title: Spatial Variability and Uncertainty of Water Use Impacts from U.S. Feed and Milk Production.
abstract: This paper addresses water use impacts of agriculture, developing a spatially explicit approach tracing the location of water use and water scarcity related to feed production, transport, and livestock, tracking uncertainties and illustrating the approach with a case study on dairy production in the United States. This approach was developed as a step to bring spatially variable production and impacts into a process-based life cycle assessment (LCA) context. As water resources and demands are spatially variable, it is critical to take into account the location of activities to properly understand the impacts of water use, accounting for each of the main feeds for milk production. At the crop production level, the example of corn grain shows that 59% of water stress associated with corn grain production in the United States is located in Nebraska, a state with moderate water stress and moderate corn production (11%). At the level of milk production, four watersheds account for 78% of the national water stress impact, as these areas have high milk production and relatively high water stress; it is the production of local silage and hay crops that drives water consumption in these areas. By considering uncertainty in both inventory data and impact characterization factors, we demonstrate that spatial variability may be larger than uncertainty, and that not systematically accounting for the two can lead to artificially high uncertainty. Using a nonspatial approach in a spatially variable setting can result in a significant underestimation or overestimation of water impacts. The approach demonstrated here could be applied to other spatially variable processes.
authors.affiliation: Environmental Health Sciences, School of Public Health, University of Michigan , Ann Arbor, Michigan 48109, United States.|University of Texas School of Public Health , Austin Regional Campus, Austin, Texas 78701, United States.
authors.forename: Andrew D
authors.identifier: 0000-0003-2436-7512
authors.initials: AD
authors.lastname: Henderson
authors.affiliation: Environmental Health Sciences, School of Public Health, University of Michigan , Ann Arbor, Michigan 48109, United States.
authors.forename: Anne C
authors.initials: AC
authors.lastname: Asselin-Balençon
authors.affiliation: Center for Sustainable Systems, School of Natural Resources and Environment, University of Michigan , 440 Church Street, Ann Arbor, Michigan 48109-1041, United States.
authors.forename: Martin
authors.initials: M
authors.lastname: Heller
authors.affiliation: Quantis, EPFL Science Park (PSE-D), CH-1015 Lausanne, Switzerland.
authors.forename: Lindsay
authors.initials: L
authors.lastname: Lessard
authors.affiliation: Quantis, EPFL Science Park (PSE-D), CH-1015 Lausanne, Switzerland.
authors.forename: Samuel
authors.initials: S
authors.lastname: Vionnet
authors.affiliation: Environmental Health Sciences, School of Public Health, University of Michigan , Ann Arbor, Michigan 48109, United States.|Quantis, EPFL Science Park (PSE-D), CH-1015 Lausanne, Switzerland.
authors.forename: Olivier
authors.initials: O
authors.lastname: Jolliet
mesh_terms: D000818:Animals; D018556:Crops, Agricultural; D008892:Milk; D012820:Silage; D035501:Uncertainty; D014867:Water; D003313:Zea mays
chemical_list: D014867:Water