University of California, Davis, Department of Civil and Environmental Engineering, One Shields Ave., Davis, CA 95616, USA.
Sci Total Environ. 2010 Nov 1;408(23):5639-48. doi: 10.1016/j.scitotenv.2009.08.013. Epub 2009 Sep 4.
Given the high proportion of water used for agriculture in certain regions, the economic value of agricultural water can be an important tool for water management and policy development. This value is quantified using economic demand curves for irrigation water. Such demand functions show the incremental contribution of water to agricultural production. Water demand curves are estimated using econometric or optimisation techniques. Calibrated agricultural optimisation models allow the derivation of demand curves using smaller datasets than econometric models. This paper introduces these subject areas then explores the effect of spatial aggregation (upscaling) on the valuation of water for irrigated agriculture. A case study from the Rio Grande-Rio Bravo Basin in North Mexico investigates differences in valuation at farm and regional aggregated levels under four scenarios: technological change, warm-dry climate change, changes in agricultural commodity prices, and water costs for agriculture. The scenarios consider changes due to external shocks or new policies. Positive mathematical programming (PMP), a calibrated optimisation method, is the deductive valuation method used. An exponential cost function is compared to the quadratic cost functions typically used in PMP. Results indicate that the economic value of water at the farm level and the regionally aggregated level are similar, but that the variability and distributional effects of each scenario are affected by aggregation. Moderately aggregated agricultural production models are effective at capturing average-farm adaptation to policy changes and external shocks. Farm-level models best reveal the distribution of scenario impacts.
鉴于某些地区农业用水量占比很高，农业水的经济价值可以成为水资源管理和政策制定的重要工具。这一价值可通过灌溉用水的经济需求曲线来量化。此类需求函数展示了水对农业生产的增量贡献。可通过计量经济学或优化技术来估算水需求曲线。经过校准的农业优化模型可利用比计量经济学模型更小的数据集来推导出需求曲线。本文首先介绍这些主题领域，然后探讨空间聚合（上推）对灌溉农业用水估值的影响。本文以墨西哥北里奥格兰德-里奥布拉沃流域为例，在四种情景下（技术变革、暖干气候变化、农产品价格变化以及农业用水成本），在农场和区域聚合层面上考察了水估值的差异：情景一为技术变革，情景二为暖干气候变化，情景三为农产品价格变化，情景四为农业用水成本变化。这些情景考虑了外部冲击或新政策带来的变化。本文采用的是演绎估值法——正数学规划（Positive Mathematical Programming，PMP），并将指数成本函数与 PMP 中常用的二次成本函数进行了比较。结果表明，农场层面和区域聚合层面的水经济价值较为相似，但聚合会影响每个情景的变异性和分布效应。适度聚合的农业生产模型可有效捕捉到农场对政策变化和外部冲击的平均适应能力。农场层面的模型能最好地揭示各情景影响的分布情况。
