Soil erosion has both on-farm and off-farm effects. On-farm, reduced soil depth can decrease land productivity, while off-farm, sediment transfer can damage streams, lakes, and estuaries. Therefore, optimal soil erosion modeling is a crucial first step in soil erosion research. One of the most important aspects of this modeling is the accuracy and applicability of the soil erosion factors used. Various methods for calculating these factors are discussed in the literature, but no single method is universally accurate. After an extensive review of the literature, we propose using the existing revised universal soil loss equation (RUSLE) factors for global application. Additionally, we conducted a grassroots-level experiment to demonstrate the effectiveness of the proposed methods. RUSLE is identified as the most suitable model for global-scale soil erosion modeling. We evaluated the potential impacts of climate and land use and land cover (LULC) by utilizing shared socio-economic pathways (SSPs) alongside projected LULC scenarios. A suitable general circulation model (GCM) was selected after comparing it with recorded data from a base period. This model was validated with experimental observations, confirming its effectiveness. This review article outlines the future direction of soil erosion modeling and provides recommendations.Graphical AbstractThe graphical abstract visually summarizes the comprehensive methodology and key findings associated with optimal soil erosion modeling and management. It highlights a structured approach, beginning with identifying optimal methods for assessing soil erosion factors: Rainfall and Runoff Erosivity (R), Soil Erodibility (K), Slope Length and Steepness (LS), Cover and Management (C), and Support Practice (P) integral components of the Revised Universal Soil Loss Equation (RUSLE). It illustrates the detailed methodological framework, emphasizing selecting suitable climate models for projecting future R factors, combined with projected land use and land cover (LULC) scenarios derived from Shared Socio-economic Pathways (SSPs). The scenarios shown range from lower emissions (SSP 126) to higher emissions (SSP 585), indicating progressive increases in future erosion risk. Moreover, it explicitly ties the research findings to policy recommendations, underscoring a holistic approach aligning soil conservation with Sustainable Development Goals (SDGs): specifically, Climate Action (SDG 13), Life on Land (SDG 15), and Zero Hunger (SDG 2). Suggested measures include integrating soil erosion control into broader policy frameworks, promoting sustainable land management practices such as agroforestry and contour plowing, and fostering policy integration and collaboration to enhance conservation effectiveness. Overall, the graphical abstract succinctly depicts how climate change, socio-economic dynamics, and LULC variations amplify future soil erosion risks, reinforcing the need for targeted, sustainable, and integrated soil conservation strategies globally.

来源平台：EARTH SYSTEMS AND ENVIRONMENT