Next Article in Journal
Impacts of Climate Change on Mean Annual Water Balance for Watersheds in Michigan, USA
Previous Article in Journal
Characterization of the Corrosive Action of Mineral Waters from Thermal Sources: A Case Study at Azores Archipelago, Portugal
Article Menu

Export Article

Open AccessArticle
Water 2015, 7(7), 3531-3564; doi:10.3390/w7073531

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

1
United Nations University, (UNU-EHS), UN Campus, Platz der Vereinten Nationen 1, 53113 Bonn, Germany
2
Department of Remote Sensing, University of Wuerzburg, 97074 Wuerzburg, Germany
3
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
*
Author to whom correspondence should be addressed.
Academic Editor: Miklas Scholz
Received: 28 February 2015 / Revised: 19 June 2015 / Accepted: 24 June 2015 / Published: 6 July 2015
View Full-Text   |   Download PDF [8643 KB, uploaded 6 July 2015]   |  

Abstract

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. View Full-Text
Keywords: community; flood hazard index; GIS; mapping; West Africa; rational model; runoff community; flood hazard index; GIS; mapping; West Africa; rational model; runoff
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Asare-Kyei, D.; Forkuor, G.; Venus, V. Modeling Flood Hazard Zones at the Sub-District Level with the Rational Model Integrated with GIS and Remote Sensing Approaches. Water 2015, 7, 3531-3564.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Water EISSN 2073-4441 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top