2015
DOI: 10.1111/gcb.13101
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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 defi… Show more

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Cited by 94 publications
(84 citation statements)
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References 65 publications
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“…WUE, EY, and EWR were higher for both species in 2015, likely due to greater SWtot, GDD, and precipitation in 2015, relative to 2014. Interannual variability in WUE was explained by different biomass accumulation between growing seasons, rather than changes in total ET, which is consistent with findings in the literature (Steduto et al, 1997;Narayanan et al, 2013;Hao et al, 2014;Dietzel et al, 2015). While both species had similar total ET, the pattern of ET accumulation within the season (Fig.…”
Section: Discussionsupporting
confidence: 91%
“…WUE, EY, and EWR were higher for both species in 2015, likely due to greater SWtot, GDD, and precipitation in 2015, relative to 2014. Interannual variability in WUE was explained by different biomass accumulation between growing seasons, rather than changes in total ET, which is consistent with findings in the literature (Steduto et al, 1997;Narayanan et al, 2013;Hao et al, 2014;Dietzel et al, 2015). While both species had similar total ET, the pattern of ET accumulation within the season (Fig.…”
Section: Discussionsupporting
confidence: 91%
“…Our specific objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. The APSIM model was selected for use in this study because of its flexibility and easy use in specifying crop rotations via the user interface, capability in simulating long-term dynamics in both soil and crop processes, advanced flexibility in simulating the effect of shallow water table dynamics that are important in this geographic region (Helmers et al, 2012) and previously determined good performance in this geographic region (Malone et al, 2007; Hammer et al, 2009; Lobell et al, 2013; Archontoulis et al, 2014a,b, 2016; Basche et al, 2016; Dietzel et al, 2016; Martinez-Feria et al, 2016). …”
Section: Introductionmentioning
confidence: 99%
“…The COBS field was established in 2008, and there are 24 plots (61 m by 27 m) and 6 cropping systems on Webster (fine-loamy, mixed, superactive, mesic Typic Endoaquolls) and Nicollet (fine-loamy, mixed, superactive, mesic Aquic Hapludolls) soils. The 6 zero-till cropping systems include corn-soybean, soybean-corn, continuous corn, and continuous corn with winter rye (Secale cereale) cover crop, reconstructed mixed prairie (C3 grasses, C4 grasses, legumes, and multi-functional group mixtures), and fertilized reconstructed mixed prairie (Daigh et al, 2015;Dietzel et al, 2015b;Jarchow et al, 2015). Measurements were made in 4 replications of 3 cropping systems (corn and soybean in corn-soybean rotation system, and reconstructed mixed prairie).…”
Section: Field Measurementsmentioning
confidence: 99%