Assessing Flood Hazard at River Basin Scale: Comparison between HECRAS-WMS and Flood Hazard Index (FHI) Methods Applied to El Maleh Basin, Morocco — Oak Academic Publishing
Research ArticleOpen AccessGoogle Scholar indexed
Assessing Flood Hazard at River Basin Scale: Comparison between HECRAS-WMS and Flood Hazard Index (FHI) Methods Applied to El Maleh Basin, Morocco
Laboratory of Applied Geology and Geo-Environment (LAGAGE), Ibn-Zohr University, Agadir, Morocco
,
Laboratory of Applied Geology and Geo-Environment (LAGAGE), Ibn-Zohr University, Agadir, Morocco
,
Laboratory of Applied Geology and Geo-Environment (LAGAGE), Ibn-Zohr University, Agadir, Morocco
,
Laboratory of Applied Geology and Geo-Environment (LAGAGE), Ibn-Zohr University, Agadir, Morocco
1 Laboratory of Applied Geology and Geo-Environment (LAGAGE), Ibn-Zohr University, Agadir, Morocco
2 Laboratory of Applied Geology and Geo-Environment (LAGAGE), Ibn-Zohr University, Agadir, Morocco
3 Laboratory of Applied Geology and Geo-Environment (LAGAGE), Ibn-Zohr University, Agadir, Morocco
4 Laboratory of Applied Geology and Geo-Environment (LAGAGE), Ibn-Zohr University, Agadir, Morocco
The cartography of floods by two different approaches enabled us to determine the limits and the advantages of each one of them. This cartography has been applied to the El Maleh basin situated in the South-East of Morocco. The HEC-RAS approach consists of a combination of the surface hydrologic model and the digital terrain model data. This combination allows thereafter the mapping of the flood zones by the use of the WMS software. Thus it can predict the probability occurrence of floods at various frequency times and determine the intensity of the flood (depth and velocity of flood water) inside the El Maleh river by using the existing hydrological data. Otherwise FHI method approach introduces a multi-criteria index to assess flood risk areas in a regional scale. Six parameters (flow accumulation, distance from drainage network, drainage network density, slope, land use, and geology) were used in this last method. The relative importance of each parameter for the occurrence and severity of flood has been connected to weight values. These values are calculated following an Analytical Hierarchy Process: AHP, a method originally developed for the solution of Operational Research problems. According to their weight values, information of the different parameters is superimposed, resulting to flood risk mapping. The use of the WMS model allowed us to accurately map the flood risk areas with precisely flood heights in different levels. However, this method is only applicable for a small portion of the basin located downstream of the hydrological station. Otherwise, the FHI method allows it to map the entire basin but without giving an indication of the water levels reached by floods. One method does not exclude the other since both approaches provide important information for flood risk assessment.
KeywordsFlooding HazardEl Maleh RiverHEC-RAS and WMSFHI Method
Heidari, A. (2014) Flood Vulnerability of the Karun River System and Short-Term Mitigation Measures. Flood Risk Manage-ment, 7, 65-80. https://doi.org/10.1111/jfr3.12032
Foudi, S., Osés-Eraso, N. and Tamayo, I. (2015) Inte-grated Spatial Flood Risk Assessment: The Case of Zaragoza. Land Use Policy, 42, 278-292. https://doi.org/10.1016/j.landusepol.2014.08.002
Hudson, P., Botzen, W., Kreibich, H., Bubeck, P. and Aerts, J. (2014) Evaluating the Effectiveness of Flood Damage Mitigation Measures by the Application of Propensity Score Match-ing. Natural Hazards and Earth System Sciences, 14, 1731-1747. https://doi.org/10.5194/nhess-14-1731-2014
Perera, E., Hiroe, A., Shrestha, D., Fukami, K., Basnyat, D., Gautam, S., Hasegawa, A., Uenoyama, T. and Tanaka, S. (2015) Community-Based Flood Damage Assessment Approach for Lower West Rapti River Basin in Nepal under the Impact of Climate Change. Natural Hazards, 75, 669-699. https://doi.org/10.1007/s11069-014-1339-5
Rahmati, O., Pourghasemi, H. and Zeinivand, H. (2015) Flood Susceptibility Mapping Using Frequency Ratio and Weights-of-Evidence Models in the Golastan Province, Iran. Geocarto International. https://doi.org/10.1080/10106049.2015.1041559
Poussin, J.K., Botzen, W.J. and Aerts, J.C. (2014) Factors of Influence on Flood Damage Mitigation Behavior by Households. Environmental Science and Policy, 40, 69-77. https://doi.org/10.1016/j.envsci.2014.01.013
Matkan, A., Shakiba, A., Pourali, H. and Azari, H. (2009) Flood Early Warning with Integration of Hydrologic and Hydraulic Models, RS and GIS (Case Study: Madarsoo Basin, Iran). World Applied Sciences Journal, 6, 1698-1704.
