A SYSTEMATIC REVIEW OF SOIL EROSION SUSCEPTIBILITY: TRENDS AND INSIGHTS FROM 2010 TO 2023

Abstract

Soil erosion is a significant threat to soil, a vital natural resource essential for human life. Mapping soil erosion susceptibility is an effective approach to identify vulnerable areas and support soil conservation efforts. This study reviews 339 articles published in English between 2010 and 2023 that focus on soil erosion susceptibility worldwide. The review aims to analyze previous research trends and to determine the most effective models and conditioning factors for future soil erosion susceptibility mapping. The methodology involved systematically collecting and examining published studies, with a focus on the models applied and conditioning factors used for erosion assessment. The results reveal a growing number of publications over the last decade, with India contributing the highest proportion (24%). Among the models, Random Forest emerged as the most widely used method (28.8% of articles), while slope gradient was the predominant conditioning factor (89.2%). The review also highlights the integration of modern technologies, such as Geographic Information Systems (GIS) and Remote Sensing (RS), which enhance the accuracy of erosion susceptibility maps. Overall, the findings suggest that combining advanced machine learning models with key environmental factors significantly improves soil erosion prediction, thereby aiding informed decision-making in land management and soil conservation.