Optimized simulation of the impact of soil health-related factors on dryland maize yield based on the CERES-Maize model
Based on three-year(2013-2015)irrigation experiments on maize,the parameters of the DSSAT-CERES-Maize model were calibrated and validated to evaluate its applicability to dryland agriculture in the Guanzhong region.This model was calibrated using full irrigation experiments in 2013 and 2014 and validated using data from the 2015 full irrigation experiment.Results showed consistency between the measured and simulated val-ues.The root mean square error and the normalized root mean square error were both below 10％,and the model ef-ficiency was greater than 90％,indicating a good simulation effect.Meteorological data from 1981 to 2020 and soil health-related factors were optimized and adjusted to explore the impact of optimizing soil health-related factors on dryland maize yields.The yields were simulated according to wet years,normal years,and dry years,respectively.The simulation analysis showed that increasing the soil drainage upper limit by 20％in dryland agriculture led to an 8.1％increase in maize yield,a 17.4％improvement in water use efficiency,and a 7.1％reduction in evapotranspi-ration.Under a comprehensive simulation that included increased soil albedo,drainage upper limit,soil organic car-bon,and other factors,dryland maize yield increased by 11.6％.In the comprehensive simulation scenario,the highest increase in yield occurred in dry years,indicating that improving soil health improved soil retention moisture and significantly promoted the growth and development of dryland maize.In conclusion,the CERES-Maize model can be effectively applied to studying dryland maize in the Guanzhong region.During periods of low water flow,ef-fective soil health management can significantly enhance water conservation and efficiency,thereby unlocking grea-ter potential.
dryland maize yieldDSSAT-CERES-Maize modelsoil health parametersoptimization
万方数据
维普
