Mapping of the Urban Sub Basins Prone to Flood Using PCA Method as A New Weighting Technique

Document Type : Research Article

Authors

1 Associate professor, Department of watershed management, Faculty of Natural Resources, University of Kashan, Iran.

2 PhD student, Department of watershed management, Faculty of Natural Resources, University of Kashan, Iran.

3 Associate professor, Department of watershed management, Faculty of Natural Resources, Urmia University, Iran.

Abstract

In urban areas, due to the development of the impermeable area, and consequently increased runoff production capacity, The risk of flood damage is more serious than other areas. The first step in the management of urban floods is identifying critical areas. In this research, the PROMETHEE II technique is used to prioritize the sub-basins of Urmia prone to flooding. For this purpose, the boundary layers of the hydrological units were determined using ArcGIS technique based on the slope of the area and the condition of the water conduits and joints. 22 subshells were determined. Physiographic characteristics of sub-basins (runoff depth, imperviousness, elevation, curve number, main channel length, form, perimeter, and area) were selected as ranking criteria. The weight of these variables should greatly affect the sub-basins ranking process and needs to determine with a specific precision. The effect of these variables is also varied in a different region. In this research, the weighting of the criteria was performed using both of the hierarchical analysis method (AHP) and analysis of the main components (PCA). In each sub-basins, the PROMETHEE II technique was applied for weighting methods, and sub-basins were prioritized and compared. The results showed that the priority of the sub-basins differed according to the weighting methods. When two methods of weighing were applied, only two of seven sub-basin have the same priority.The first criteria were runoff depth, and its weight was different for PCA and AHP methods (0.150 and 0.280 respectively). The effect of the difference in the weight of the criteria and their priority in flooding was significant. Among the first seven sub-catchments, there are only four common sub-catchments and, among these four sub-catchments, only two of them had the same ranks. This shows that the PCA method is more accurate in weighing the criteria due to the consideration of the spatial characteristics of the criteria and elimination of the error in the survey based methods.

Keywords


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  • Receive Date: 24 October 2017
  • Revise Date: 02 October 2018
  • Accept Date: 24 November 2018
  • First Publish Date: 22 May 2019
  • Publish Date: 22 May 2019