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Risk assessment of soil erosion by application of remote sensing and GIS in Yanshan Reservoir catchment, China

Yanfang Hu, Guohang Tian (), Audrey Mayer () and Ruizhen He

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2015, vol. 79, issue 1, 277-289

Abstract: Soil erosion is considered to be a serious problem for environmental sustainability. Healthy and stable soils are crucial for human well-being, providing important ecosystem functions and services. There is a need for a simple and practical approach which estimates and maps soil erosion risk that uses available information as input data to facilitate water and soil conservation. In this work, we developed a predictive approach to estimating the soil erosion risk of the Yanshan Reservoir catchment, which combines remote sensing information, geographic information system spatial analysis technology and a soil erosion risk assessment model. Three dominating factors affecting soil erosion were considered: vegetation coverage, topographic slope and land use. The soil erosion risk was divided into six levels: slight, light, moderate, intense, severe and extremely severe. The slight and light erosion risk accounted for about 83 % of the watershed and was prominent in cultivated land areas, while areas with relatively higher erosion risk were on steep slopes. This approach pointed to inappropriate land use and development as a source of increased risk of soil erosion of the Yanshan Reservoir catchment. Compared with field survey data, the soil erosion modeling approach was shown to have a high accuracy. Therefore, this model could be used to estimate and map soil erosion intensity and distribution at the catchment scale, and could provide useful information for managers and planners to make land management and conservation decisions. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: Soil erosion; Risk assessment; VSCI model; Remote sensing; GIS (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11069-015-1841-4

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