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10 July 2009 Development of a distributed agricultural drought prediction model based on TOPMODEL and GIS
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Proceedings Volume 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering; 74910K (2009) https://doi.org/10.1117/12.836758
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China
Abstract
Drought disasters occur frequently in eastern China and are typical in China and even in the world. Severe droughts seriously affect the agricultural production, social and economic development, ecology and human life. In this paper, a new agricultural drought prediction model was developed based on GIS technology and TOPMODEL, which is a physically based watershed hydrological model that simulates the variable-source-area concept of stream-flow generation and has been widely used to study a variety of research areas. In this study, the original TOPMODEL was extended to be a distributed hydrological model. The watershed is divided into a number of regular grids, corresponding to the grids of DEM, and each grid is viewed as a sub-basin. So the surface runoff production was calculated at each grid. The runoff at each grid is routed along the stream flow direction to the main watershed outlet respectively at different velocity depending on the slop of this grid and watershed-average routing velocity. The soil moisture is predicted using the new distributed hydrological model. Finally, drought prediction is conducted by combining the predicted soil moisture and drought indices. The new model was tested in Linyi watershed, Shandong province, China. The results show that the model performs well in agricultural drought prediction.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jingwen Xu, Wanchang Zhang, Changquan Wang, Xuemei Zhu, and Jiongfeng Chen "Development of a distributed agricultural drought prediction model based on TOPMODEL and GIS", Proc. SPIE 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering, 74910K (10 July 2009); https://doi.org/10.1117/12.836758
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