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Risk modelling of soil erosion in semi-arid watershed of Tamil Nadu, India using RUSLE integrated with GIS and Remote Sensing

机译:泰米尔纳德邦半干旱地区土壤侵蚀风险建模,印度利用GIS与遥感集成的风险

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Water-induced soil erosion is one of the challenging threats in various parts of the world, thus systematic investigations of soil loss risk are more crucial for sustainable agricultural production and water management. The present study was carried out to estimate the average soil loss in the Amravati watershed of Tamil Nadu state in South India using Revised Universal Soil Loss Equation (RUSLE) along with Geographical Information System (GIS) and Remote Sensing techniques. In this study, the rain gauge-based rainfall data were completely substituted with the CHIRPS datasets to compute the R factor, since it gives continuous surface rainfall data rather than location-based measurement. The estimated soil loss in the watershed was found to be in the range of 0-280.2 t/ha(-1)/yr(-1), in which about 64.7% of the watershed under very low erosion risk whilst about 12.9% of the area prone to moderately high-to-very high erosion risk. The maximum soil loss rate was identified in the Degraded forest with a mean loss of 59.51 t/ha(-1)/yr(-1) followed by the Degraded plantation (32.17 t/ha(-1)/yr(-1)), Scrubland/Wasteland (17.75 t/ha(-1)/yr(-1)), Current fallow (12.08 t/ha(-1)/yr(-1)), and Rainfed cropland (10.03 t/ha(-1)/yr(-1)). The study shows that the present land use / land cover and the landscape of the watershed have a great influence on soil loss. To check the efficiency of the RUSLE model for the assessment of soil erosion risk, the final derived output was validated with the use of 4k UHD Google Earth images.
机译:水诱导的土壤侵蚀是世界各地的挑战威胁之一,因此对土壤损失风险的系统调查对可持续农业生产和水管理来说更为重要。本研究进行了利用修订的通用土壤损失方程(限制)以及地理信息系统(GIS)和遥感技术,估计南印度泰米尔纳德州州泰米尔纳德州州的Amravati流域的平均土壤流失。在这项研究中,基于雨量的降雨数据完全被啁啾数据集取代以计算R因子,因为它给出了连续的表面降雨数据而不是基于位置的测量。发现分水岭中的估计土壤损失为0-280.2吨/该地区容易出现中度高至关上的侵蚀风险。在降解的森林中鉴定了最大土壤损失率,平均损失为59.51吨/小时(-1)/ Yr(-1),然后是降解的种植酸盐(32.17吨/哈(-1)/ Yr(-1) ),灌木/荒地(17.75 T / HA(-1)/ YR(-1)),电流休耕(12.08 T / HA(-1)/ YR(-1))和雨量农作物(10.03 T / HA( -1)/ Yr(-1))。该研究表明,目前的土地使用/陆地和流域的景观对土壤损失有很大影响。为了检查对土壤侵蚀风险评估的风险模型的效率,通过使用4K UHD Google地球图像验证了最终导出的产出。

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