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Integrated Remote Sensing and Geographic Information System Based RUSLE Modelling for Estimation of Soil Loss in Western Himalaya, India

机译:基于遥感与地理信息系统的综合RUSLE模型估算印度喜马拉雅山西部土壤流失

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摘要

Soil loss due to water erosion was estimated in Kangra region of western Himalaya using revised universal soil loss equation modelling (RUSLE) in conjunction with Remote Sensing (RS) and Geographic Information Systems (GIS). The various parameters such as rainfall erosivity (R), soil erodibility (K), topographic factor (LS), crop management factor (C) and support practice factor (P) were derived using standard techniques. The study revealed that forest cover, crop land and scrub/grass land constitute 87.4 of soil erosion susceptible area. The rate of depletion of soil was estimated at 25.63 t/ha/yr. It was highest in stony/barren land (60.3 t/ha/yr) and lowest in case of tea garden (16.09 t/ha/yr). It was felt that there is a need of implementation of soil and water conservation measures in the region to curb the soil loss. The undulating nature of terrain was observed as the main contributing factor for soil erosion. It was concluded that RS and GIS based RUSLE model can be efficiently used in mountainous regions to determine the status and extent of soil erosion.
机译:在喜马拉雅山西部的Kangra地区,使用修订后的通用土壤流失方程模型(RUSLE)结合遥感(RS)和地理信息系统(GIS)估算了水土流失造成的土壤流失。采用标准技术推导了降雨侵蚀因子(R)、土壤可蚀性(K)、地形因子(LS)、作物管理因子(C)和支撑实践因子(P)等各种参数。研究表明,森林覆盖率、农田和灌木/草地占土壤侵蚀易发面积的87.4%。土壤枯竭率估计为25.63吨/公顷/年。石质/贫瘠土地的产量最高(60.3吨/公顷/年),茶园最低(16.09吨/公顷/年)。人们认为有必要在该地区实施水土保持措施,以遏制土壤流失。地形的起伏性是造成水土流失的主要因素。结果表明,基于RS和GIS的RUSLE模型可以有效地用于山区土壤侵蚀的现状和程度。

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