Comparison of Cropping System Models for Simulation of Soybean Evapotranspiration with Eddy Covariance Measurements in a Humid Subtropical Environment

Abstract

Crop evapotranspiration (ETC) water demands are critical decision support information for the sustainable use of water resources for optimum crop productivity. When measurements of ETC at all locations are not feasible, the prediction of ETC and crop growth from weather and soil–water–crop management data using state-of-the-science cropping system simulations is a viable alternative. This study compared soybean (Glycine max (L.) Merr.) ETC quantified using the eddy covariance (EC) method against simulations from two models, (i) the CSM-CROPGRO-soybean module within the Decision Support System for Agroecology Transfer (DSSAT) and (ii) CSM-CROPGRO-soybean module within the Root Zone Water Quality Model v2.0 (RZWQM) for a grower’s field in the Mississippi Delta, USA, during 2017, 2018, and 2019 growing seasons. The measured soybean grain yields during the three seasons, respectively, were 4979 kg ha−1, 5157 kg ha−1, and 5665 kg ha−1. The DSSAT and RZWQM simulated yields deviated from the measured yields by −10.8% and 15.4% in 2017, −24.0% and 1.56% in 2018, and −6.22%, and 9.98% in 2019. Simulated daily ETC values were less than EC estimates by 0.33 mm, 0.29 mm, and 0.23 mm for DSSAT and 0.05 mm, 0.42 mm, and 0.24 mm for RZWQM, respectively, for the three seasons. EC-quantified seasonal values of ETC were 584 mm, 532 mm, and 566 mm, respectively, for three seasons. Similarly, simulated seasonal ETC values were less than EC estimates by 40 mm, 31 mm, and 16 mm by DSSAT, and 7 mm, 46 mm, and 29 mm by RZWQM. The results obtained demonstrated that accuracy in the prediction of ETC varied among models and growing seasons. When the magnitude of errors in daily ETC simulations does not deter its applications in tactical irrigation water management decisions, a higher degree of agreement between measured and simulated ETC values at a seasonal scale is more promising for strategical irrigation water management planning decision support. Further improvement of the models for more accurate simulations of daily ETC can help in more confident applications of these models for tactical crop-water management applications.