Fuzzy-Based Regional Water Quality Index for Surface Water Quality Assessment
Publication: Journal of Hazardous, Toxic, and Radioactive Waste
Volume 23, Issue 4
Abstract
Evaluation of the water quality index is highly complex and needs competent models to assess at global and regional scales. A fuzzy-based inference system (FIS) provides an effective tool for solving this type of complex problems. This study presents the development of a Mamdani-type fuzzy-based regional water quality index (FRWQI) consisting of 10 water quality parameters such as dissolved oxygen (DO), fecal coliforms (FC), biological oxygen demand (BOD), pH, nitrogen, suspended solids (SS), alkalinity, turbidity, chemical oxygen demand (COD), and electrical conductivity (EC). It can be used for the evaluation of the water quality index of various river basins across the world. The assessment of surface water quality was proposed with three classes using classifications from six countries in various geographic regions. The FRWQI is comparable to water quality models used in India, Malaysia, and the United States, despite its varied geographic origin, and can help in the self-assessment of regional water quality on a global scale.
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Acknowledgments
The authors would like to acknowledge the support of Frontier Areas of Science and Technology—Centre of Excellence (FAST-CoE) in Sustainable Development at I.I.T. Hyderabad, funded by the Ministry of Human Resource Development, India. The authors would also like to make special mention of the United Nations Environment Programme Global Environment Monitoring System (GEMS) Water Programme for the data support.
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Information & Authors
Information
Published In
Journal of Hazardous, Toxic, and Radioactive Waste
Volume 23 • Issue 4 • October 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: Nov 15, 2018
Accepted: Feb 22, 2019
Published online: May 25, 2019
Published in print: Oct 1, 2019
Discussion open until: Oct 25, 2019
ASCE Technical Topics:
- Artificial intelligence and machine learning
- Business management
- Chemical processes
- Chemistry
- Computer programming
- Computing in civil engineering
- Energy engineering
- Energy sources (by type)
- Engineering fundamentals
- Environmental engineering
- Fuzzy logic
- Hydro power
- Management methods
- Models (by type)
- Oxygen demand
- Practice and Profession
- Quality control
- Renewable energy
- Scale models
- Surface water
- Water (by type)
- Water and water resources
- Water demand
- Water management
- Water quality
- Water supply
- Water treatment
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