Flood Risk Assessment and Zoning of Human Settlements in line with Sustainable Development using Fuzzy AHP in GIS Envoronmnet and DPSIR Model (Case study: Abali)

Subject Areas : environmental management

Morteza Ghobadi ¹ , Masumeh Ahmadipari ² , Esmaeil Salehi ³

1 - Assistant Professor, Depatment of Environment, Faculty of Agriculture and Natural Resources, University of Lorestan, Iran. * ( Corresponding Author)
2 - Ph.D. Student, Department of Environmental Planning, Graduate Faculty of Environment, University of Tehran, Iran
3 - Associate Professor, Department of Environmental Planning, Graduate Faculty of Environment, University of Tehran, Iran.

Received: 2014-10-26 Accepted : 2015-03-16 Published : 2016-11-21

Keywords: Flood risk, human settlements, Abali area, DPSIR model, Fuzzy AHP,

Abstract :

Background and Objective: Flood risk assessment and zoning in human settlements is an important activity in line with sustainable development of human settlements. The reason is that these settlements are developed alongside the rivers, and bed and margins of torrential plains ignoring the hydrological and dynamical conditions of rivers and upstraem river basins that can increase flood risk and life, financial, and sub-structural damages. This study aims to identify the flood reasons and predict the range of subsequent damages within Abali area. Method: The conceptual model of DPSIR has been used to analyze the elements effective on the flood in the area. In DPSIR analysis of the area for its vulnerability against flood risk, societal, economic, spatial and environmental factors are considered asdriving forces. Then, the flood risk levele in the study area is determined by making plots for the driving forces and zoning the area. For this reason, Fuzzy AHP was used for calculation of layers weight and programming in MATLAB software was done to run it. Finally, risk zoning was carried out based on the weights extracted by Fuzzy AHP method in GIS environment. Results: The results show that from the total area of the case study, about 1788 hectare has a very high risk, 5098 hectare has a high risk, 6190.75 hectare has an average risk, and 3038.75 hectare has a low risk of flood. Conclusion: The results from integration of Decision Support Systems (DSS) models and GIS, as approved in previuos studies, indicate their high efficiency in identifying the areas with high flood risk. Therefore, it is essential to consider the zoning layers in planinig proceses, particularly rsik assessment.

References:

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