4.6 Article

Identification of the source and sink patterns influencing non-point source pollution in the Three Gorges Reservoir Area

Journal

JOURNAL OF GEOGRAPHICAL SCIENCES
Volume 26, Issue 10, Pages 1431-1448

Publisher

SCIENCE PRESS
DOI: 10.1007/s11442-016-1336-6

Keywords

non-point source pollution; landscape resistance/motivation; distance cost; source/sink landscape; Three Gorges Reservoir Area

Funding

  1. Science and Technology Great Special Project on Controlling and Fathering Water Pollution during the National 12th Five-Year Plan [2012ZX07104-003]

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Non-point source pollution is one of the primarily ecological issues affecting the Three Gorges Reservoir Area. In this paper, landscape resistance and motivation coefficient, which integrated various landscape elements, such as land use, soil, hydrology, topography, and vegetation, was established based on the effects of large-scale resistance and motivation on the formation of non-point source pollution. In addition, cost models of the landscape resistance and motivation coefficients were constructed based on the distances from the landscape units to the sub-basin outlets in order to identify the source and sink patterns affecting the formation of non-point source pollution. The results indicated that the changes in the landscape resistance and motivation coefficients of the 16 sub-basins exhibited inverse relationships to their spatial distributions. The landscape resistance and motivation cost curves were more volatile than the landscape resistance and motivation coefficient curves. The landscape resistance and motivation cost trends of the 16 sub-basins became increasingly apparent along the flow of the Yangtze River. The landscape resistance and motivation cost models proposed in this paper could be used to identify large-scale non-point source pollution source and sink patterns. Moreover, the proposed model could be used to describe the large-scale spatial characteristics of non-point source pollution formation based on source and sink landscape pattern indices, spatial localization, and landscape resistance and motivation coefficients.

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