Development of an entropy- based fuzzy eutrophication index for reservoir water quality evaluation

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

Water quality trading using tradable discharge permit in a river and assessment of its cost-effectiveness

Localizing water resource management with optimum waste allocation approach in rivers is one of the strategies for reducing the pollution. In this regard, a water quality trading program among pollution sources can fulfill this issue. This program is achieved through a tradable discharge permits system which is based on the river self purification capacity and creates an economical incentive to reduce the pollutants. Water quality trading emerges from the concept of hydrology and economy based on the transfer coefficient which is the fraction of pollution load that is transferred from the upstream to the downstream. Transfer coefficient is obtained from the water quality model. In this paper, execution of a tradable discharge permit program for the index pollutants has been assessed. Finally the results are analyzed for evaluating the cost effectiveness