Resistance evaluation and "source-sink" risk spatial pattern of agricultural non-point source pollution in small catchment
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Abstract
Abstract: It has important practical significance for the prevention and control planning of agricultural non-point source pollution in small catchment by identifying and evaluating "source-sink" risk pattern impacting agricultural non-point source pollution. Therefore, in this paper, a case study was carried out in a small catchment named Wangjiagou, which located in the typical agricultural region of the Three Gorges Reservoir Region, and the minimal cumulative resistance model (MCR) was used to evaluate resistance and identify "source-sink" risk of agricultural non-point source pollution. At first, the source lands were divided into 6 grades by processing and analyzing on the land use data. Secondly, the resistance base surface impacting the agricultural non-point source pollution was constructed based on the selection of main natural influence factors, including topography factors (relative elevation and slope), land use factors (source-sink landscape type and vegetable interception index), hydrological factors (flow length and topographic wetness index), soil factors (soil loss vertical distance index and soil erosion intensity), nitrogen and phosphorus factors (nitrogen input and phosphorus input). Thirdly, MCR model was applied to obtain nitrogen, phosphorus and total resistance surface, respectively, and by which spatial distribution trend of resistance were identified. In the end, according to the resistance threshold, "source-sink" risk pattern was classified. The results showed that: 1) There were obvious difference among the spatial distribution of different resistance factors impacted on agricultural non-point source pollution, which established the foundation for spatial heterogeneity of resistance base surface. Resistance base surface reflected the spatial difference of "source-sink" landscape in the small catchment in the Three Gorges Reservoir Region, with the resistance base surface value of "source" landscape smaller than that of "sink" landscape. The obvious characteristic of resistance surface was that resistance surface changes were mainly influenced by spatial distance, and the value of resistance surface was smallest in the buffers located at the source lands, while the value was bigger and bigger as the distance was far from the source lands. 2) The MCR model was applied to classify "source-sink" risk pattern in the small catchment into 5 grades, including extremely high risk zone (0.297 7 km2), high risk zone (0.154 4 km2), medium risk zone (0.147 5 km2), low risk zone (0.147 4 km2) and extremely low risk zone (0.016 0 km2), which indicated that there was a high risk trend of "source-sink" risk pattern, while there were still a certain range of low risk areas in the small catchement, which can ensure the effective interception for nitrogen and phosphorus loss. The results are helpful to evaluate the risk degree and rank of non-point source pollution produced by "source-sink" landscape from the angle of resistance surface, and can provide the policy-making basis for preventing and controlling agriculture non-point source pollution scientifically.
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