<p>Groundwater is a major source for irrigated agriculture yet often managed unsustainably. Groundater overdraft compromises future viability of irrigated agriculture, water for cities, streams baseflows and groundwater dependent ecosystems. The recent 2012-2016 California drought heightened the role of groundwater as a buffer resource and catalyzed the 2014 Sustainable Groundwater Management Act (SGMA). Under this regulation, by 2040 all groundwater basins need to achieve balance in recharge and extractions. Groundwater overdraft in California&#8217;s Central Valley accounts for roughly 15 percent of the total agricultural use. The greater Kern region within California&#8217;s Central Valley, the most productive region for fruits, nuts and vegetables in the USA, suffers from chronic overdraft and demand hardening due to a rapid increase in perennial crops. This paper presents an integrated multi-objective framework to analyze agricultural production in the greater Kern region as it achieves groundwater sustainability at the irrigation district level by 2040. The model employs a programing model approach with a selection of open access components to predict cropping decisions that maximize net economic returns, using a 1997-2015 calibration period. The agricultural production model bundles with a groundwater module based on the Integrated Water Model Flow model (IWFM) from the California Department of Water Resources to meet sustainability objectives. &#160;Modeling scenarios include SGMA groundwater restrictions, water shortages under climate change and environmental regulations, with and without markets, managed aquifer recharge and infrastructure enhancements. Results show that more flexible water allocations using markets and managed recharge can help mitigate the economic impacts from SGMA and also improve prospects for managing financial risk under economic uncertainty at the irrigation district level.</p>
The modeling of coupled food-water systems to represent the effect of water supply variability as well as shocks that may emerge from changes in policies, economic drivers, and productivity requires an understanding of dominant uncertainties. These uncertainties cascade into forecasts of impacts of water management policies, such as groundwater pumping restrictions. This paper assesses how parametric, crop price, crop yields, surface water price, and electricity price uncertainties shape hydro-economic model estimates for agricultural production through a diagnostic global sensitivity analysis (GSA).The diagnostic GSA explores how the uncertainties in combination with a candidate groundwater pumping restriction influence three metrics of concern: total economic revenue, total land use and groundwater depth change. The hydro-economic model integrates a Groundwater Response Function (GRF) by integrating an Artificial Neural Network (ANN) into a calibrated Positive Mathematical Programming (PMP) production model for the Wheeler Ridge-Maricopa Water Storage District located in Kern County, California. Our results show that in addition to groundwater pumping restriction, performance metrics of the system are highly sensitive to prices and yields particularly of profitable crops. These sensitivities become salient during dry years when there is a higher reliance on groundwater.
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