Modeling Flood Hazard Zones at the Sub-District Level with the Rational Model Integrated with GIS and Remote Sensing Approaches

Water

Daniel Asare-Kyei¹  Gerald Forkuor³  Valentijn Venus² 

[1] United Nations University, (UNU-EHS), UN Campus, Platz der Vereinten Nationen 1, 53113 Bonn, Germany;Department of Natural Resources, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Hengelosestraat 99, P.O. Box 217, 7500 AE Enschede, The Netherlands; E-Mail:;Department of Remote Sensing, University of Wuerzburg, 97074 Wuerzburg, Germany; E-Mail:

关键词: community;    flood hazard index;    GIS;    mapping;    West Africa;    rational model;    runoff;   

DOI  :  10.3390/w7073531

来源: mdpi

【 摘 要 】

Robust risk assessment requires accurate flood intensity area mapping to allow for the identification of populations and elements at risk. However, available flood maps in West Africa lack spatial variability while global datasets have resolutions too coarse to be relevant for local scale risk assessment. Consequently, local disaster managers are forced to use traditional methods such as watermarks on buildings and media reports to identify flood hazard areas. In this study, remote sensing and Geographic Information System (GIS) techniques were combined with hydrological and statistical models to delineate the spatial limits of flood hazard zones in selected communities in Ghana, Burkina Faso and Benin. The approach involves estimating peak runoff concentrations at different elevations and then applying statistical methods to develop a Flood Hazard Index (FHI). Results show that about half of the study areas fall into high intensity flood zones. Empirical validation using statistical confusion matrix and the principles of Participatory GIS show that flood hazard areas could be mapped at an accuracy ranging from 77% to 81%. This was supported with local expert knowledge which accurately classified 79% of communities deemed to be highly susceptible to flood hazard. The results will assist disaster managers to reduce the risk to flood disasters at the community level where risk outcomes are first materialized.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.