Abstract
BackgroundThe aim of this work is to propose a new river water quality index using fuzzy logic. The proposed fuzzy index combines quality indicators’ prescribed thresholds extracted mainly from the Moroccan and the Quebec water legislations. The latter is reputed for its strict water quality assessment. The proposed index combines six indicators, and not only does it exhibit a tool that accounts for the discrepancy between the two base indices, but also provides a quantifiable score for the determined water quality. These classifications with a membership grade can be of a sound support for decision-making, and can help assign each section of a river a gradual quality sub-objective to be reached.ResultsTo demonstrate the applicability of the proposed approach, the new index was used to classify water quality in a number of stations along the basins of Bouregreg-Chaouia and Zizi-Rhéris. The obtained classifications were then compared to the conventional physicochemical water quality index currently in use in Morocco. The results revealed that the fuzzy index provided stringent classifications compared to the conventional index in 41% and 33% of the cases for the two basins respectively. These noted exceptions are mainly due to the big disparities between the different quality thresholds in the two standards, especially for fecal coliform and total phosphorus.ConclusionsThese large disparities put forward an argument for the Moroccan water quality legislation to be upgraded to align water and environmental assessment methods with other countries in order to mitigate the risks of failing to achieve a good ecological status.
Highlights
The aim of this work is to propose a new river water quality index using fuzzy logic
There exist a number of water quality indices based on different indicators and aggregation methods used today throughout the world, such as the U.S National Sanitation Foundation Water Quality Index (NSFWQI); the Canadian Council of Ministers of the Environment Water Quality Index (CCMEWQI); the British Columbia Water Quality Index (BCWQI), and the Oregon Water Quality Index (OWQI)
A general flaw with conventional water quality indices is that they depend on human expertise with subjective and ambiguous information, which might raise a number of issues in water quality assessment
Summary
The aim of this work is to propose a new river water quality index using fuzzy logic. The proposed index combines six indicators, and does it exhibit a tool that accounts for the discrepancy between the two base indices, and provides a quantifiable score for the determined water quality These classifications with a membership grade can be of a sound support for decision-making, and can help assign each section of a river a gradual quality sub-objective to be reached. According to the authors, using fuzzy logic is very convenient in the assessment of environmental issues because it can solve properly the ambiguities and subjectivity inherent in these problems It helps conciliating conflicting observations due to human expertise, and last but not least, it can provide decision-makers with the ability to make well-informed decisions that are technically sound and legally defensible. With fuzzy logic one can describe water quality in a location as being 10% excellent and 90% just good, which is not possible with classical approaches to water quality
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