Improving evapotranspiration simulations in the CERES-Maize model under limited irrigation

Abstract

a b s t r a c tLimitations on water resources for agriculture in places such as Colorado, USA, have caused farmers to consider limited irrigation as an alternative to full irrigation practices, where the crop is intentionally stressed during specific growth stages in an effort to maximize yield per unit water consumed, or evapotranspiration (ET). While crop growth models such as CERES-Maize provide the ability to evaluate numerous management scenarios without the costs associated with multiyear field experiments, recent studies have shown that CERES-Maize performs well under full irrigation but overestimates ET of corn under limited irrigation management. The primary objective of this study was to improve CERES-Maize ET simulation under limited irrigation management while maintaining accuracy of other important model output responses. Field experiments with corn were performed in northern Colorado, USA from 2006 to 2010, where four replicates each of full (ET requirement supplied by irrigation throughout the season) and limited (no irrigation before the V12 growth stage unless necessary for emergence, then full irrigation afterwards) irrigation treatments were analyzed. The local sensitivity of model input parameters affecting ET was evaluated, prompting changes to the model code with a new dynamic crop coefficient (K CD ) as a function of the crop leaf area index. The modified CERES-Maize model more accurately represented ET under full and limited irrigation, for example reducing late-season ET potential from a plant with reduced canopy and more closely matched FAO-56 crop coefficient curves under full irrigation. Using the limited irrigation data for evaluation, the modified model showed significant decreases in model error for seasonal cumulative ET (root mean square deviation RMSD from 80.9 mm to 49.9 mm) and water productivity (RMSD from 5.97 kg ha −1 mm −1 to 2.86 kg ha −1 mm −1 ) as compared to the original model. The modified model was subsequently applied to several hypothetical irrigation management strategies, indicating that reducing weekly vegetative stage water applications from 20 mm to 2.5 mm can increase simulated water productivity by over 15%. While these synthetic water production functions may not be feasible in a production field with natural climate variability, the modified ET model indicates promise for limited irrigation management increasing water productivity.Published by Elsevier B.V.

Cotton Irrigation Scheduling Using a Crop Growth Model and FAO-56 Methods: Field and Simulation Studies

“…Thorp et al (2010) evaluated DSSAT-CSM for Arizona wheat and reported difficulty in simulating crop growth and water use unless the model's current crop coefficient parameter (EORATIO) was set to an unreasonably high value of 1.8. Independently, DeJonge et al (2012) developed a crop coefficient equation for the CSM-CERES-Maize model that better followed the FAO-56 protocol and led to better simulations of maize (Zea mays L.) ET under both full and limited irrigation in Colorado. Thorp et al (2014b) modified DSSAT-CSM to include the DeJonge et al (2012) crop coefficient equation and the Walter et al (2005) standard algorithm for grass reference ET o calculations.…”

“…Independently, DeJonge et al (2012) developed a crop coefficient equation for the CSM-CERES-Maize model that better followed the FAO-56 protocol and led to better simulations of maize (Zea mays L.) ET under both full and limited irrigation in Colorado. Thorp et al (2014b) modified DSSAT-CSM to include the DeJonge et al (2012) crop coefficient equation and the Walter et al (2005) standard algorithm for grass reference ET o calculations. The updates improved the simulation of seasonal cotton ET in Arizona, which was underestimated by 15% with the model's original FAO-56 approach.…”

Implementing Standardized Reference Evapotranspiration and Dual Crop Coefficient Approach in the DSSAT Cropping System Model

“…As noted by DeJonge et al (2012a), K cs is not necessarily the same as crop coefficients described in FAO-56 (i.e., K c in eq. A4).…”

“…Comparatively, it is easier to program an algorithm from existing standardized equations than to (1) program a completely novel ET algorithm without error or (2) debug an existing ET algorithm that is misbehaving due to syntactical or conceptual errors. In each of these cases, coding improvements can be facilitated by comparisons to the benchmark ET standard.The motivation for the present study arose from the authors' independent work to use the Decision Support System for Agrotechnology Transfer (DSSAT) cropping system model (CSM) for irrigation management applications in semi-arid to arid environments of the western U.S.: maize in Colorado (DeJonge et al, 2011(DeJonge et al, , 2012a and wheat and cotton in Arizona (Thorp et al, 2010(Thorp et al, , 2014. Those studies highlighted issues with the ET methods of DSSAT-CSM, which the authors sought to remedy by bringing the model code into agreement with accepted standardized ET methods.…”

Crop Modeling Applications in Agricultural Water Management

“…DeJonge and compared simulated ET o to outputs from Ref-ET software (Allen, 2000) and crop coefficients determined by three different approaches: the current approach (K cs ) as implemented in DSSAT, a previously published adjustment to the model's K c equation (K cd ;DeJonge et al, 2012), and a new dual K c approach that follows FAO-56 explicitly (K cb ), presented by DeJonge and . Their results showed that crop coefficient simulations with the new ET o -K cb method better mimicked theoretical behavior, including spikes in the soil evaporation coefficient (K e ) due to irrigation and rainfall events and the basal crop coefficient response associated with simulated crop growth.…”