In this study, a GIS-based integration of multi-criteria analysis and the Height Above Nearest Drainage (HAND) terrain model was adopted to delineate potential flood hazard zones and vulnerability of the Ogun River Basin, Nigeria. Flood causative factors were used as input for multi-criteria analysis using an analytical hierarchy process (AHP) and weighted overlay ArcGIS 10.5 to generate potential flood hazard zones. The flood hazard map was overlaid with demographic population data to identify areas where vulnerable people and assets are located. The results show the varying degree of people’s susceptibility to flood hazards. Flood hazard zones were classified into Very High, High, Moderate, Low and Very Low, with area coverage of 1269.40, 14139.50, 7188.40, 17.41 and 0.85 km², respectively (occupied by 466 290, 355 542, 69 554, 231 and 54 people, respectively). This study serves as a preliminary guide for early warning and policy decision-making for flood disaster risk reduction.

A Review of Flood Risk Analysis in Nigeria

Frequencies of extreme precipitation are likely to increase under changing climate, which may result in more damage to exposed properties in the future. This study presents a methodological framework for estimating potential economic damages to flood hazards based on current and future climatic information using loss functions. Loss functions for Sri Lanka’s residential structure categories were derived from empirical data through a questionnaire survey in Kelani River basin, Sri Lanka. Flood prediction was done using a bias-corrected 5-year time series of the Japanese Meteorological Research Institute (MRI)’s Regional Climate Model (RCM) precipitation data for current (1985–1989) and near future climate (2028–2032), and a hypothetical future climate projection using a 10% increase in current high rainfall events. The authors simulated extreme river discharges and inundation depths for potential current and future flood events using similar hydrologic element response (SHER) and geographic information system (GIS) grid-based models, respectively. Simulated extreme flood hazards were integrated with the established loss functions and exposures to simulate the potential damages using a raster-based spatial model. Results revealed a little reduction in the MRI projected near future discharges and flood damages, but an increase in the frequency of flood events compared to the current projection. However, the hypothetical projection showed a 10.2% increase in potential damages in the future climate compared with the current climate. Future adaptation measures in the river basin are suggested.

The continuous increase in damages to flood disasters globally has informed the need to assess vulnerability of built-up exposures for future flood risk reduction. The aim of this paper is to understand the contributions of some important variables in flood damage processes and develop loss functions for global building types, for the estimation of flood economic damages in Chao Phraya river basin, Thailand. We obtained empirical damage data (118 samples) through questionnaire survey in the study area for analysis. Using multiple linear regressions analysis, we generated loss functions for the aggregated residential building incorporating multiple damage factors. Further, disaggregated vulnerability curves (as a function of water depth) were established using logarithm function for three global building types in the study area. Results showed that, under flood condition in the study area, water depths and building age are very important damage factors, other variables are also emphasized. The loss models show maximum predicted vulnerability indices of 0.36, 0.30 and 0.10 for wooden, concrete frame and unreinforced masonry, and reinforced concrete moment frame, respectively. These functions can be used for modeling flood damage, for future disaster risk reduction and for risk comparison across countries.