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Modeling Water Resources Management at the Basin Level Methodology and Application to the Maipo River Basin

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Modeling Water Resources Management at the Basin Level Methodology and Application to the Maipo River Basin Modeling Water Resources Management at the Basin Level Methodology and Application to the Maipo River Basin Ximing Cai Claudia Ringler Mark W. Rosegrant RESEARCH REPORT 149 INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE WASHINGTON, D.C. Copyright © 2006 International Food Policy Research Institute. All rights reserved. Sections of this material may be reproduced for personal and not-for-profit use without the express written permission of but with acknowledgment to IFPRI. To reproduce the material contained herein for profit or commercial use requires express written permission. To obtain permission, contact the Communications Division <[email protected]>. International Food Policy Research Institute 2033 K Street, N.W. Washington, D.C. 20006–1002 U.S.A. Telephone +1–202–862–5600 www.ifpri.org DOI: 10.2499/0896291529RR149 An earlier version of Chapter 7 by X. Cai, M. W. Rosegrant, and C. Ringler appeared as “Physical and economic efficiency of water use in the river basin: Implications for water management” in Water Resources Research (2003, Vol. 39, Issue 1, pp. 1–13). Copyright 2003 American Geophysical Union. An earlier version of Chapter 8, by X. Cai and M. W. Rosegrant appeared as “Irrigation technology choices under hydrologic uncertainty: A case study from Maipo River Basin, Chile” in Water Resources Research (2004, Vol. 40, Issue 4, pp. 1–10). Copyright 2004 American Geophysical Union. The current modified versions appear with the permission of the American Geophysical Union. Library of Congress Cataloging-in-Publication Data Cai, Ximing, 1966– Modeling water resources management at the basin level : methodology and appli- cation to the Maipo River Basin / Ximing Cai, Claudia Ringler, Mark Rosegrant. p. cm. — (Research report ; 149) Includes bibliographical references. ISBN 0-89629-152-9 1. Water resources development—Chile—Maipo River Watershed—Econometric models. 2. Watershed management—Chile—Maipo River Watershed—Econometric models. 3. Maipo River Watershed (Chile). I. Ringler, Claudia. II. Rosegrant, Mark W. III. Title. IV. Series: Research report (International Food Policy Research Institute) ; 149. HD1696.C5C34 2006 333.91′62098331—dc22 2006010577 Contents List of Tables iv List of Figures vii List of Boxes xi Foreword xii Acknowledgments xiii Summary xiv 1. Introduction 1 2. The Chilean Context and the Study Basin 4 3. Modeling Framework 19 4. Model Implementation and Solution 38 5. Basin-Optimizing Solution and Sensitivity Analyses 46 6. Water Trade Analysis 59 7. Water Use Efficiency Analysis 64 8. Irrigation Technology Choice under Uncertainty 82 9. Analysis of Water versus Other Inputs in an Integrated Economic–Hydrologic Modeling Framework 94 10. Conclusions and Recommendations 112 Appendix A: Model Formulation 118 Appendix B: Input Parameters and Model Output 129 Appendix C: Average Crop-Level Shadow Prices versus Demand-Site Level Shadow Values 146 References 147 iii Tables 2.1 Irrigated area by crop, Chile, mid-1990s 6 2.2 Water demand at the offtake level by hydrologic unit, Maipo River Basin, mid-1990s 11 2.3 Irrigation districts in the Maipo/Mapocho Basin 12 2.4 Municipal surface water withdrawals by hydrologic unit, Maipo River Basin 13 2.5 Average water tariffs, April 1997 13 2.6 Hydropower stations, Maipo River Basin 14 2.7 Main water rights holders, first section, Mapocho River, September 1999 18 3.1 Optimal water application at given levels of other inputs in A1 31 3.2 Coefficients of the shadow price–water regression function for different demand sites 35 4.1 Comparison of the performance of objective formulations, water application in crop growth stages, example of wheat 41 4.2 Model statistics at different steps 44 5.1 Harvested area under the Basin-optimizing solution 47 5.2 Harvested area from Basin-optimizing solution as a ratio of actual harvested area 47 5.3 Crop yield under Basin-optimizing solution scenario as a ratio of maximum crop yield 48 5.4 Crop production under the Basin-optimizing solution scenario (BOS) and comparison of basinwide production under BOS with actual crop production 48 5.5 Ratio of crop water applied to maximum evapotranspiration at each crop growth stage, demand site A1 51 5.6 Irrigation (field application) efficiency, by crop and demand site 52 5.7 Water withdrawals, by crop and demand site 52 5.8 Profit per unit of water withdrawal, by crop and demand site 53 5.9 Profit, by crop and demand site 53 5.10 Return flows from agriculture, by period and demand site 54 5.11 Salt concentration in mixed irrigation sources 54 iv TABLES v 5.12 Salt concentration in deep percolation, by crop and demand site 55 5.13 