Estimating economic value of agricultural water under changing conditions and the effects of spatial aggregation

摘要: Given the high proportion of water used for agriculture in certain regions, economic value agricultural can be an important tool management and policy development. This is quantified using demand curves irrigation water. Such functions show incremental contribution to production. Water are estimated econometric or optimisation techniques. Calibrated models allow derivation smaller datasets than models. paper introduces these subject areas then explores effect spatial aggregation (upscaling) on valuation irrigated agriculture. A case study from Rio Grande-Rio Bravo Basin North Mexico investigates differences at farm regional aggregated levels under four scenarios: technological change, warm-dry climate changes commodity prices, costs The scenarios consider due external shocks new policies. Positive mathematical programming (PMP), a calibrated method, deductive method used. An exponential cost function compared quadratic typically PMP. Results indicate that level regionally similar, but variability distributional effects each scenario affected by aggregation. Moderately production effective capturing average-farm adaptation shocks. Farm-level best reveal distribution impacts.