Unique water scarcity footprints and water risks in US meat and ethanol supply chains identified via subnational commodity flows

Abstract

Within the US, supply chains aggregate agricultural production and associated environmental impacts in specific downstream products and companies. This is particularly important for meat and ethanol, which consume nearly half of global crop production as feed and feedstocks. However, lack of data has thus far limited the ability to trace inputs and impacts of commodity crops through domestic supply chains. For the first time, we use a commodity-flow model to link spatially distributed water resource impacts of corn and soy to individual meat and ethanol processing facilities. This creates transparency in the supply chains, illuminating substantial variation in embedded irrigation water and water scarcity footprints among meat and ethanol processed at different facilities. By calculating unique blue water scarcity footprints for end-products, we show that beef processed in Iowa or Illinois, for example, has fewer water impacts than chicken processed in California and pork processed in Oklahoma. We find that over 75% of irrigated feed embedded in meat is consolidated in six companies and 39% of irrigated feedstock for ethanol is consolidated in five companies, with potentially negative impacts to supply costs and risk management. This subnational variation and consolidation of impacts in key supply chains creates opportunities for producers and consumers of agriculture-based products to make management, investment, and sustainability decisions about those products.

Landsat-based Irrigation Dataset (LANID): 30 m resolution maps of irrigation distribution, frequency, and change for the US, 1997–2017

“…print of their sourced products (Brauman et al, 2020). Additional applications may include business decision-making and financial investment (Turral et al, 2010), precise fieldlevel water use estimation and solutions (Sadler et al, 2005), and crop yield prediction and its water resilience (Troy et al, 2015).…”

Landsat-based Irrigation Dataset (LANID): 30-m resolution maps of irrigation distribution, frequency, and change for the U.S., 1997–2017

“…Our dataset may also be useful for agribusinesses and entities across agricultural supply chains. For example, our maps could be used by companies that seek to reduce risk from water scarcity within their supply chains or lower the water footprint of their sourced products (Brauman et al, 2020). Additional applications may include business decision-making and financial investment (Turral et al, 2010), precise field-level water use estimation and solutions (Sadler et al 2005), and crop yield prediction and its water resilience (Troy et al, 2015).…”

The Water Footprint of the United States

“…Following his lead, studies have examined virtual water flows associated with energy systems in the US. Virtual water transfers associated with domestic ethanol supply chains highlight water risks to energy systems [59]. Virtual water transfers in both food and energy crops have been comprehensively evaluated to provide a complete picture of the US Food-Energy-Water (FEW) system [60], highlighting the tight coupling of these resources.…”

“…It is important for decision-makers to consider the full life-cycle water use of technological solutions to water stress, to avoid unintended consequences that may actually intensify water stress [87,88]. We can all reduce our water footprint by adopting a less water-intensive diet [20,59,76] and wasting less food [74,76,89].…”