###### Abstract
Over the past century, land degradation has intensified, resulting in the loss of approximately twenty-four million tons of productive topsoil from agricultural lands worldwide [24]. According to the United Nations Food and Agriculture Organization, 90% of the Earth's precious topsoil will likely be at risk by 2050 [25]. Traditional soil erosion evaluation methods based on field surveys are labor-intensive, expensive, and time-consuming [26]. Therefore, a numerical evaluation technique is often desirable for developing regional management strategies to estimate the severity of soil erosion and quantify the amount of soil loss, enabling better management strategies to be developed. This provides an alternative way to study and simulate the long-term and short-term consequences of land use activities on the natural system [27] and to assess other land management strategies in gauged and ungauged basins. Effective use of land resources can also be achieved by developing several land use cases and evaluating their results using soil erosion models [28; 29; 30]. These models have been developed and used for more than seven decades, with examples including the Water Erosion Prediction Project (WEPP) [31; 32; 33], the Soil and Water Assessment Tool (SWAT) [31; 34], the revised model of Morgan and Finney (RMMF) [35], the Soil Erosion Model for Mediterranean Regions (SEMMED) [31], and the European Soil Erosion Model EUROSEM. There are several levels of complexity in these models, with the most popular empirical model used to estimate soil erosion being the Universal Soil Loss Equation (USLE) [26]. The USLE model was revised and digitized in the early 1990s to produce the Revised Universal Soil Loss Equation (RUSLE), which is widely used to predict soil erosion [36; 37; 38]. The Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) [39; 40] are mostly used worldwide under a variety of circumstances. The three categories of soil erosion models are empirical, conceptual (partially empirical/mixed), and physical, with USLE and RUSLE being classified as empirical and conceptual (partly empirical) based models [41]. The RUSLE model has been used for more than 80 years due to its good reliability, ease of applicability, high degree of flexibility, correctness, and data accessibility [42; 43; 44; 45; 46; 47; 48]. The current study used RUSLE Model and Geo-Information tools to quantify soil erosion. The aim of this study is to utilize the revised Universal Soil Loss Equation and geographic information techniques for the following purposes: (i) to calculate the potential soil loss in the Jhelum River watershed, (ii) to create maps of soil erosion risk and severity, and (iii) to identify areas with critical soil erosion conditions that necessitate immediate conservation and land management measures. The study shall help the authorities in the adaptation of adequate measures and best management practices for soil and water conservation in the zones with high erosion risk. The method of the applied RUSLE model in combination with GIS can be transferred at the desired rate of complexity to similar catchments in the south Asian region.