Estimating flooding extent at high return period for ungauged braided systems using remote sensing: a case study of Cuvelai Basin, Angola

A. Awadallah () and D. Tabet

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2015, vol. 77, issue 1, 255-272

Abstract: Floods are the most expensive natural hazard experienced in many places in the world. The current study aimed at estimating the flooding extent at high return periods in the Cuvelai Basin, southern Angola, where no flow, rainfall or accurate topographic data are available. The flooding study thus relies on remote sensing information: archival optical satellite images, data retrieved from the global flood detection system (GFDS) and Tropical Rainfall Measurement Mission data to help characterize flooding events and determine their extents for high return periods, well beyond the available remote sensing record. Landsat and Earth Observing-1 Mission satellite images are used as optical images. The GFDS provides a monitoring of ongoing flood events everyday. Comparison revealed that the GFDS values in the wetland areas are always less than the other satellite flooding extent by about 25 km 2 . Frequency analysis was undertaken on the annual maxima flooded areas for monitored GFDS locations using Gumbel distribution. The frequency analysis shows that the potential inundation areas for the 100-year flood event increase by 25 % (±5 %) more than the 10-year event. The remote sensing for the 2009 Landsat image is used to get approximately the flooded areas for the 10-year return period for the whole basin. To assess flooding areas for higher return periods such as the 100-year event, the flooded areas are increased based on the frequency analysis ratio results to give the 100-year inundation extents. Interpolation is undertaken for areas where no data are available from the GFDS website. The Cuvelai Basin inundation areas are thus estimated for non-recorded flooding events. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: Floods; Remote sensing; Flood frequency analysis; Flooding extent; Cuvelai Basin; Angola (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s11069-015-1600-6

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