Nature-based solutions to combat flooding in coastal region of Bangladesh using spatial multi-criteria analysis and remote sensing techniques

Climate change is causing more frequent and intense rainfall, storms, and floods, challenging traditional flood control measures. In response, Nature-Based Solutions (NBS) have gained attention as a flexible and effective way to reduce flood risks while offering additional environmental and social benefits. However, most existing studies focus only on either small-scale or large-scale NBS, and implementation is often confined to urban or rural areas. This narrow approach is insufficient in a hydrologically connected urban-rural catchment, where diverse geography and land use patterns amplify compound flood risks. This study addresses these challenges by developing a holistic approach that integrates multi-scale NBS across connected rural and urban areas. This is especially important for cities like Chittagong, Bangladesh, where space is limited and stormwater from the countryside flows through the inadequate urban drainage systems to the receiving basin. Using Spatial Multi-Criteria Analysis (SMCA), the Analytical Hierarchy Process (AHP), and Geographic Information Systems (GIS), we first mapped flood hazard, based on elevation, rainfall, distance to river, slope, drainage density, soil texture, and geology. The study area was classified into five hazard zones: Very Low (9.24 %), Low (16.84 %), Moderate (23.87 %), High (29.28 %), and Very High (20.77 %). The model demonstrated excellent predictive accuracy, achieving 91.30 % ROC-AUC. Then, a vulnerability map was created using four key influencing factors (land use/land cover, population density, distance to road and NDVI). By multiplying flood hazard and vulnerability data, we generated a detailed Flood Risk Zone (FRZ) map, which shows five risk zones: Very Low (21 %), Low (26 %), Moderate (25 %), High (19 %), and Very High (9 %). Comprehensive Geospatial Analysis (CGA) revealed in-depth geophysical and land use characteristics of each FRZ. Finally, using Qualitative Comparative Analysis (QCA), the study identified the best types of NBS for each FRZ, based on the CGA result. The synergistic integration of multi-scaled NBS with existing engineering solutions offers a holistic and comprehensive approach that could collectively reduce surface runoff and inundation in the study area. This research provides clear, location-specific information that can help planners and decision-makers choose and place NBS where they are most needed. The approach can also be used in similar locational contexts and flood risks.