 100.0 102.5 96.8 97.5 87.1 82.5 1,095.7 Water vurplus D.0 0.0 9.5 54.5 141.5 107.2 23.0 3 1.5 1J.5.2 139.5 121.9 45.5 Soil parameters: soil depth = 200.0 mm; bi capacity = 97.9 mm; permanent wilting point Jan. I'eb. Mean air temperature 16.0 16.0 Mean biotamperatnre 16.0 16.0 Potential evapotranspiration 80.0 73.0 Pot. -p. adj, dry climate 80.0 73.0 Precipitation 77.0 44.0 Actual -po0an