Spatial analytic hierarchy process model for flood forecasting: An integrated approach
Various flood influencing factors such as rainfall, geology, slope gradient, land use, soil type, drainage density, temperature etc. are generally considered for flood hazard assessment. However, lack of appropriate handling/integration of data from different sources is a challenge that can make any...
| Main Authors: | Matori, A.N., Lawal, D.U., Yusof, K.W., Hashim, M.A., Balogun, A.-L. |
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| Format: | Conference or Workshop Item |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.32085 / |
| Published: |
Institute of Physics Publishing
2014
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906539492&doi=10.1088%2f1755-1315%2f20%2f1%2f012029&partnerID=40&md5=9620cdb9c8b1a6eb9db57c2ebb4b62c2 http://eprints.utp.edu.my/32085/ |
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| Summary: |
Various flood influencing factors such as rainfall, geology, slope gradient, land use, soil type, drainage density, temperature etc. are generally considered for flood hazard assessment. However, lack of appropriate handling/integration of data from different sources is a challenge that can make any spatial forecasting difficult and inaccurate. Availability of accurate flood maps and thorough understanding of the subsurface conditions can adequately enhance flood disasters management. This study presents an approach that attempts to provide a solution to this drawback by combining Geographic Information System (GIS)-based Analytic Hierarchy Process (AHP) model as spatial forecasting tools. In achieving the set objectives, spatial forecasting of flood susceptible zones in the study area was made. A total number of five set of criteria/factors believed to be influencing flood generation in the study area were selected. Priority weights were assigned to each criterion/factor based on Saaty's nine point scale of preference and weights were further normalized through the AHP. The model was integrated into a GIS system in order to produce a flood forecasting map. © Published under licence by IOP Publishing Ltd. |
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