FLOOD LEVEL MAPPING FROM DIGITAL ELEVATION MODEL (DEM) THROUGH REMOTE SENSING/GIS IN YOLA CATCHMENT AREA, NORTHERN UPPER BENUE TROUGH, NIGERIA

Abstract

Yola catchment has recently experienced extreme climatic conditions attributed to climate change, leading to a substantial increase in rainfall intensity and, consequently, more frequent flooding in the region. Effective management of such disasters can be achieved through the utilization of precise datasets, such as Digital Elevation Models (DEMs), to delineate flood levels. DEMs are preferred due to their accessibility and lower computational demands in modeling applications. The topographic data derived from DEMs serve as crucial input parameters for comprehensive flood level mapping. Methods based on DEMs facilitate the identification of areas that are geomorphologically susceptible to flooding. In this study, DEM-based techniques were utilized to delineate areas that are susceptible to flooding due to their geomorphological characteristics. DEM data from SRTM satellite imagery were processed using Arcgis10.6 to categorize flood level areas according to the terrain and landform characteristics of the study area. The DEM classified flood levels into two categories were imported into ArcGIS 10.6 and reclassified. The analysis revealed two classifications of flood levels: the most floodable areas, which constitute 33.3% of the study area and cover 170.6 km², impacting nine villages, and the less floodable areas, which account for 25.41% of the study area, covering 130.1 km² and affecting twenty villages. This flood level mapping is intended to enhance awareness among residents, prioritize land development, and improve emergency preparedness, including aid and relief operations in areas at high risk of flooding in the future.