• DocumentCode
    2855080
  • Title

    Soil Erosion Prediction Using RUSLE with GIS: A Case Study in Upper Chaobai River Basin of China

  • Author

    LIN, Qinghui ; Wang, Xiaoyan

  • Author_Institution
    Inst. of Geographic Sci. & Natural Resources Res., Chinese Acad. of Sci. (CAS), Beijing
  • fYear
    2006
  • fDate
    July 31 2006-Aug. 4 2006
  • Firstpage
    1086
  • Lastpage
    1089
  • Abstract
    This research integrated the RMsed Universal Soil Loss Equation (RUSLE) model with RS and GIS techniques to quantify soil erosion risk, took upper Chaobai River basin, China as an example to map soil erosion within ArcGIS environment by using the RUSLE model. The RUSLE factors were developed from local rainfall, topographic, soil classification and land use data. This study proved that the integration of soil erosion models with GIS and RS was a simple and effective tool for soil conservation. Statistical analysis determined that 14537.5 km2 (75.1%) had minimal to low soil degradation in the upper Chaobai River basin, 2381.0 km2 (12%) had medium soil degration, 1726.0 km2 (8.9%) had high to very high soil degradation, only 709.5 km2 (3.7%) had extreme soil erosion. The study area, in general, was exposed to a low risk of soil water erosion.
  • Keywords
    erosion; geographic information systems; hydrological techniques; rain; remote sensing; rivers; soil; water resources; ArcGIS environment; China; RMsed universal soil loss equation model; RUSLE model; geographic information systems; land use data; rainfall; remote sensing; soil classification; soil conservation; soil degration; soil erosion prediction; soil water erosion; statistical analysis; topographic data; upper Chaobai River basin; Chaos; Content addressable storage; Degradation; Equations; Geographic Information Systems; Predictive models; Rivers; Soil; Water conservation; Water resources;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006. IEEE International Conference on
  • Conference_Location
    Denver, CO
  • Print_ISBN
    0-7803-9510-7
  • Type

    conf

  • DOI
    10.1109/IGARSS.2006.280
  • Filename
    4241427