Flood hazard assessment by means of remote sensing and spatial analyses in the Cuvelai basin : case study, Ohangwena region, northern Namibia

Sammanfattning: Popular summary: Amongst other affected countries, Namibia endures seasonal floods in different parts of the country namely, Karas, Kavango, Caprivi, Ohangwena, Omusati, and Oshana regions. However, the study concentrated only on the floods within the Ohangwena region. Major flooding in this region became eminent from 2007, and only rapid appraisal assessments were conducted. As a consequence, up-to-date post flood information is not available nor do mitigation measures to cater for the floods. Therefore, the study aim was to assess the impact of the floods and determine flood hazard areas using satellite images and Geographical Information Systems (GIS). The main data used in the analysis was the Oshana water area for years from 2003 to 2010. This was extracted from the Landsat satellite images by means of Modified Normalized Difference Water Index (MNDWI) method. The effectiveness of the MNDWI to extract water from the images was assessed by means of accuracy matrix, with data obtained via homestead survey. The other data used was the spatial location of homesteads in the area, digitized from the 2007 orthophoto. Analysis was conducted by means of spatial overlaying of delineated Oshana water and the homesteads. Those homesteads that are within the Oshana flood waters were considered as flooded homesteads and the rest were considered as non-flooded homesteads. Further analyses were conducted by calculating the frequency of flooding per homesteads and the percentage of homesteads flooded per village. Lastly, analysis was conducted on the impacted villages to determine the geographical distribution of the impacted villages, whether they are clustered or randomly distributed. Based on the assessment, a soaring increase in the water area was detected as from 2008 to 2010, specifically the introduction of significant water towards the northeast side of the study area. Similarly, the number of impacted homesteads increased significantly from 2003 to 2008, mostly toward the east of the study area. The most affected villages were also clustered on the northern side of the study area, this are areas that are usually not prone the Cuvelai annual flooding. Considering the high accuracy obtained for the delineated water, one can accurately map the flooded areas and eventually determine the affected homesteads. Thus, the result can aid in identifying flood impact areas that require humanitarian assistance during and post flooding. Moreover, it can help in allocating further studies to the considerably impacted villages. However, the limitation the study was that the actual number of homesteads flooded per villages was unknown to further validate the flooded homesteads results obtained from this study. In addition, the method depend primary on satellite images, thus unavailability of cloud free images might hampered the study. On the clouds limitation, alternatively, imaging radar data can be used to detect water bodies to ease the problem of clouds.