Modeling soil water regime and corn yields considering climatic uncertainty

被引:13
作者
Huang, GH [1 ]
机构
[1] China Agr Univ, Dept Irrigat & Drainage, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
crop-yield functions; Kalman filter technique; real time modeling; water balance; yield and soil moisture prediction;
D O I
10.1023/B:PLSO.0000020966.88449.8f
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Real time estimation of soil moisture and crop yield plays an important role for best irrigation management practices especially in arid and semiarid regions. A simulation model able of real time estimating and forecasting soil water storage and corn yield response to soil moisture was developed by combining two existing models. Soil water storage was estimated through the soil water balance equation considering the uncertainty of evapotranspiration and combing with Kalman filter technique. Crop dry matter and grain yield were simulated by using a functional relationship between yield and soil moisture. Some improvements have been made in the response function by considering different impacts of moisture stress on crop growth and yield for the different growing stages. Four years data sets collected in an experimental station in the North China Plain were used to calibrate and test the model. Results indicate that soil moisture storage in the soil profile estimated and predicted by the model agrees well with the measured data, and the relative error of yield prediction is around 10%, which means that the combined model and the methodology applied are capable of predicting crop yield and soil water storage dynamics.
引用
收藏
页码:221 / 229
页数:9
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