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Estimation of soil erosion using RUSLE in Caijiamiao watershed, China

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  • Jinghu Pan
  • Yan Wen

Abstract

Soil erosion is a serious environmental and production problem in China. In particular, natural conditions and human impact have made the Chinese Loess Plateau particularly prone to intense soil erosion area. To decrease the risk on environmental impacts, there is an increasing demand for sound, and readily applicable techniques for soil conservation planning in this area. This work aims at the assessment of soil erosion and its spatial distribution in hilly Loess Plateau watershed (northwestern China) with a surface area of approximately 416.31 km 2 . This study was conducted at the Caijiamiao watershed to determine the erosion hazard in the area and target locations for appropriate initiation of conservation measures using the revised universal soil loss equation (RUSLE). The erosion factors of RUSLE were collected and processed through a geographic information system (GIS)-based approach. The soil erosion parameters were evaluated in different ways: The R-factor map was developed from the rainfall data, the K-factor map was obtained from the soil map, the C-factor map was generated based on Landsat-5 Thematic Mapper image and spectral mixture analysis, and a digital elevation model with a spatial resolution of 25 m was derived from topographic map at the scale of 1:50,000 to develop the LS-factor map. Support practice P factor was from terraces that exist on slopes where crops are grown. By integrating the six-factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the study area was obtained by the RUSLE model. The results showed that spatial average soil erosion at the watershed was 78.78 ton ha −1 year −1 in 2002 and 70.58 ton ha −1 year −1 in 2010, while the estimated sediment yield was found to be 327.96 × 10 4 and 293.85 × 10 4 ton, respectively. Soil erosion is serious, respectively, from 15 to 35 of slope degree, elevation area from 1,126 to 1,395 m, in the particular area of soil and water loss prevention. As far as land use is concerned, soil losses are highest in barren land and those in waste grassland areas are second. The results of the study provide useful information for decision maker and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a river watershed scale on a cell basis in Chinese Loess Plateau and for planning of conservation practices. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Jinghu Pan & Yan Wen, 2014. "Estimation of soil erosion using RUSLE in Caijiamiao watershed, China," 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. 71(3), pages 2187-2205, April.
  • Handle: RePEc:spr:nathaz:v:71:y:2014:i:3:p:2187-2205
    DOI: 10.1007/s11069-013-1006-2
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    Citations

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    Cited by:

    1. 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.
    2. Arun Mondal & Deepak Khare & Sananda Kundu, 2016. "Impact assessment of climate change on future soil erosion and SOC loss," 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. 82(3), pages 1515-1539, July.
    3. Elsayed A. Abdelsamie & Mostafa A. Abdellatif & Farag O. Hassan & Ahmed A. El Baroudy & Elsayed Said Mohamed & Dmitry E. Kucher & Mohamed S. Shokr, 2022. "Integration of RUSLE Model, Remote Sensing and GIS Techniques for Assessing Soil Erosion Hazards in Arid Zones," Agriculture, MDPI, vol. 13(1), pages 1-19, December.
    4. Elias Rodrigues Cunha & Vitor Matheus Bacani & Elói Panachuki, 2017. "Modeling soil erosion using RUSLE and GIS in a watershed occupied by rural settlement in the Brazilian Cerrado," 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. 85(2), pages 851-868, January.
    5. Sumedh R. Kashiwar & Manik Chandra Kundu & Usha R. Dongarwar, 2022. "Soil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS," 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. 110(2), pages 937-959, January.
    6. L. Zhang & Ke Z. Bai & Man J. Wang & R. Karthikeyan, 2016. "Basin-scale spatial soil erosion variability: Pingshuo opencast mine site in Shanxi Province, Loess Plateau of China," 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. 80(2), pages 1213-1230, January.
    7. L. Zhang & Ke Bai & Man Wang & R. Karthikeyan, 2016. "Basin-scale spatial soil erosion variability: Pingshuo opencast mine site in Shanxi Province, Loess Plateau of China," 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. 80(2), pages 1213-1230, January.
    8. Ranghu Wang & Shuwen Zhang & Jiuchun Yang & Luoman Pu & Chaobin Yang & Lingxue Yu & Liping Chang & Kun Bu, 2016. "Integrated Use of GCM, RS, and GIS for the Assessment of Hillslope and Gully Erosion in the Mushi River Sub-Catchment, Northeast China," Sustainability, MDPI, vol. 8(4), pages 1-20, March.
    9. Taingaun Sourn & Sophak Pok & Phanith Chou & Nareth Nut & Dyna Theng & P. V. Vara Prasad, 2022. "Assessment of Land Use and Land Cover Changes on Soil Erosion Using Remote Sensing, GIS and RUSLE Model: A Case Study of Battambang Province, Cambodia," Sustainability, MDPI, vol. 14(7), pages 1-24, March.
    10. Yanhua Zhuang & Chao Du & Liang Zhang & Yun Du & Sisi Li, 2015. "Research trends and hotspots in soil erosion from 1932 to 2013: a literature review," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(2), pages 743-758, November.

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