Spatial Modeling of Flood-Prone Areas Through Multi-Criteria Analysis Applied to a Brazilian Municipality - Nicomedes, Nícholas de Paula; Nery, Liliane Moreira; Gomes, Gabriela; Cunha e Silva, Darllan Collins da (Journal of Environmental Science and Engineering Technology, 2025)
This study applied a spatial multi-criteria analysis (MCA) integrated with Geographic Information Systems (GIS) to identify flood risk areas in Sorocaba, Brazil. The variables—slope, elevation, flow accumulation, soil susceptibility, and land use and land cover (LULC)—were standardized, reclassified into vulnerability levels, and integrated using the categories very low, low, moderate, and high, resulting in a flood risk map. Additionally, a spatial overlap analysis between LULC classes was performed to identify occupation patterns in risk areas. The areas classified as high and moderate risk are concentrated in low-altitude regions, characterized by high environmental susceptibility and intense anthropogenic occupation, especially along the Sorocaba River and its tributaries. In contrast, very low-risk zones are located in forested or silvicultural areas, associated with higher altitudes and greater infiltration capacity. The spatial overlap between risk and land use revealed that non-vegetated surfaces (38.0%) and pasture/agriculture areas (58.6%) predominate in the highest-risk zones, indicating low infiltration and increased surface runoff. These results demonstrate that flood vulnerability arises from the interaction between geomorphological and anthropogenic factors, reinforcing that land cover changes and environmental degradation intensify hydrological events. The proposed model proved efficient, transparent, and replicable, providing technical support for territorial planning, disaster risk management, and the formulation of preventive public policies.