In general, agricultural intensification and human intervention lead to the soil erosion problem. Remarkably, marginal alluvial plains of vast Indo-Gangetic plain consistently suffer a great peril of land degradation in and around the Yamuna-Chambal valley. This is probably due to the geologic evolution of the landscape. Geomorphology and the land forms developed in and around the studied countryside themselves indicate the erosional processes. However, quantification of erosion rates and mapping of most intense erosion areas in and around Agra, Firozabad and Etawah district of Uttar Pradesh have been carried out using geospatial technology. A Geographic Information System (GIS)-based Revised Universal Soil Loss Equation (RUSLE) model was used to analyse grid cell–based erosion rates by incorporating all the crucial factors, i.e. rainfall, slope, soil, length slope, cover management and practice management factors. An average annual soil loss rate of 445 t ha⁻¹ year⁻¹ was observed in the study area. Moreover, the intensity-based categorization reveals that 64% area is at high erosion risk. The Google Earth imagery along with Triangular Irregular Network (TIN) model presents the erosion-associated features and slope gradient of the Yamuna River watershed further validates the results obtained in the present study.

中文翻译：

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利用RUSLE评估亚穆纳河洪水平原及其周围地区潜在的土壤侵蚀风险

通常，农业集约化和人为干预会导致水土流失问题。值得注意的是，印度洋-恒河大平原的边缘冲积平原在亚穆纳-尚巴尔山谷及其周围地区始终遭受着巨大的土地退化危险。这可能是由于景观的地质演化所致。在所研究的乡村中及其周围发展的地貌和土地形态本身表明了侵蚀过程。但是，北方邦的阿格拉，费罗扎巴德和以太瓦地区及其周围地区侵蚀率的定量化和最强烈侵蚀区域的制图已经使用地理空间技术进行了。基于地理信息系统（GIS）的修订的通用土壤流失方程（RUSLE）模型通过结合所有关键因素（例如降雨，坡度，土壤，坡度，覆盖管理和实践管理因素。年平均土壤流失率为445吨公顷在研究区域观察到- ¹年- ¹年。此外，基于强度的分类显示64％的区域处于高侵蚀风险。Google Earth影像与不规则三角网（TIN）模型一起显示了亚穆纳河流域的侵蚀相关特征和坡度，这进一步验证了本研究获得的结果。