Abstract:
Tackling the challenge of flood and gully erosion requires good understanding of factors that induces them. This study aims at assessing the magnitude and extent of flood and gully erosion in Imo state. Primary and Secondary data were acquired to model the flood and gully erosion vulnerability. Precipitation data was acquired from NIMET for the period of 1985 to 2015. Landsat TM, ETM+ and OLI were acquired from USGS Website for 1986, 2000 and 2015 respectively. Soil data were also acquired from the Harmonised World Soil Database. Scanned geology map for Imo state was acquired from the Nigeria Geological Survey Agency. SRTM DEM data was acquired from the USGS Website. Rainfall trend for 1985 to 2015 trend were plotted to show their annual total and mean pattern. Standard Precipitation Index (SPI) was used to identify the flood years between 1985 and 2015. Multicriteria analysis and fuzzy logic were used to make the flood risk assessment. Revised Universal Soil Loss Equation (RUSLE) was used to determine the soil erosion. Criteria such as rainfall, runoff, slope, distance to drainage, drainage density, soil type, geology formation types and land use. The criteria were reclassified according to their impact in causing flood within Imo State. The result from the fuzzy overlay was used to create the flood risk map which shows that 62.9% of Imo State lies in low risk area, 17.2% lies in the medium risk area and 19.9% lies in the high risk area. 214 towns and villages lies in the low risk areas, 64 towns and villages lies in the medium vulnerable area and 52 towns and villages lies in the high vulnerable areas. The soil loss amount generated ranges from 0 to 123,922 ha/ton/yr. The erosion risk map was classified into very low, low, moderate, high and very high risk zones. 87.3% of the Imo state lies in the very low risk area, 8.1% of the Imo state lies in the low risk area, 4.3% lies in the moderate risk area, 0.3% lies in the high risk area and 0.2% lies on the very high risk area. Soil loss was more prevalent in Northern part of Imo State. The effects were lesser in the southern parts as they are low lying areas. A database was created for effective flood and soil erosion management.
