Integration of WRASTIC Method by Multi-Criteria Evaluation and a Fuzzy Model to Evaluate the Risk of Surface Water Pollution (Case study: Tehran Province and Part of Neighboring Provinces)

Nowadays, there is not a comprehensive methodology for contamination risk assessment and modeling of surface water resources. Existing methods just investigate some of the criteria and there is not a GIS-based methodology that can provide the overall risk status in an area by modeling. Consequently, the only existing way is WRASTIC Index which offers a free location overall assessment of the risk status by grading to seven parameters of human and animal wastewater, doing entertainment and recreational, agricultural, industrial activities, size of the area, road and transportation and vegetation density. This research describes the surface water resources contamination risk in new method. In this study, the major part of Tehran province, as well as part of Semnan, Qom, Mazandaran and Alborz provinces by help of a method which is placed in the Multi-criteria evaluation framework (MCE), some criteria are evaluated by WRASTIC method and finally is developed  by Fuzzy-WRASTIC method. The process of this method are based on producing different layers maps by weighting the criteria and sub-criteria and using the WLC weights. Then, final maps were produced by their fuzzy combination. In the next step, first these sub-layers were combined together by the provided method in WRASTIC model. And then, modeling of pollution risk status was done by fuzzy overlay method and applying the OR، AND ، SUM ، PRODUCT and GAMMA operators. The results show that use of the OR operator due to a balanced range of values from low to very high in the whole region is the most appropriate operator of risk assessment and analysis for the production of maps. On this basis 31.14 and 27.38 percent of the study area (that is a major part of Tehran and Semnan province) due to the concentration of population and different activities are faced with the high and very high risk for their surface water resources