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Development Of An Entropy- Based Fuzzy Eutrophication Index For Reservoir Water Quality Evaluation
Ist Teil von
Iranian journal of environmental health science & engineering, 2010-01, Vol.7 (1), p.1-14
Ort / Verlag
Iran: Iranian Association of Environmental Health (IAEH)
Erscheinungsjahr
2010
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
Eutrophication phenomenon is one of the most common water quality
problems in reservoirs in many regions. Determining the trophic status
of the reservoirs is not a precise process and contains vagueness.
Fuzzy set and entropy theories are concepts which can model uncertainty
and imprecision in the data and the analysis. In this study, an
Entropy-based Fuzzy Eutrophication Index model has been developed for
classification of trophic level of Satarkhan Reservoir in the
north-western part of Iran. Through the Fuzzy Synthetic Evaluation
technique, trophic levels were considered as fuzzy sets and a fuzzy
evaluation matrix was formed by defining the membership function of
water quality indicators. The indicators were weighed by integrating
both objective and subjective criteria. In this regard, the entropy
method was used to determine the objective weights of the indicators
based on the amount of useful information available in the data set and
the subjective weight was determined by the analytical hierarchy
process using a pairwise comparison done by the expert judgment.
Classification of the trophic status of the reservoir was determined by
multiplying the weighed vector by the fuzzy evaluation matrix. The
results showed that critical months for eutrophication in Satarkhan
reservoir occur in autumn and spring after the overturning phenomena.
The strength of the results of developed entrophy-based fuzzy
entrophication index is that the trophic level in each month was
expressed with a degree of certainty. Also due to the ability of the
model to integrate different kinds of objective and subjective quality
observations considering the information included in the data, the
proposed model is more robust than the previous index models such as
Trophic Status Index and fuzzy trophic index.