Amirkabir University of Technology Amirkabir Journal of Civil Engineering 2588-297X 48 3 2016 10 22 Optimal Urban Flood Management Using Spatial Multi Criteria Decision Making Approach Optimal Urban Flood Management Using Spatial Multi Criteria Decision Making Approach 227 240 672 10.22060/ceej.2016.672 FA A. Radmehr Postgraduate of Water Resources Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran S. Araghinejad Assistant Professor, Faculty of Agricultural Engineering and Technology, University of Tehran Journal Article 2012 10 26 Water management in urban areas includes controlling storm water and developing efficient drainage<br />systems. High-intensity rainfall events, reduced permeability due to the urban development as well as<br />the aging of the drainage systems, are the main reasons for the occurrence of destructive floods in urban<br />areas. Developing the map of areas with potential of flood hazard could be an appropriate tool for<br />urban planning and development strategies. Vulnerability analysis of different urban areas is a complex<br />process because it depends on the various spatial and temporal parameters and criteria. The purpose of<br />this research is to prepare a tool to determine more precise decisions in urban flood management using a<br />combination of multi-criteria decision making and geographic information system. Development of an<br />artificial neural network (ANN) model as an alternative for the weighting process of the decision makers<br />is presented as a solution to mitigate the disagreement among decision makers on the weighting process<br />of decision making analysis. The developed spatial multi-criteria decision-making (SMCDM) tool enables<br />processing of necessary data and criteria and combining them through the decision making process.<br />All of the necessary data analysis and processing are automatically run within a developed toolbox. The<br />advantages of using the developed toolbox in generating flood management strategies are discussed in<br />the case study of Tehran city, Iran. Water management in urban areas includes controlling storm water and developing efficient drainage<br />systems. High-intensity rainfall events, reduced permeability due to the urban development as well as<br />the aging of the drainage systems, are the main reasons for the occurrence of destructive floods in urban<br />areas. Developing the map of areas with potential of flood hazard could be an appropriate tool for<br />urban planning and development strategies. Vulnerability analysis of different urban areas is a complex<br />process because it depends on the various spatial and temporal parameters and criteria. The purpose of<br />this research is to prepare a tool to determine more precise decisions in urban flood management using a<br />combination of multi-criteria decision making and geographic information system. Development of an<br />artificial neural network (ANN) model as an alternative for the weighting process of the decision makers<br />is presented as a solution to mitigate the disagreement among decision makers on the weighting process<br />of decision making analysis. The developed spatial multi-criteria decision-making (SMCDM) tool enables<br />processing of necessary data and criteria and combining them through the decision making process.<br />All of the necessary data analysis and processing are automatically run within a developed toolbox. The<br />advantages of using the developed toolbox in generating flood management strategies are discussed in<br />the case study of Tehran city, Iran. https://ceej.aut.ac.ir/article_672_2dea61eed4bceec564a00115c4d21334.pdf