15 October 2009 Analysis on influence of non-point source pollution in Fuhe watershed based on the SWAT model and ArcGIS
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Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 74923X (2009) https://doi.org/10.1117/12.838476
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China
Abstract
Precipitation and topography are the most important influence factors of non-point source pollution, especially for soil erosion. Based on the SWAT model and ArcGIS, the Fuhe watershed was divided into 50 sub-basins. Combined with the standard deviation gradational method, statistical analyses on characteristics of the spatial and temporal variation of rainfall in Fuhe watershed were carried out1 based on the rainfall observation data from January 1st, 1986 to December 31st, 2005 from 25 stations within the watershed. The results showed that the spatial-temporal distribution of precipitation was uneven. Spatially, the average annual rainfall was divided into five grades. Temporally, there was great variation in inter-year precipitation. The inter-year rainfall distribution was extremely uneven, focused on March to June, which accounted for 56 % of the total. The analysis of topography in Fuhe watershed was carried out by using the standard deviation gradational method. The slope of the basin was divided into five grades. The basin was divided into four grades of the NPS risk by using pollution average slope and rainfall to calculate a weighted value of the risk of NPS pollution. The first and second level district were mainly distributed in the western, the eastern area, and sporadically distributed in certain areas of the southern in the watershed, which accounted for 55.6% of the basin area; the risk values were very large in these districts.
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XianChun Guo, BaoGui Zhao, DaJun Li, JunChang Xiao, "Analysis on influence of non-point source pollution in Fuhe watershed based on the SWAT model and ArcGIS", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74923X (15 October 2009); doi: 10.1117/12.838476; https://doi.org/10.1117/12.838476
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