Spatial Evaluation of Flood Risk Using Geospatial and Multi-Criteria Decision Analysis (MCDA): A Case Study in Obio-Akpor, Rivers State, Nigeria

Abstract

This study assesses flood risk in Obio-Akpor, Rivers State, Nigeria, using a Geospatial and Multi-Criteria Decision Analysis (MCDA) approach, incorporating Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP). The research aims to evaluate flood risk by analyzing critical environmental factors, including Digital Elevation Model (DEM), Land Use/Land Cover (LULC), slope, drainage density, flow accumulation, rainfall, geological type, Normalized Difference Water Index (NDWI), and curvature. This study addresses the need for a reliable flood risk assessment tool to aid urban planning and disaster management in flood-prone areas. The methodology involved processing spatial data with MCDA and AHP, analyzed using ArcGIS 10.6. Data were sourced from the United States Geological Survey (SRTM), European Space Agency (Sentinel-2 imagery), Nigeria Geological Survey Agency (geological map), and Nigerian Meteorological Agency (rainfall data). AHP was used to assign weights to flood risk factors based on expert judgment, and the reclassified data generated a flood risk map. The results indicate that 33% of the area is at low risk, 37% at moderate risk, 20% at high risk, and 10% at very high risk. The study concludes that DEM, LULC, and slope are the most significant factors influencing flood risk, while rainfall, geology, NDWI, and curvature have a lesser impact. These findings highlight the importance of elevation and land use in flood risk assessment and identify areas vulnerable to flooding. This research provides valuable insights for urban planners and policymakers, offering a robust tool for managing flood risks and enhancing resilience in vulnerable regions.