首页> 外文期刊>Eurasian Journal of Soil Science >Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS
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Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS

机译:通过将RUSLE模型与GIS集成来对喜马拉雅中部山区流域的土壤侵蚀风险进行建模

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Soil erosion is one of the major cause of land degradation and is a serious threat to food security and agricultural sustainability. Revised Universal Soil Loss equation (RUSLE) model using remote sensing (RS) and Geographical Information Systems (GIS) inputs was employed to estimate soil erosion risk in a watershed of mid-Himalaya in Uttarakhand state, India. Spatial distribution of soil erosion risk area in the watershed was estimated by integrating various RUSLE factors (R, K, LS, C, P) in raster based GIS environment. RUSLE model factor maps were generated using remote sensing satellite data (IRS LISS III and LANDSAT-8) and Digital elevation model. Agriculture (59%) was found to be the dominant land use system followed by scrub land (20%) in the watershed. Rainfall erosivity (R) factor was estimated using past 23 years rainfall data. SRTM DEM was used to generate slope length –steepness (LS) factor in this highly rugged terrain. Nearly 70% of the watershed is having steep to moderately steep slope (>40%). Satellite data was interpreted to prepare physiographic map at 1:50,000 scale. Surface soil samples collected in each physiograpohic unit was analyzed to generate soil erodibility (K) map. Soil erodibility factor ranged from 0.033 to 0.077 in the watershed. Soil erosion risk analysis showed that 36.25%, 9.31%, 15.80%, 15.27%, 11.46% and 11.89% area of watershed falls under very low, low, moderate, moderate high, high and very high erosion risk classes respectively. The average annual erosion rate was predicted to be 65.84 t/ha/yr. The soil erosion rates were predicted to vary from 3.24 t/ha/yr in dense mixed forest cover to 87.98 t/ha/yr in open scrub land. The soil erosion map thus generated employing remote sensing and GIS techniques, can serve as a tool for deriving strategies for effective planning and implementation of various management and conservation practices for soil and water conservation in the watershed.
机译:土壤侵蚀是土地退化的主要原因之一,对粮食安全和农业可持续性构成严重威胁。使用遥感(RS)和地理信息系统(GIS)输入的经修订的通用土壤流失方程(RUSLE)模型,用于估算印度北阿坎德邦喜马拉雅中部流域的土壤侵蚀风险。通过在基于栅格的GIS环境中综合各种RUSLE因子(R,K,LS,C,P)来估算流域水土流失风险区的空间分布。使用遥感卫星数据(IRS LISS III和LANDSAT-8)和数字高程模型生成RUSLE模型因子图。发现农业(59%)是主要的土地利用系统,其次是流域中的灌木土地(20%)。使用过去23年的降雨数据估算了降雨侵蚀力(R)因子。 SRTM DEM用于在这种高度崎terrain的地形中生成边长-陡度(LS)因子。近70%的流域具有陡峭至中等陡峭的坡度(> 40%)。解释卫星数据以准备1:50,000比例的地形图。分析在每个理疗单位中收集的表层土壤样品,以生成土壤可蚀性(K)图。流域的土壤侵蚀因子在0.033至0.077之间。水土流失风险分析表明,流域面积分别有36.25%,9.31%,15.80%,15.27%,11.46%和11.89%属于极低,低,中,高,中和高侵蚀风险等级。预计年平均侵蚀速率为65.84吨/公顷/年。预计土壤侵蚀速率从茂密的混交林覆盖面积的3.24吨/公顷/年到开阔灌木地的87.98吨/公顷/年不等。因此,利用遥感和GIS技术生成的土壤侵蚀图可作为一种工具,用于推导有效规划和实施流域水土保持的各种管理和保护措施的战略。

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