The effect of up-scaling soil properties and model parameters on predictive accuracy of DSSAT crop simulation model under variable weather conditions

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• 作者：Jessica Fry^a ; ^{fryjess1@msu.edu} ; Andrey K. Guber^a ; ^{akguber@msu.edu} ; Moslem Ladoni^b ; ^{moslemladoni@gmail.com} ; Juan D. Munoz^a ; ^{munozro3@msu.edu} ; Alexandra N. Kravchenko^a ; ^{kravche1@msu.edu}
• 关键词：DSSAT-CSM ; Decision Support System for Agrotechnology Transfer with Crop Simulation Model ; LTER KBS ; the Long Term Ecological Research Kellogg Biological Station ; SSURGO ; Soil Survey Geographic database ; ET ; potential evapotranspiration ; P ; precipitation ; TOC ; total organic carbon content ; RMSE ; root mean squared error ; RAE ; relative absolute error ; CN ; runoff curve number
• 刊名：Geoderma
• 出版年：2017
• 出版时间：1 February 2017
• 年：2017
• 卷：287
• 期：Complete
• 页码：105-115
• 全文大小：1781 K
• 卷排序：287

文摘

Spatial variability in soil properties and soybean yield was studied in field. Calibrated and validated DSSAT-CSM generated yield for 22 weather scenarios. Four techniques for upscaling DSSAT-CSM parameters were tested to predict yield. All upscaling techniques provided reasonable estimates of yield at field scale. The model was sensitive to runoff curve numbers, but was not to soil properties.