农业工程学报
農業工程學報
농업공정학보
2012年
21期
177-185
,共9页
Wang Erda%Bertis B. Little%Jimmy R. Williams%Yu Yang
Wang Erda%Bertis B. Little%Jimmy R. Williams%Yu Yang
Wang Erda%Bertis B. Little%Jimmy R. Williams%Yu Yang
crops%economic analysis%agriculture%EPIC%soil type%hail damage%simulation model
crops%economic analysis%agriculture%EPIC%soil type%hail damage%simulation model
crops%economic analysis%agriculture%EPIC%soil type%hail damage%simulation model
In this study, a computer simulation model was used for predictive analysis of hail effect on crop yield losses. A pre-existed environmental policy integrated climate ( EPIC ) model was modified by introducing the hail weather module using an embedded stochastic probability function. This study focuses on estimating effects of the three important weather factors (hail, dry and cold) which make the most important contribution to the crop yield losses in U.S. corn-belt states of Iowa, Illinois and Indiana. Data sources, model development, calibration, and validation were described in detail, the model performance was tested, and statistical comparisons of simulated losses of crop yields against observed hail-induced crop yield losses were made. The results showed that the crop yield predictions reach 95% or higher accuracy and hail damage simulation also achieve a reasonable level of reliability ( R2 was above 0.7). These suggest that using the hail-integrated EPIC model can properly provide a reliable method for hail-related crop yield loss estimation. The model can be utilized to simulate hailstorm events and their damages to various field crops.
In this study, a computer simulation model was used for predictive analysis of hail effect on crop yield losses. A pre-existed environmental policy integrated climate ( EPIC ) model was modified by introducing the hail weather module using an embedded stochastic probability function. This study focuses on estimating effects of the three important weather factors (hail, dry and cold) which make the most important contribution to the crop yield losses in U.S. corn-belt states of Iowa, Illinois and Indiana. Data sources, model development, calibration, and validation were described in detail, the model performance was tested, and statistical comparisons of simulated losses of crop yields against observed hail-induced crop yield losses were made. The results showed that the crop yield predictions reach 95% or higher accuracy and hail damage simulation also achieve a reasonable level of reliability ( R2 was above 0.7). These suggest that using the hail-integrated EPIC model can properly provide a reliable method for hail-related crop yield loss estimation. The model can be utilized to simulate hailstorm events and their damages to various field crops.
In this study, a computer simulation model was used for predictive analysis of hail effect on crop yield losses. A pre-existed environmental policy integrated climate ( EPIC ) model was modified by introducing the hail weather module using an embedded stochastic probability function. This study focuses on estimating effects of the three important weather factors (hail, dry and cold) which make the most important contribution to the crop yield losses in U.S. corn-belt states of Iowa, Illinois and Indiana. Data sources, model development, calibration, and validation were described in detail, the model performance was tested, and statistical comparisons of simulated losses of crop yields against observed hail-induced crop yield losses were made. The results showed that the crop yield predictions reach 95% or higher accuracy and hail damage simulation also achieve a reasonable level of reliability ( R2 was above 0.7). These suggest that using the hail-integrated EPIC model can properly provide a reliable method for hail-related crop yield loss estimation. The model can be utilized to simulate hailstorm events and their damages to various field crops.
