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Assessing impacts on coupled food-water systems that may emerge from water policies, changes in economic drivers and crop productivity requires an understanding of dominant uncertainties. This paper assesses how a candidate groundwater pumping restriction and crop prices, crop yields, surface water price, electricity price, and parametric uncertainties shape economic and groundwater performance metrics from a coupled hydro-economic model (HEM) through a diagnostic global sensitivity analysis (GSA). The HEM used in this study integrates a groundwater depth response, modeled by an Artificial Neural Network (ANN), into a calibrated Positive Mathematical Programming (PMP) agricultural production model. Results show that in addition to a groundwater pumping restriction, performance metrics are highly sensitive to prices and yields of perennial tree crops. These sensitivities become salient during dry years when there is a higher reliance on groundwater. Furthermore, results indicate that performing a GSA for two different water baseline conditions used to calibrate the production model, dry and wet, result in different sensitivity indices magnitudes and factor prioritization. Diagnostic GSA results are used to understand key factors that affect the performance of a groundwater pumping restriction policy. This research is applied to the Wheeler Ridge-Maricopa Water Storage District located in Kern County, California, region reliant on groundwater and vulnerable to surface water shortages.

Irrigated agriculture in snow-dependent regions contributes significantly to global food production. This study quantifies the impacts of climate change on irrigated agriculture in the snow-dependent Yakima River Basin (YRB) in the Pacific Northwest United States. Here we show that increasingly severe droughts and temperature driven reductions in growing season significantly reduces expected annual agricultural productivity. The overall reduction in mean annual productivity also dampens interannual yield variability, limiting yield-driven revenue fluctuations. Our findings show that farmers who adapt to climate change by planting improved crop varieties may potentially increase their expected mean annaul productivity in an altered climate, but remain strongly vulnerable to irrigation water shortages that substantially increase interannual yield variability (i.e., increasing revenue volatility). Our results underscore the importance for crop adaptation strategies to simultaneously capture the biophysical effects of warming as well as the institutional controls on water availability.