Fenicia, F., Kavetski, D., Savenije, H.H.G., Clark, M.P., Schoups, G., Pfister, L. and Freer, G. (2013) Catchment Properties, Function, and Conceptual Model Representation: Is There a Corre-spondence? Hydrological Processes, 28, 2451-2467. https://doi.org/10.1002/hyp.9726
Qafari, G. (2004) Flood Hazard Zoning Using GIS (Case Study: Babolrood River, Mazandaran Province, Iran). M.Sc Thesis of Watershed Man-agement. Faculty of Natural Resources of University of Mazandaran, 126 p.
Echogdali, F.Z., Boutaleb, S., Jauregui, J. and Elmouden, A. (2018) Cartography of Flooding Hazard in Semi-Arid Climate: The Case of Tata Valley (South-East of Mo-rocco). Journal of Geography & Natural Disasters, 8, 1-11. https://doi.org/10.4172/2167-0587.1000214
Jaafari, A., Najafi, A., Pourghasemi, H.R., Rezaeian, J. and Sat-tarian, A. (2014) GIS-Based Frequency Ratio and Index of Entropy Models for Landslide Susceptibility Assessment in the Caspian Forest, Northern Iran. International Journal of Environmental Science and Technology, 11, 909-926. https://doi.org/10.1007/s13762-013-0464-0
Moel, H.D., Vliet, M.V. and Aerts, J.C.J.H. (2014) Evaluating the Effect of Flood Damage-Reducing Measures: A Case Study of the Unembanked Area of Rotterdam, the Netherlands. Regional Environmental Change, 14, 895-908.
Pradhan, B., Hagemann, U., Shafapour Tehrany, M. and Prechtel, N. (2014) An Easy to Use ArcMap Based Texture Analysis Program for Extraction of Flooded Areas from TerraSAR-X Satellite Image. Computers Geosciences, 63, 34-43. https://doi.org/10.1016/j.cageo.2013.10.011
Tehrany, M.S., Lee, M.J., Pradhan, B., Jebur, M.N. and Lee, S. (2014) Flood Susceptibility Mapping Using Integrated Bivariate and Multivariate Statis-tical Models. Environmental Earth Sciences, 72, 4001-4015. https://doi.org/10.1007/s12665-014-3289-3
Tehrany, M.S., Pradhan, B. and Jebur, M.N. (2014) Spatial Pre-diction of Flood Susceptible Areas Using Rule Based Decision Tree (DT) and a Novel Ensemble Bivariate and Multivariate Statistical Models in GIS. Journal Hydrology, 504, 69-79. https://doi.org/10.1016/j.jhydrol.2013.09.034
Malczewski, J. (2006) GIS-Based Multicriteria Decision Analy-sis: A Survey of the Literature. International Journal of Geographical Information Science, 20, 703-726. https://doi.org/10.1080/13658810600661508
Ghanbarpour, M.R., Salimi, S. and Hipel, K.W. (2013) A Com-parative Evaluation of Flood Mitigation Alternatives Using GIS-Based River Hydraulics Modelling and Multicriteria Decision Analysis. Flood Risk Management, 6, 319-331. https://doi.org/10.1111/jfr3.12017
Paquette, J. and Lowry, J. (2012) Flood Hazard Modelling and Risk Assessment in the Nadi River Basin, Fiji, Using GIS and MCDA. South Pacific Journal of Natural and Applied Sciences, 30, 33-43. https://doi.org/10.1071/SP12003
Kritikos, T. and Davies, T.R.H. (2011) GIS-Based Multi-Criteria Decision Analysis for Landslide Susceptibility Mapping at Northern Evia, Greece. Zeitschrift der Deutschen Gesellschaft für Geowissenschaften, 162, 421-434. https://doi.org/10.1127/1860-1804/2011/0162-0421
Bui, D.T., Tuan, T.A., Klempe, H., Pradhan, B. and Revhaug, I. (2015) Spatial Prediction Models for Shallow Landslide Hazards: A Comparative Assessment of the Efficacy of Support Vector Machines, Artificial Neural Networks, Kernel Logistic Regression, and Logistic Model Tree. Landslides, 13, 361-378. https://doi.org/10.1007/s10346-015-0557-6
Saaty, T.L. (1980) The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill, New York.
