The Revised Universal Soil Loss Equation (RUSLE) model by using a large-scale soil mapping dataset, remote sensing, and GIS techniques were adopted to determine the soil erosion vulnerability in part of South Deccan Plateau, India. Based on the detailed soil survey information, 11 soil series were identified, and R, K, LS, C, P factors were computed to assess the soil erosion. Results revealed that annual soil loss was extremely severe (> 40 t/ha/yr) and very severe (20–40 t/ha/yr) in 447.2 ha (15.19%) and 314.3 ha (10.68%) in kharif and 502.73 ha (17.1%) and 907.74 ha (30.8%) in rabi season, respectively. Among the soil series, Mittapalle (MTP) series (17.9%) was highly prone to erosion followed by Venukayagayyapalle (VGP) (16.55%) and Inagalur (IGR) (13.57%) series in both seasons. The Weighted Index Overlay technique was adopted to estimate the soil erosion probability zones and the result showed that erosion risk was high in 8.90% area, medium in 55%, and low in 35% area. Spatial assessment of soil erosion using plot-wise information is a key factor for identifying site-specific suitable soil conservation measures for sustainable crop production.

利用大规模土壤测绘数据集、遥感和GIS技术，采用修订后的通用土壤流失方程（RUSLE）模型来确定印度南德干高原部分地区的土壤侵蚀脆弱性。根据详细的土壤调查信息，确定了11个土壤系列，并计算了R、K、LS、C、P因子来评估土壤侵蚀。结果显示，年土壤流失极为严重（> 40吨/公顷/年），极重度（20-40吨/公顷/年）在447.2公顷（15.19％）和314.3公顷（10.68％）夏播和502.73公顷(17.1%) 和 907.74 公顷 (30.8%) 在狂犬病季节，分别。在土壤系列中，Mittapalle (MTP) 系列 (17.9%) 极易受到侵蚀，其次是 Venukayagayyapalle (VGP) (16.55%) 和 Inagalur (IGR) (13.57%) 系列。采用加权指数叠加技术估计土壤侵蚀概率区，结果表明侵蚀风险在8.90%区域为高，55%为中等，35%区域为低。使用地块信息对土壤侵蚀进行空间评估是确定针对可持续作物生产的针对特定地点的合适土壤保持措施的关键因素。