Sensitivity analysis, various parameters 56 5.14 Sensitivity analysis for agricultural water price at 50 percent of normal inflow 57 6.1 Scenario analysis under the Basin-optimizing solution, Fixed water rights, and Water rights with trading scenarios 60 6.2 Transaction cost scenarios (Case A) 60 6.3 Harvested irrigated area with normal inflows under Basin-optimizing solution, Fixed water rights, and Water rights with trading scenarios 62 6.4 Irrigation technology under Basin-optimizing solution, Fixed water rights, and Water rights with trading scenarios, dry and normal years 63 7.1 Change in field application efficiency for various crops (under 60 percent of normal inflow) under the Basin-optimizing solution, Fixed water rights, and Water rights with trading scenarios 69 7.2 Aggregated field application efficiency by demand sites, at 100 percent of normal inflow (normal year) and 60 percent of normal inflow (dry year) under the Basin-optimizing solution, Fixed water rights, and Water rights with trading scenarios 69 7.3 Water withdrawals at 60 percent of normal inflow under the Basin- optimizing solution, Fixed water rights, and Water rights with trading scenarios 70 7.4 Economic crop value per unit of water use at 60 percent of normal inflows under the Basin-optimizing solution, Fixed water rights, and Water rights with trading scenarios 71 7.5a Basin-level aggregation at 60 percent of normal inflows under the Basin- optimizing solution, Field irrigation technology, Fixed water rights, and Water rights with trading scenarios, selected results 72 7.5b Irrigation demand sites at 60 percent of normal inflows under the Basin- optimizing solution, Field irrigation technology, Fixed water rights, and Water rights with trading scenarios, selected results 72 7.6 Comparison of wheat and grape production at the basin level under the Basin-optimizing solution and Fixed water rights scenarios, selected results 73 9.1 Opportunity cost of water, by crop and demand site 99 9.2 Opportunity cost of crop land, by crop and demand site 99 9.3 Calibrated water loss coefficients, by demand site and period 100 9.4 Agricultural inputs and net profit, by irrigation demand site, under the Baseline scenario 104 9.5a Changes in agricultural inputs and net profits, by irrigation demand site under the Full optimization scenario compared with the Baseline scenario 105 vi TABLES 9.5b Percentage change in agricultural inputs and net profits, by irrigation demand site, under the Full optimization scenario compared with the Baseline scenario 105 9.6a Changes in agricultural inputs and net profits, by irrigation demand site, under the Substitution among water and other inputs scenario compared with the Baseline scenario 106 9.6b Percentage change in agricultural inputs and net profits, by irrigation demand site, under the Substitution among water and other inputs scenario compared with the Baseline scenario 107 9.7 Net profit of water, share of low-value crops, and inferred shadow prices of water, by irrigation demand site 107 B.1 Input parameters for the simulation program 130 B.2 Area of irrigation demand sites 131 B.3 Total water supply for municipal and industrial demand sites 131 B.4 Crop parameters by crop category 131 B.5 Potential crop evapotranspiration, demand site A1 132 B.6 Effective rainfall, demand site A1 133 B.7 Within-season yield response coefficients, Ky 134 B.8 Production function coefficients: Regression coefficients based on outputs from the simulation model 135 B.9 Agricutural inputs: Average values from the field survey 136 B.10a Production function coefficients from the generalized maximum entropy program: Linear coefficients 139 B.10b Production function coefficients from the generalized maximum entropy program (b): Nonlinear intersectoral coefficients 140 B.11 Data for hydropower stations 142 B.12 Fluviometric stations in the Maipo River Basin 143 B.13 Inflow to rivers and tributaries in a normal year 144 B.14 Parameters for groundwater sources 145 Figures 2.1 Location of the Maipo River Basin in Chile 8 2.2 Geographic and administrative features of the Maipo River Basin 9 2.3 Average monthly rainfall and variation coefficient, Santiago, Chile, 1950–98 9 3.1 The Maipo River Basin network 21 3.2 Conceptual framework of a basin model—Hydrologic processes and water uses 22 3.3 Hydrologic processes considered in the crop field 22 3.4 The relationship between municipal and industrial sites and the hydrologic components 23 3.5 Production function, crop (wheat) yield versus water application (indicator of irrigation technology, Christiansen Uniformity Coefficient, CUC = 70, salinity = 0.7 grams per liter) 24 3.6 Yield-salinity relationship, the example of wheat 25 3.7 Yield versus crop water use under different levels of irrigation technology (Christiansen Uniformity Coefficient [CUC]), example of wheat 25 3.8a Relationship between optimal water application and
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