Water Quality Index: A Fuzzy River-Pollution Decision Support Expert System
Publication: Journal of Water Resources Planning and Management
Volume 133, Issue 2
Abstract
Water quality management policies, which are proposed to prevent, control, or treat environmental problems related to quality of water, are broad and complex issues. We have various types of water resources, different water uses, and a lot of decision parameters with several levels of decision makers involved. Moreover, there are a lot of strategies and technologies available to be applied for water quality management and so environmental decision makers are required to evaluate and prioritize them in order to choose the best possible plan for each particular problem. To provide a comprehensive but easy to use tool in the assessment and evaluation of water quality policies, the concept of water quality index (WQI) has been developed. Due to the abovementioned complexities, to get this index, there is a need for a methodology to not only structure and identify information relevant to the problem but also to help users reach a decision. Designing a multiple-attribute decision support expert system, which makes expert knowledge available to nonexpert users, can do this. In doing so, we may encounter qualitative or linguistic assessments in the index making process. Thus, fuzzy set theory can be applied to recognize this inherent fuzziness of such a process. Briefly, in this study we propose a fuzzy multiple-attribute decision support expert system to compute the water quality index and to provide an outline for the prioritization of alternative plans based on the amount of improvements in WQI. At the end, applicability and usefulness of the proposed methodology is revealed by a case study.
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Acknowledgments
The writers of this paper are very grateful to Gerald Fuller at the University of Regina for support. The writers are also very thankful to anonymous reviewers for very insightful comments and suggestions which were helpful in improving the manuscript.
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Published In
Journal of Water Resources Planning and Management
Volume 133 • Issue 2 • March 2007
Pages: 95 - 105
Copyright
© 2007 ASCE.
History
Received: Jun 17, 2004
Accepted: Dec 21, 2005
Published online: Mar 1, 2007
Published in print: Mar 2007
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