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Proceedings Paper

Development of a soil moisture prediction model based on Xinanjiang model and GIS
Author(s): Jingwen Xu; Wanchang Zhang; Changquan Wang; Ziyan Zheng; Jiongfeng Chen
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Paper Abstract

Soil moisture conditions are very important in agriculture - they control crops growth and development and are used directly to assess irrigation needs for a variety of crops. In this paper, a new soil moisture prediction model was developed based on GIS technology and the hydrological model Xinanjiang, which has been successfully and widely applied in humid and semi-humid regions in China since its development. The original Xinanjiang model uses a single parabolic curve to represent the spatial distribution of the soil moisture storage capacity over the catchment, where the exponent parameter b measures the non-uniformity of this distribution. It was extended to be a distributed hydrological model by using GIS technology. 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 for each grid. The runoff in each grid cell 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. The new model was tested in Linyi watershed, Shandong province, China. The results show that the soil moisture predicted by the new model agrees with the field observed.

Paper Details

Date Published: 10 July 2009
PDF: 6 pages
Proc. SPIE 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering, 74910L (10 July 2009); doi: 10.1117/12.836762
Show Author Affiliations
Jingwen Xu, Sichuan Agricultural Univ. (China)
Institute of Atmospheric Physics (China)
Graduate School of the Chinese Academy of Sciences (China)
Wanchang Zhang, Institute of Atmospheric Physics (China)
Changquan Wang, Sichuan Agricultural Univ. (China)
Ziyan Zheng, Institute of Atmospheric Physics (China)
Jiongfeng Chen, Institute of Atmospheric Physics (China)

Published in SPIE Proceedings Vol. 7491:
PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering
Honghua Tan; Qi Luo, Editor(s)

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