Pourghasemi, H.R., Pradhan, B. and Gokceoglu, C. (2012) Application of Fuzzy Logic and Analytical Hierarchy Process (AHP) to Landslide Susceptibility Mapping at Haraz Watershed, Iran. Natural Hazards, 63, 965-996. https://doi.org/10.1007/s11069-012-0217-2
Beauchamp, W., Allmendinger, R.W., Barazangi, M., Demnati, A., El Alji, M. and Dahmani, M. (1999) Inversion Tectonics and the Evolu-tion of the High Atlas Mountains, Morocco, Based on a Geological-Geophysical Transect. Tectonics, 18, 163-184. https://doi.org/10.1029/1998TC900015
Piqué, A. (2001) Geology of Northwest Africa, 29. Beiträge zur re-gionalen Geologie der Erde, Gebrüder Bornträger, Berlin, Stuttgart.
Gilles, D. and Moore, M. (2010) Review of Hydrau-lic Flood Modeling Software Used in Belgium, the Netherlands, and the United Kingdom.
US Army Corps of Engineers (2010) Hydrologic Engineering Center, HEC-RAS River Analysis System, User’s Manual.
Brunner, G.W. (1995) HEC-RAS, River Analysis System. Hydraulic Reference Manual. US Army Corps of Engineers, Hydrologic Engineering Cen-ter.
FEMA (2013) Multi-Year Flood Hazard Identification Plan (MHIP). 1-18.
Aaron, C. and Venkatesh, M. (2009) Effect of Topographic Data, Geometric Configuration and Modeling Approach on Flood Inundation Mapping. Journal of Hydrology, 377, 131-142. https://doi.org/10.1016/j.jhydrol.2009.08.015
El Adlouni, S., Ouarda, T.B.M.J., Zhang, X., Roy, R. and Bobée, B. (2007) Generalized Maximum Likelihood Estimators for the Nonstationary Generalized Ex-treme Value Model. Water Resources. Research, 43, 1-13. https://doi.org/10.1029/2005WR004545
Akaike, H. (1973) Information Theory and an Extension of the Maximum Likelihood Principle. In: Petrovand, B.N. and Csaki, F., Eds., 2nd International Symposium on Information Theory, Akademiai Kiado, Budapest, 267-281.
Schwarz, G. (1978) Es-timating the Dimension of a Model. Annals of Statistics, 6, 461-464. https://doi.org/10.1214/aos/1176344136
Elkhrachy, I. (2015) Flash Flood Hazard Mapping Using Satellite Images and GIS Tools: A Case Study of Najran City, Kingdom of Saudi Arabia (KSA). The Egyptian Journal of Remote Sensing and Space Sciences, 18, 261-278. https://doi.org/10.1016/j.ejrs.2015.06.007
Kazakis, N., Kougias, I. and Pat-sialis, T. (2015) Assessment of Flood Hazard Areas at a Regional Scale Using an Index Based Approach and Analytical Hier-archy Process: Application in Rhodope-Evros Region, Greece. Science of the Total Environment, 538, 555-563. https://doi.org/10.1016/j.scitotenv.2015.08.055
Haan, C.T., Barfield, B.J. and Hayes, J.C. (1994) Design Hy-drology and Sedimentology for Small Catchments. Elsevier, New York.
Saaty, T.L. (1977) A Scaling Method for Priori-ties in Hierarchical Structures. Journal of Mathematical Psychology, 15, 234-281. https://doi.org/10.1016/0022-2496(77)90033-5
Saaty, T.L. (1990) How to Make a Decision: The Analytic Hierarchy Process. European Journal Operational Research, 48, 9-26. https://doi.org/10.1016/0377-2217(90)90057-I
Saaty, T.L. (2008) Decision Making with the Analytic Hier-archy Process. International Journal of Services Sciences, 1, 83-98. https://doi.org/10.1504/IJSSCI.2008.017590
Jenks, G.F. (1967) The Data Model Concept in Statistical Map-ping. International Yearbook Cartography, 7, 186-190.
Demek, J. (1972) Manual of Detailed Geomorphological Map-ping. Academia, Prague.
Saaty, T.L. (2012) Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World. Third Revised Edition, RWS Publications, Pittsburgh.
Dodson, R. and Li, X. (2000) The Accuracy and Efficiency of GIS-Based Floodplain Determinations. In: Maidment, D. and Djokic, D., Eds., Hydrologic and Hydraulic Modeling Support with Geographic Information Systems, ESRI Press, New York, 29-52.