Innovative groundwater management strategies are essential to preserve aquifers for crop irrigation. In western Kansas, USA, irrigators self-organized to extend the aquifer’s lifespan by self-imposing groundwater pumping limits enforced over a five-year period. While the five-year groundwater allocation period granted irrigators additional flexibility, it adds a new temporal dimension to their decision-making beyond the typical annual/sub-annual cropping and irrigation decisions. Pumping restrictions, along with uncertain precipitation, complicate multi-year farm planning. We formulated a two-stage stochastic modeling framework to design optimal annual cropping and irrigation allocations under pumping restrictions and uncertain precipitation. Optimal cropping and allocation strategies by the stochastic optimization model significantly outperform observed farmer strategies during the first two five-year LEMA periods (2013-2022) but only outperformed the optimal strategy by the deterministic optimization model assuming long-term average precipitation during drier conditions. We show that optimal cropping decisions shift from predominately corn to sorghum if more stringent pumping restrictions are imposed. Furthermore, irrigators are better off to use less water in the earlier years and saving more water for later years under more stringent five-year pumping restrictions, while they should use more of their allocation earlier under less stringent pumping limits. Extending the duration of the groundwater allocation window allows additional operational flexibility and enhances profits but the marginal gains for each additional year drop off after around seven years. Our versatile modeling framework is applicable to other regions considering groundwater pumping restrictions with the aim of balancing water conservation with farmer profitability and adaptability.

Irrigated agriculture depends on surface water and groundwater, but we do not have a clear picture of how much water is consumed from these sources by different crops across the US over time. Current estimates of crop water requirements are insufficient in providing the spatial granularity and temporal depth required for comprehensive long-term analysis. To fill this data gap, we utilized crop growth models to quantify the monthly crop water consumption - distinguishing between rainwater, surface water, and groundwater - of the 30 most widely irrigated crops in the US from 1981 to 2019 at 2.5 arc minutes. These 30 crops represent approximately 95% of US irrigated cropland. We found that the average annual total crop water consumption for these 30 irrigated crops in the US was 154.2 km3, 70% of which was from irrigation. Corn and alfalfa accounted for approximately 16.7 km3 and 24.8 km3 of average annual blue crop water consumption, respectively, which is nearly two-fifths of the blue crop water consumed in the US. Surface water consumption decreased by 41.2%, while groundwater consumption increased by 6.8%, resulting in a 17.3% decline in blue water consumption between 1981 and 2019. We find good agreement between our results and existing modeled evapotranspiration (ET) products, remotely sensed ET estimates (OpenET), and water use data from the US Geological Survey and US Department of Agriculture. Our dataset and model can help assess the impact of irrigation practices and water scarcity on crop production and sustainability.