Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS

Q3 Agricultural and Biological Sciences
Justin George Kalambukattu, Suresh Kumar
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引用次数: 24

Abstract

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.
基于RUSLE模型和GIS的喜马拉雅中部山区流域土壤侵蚀风险建模
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。利用遥感(RS)和地理信息系统(GIS)输入的修正通用土壤流失方程(RUSLE)模型,估算了印度北阿坎德邦中喜马拉雅流域的土壤侵蚀风险。在栅格GIS环境下,综合RUSLE因子(R、K、LS、C、P)估算流域土壤侵蚀危险区的空间分布。利用遥感卫星数据(IRS LISS III和LANDSAT-8)和数字高程模型生成RUSLE模型因子图。农业(59%)是主要的土地利用系统,其次是灌丛地(20%)。利用过去23年的降水资料估算了降雨侵蚀力(R)因子。利用SRTM DEM在这一高度崎岖的地形上生成坡长陡度因子。近70%的流域有陡坡到中陡坡(约40%)。对卫星数据进行解译,编制1:50 000比例尺的地形图。对各地貌单元的表层土壤样品进行分析,生成土壤可蚀性(K)图。流域土壤可蚀性因子范围为0.033 ~ 0.077。土壤侵蚀风险分析表明,流域土壤侵蚀风险等级分别为极低、低、中、中高、高和极高,分别为36.25%、9.31%、15.80%、15.27%、11.46%和11.89%。年平均侵蚀速率为65.84 t/ha/yr。预测土壤侵蚀速率从茂密混交林的3.24 t/ha/yr到开阔灌丛地的87.98 t/ha/yr。利用遥感和地理信息系统技术绘制的土壤侵蚀图可作为制定战略的工具,以便有效规划和执行流域内水土保持的各种管理和养护做法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Eurasian Journal of Soil Science
Eurasian Journal of Soil Science Environmental Science-Environmental Science (miscellaneous)
CiteScore
2.00
自引率
0.00%
发文量
40
审稿时长
16 weeks
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