GIS-Based Climate Change Induced Flood Risk Mapping in Uhunmwonde Local Government Area, Edo State, Nigeria
Obot Akpan Ibanga, Osaretin Friday Idehen
International Journal of Environment and Climate Change · pp. 8–23 · Published 25 Jul 2020
10.9734/ijecc/2020/v10i930225Abstract
Introduction: Flood is one of the climate change induced hazards occurring in most parts of the world. It exposes humanity and many socio-ecological systems to various levels of risks. In Nigeria, extreme rainfall events and poor drainage system have caused inundation of several settlements to flooding. To contain the disaster, risk mapping were among the measures recommended. Aims: The aim of this paper is to highlight flood risk zones (FRZ) in Uhunmwonde Local Government Area (LGA), Edo State, Nigeria. Methodology: Flood risk (FR) was mapped using hazards and vulnerability and implemented using geographic information system (GIS)-based multi-criteria analysis analytic hierarchy process (MCA-AHP) framework by incorporating seven environmental and two socio-economic factors. Elevation, flow accumulation, soil water index of wettest quarter, normalized difference vegetation index, rainfall of wettest quarter, runoff of wettest quarter and distance from rivers constituted the hazard component while population density and area of agricultural land use was the vulnerability layer. The climate change induced flood risk was validated using the responses of 150 residents in high, moderate and low flood risk zones. Results: The resulting flood risk map indicated that about 40.4% of Uhunmwonde LGA fell within high flood risk zone, 35.3% was categorized under moderate flood risk zone whereas low flood risk zone extended up to about 24.3% of the LGA. The high number of respondents who reported occurrence of flooding with frequency being very often and the fact that flooding was a very serious environmental threat during on-the-spot field assessment validated the generated climate change induced flood risk. Conclusion: The utilitarian capabilities of GIS-based MCA-AHP framework in integrating remotely-sensed biophysical and climate change related flood inducing indicators with socio-economic vulnerabilities to arrive at composite flood risk was demonstrated.
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