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Abstract We provide a dataset of irrigation water withdrawals by crop, county, year, and water source within the United States. We employ a framework we previously developed to establish a companion dataset to our original estimates. The main difference is that we now use the U.S. Geological Survey (USGS) variable ‘irrigation — total’ to partition PCR-GLOBWB 2 hydrology model estimates, instead of ‘irrigation — crop’ as used in previous estimates. Our findings for Surface Water Withdrawals (SWW), total Groundwater Withdrawals (GWW), and nonrenewable Groundwater Depletion (GWD) are similar to those of prior estimates but now have better spatial coverage, since several states are missing from the USGS ‘irrigation — crop’ variable that was originally used. Irrigation water use increases in this study, since more states are included and ‘irrigation — total’ includes more categories of irrigation than ‘irrigation — crop’. Notably, irrigation in the Mississippi Embayment Aquifer is now captured for rice and soy. We provide nearly 2.5 million data points with this paper (3,142 counties; 13 years; 3 water sources; and 20 crops). 

Abstract Civil infrastructure underpins urban receipts of food, energy, and water (FEW) produced in distant watersheds. In this study, we map flows of FEW goods from watersheds of the contiguous United States to major population centers and highlight the critical infrastructure that supports FEW flows. To do this, we draw upon detailed records of agriculture, electricity, and public water supply production and couple them with commodity flow and infrastructure information. We also compare the flows of virtual water embedded in food and energy commodity flows with physical water flows in inter‐basin water transfer projects around the country. We found that the virtual blue water transfers through crops and electricity to major US cities was 53 billion and 8 billion m³in 2017, respectively, while physical interbasin water transfers for crops, electricity, and public supply water averaged 20.8 billion m³. Highways are the primary infrastructure used to import virtual water associated with food and fuel into cities, although waterways and railways are most utilized for long‐distance transport. All of the 204 watersheds in the contiguous US support the food, energy, and/or water supplies of major US cities, with dependencies stretching far beyond each city's borders. Still, most cities source the majority of their FEW and embedded water resources from nearby watersheds. Infrastructure such as water supply dams and inland ports serve as important buffers for both local and supply‐chain sourced water stress. These findings can inform efforts to reduce water resources and infrastructure risks in domestic supply chains. 

Abstract The production of food, electricity, and treated water is often tracked and managed along political or infrastructure boundaries. Yet, water resources, a critical input in the production of these goods, are delineated along natural landscape features (i.e., watersheds). The boundary mismatch between water resources and the associated production of economic goods conceals hydrologic dependencies and vulnerabilities in the provisioning of Food‐Energy‐Water (FEW) resources. In this study, we pair economic, infrastructure, and hydrologic data to evaluate the production of food, electricity, and treated water within watersheds of the conterminous United States. The US FEW sectors produced 950 million tonnes of crops, 3,973 million MWh of electricity, and supplied water to 263 million people in 2017. FEW production consumed 128 km³of blue water (18%) and 583 km³of green water (82%). Watersheds in central and southern California, the Midwest, and the Southwest have the largest FEW blue water consumption and the greatest exposure to water stress. Nearly three‐fifths of FEW production occurs in regularly water‐stressed watersheds. FEW production in watersheds in the Great Plains and Midwest relies heavily on groundwater to buffer against intra‐ and inter‐annual streamflow variability, while surface reservoir storage buffers against water shortages in all watersheds. We show where FEW production may be susceptible to curtailments due to ongoing groundwater depletion or known infrastructure deficiencies. This study adds to our understanding of how a nation's water resources and associated infrastructure support economic activity, as well as areas where economic activity is exposed to hydrological and infrastructure risks. 

Abstract Agriculture is the largest user of water in the United States. Yet, we do not understand the spatially resolved sources of irrigation water use (IWU) by crop. The goal of this study is to estimate crop‐specific IWU from surface water withdrawals (SWW), total groundwater withdrawals (GWW), and nonrenewable groundwater depletion (GWD). To do this, we employ the PCR‐GLOBWB 2 global hydrology model to partition irrigation information from the U.S. Geological Survey Water Use Database to specific crops across the Continental United States (CONUS). We incorporate high‐resolution input data on agricultural production and climate within the CONUS to obtain crop‐specific irrigation estimates for SWW, GWW, and GWD for 20 crops and crop groups from 2008 to 2020 at county spatial resolution. Over the study period, SWW decreased by 20%, while both GWW and GWD increased by 3%. On average, animal feed (alfalfa/hay) uses the most irrigation water across all water sources: 33 from SWW, 13 from GWW, and 10 km³/yr from GWD. Produce used less SWW (43%), but more GWW (57%), and GWD (27%) over the study time‐period. The largest changes in IWU for each water source between the years 2008 and 2020 are: rice (SWW decreased by 71%), sugar beets (GWW increased by 232%), and rapeseed (GWD increased by 405%). These results present the first national‐scale assessment of irrigation by crop, water source, and year. In total, we contribute nearly 2.5 million data points to the literature (3,142 counties; 13 years; 3 water sources; and 20 crops). 

Abstract Food supply chains are essential for distributing goods from production to consumption points. These complex supply chains are important for food security and availability. Recent research has developed novel methods to estimate food flows with high spatial resolution, but we do not currently understand how fine-grained food supply chains vary in time. In this study, we use an improved version of the Food Flow Model to estimate food flows (kg) between all county pairs across all food commodity groups for the years 2007, 2012, and 2017 (which requires estimating 206.3 million links). We then determine the core counties to the US food flow networks through time with a multi-criteria decision analysis technique. Our estimates of county-to-county food flows in time are freely available with this paper and could be useful for future research, policy, and decision-making. 

Abstract Food consumption and production are separated in space through flows of food along complex supply chains. These food supply chains are critical to our food security, making it important to evaluate them. However, detailed spatial information on food flows within countries is rare. The goal of this paper is to estimate food flows between all county pairs within the United States. To do this, we develop the Food Flow Model, a data-driven methodology to estimate spatially explicit food flows. The Food Flow Model integrates machine learning, network properties, production and consumption statistics, mass balance constraints, and linear programming. Specifically, we downscale empirical information on food flows between 132 Freight Analysis Framework locations (17 292 potential links) to the 3142 counties and county-equivalents of the United States (9869 022 potential links). Subnational food flow estimates can be used in future work to improve our understanding of vulnerabilities within a national food supply chain, determine critical infrastructures, and enable spatially detailed footprint assessments. 

Abstract The food system is an important contributor to carbon dioxide (CO 2 ) emissions. The refrigerated food supply chain is an energy-intensive, nutritious and high-value part of the food system, making it particularly important to consider. In this study, we develop a novel model of cold chain food flows between counties in the United States. Specifically, we estimate truck transport via roadways of meat and prepared foodstuffs for the year 2017. We use the roadway travel distance in our model framework rather than the haversine distance between two locations to improve the estimate for long-haul freight with a temperature-controlled system. This enables us to more accurately calculate the truck fuel consumption and CO 2 emissions related to cold chain food transport. We find that the cold chain transport of meat emitted 8.4 × 10 6 t CO 2 yr −1 and that of prepared foodstuffs emitted 14.5 × 10 6 t CO 2 yr −1 , which is in line with other studies. Meat has a longer average refrigerated transport distance, resulting in higher transport CO 2 emissions per kg than processed foodstuffs. We also find that CO 2 emissions from cold chain food transport are not projected to significantly increase under the temperatures projected to occur with climate change in 2045. These county-level cold chain food flows could be used to inform infrastructure investment, supply chain decision-making and environmental footprint studies.