TOPOGRAPHIC-BASED FRAMEWORK FOR FLOOD VULNERABILITY CLASSIFICATION: A CASE OF NIGER STATE, NIGERIA

Abstract

Flood vulnerability classification often provides insights on measures aimed at mitigating flood-induced disasters, by revealing the factor(s) contributing to regional flood vulnerability. In this present study, the regional flood vulnerability classification within Niger State, Nigeria, which is overwhelmed by annual flooding event is considered as the study area. The study required the pre-processing of spatial data sets within a Quantum Geographic Information System (QGIS) environment to extract topographic flood causative factors depicting the levels of flood vulnerability in various regions within the study area. The extracted features were employed to classify regions based on their relative vulnerability to potential floods. In assessing the accuracy of the obtained results, Flood Inventory (record of flooding events) from 2006-2017 was utilized. The results showed that regional vulnerability classification was accurately represented using the slope than the elevation feature. Thus, giving preference to the slope-based classification to provide guidance for identifying the most reliable and suitable practical means of regional flood mitigation within the study area