Optimal Urban Flood Management Using Spatial Multi Criteria Decision Making Approach

Document Type : Research Article


1 Postgraduate of Water Resources Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran

2 Assistant Professor, Faculty of Agricultural Engineering and Technology, University of Tehran


Water management in urban areas includes controlling storm water and developing efficient drainage
systems. High-intensity rainfall events, reduced permeability due to the urban development as well as
the aging of the drainage systems, are the main reasons for the occurrence of destructive floods in urban
areas. Developing the map of areas with potential of flood hazard could be an appropriate tool for
urban planning and development strategies. Vulnerability analysis of different urban areas is a complex
process because it depends on the various spatial and temporal parameters and criteria. The purpose of
this research is to prepare a tool to determine more precise decisions in urban flood management using a
combination of multi-criteria decision making and geographic information system. Development of an
artificial neural network (ANN) model as an alternative for the weighting process of the decision makers
is presented as a solution to mitigate the disagreement among decision makers on the weighting process
of decision making analysis. The developed spatial multi-criteria decision-making (SMCDM) tool enables
processing of necessary data and criteria and combining them through the decision making process.
All of the necessary data analysis and processing are automatically run within a developed toolbox. The
advantages of using the developed toolbox in generating flood management strategies are discussed in
the case study of Tehran city, Iran.


Main Subjects

[1] Alcantara-Ayala, I.; “Geomorphology, Natural Hazards,Vulnerability and Prevention of Natural Disasters in Developing Countries,” J. Geomorphology, Vol. 47,pp. 107–124, 2002
[2] Bellal., M.; Sillen, X. and Zeck, Y.; “Coupling GIS with a Distributed Hydrological Model for Studying the Effect of arious Urban Planning Options on Rainfall-Runoff Relationship in Urbanized Watersheds,” Proc. Vienna Conference, Application of Geographic Information Systems in Hydrology and Water Resources Management, pp. 99–106, 1996..
[3] Gumbo, B.; Munayamba, N.; Sithol, G. and Savenije,H. G.; “Coupling of Digital Elevation Model and Rainfall-Runoff Model in Storm Drainage Network Design,” J. Physics and Chemistry of the Earth, Vol. 27, pp. 755–764, 2002.
[4] Cadier, E.; “Small Watershed Hydrology in Semi-Arid North Eastern Brazil Basin Topography and Transposition of Annual Runoff Data,” J. Hydrology,Vol. 182, pp. 117–141, 1996.
[5] Sanders, B. F.; Pau, J. C. and Jaffe, D. A.; “Passive and Active Control of Diversions to an Off–Line Reservoir for Flood Storage Reduction,” J. Adv. Water Resour,Vol. 29, pp. 861–871, 2006.
[6] Scholz, M.; “Classification Methodology for Sustainable Flood Retention Basins,” J. Landscape and Urban Planning, Vol. 81, pp. 246–256, 2007.
[7] Macleod, C. J. A.; Scholefield, D. and Haygarth, P. M.; “Integration for Sustainable Catchment Management,”J. Science of the Total Environment, Vol. 373, pp. 591–602, 2007.
[8] Asgharpour, M. J.; “Multi-Criteria Decision Making,” Tehran University Press, 6th eds, 2004.
[9] Abrishamchi, A.; Ebrahimian, A.; Tajirishi, M. and Marino, M.; “Application of Multi Criteria Decision Making to Urban Water Supply,” J. Water Res. Planning and Management, ASCE, Vol. 131, pp. 326– 335, 2005.
[10] Simonovic, S. P. and Verma, R.; “A New Methodology for Water Resources Multi–Criteria Decision Making under Uncertainty,” J. Physics and Chemistry of the Earth, Vol. 33, pp. 322–329, 2008.
[11] Afshar, A.; Marino, M.; Saadatpour, M. and Afshar, A.; “Fuzzy TOPSIS Multi-Criteria Decision Analysis Applied to Karun Reservoirs system,” J. Water Resour Manage, Vol. 25, pp. 545–563, 2010.
[12] Chang, N. B.; Parvathinathan, G. and Breeden, J. B.; “Combining GIS with Fuzzy Multi Criteria Decision Making for Landfill Siting in a Fast-Growing Urban Region,” J. Environmental Management, Vol. 87, pp. 139–153, 2008.
[13] Malczewski, J.; “Ordered Weighted Averaging with Fuzzy Quantifiers: GIS-Based Multicriteria Evaluation for Land-Use Suitability Analysis,” Int. J. Applied Earth Observation and Geoinformation, Vol. 8, pp.270–277, 2006.
[14] Cheng, S.; Chan, C. W. and Huang, G. H.; “An Integrated Multi–Criteria Decision Analysis and Inexact Mixed Integer Linear Programming Approach for Solid Waste Management,” J. Engineering Applications of Artificial Intelligence, Vol. 16, pp. 543–554, 2003.
[15] Kao, H. P.; Wang, B.; Dong, J. and Ku, K. C.; “An Event–Driven Approach with Makespan/Cost Tradeoff Analysis for Project Portfolio Scheduling,”J. Computers in Industry, Vol. 57, pp. 379–397, 2006.
[16] Montanari, R.; “Environmental Efficiency Analysis for Enel Thermopower Plants,” J. Cleaner Production, Vol. 12, pp. 403–414, 2004.
[17] Srdjevic, B.; Medeiros, Y. D. P. and Faria, A. S.; “An Objective Multi-Criteria Evaluation of Water Management Scenarios,” J. Water Resources Management, Vol. 18, pp. 35–54, 2004.
[18] Rodrigues, F.; Andrieu, H. and Creutin, J. D.;“Surface Runoff in Urban Catchments Morphological Identification of Unit Hydrograph from Urban Databanks,” J. Hydrology, Vol. 283, pp. 146–168, 2003.
[19] Yazdandoost, F. and Bozorgy, B.; “Flood Risk Management Strategies Using Multi-Criteria Analysis,” J. ICE-Water Management, Vol. 161, pp. 261–266, 2008.
[20] Phua, M. H. and Minowa, M.; “A GIS-Based Multi-Criteria Decision Making Approach to Forest Conservation Planning at a Landscape Scale,” J. Landscape and Urban Planning, Vol. 71, pp. 207–222, 2005.
[21] Fernandez, D. S. and Lutz, M. A.; “Urban Flood Hazard Zoning in Tucuman Province, Argentina, using GIS and Multicriteria Decision Analysis,” J.Engineering Geology, Vol. 111, pp. 90–98, 2010.
[22] Saaty, T. L.; “The Analytic Hierarchy Process: Planning, Priority Setting,” Resource Allocation, RWS Publication, 1996.
[23] Araghinejad, S.; Azmi, M. and Kholghi, M.; “Application of Artificial Neural Network Ensembles in Probabilistic Hydrological Forecasting,” J. Hydrology, Vol. 407, pp. 94–104, 2011.
[24] Kavzoglu, T.; “An Investigation of the Design and Use of Feed-Forward Artificial Neural Networks in the Classification of Remotely Sensed Images,” Ph.D. Thesis, Univ. of Nottingham, UK, 2001.