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Surface Water Contamination Risk Assessment Modeled by Fuzzy‐WRASTIC
Author(s) -
Alavipoor Fatemeh Sadat,
Ghorbaninia Zahra,
Karimi Saeed,
Jafari Hamidreza
Publication year - 2016
Publication title -
water environment research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 73
eISSN - 1554-7531
pISSN - 1061-4303
DOI - 10.2175/106143016x14609975746361
Subject(s) - geographic information system , overlay , fuzzy logic , contamination , environmental science , computer science , product (mathematics) , resource (disambiguation) , data mining , environmental engineering , mathematics , remote sensing , geography , artificial intelligence , biology , programming language , ecology , computer network , geometry
This research provides a Fuzzy‐WRASTIC new model for water resource contamination risk assessment in a GIS (Geographic Information System) environment. First, this method setting in a multi‐criteria evaluation framework (MCE) reviewed and mapped the sub criteria of every above‐mentioned criterion. Then, related sub‐layers were phased by the observance of GIS environment standards. In the next step, first the sub‐layers were combined together, next the modeling of pollution risk status was done by utilizing a fuzzy overlay method and applying the OR, AND, SUM, PRODUCT and GAMMA operators by using WLC (Weighted Linear Combination) method and providing weights in the WRASTIC model. The results provide the best combination of modeling and the percentages of its risk categories of low, medium, high and very high, which are respectively 1.8, 14.07, 51.43 and 32.7. More areas have severe risk due to the unbalanced arrangement and compact of land uses around the compact surface water resources.