Risk assessment of non-point source pollution in karst reservoirs based on 'source-sink' landscape theory

Abstract

The quantitative identification of areas at risk for such pollution is conducive to allocating limited government funds to critical areas and the efficient and economical management of water environments. Here, the Baihua Lake watershed, an important drinking water source for Guiyang City, was taken as the study area. The location-weighted landscape contrast index (LCI) and non-point source pollution risk index (NSPRI) were developed based on the 'source-sink' landscape theory. The method takes into account the risk of pollution source formation and pollutant transport. A total of 348 natural sub-watersheds were used as assessment units by estimating the nitrogen and phosphorus pollution emission (absorption) potentials of different landscape types in the sub-watersheds and considering the influence of vegetation cover, distance from the reservoir, and slope in the transmission process, a quantitative assessment of Baihua Lake's pollution was carried out; the reliability of the method was verified by comparing the assessment results with measured water quality data and field surveys. The results indicate (1) 132 sub-watersheds (37.93%) dominated by source effects, mainly distributed in Yanshanhong Township, Yeya Township, and the Qinglong Subdistrict, with construction land and farmland as the main landscape types, and 216 sub-watersheds (62.07%) dominated by sink effects, mainly distributed in Zhanjie and Baihuahu Townships, with forests as the primary landscape type. (2) Additionally, 17 sub-watersheds (4.89%) show extremely high risk for non-point source pollution; these watersheds are mainly distributed in the Qinglong Subdistrict and mainly consist of urban residential areas and schools. These sub-watersheds discharge a large volume of sewage, which threatens the water quality of the upper reaches of Baihua Lake and must be managed. (3) The rivers corresponding to relatively highrisk, high-risk, and extremely high-risk sub-watersheds include the Dongmenqiao, Limu, Changchong, and Maixi Rivers.