19 research outputs found

    Satellite‐Based Monitoring of Irrigation Water Use: Assessing Measurement Errors and Their Implications for Agricultural Water Management Policy

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    Reliable accounting of agricultural water use is critical for sustainable water management. However, the majority of agricultural water use is not monitored, with limited metering of irrigation despite increasing pressure on both groundwater and surface water resources in many agricultural regions worldwide. Satellite remote sensing has been proposed as a low-cost and scalable solution to fill widespread gaps in monitoring of irrigation water use in both developed and developing countries, bypassing the technical, socioeconomic, and political challenges that to date have constrained in situ metering. In this paper, we show through a systematic meta-analysis that the relative accuracy of different satellite-based irrigation water use monitoring approaches remains poorly understood, with evidence of large uncertainties when water use estimates are validated against in situ irrigation data at both field and regional scales. Subsequently, we demonstrate that water use measurement errors result in large economic welfare losses for farmers and may negatively impact ability of policies to limit acute and nonlinear externalities of irrigation abstraction on both the environment and other water users. Our findings highlight that water resource planners must consider the trade-offs between accuracy and costs associated with different water use accounting approaches. Remote sensing has an important role to play in supporting improved agricultural water accounting—both independently and in combination with in situ monitoring. However, greater transparency and evidence is needed about underlying uncertainties in satellite-based models, along with how these measurement errors affect the performance of associated policies to manage different short- and long-term externalities of irrigation water use

    Estimating the economic value of interannual reservoir storage in water resource systems

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    Reservoir operators face pressures on timing releases of water. Releasing too much water immediately can threaten future supplies and costs, but not releasing enough creates immediate economic hardship downstream. This paper examines how the economic valuation of end‐of‐year carryover storage can lead to optimal amounts of carryover storage in complex large water resource systems. Economic carryover storage value functions (COSVFs) are developed to represent the value of storage in the face of interannual inflow uncertainty and variability within water resource optimization models. The approach divides a perfect foresight optimization problem into year‐long (limited foresight) subproblems solved sequentially by a within‐year optimization engine to find optimal short‐term operations. The final storage state from the previous year provides the initial condition to each annual problem, and end‐of‐year COSVFs are the final condition. Here the COSVF parameters that maximize the interannual benefits from river basin operations are found by evolutionary search. This generalized approach can handle nonconvexity in large‐scale water resources systems. The approach is illustrated with a regional model of the California Central Valley water system including 30 reservoirs, 22 aquifers, and 51 urban and agricultural demand sites. Head‐dependent pumping costs make the optimization problem nonconvex. Optimized interannual reservoir operation improves over more cautious operation in the historical approximation, reducing the average annual scarcity volume and costs by 80% and 98%, respectively, with more realistic representation of hydrologic foresight for California's Mediterranean climate. The economic valuation of storage helps inform water storage decisions
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