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Proceedings Paper

Distributed hydrological modeling with GIS and remote sensing datasets: a case study in Qingjiang River basin, China
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Paper Abstract

A distributed hydrological model incorporating the catchment's spatial information including topography, land cover and soil, was developed in this paper. The proposed model splits the concerned catchment into a series of sub-catchments linked with stream networks derived from digital elevation model. A revised TOPMODEL, which includes a forest canopy sub-module to descript the temporal and spatial heterogeneity of forest cover, was used to simulate runoff processes of each sub-catchment. The model was implemented to fully integrate with Arc/Info and input parameters derived from remote sensing images could be generated effectively through the geographic information system. The model was applied to a case study in the QingJiang river basin, which is one of the largest catchments in the middle reach of the Yangtze River. The voids-filled SRTM DEM was used to derive stream networks and topographic information including area, topographic index distribution of each sub-catchment. Land cover and LAI products of MODIS incorporated with the FAO global soil map were used to derive other relative model parameters. The model was calibrated and validated with observed hydrological datasets and the result indicates that the model can simulate reasonably well the runoff hydrograph and a distributed hydrological modeling system integrated with GIS and remote sensing has a great potential for both research and application.

Paper Details

Date Published: 28 October 2006
PDF: 9 pages
Proc. SPIE 6420, Geoinformatics 2006: Geospatial Information Science, 64201P (28 October 2006); doi: 10.1117/12.712904
Show Author Affiliations
Feng Ling, HuaZhong Univ. of Science and Technology (China)
Qiu-wen Zhang, HuaZhong Univ. of Science and Technology (China)
Cheng Wang, HuaZhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 6420:
Geoinformatics 2006: Geospatial Information Science
Jianya Gong; Jingxiong Zhang, Editor(s)

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