Abstract

Flooding is one of the disasters that are common in our towns and villages. It occurs as a result of heavy or continuous rainfall over a period of time. Occurrence of flood damages our valuable infrastructure such as buildings, roads, bridges, and schools, churches etc. The study area being a coastal region is confronted with frequent flooding and the extent of damage, and contributing factors has not been fully studied, particularly in applying remote sensing and geographic information system. Also, very little information is known about the combine impacts of urbanization and climate change on urban flooding in the area. Hence this study was aimed at evaluating the impact of climate change and urban development on urban flooding in South – South Nigeria using geospatial techniques. Datasets utilized for the study includes; land use/ land cover derived from Landsat satellite data, soil map, slope model, soil infiltration rate, impervious surface derived from vegetation indices, distance from river, precipitation, and surface temperature data. These datasets were processed into common coordinate system. Landsat data of four epochs (1990 – 2020) was used to map urbanization. Accordingly, the variations in climate variables were investigated using NiMET reported and the satellite derived values. Flood vulnerability zones was determined using multi-criteria analysis implemented in ArcGIS weighted overlay tool. The study observed that urbanization increases from 1990 to 2020, which also increase impervious surfaces, making the area more vulnerable to flooding. In addition, wetland and vegetation cover are being replaced by built-up thereby decreasing the ability of wetland to retained flood water. The lowest rainfall was in 1990 with value 293.70mm and the highest was in 2000 with value 454.90mm. There is general variation of rainfall and temperature from 1990 – 2020 due to climate change. Total built-up at risk was 8873.55ha with most of them situated along the river banks. Geospatial technology is suitable for urban flood vulnerability modeling. For further study, it is recommended that high spatial resolution image should be use to map trends in urbanization. In addition, drainage density should be integrated in flood vulnerability modeling.

Full Text
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