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Capability of a solar energy-driven crop model for simulating water consumption and yield of maize and its comparison with a water-driven crop model
Agricultural and Forest Meteorology ( IF 5.6 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.agrformet.2020.107955 Hui Ran , Shaozhong Kang , Xiaotao Hu , Sien Li , Wene Wang , Fulai Liu
Agricultural and Forest Meteorology ( IF 5.6 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.agrformet.2020.107955 Hui Ran , Shaozhong Kang , Xiaotao Hu , Sien Li , Wene Wang , Fulai Liu
Abstract As water scarcity becomes more acute in many parts of the world, crop modeling tools that effectively simulating crop response to deficit irrigation strategies to help investigate management improvement are needed. Identifying the strengths and weaknesses of the crop models with different growth-engines are therefore of great importance. The objective of this study was to investigate the capability and improvements of the new version of a solar energy-driven crop model (DSSAT-CERES-Maize, v4.7.5.0) in simulating water consumption and yield of hybrid seed maize under different soil water conditions, and its comparison with a water-driven crop model (AquaCrop, v4.0). Data obtained from a 4-year (2012–2015) field trial on maize grown under different irrigation treatments at Wuwei, Northwest China, was used for this assessment. These models were calibrated and validated using measured daily evapotranspiration (ET), leaf area index (LAI), aboveground biomass, yield (Y), harvest index (HI) and soil water content (SWC). Daily ET was measured using a combination of an eddy covariance (EC) system, sap flow sensors, and micro-lysimeter cylinders. The ability of DSSAT-CERES-Maize using the two different ET options, i.e., Priestley-Taylor/Ritchie (PT) and FAO-56 Penman-Monteith (PM) was analyzed. The results showed that DSSAT-CERES-Maize with the PT approach had fair agreement with measured daily ET of maize under non-water stress condition (R2=0.85; NRMSE=26.7%), but poor agreement with ET under water stress conditions (R2=0.51; NRMSE=43.8%). DSSAT-CERES-Maize with the PM approach systematically underestimated ET by up to 13% under non-water stress condition, which was mainly attributed to that the maximum static CERES-Maize crop coefficient (EORATIO) was currently hard coded to 1.0. Using the PT or FAO-56 PM approach as ET input in DSSAT-CERES-Maize showed no different effect on final biomass (B) and Y simulation for full irrigation. But for water stress conditions, DSSAT-CERES-Maize with the FAO-56 PM approach simulated B and Y with higher overestimation to the measured data than those simulated using the PT approach. The simulated LAI, biomass and SWC by DSSAT-CERES-Maize using the PT approach generally well followed the trend of the measured values for most irrigation treatments. The model with the PT approach showed acceptable prediction for B and Y of different irrigation treatments across years, with NRMSE of 15.5% and 26.2%, respectively, but the accuracy decreased with an aggravation of water stress. Furthermore, the strengths and weaknesses of DSSAT-CERES-Maize and AquaCrop, and their different cores of growth-engines, i.e. RUE and normalized water productivity (WP*) were carefully discussed. It was concluded that DSSAT-CERES-Maize was a superior estimate of maize yield than was AquaCrop, especially when the climate varied dramatically between years. But DSSAT-CERES-Maize, for the simulation of maize water consumption in an arid region where drought often occurs, was inferior to AquaCrop. These results contribute to recommend the appropriate crop model for specific modeling goals.
更新日期：2020-06-01
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