title: How efficiently do corn- and soybean-based cropping systems use water? A systems modeling analysis.
abstract: Agricultural systems are being challenged to decrease water use and increase production while climate becomes more variable and the world's population grows. Low water use efficiency is traditionally characterized by high water use relative to low grain production and usually occurs under dry conditions. However, when a cropping system fails to take advantage of available water during wet conditions, this is also an inefficiency and is often detrimental to the environment. Here, we provide a systems-level definition of water use efficiency (sWUE) that addresses both production and environmental quality goals through incorporating all major system water losses (evapotranspiration, drainage, and runoff). We extensively calibrated and tested the Agricultural Production Systems sIMulator (APSIM) using 6 years of continuous crop and soil measurements in corn- and soybean-based cropping systems in central Iowa, USA. We then used the model to determine water use, loss, and grain production in each system and calculated sWUE in years that experienced drought, flood, or historically average precipitation. Systems water use efficiency was found to be greatest during years with average precipitation. Simulation analysis using 28 years of historical precipitation data, plus the same dataset with ± 15% variation in daily precipitation, showed that in this region, 430 mm of seasonal (planting to harvesting) rainfall resulted in the optimum sWUE for corn, and 317 mm for soybean. Above these precipitation levels, the corn and soybean yields did not increase further, but the water loss from the system via runoff and drainage increased substantially, leading to a high likelihood of soil, nutrient, and pesticide movement from the field to waterways. As the Midwestern United States is predicted to experience more frequent drought and flood, inefficiency of cropping systems water use will also increase. This work provides a framework to concurrently evaluate production and environmental performance of cropping systems.
authors.affiliation: Department of Agronomy, Iowa State University, Ames, IA, USA.
authors.forename: Ranae
authors.initials: R
authors.lastname: Dietzel
authors.affiliation: Department of Agronomy, Iowa State University, Ames, IA, USA.
authors.forename: Matt
authors.initials: M
authors.lastname: Liebman
authors.affiliation: Department of Agronomy, Iowa State University, Ames, IA, USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Ewing
authors.affiliation: Agricultural and Biosystems Engineering Department, Iowa State University, Ames, IA, USA.
authors.forename: Matt
authors.initials: M
authors.lastname: Helmers
authors.affiliation: Department of Agronomy, Iowa State University, Ames, IA, USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Horton
authors.affiliation: Department of Biology, University of South Dakota, Ames, IA, USA.
authors.forename: Meghann
authors.initials: M
authors.lastname: Jarchow
authors.affiliation: Department of Agronomy, Iowa State University, Ames, IA, USA.
authors.forename: Sotirios
authors.initials: S
authors.lastname: Archontoulis
mesh_terms: D000383:Agriculture / Q000379:methods*; D018533:Biomass; D055864:Droughts; D055868:Floods; D015146:Midwestern United States; D008962:Models, Theoretical; D012621:Seasons; D012987:Soil / Q000737:chemistry; D013025:Glycine max / Q000254:growth & development; D014867:Water / Q000032:analysis; D003313:Zea mays / Q000254:growth & development
chemical_list: D012987:Soil; D014867:Water
keywords: agricultural production systems simulator; biomass production; drainage; environment; soil water; water use efficiency