Quantitatively estimating soil erosion with an integration of geographic information system (GIS) and the revised universal soil loss equation (RUSLE) under four different exposed soil proportion scenarios caused by f...Quantitatively estimating soil erosion with an integration of geographic information system (GIS) and the revised universal soil loss equation (RUSLE) under four different exposed soil proportion scenarios caused by forest management practices was studied at Jianchang Forest Farm. The GIS provided means of input data generation required by RUSLE model and allowed a spatial assessment of the erosion hazard over the study area. Four exposed soil proportion scenarios of 5%, 10%, 20% and 30% were tested with the GIS-based RUSLE model to evaluate soil erosion hazard. The predicted soil erosion potentials were classified into five categories in order to provide valuable aids for management planning.展开更多
文摘Quantitatively estimating soil erosion with an integration of geographic information system (GIS) and the revised universal soil loss equation (RUSLE) under four different exposed soil proportion scenarios caused by forest management practices was studied at Jianchang Forest Farm. The GIS provided means of input data generation required by RUSLE model and allowed a spatial assessment of the erosion hazard over the study area. Four exposed soil proportion scenarios of 5%, 10%, 20% and 30% were tested with the GIS-based RUSLE model to evaluate soil erosion hazard. The predicted soil erosion potentials were classified into five categories in order to provide valuable aids for management planning.
