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Estimation of soil erosion in some sections of Lower Jinsha River based on RUSLE

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  • Liguang Jiang
  • Zhijun Yao
  • Zhaofei Liu
  • Shanshan Wu
  • Rui Wang
  • Lei Wang

Abstract

Soil erosion increasingly poses a great threat to human food security and environmental quality. It is necessary to implement the assessment of soil erosion so as to provide precautionary measures and relevant suggestions for soil conservation. In this paper, the soil erosion model, revised universal soil loss equation (RUSLE), was used to quantify the soil loss in a large mountainous area of Lower Jinsha River Basin. The analysis of the datasets by means of geographic information systems (GIS) together with RUSLE led to the estimation of soil erosion. Results show that the average annual soil erosion was estimated at 52.1 t ha −1 year −1 and the total annual soil loss was 4.5 × 10 8 t. The highest erosion was found along the main course of Jinsha River. Soil erosion was serious in the elevation zone between 1,675 and 2,153 m and slope zone with slopes between 15° and 35°. As for land use types, cropland and grassland contributed 84.1 % to total soil loss due to the large areas and higher erosion rates. The results can be used to advice the local government in prioritizing the areas of immediate conservation practices. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Liguang Jiang & Zhijun Yao & Zhaofei Liu & Shanshan Wu & Rui Wang & Lei Wang, 2015. "Estimation of soil erosion in some sections of Lower Jinsha River based on RUSLE," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 76(3), pages 1831-1847, April.
    • Handle: RePEc:spr:nathaz:v:76:y:2015:i:3:p:1831-1847
    DOI: 10.1007/s11069-014-1569-6
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    References listed on IDEAS

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    1. Rahman, Md. Rejaur & Shi, Z.H. & Chongfa, Cai, 2009. "Soil erosion hazard evaluation—An integrated use of remote sensing, GIS and statistical approaches with biophysical parameters towards management strategies," Ecological Modelling, Elsevier, vol. 220(13), pages 1724-1734.
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    7. Jun Pei & Wei Yang & Yangpeng Cai & Yujun Yi & Xiaoxiao Li, 2018. "Relationship between Vegetation and Environment in an Arid-Hot Valley in Southwestern China," Sustainability, MDPI, vol. 10(12), pages 1-14, December.
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