Validation of crop model for simulating summer maize in the Huang-Huai Plain of China and its application on analyzing drought effects

Shuyan Li; Ronghua Liu; Lin Cheng; Wensong Fang; Xinli Wang

doi:10.1117/12.825223

20 August 2009 Validation of crop model for simulating summer maize in the Huang-Huai Plain of China and its application on analyzing drought effects

Shuyan Li, Ronghua Liu, Lin Cheng, Wensong Fang, Xinli Wang

Author Affiliations +

Proceedings Volume 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI; 74541H (2009) https://doi.org/10.1117/12.825223
Event: SPIE Optical Engineering + Applications, 2009, San Diego, California, United States

Abstract

Using datasets of 1991-2004 meteorological and soil data as well as field management from 8 stations in the summer-sown maize zone over the Huang-Huai River Basin, North China, study is performed of the water deficit in various phases of growth of the crop impacting on the final yield by means of CERES-Maize of DSSAT Version 4.0, whose parameters are adjusted for local conditions. Results show that 1) in the jointing stage of vegetative growth and the filling stage (especially its earlier part) of the reproduction growth, field moisture acts as a key factor affecting the yield; 2) deficient moisture in the 7-leaf and jointing periods would cause maximum leaf area index to significantly drop, keeping dry matter from accumulation, leading to appreciable diminution of weight of dry stem and leaves; 3) water deficit in the earlier (middle) filling stage would result in reduced number of grains per cob (decrease substantially the weight of 100 grains). The findings in conjunction with measured moisture can be used to implement the "efficient irrigation with less water" practice in this vast region.

Citation Download Citation

Shuyan Li, Ronghua Liu, Lin Cheng, Wensong Fang, and Xinli Wang "Validation of crop model for simulating summer maize in the Huang-Huai Plain of China and its application on analyzing drought effects", Proc. SPIE 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI, 74541H (20 August 2009); https://doi.org/10.1117/12.825223

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