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Abstract This study investigates residential indoor water consumption variability across 39 US cities using data from 26,441 single‐family smart water meters. Employing functional data analysis and mixed‐effects random forest, we identified distinct usage patterns across city clusters, with 13 high and 6 low water‐using cities (all in coastal California) differing significantly from 20 medium water‐using cities. Shower and toilet use were primary drivers of indoor use differences between clusters, influenced by both behavioral and fixture efficiency factors. The presence of appliances, certain household features, and weather also affect indoor water use, with varying influence on indoor water use across clusters. Our findings highlight the effectiveness of state‐level water efficiency interventions and emphasize the importance of considering both behavioral factors and appliance efficiency in conservation strategies, providing valuable insights for targeted water demand management in urban areas. 

Irrigation reduces crop vulnerability to drought and heat stress and thus is a promising climate change adaptation strategy. However, irrigation also produces greenhouse gas emissions through pump energy use. To assess potential conflicts between adaptive irrigation expansion and agricultural emissions mitigation efforts, we calculated county-level emissions from irrigation energy use in the US using fuel expenditures, prices, and emissions factors. Irrigation pump energy use produced 12.6 million metric tonnes CO2-e in the US in 2018 (90% CI: 10.4, 15.0), predominantly attributable to groundwater pumping. Groundwater reliance, irrigated area extent, water demand, fuel choice, and electrical grid emissions intensity drove spatial heterogeneity in emissions. Due to heavy reliance on electrical pumps, projected reductions in electrical grid emissions intensity are estimated to reduce pumping emissions by 46% by 2050, with further reductions possible through pump electrification. Quantification of irrigation-related emissions will enable targeted emissions reduction efforts and climate-smart irrigation expansion. 

Innovative groundwater management strategies are needed to preserve aquifers for crop irrigation. For sustainability to be lasting, any strategy must balance environmental goals with the economic aims of farmers. These tradeoffs are difficult to manage due to the inherent uncertainty in farming. To address these challenges, we develop a transferable two‐stage stochastic modeling framework to support optimal multi‐year crop and irrigation planning under groundwater pumping restrictions and uncertain precipitation. This modular framework is broadly applicable to regions facing groundwater overuse, helping to balance aquifer sustainability and farmer profitability under uncertainty. We illustrate the model using a case study from western Kansas, USA, where irrigators self‐imposed 5‐year groundwater pumping limits to extend the aquifer's lifespan. While these multi‐year allocation periods offer flexibility, they introduce a temporal dimension to decision‐making beyond typical annual planning. Optimal cropping and irrigation strategies from the stochastic model significantly outperform observed farmer behavior during the first two 5‐year allocation periods (2013–2022), and outperform a deterministic model assuming long‐term average precipitation during dry conditions. We show that optimal crop choices shift from corn to sorghum under more stringent pumping restrictions. Under these constraints, irrigators benefit by conserving water in earlier years and using more in later years, whereas the reverse holds under more lenient restrictions. Extending the allocation window further enhances profitability, though marginal gains diminish beyond 7 years. This modeling framework offers insights for agricultural regions seeking to improve long‐term groundwater management through strategies that support both economic resilience and hydrologic sustainability. 

Abstract Groundwater wells are critical infrastructure that enable the monitoring, extraction, and use of groundwater, which has important implications for the environment, water security, and economic development. Despite the importance of wells, a unified database collecting and standardizing information on the characteristics and locations of these wells across the United States has been lacking. To bridge this gap, we have created a comprehensive database of groundwater well records collected from state and federal agencies, which we call the United States Groundwater Well Database (USGWD). Presented in both tabular form and as vector points, USGWD comprises over 14.2 million well records with attributes, such as well purpose, location, depth, and capacity, for wells constructed as far back as 1763 to 2023. Rigorous cross-verification steps have been applied to ensure the accuracy of the data. The USGWD stands as a valuable tool for improving our understanding of how groundwater is accessed and managed across various regions and sectors within the United States.