Mapping Erosion Susceptibility Using Multi-Criteria Decision-Making and Geographic Information Systems in the Las Flores Watershed, Chiapas, Mexico

Currently, water erosion represents one of the main environmental degradation issues in tropical watersheds. Therefore, the main objective of this research was to determine the spatial distribution of erosion susceptibility by integrating multi-criteria decision-making (MCDM) and Geographic Information Systems (GIS) in the “Las Flores” Watershed, Chiapas, Mexico, which covers an area of 2519 km2. The Analytic Hierarchy Process (AHP) was implemented in combination with twelve spatial variables: watershed curve number (CNW), topographic wetness index (TWI), sediment transport index (STI), slope (SLP), soil type (STF), distance to rivers (DTR), precipitation (PCP), drainage density (DDN), terrain curvature (CUR), land use and vegetation cover (LCI), normalized difference vegetation index (NDVI), and normalized difference water index (NDWI). The model was evaluated using a Receiver Operating Characteristic (ROC) curve based on 135 erosion points identified through multitemporal image analysis. The results reveal that the variables of SLP (19.30%), PCP (16.70%), CNW (11.89%), and LCI (10.04%) had the most influence on the modeling of erosion susceptibility. In this regard, the high and very high susceptibility categories encompass a significant portion of the basin’s territory, representing 29.20% (735.41 km2), mostly concentrated in areas near the watershed, where the highest precipitation occurs, soils with shallower layers, and areas dedicated to pastures and agriculture. The model achieved very good predictive performance, with an area under the ROC curve (AUC) of 0.82. Therefore, the resulting zoning indicates that spatial modeling can reliably represent erosion susceptibility, serving as an essential technical tool for decision-makers to optimize resource distribution and develop intervention plans in high-priority areas.