Application of Principle of Maximum Entropy in Determining the Optimum Number of Surface Water Quality Monitoring Stations

Optimization of monitoring network is a decision-making process through which, the best combination of existing stations is selected. Regarding the economic considerations and reducing monitoring costs, optimization approach in this study is to reduce the number of surface water quality monitoring stations in Dez basin in Lorestan province. In this regard, using an algorithm based on the principle of maximum entropy and water quality index of SO44, Cl, HCO3, K, Na, Ca, Mg, pH, TH, SAR, EC and TDS parameters, the optimization procedure was done for 18 existing monitoring stations during the statistical period of 1387-1396 (2008-2017). First, the average rank of each station in the mentioned 10 statistical years was obtained, then some models were proposed for the network entropy according to the number of stations and year. After fitting the best model, the results showed that based on SO4, Cl, HCO3, K, Na, Ca, Mg, pH, TH, TD, SAR and EC parameters, the number of sufficient stations as surface water quality monitoring network in the study area were 9, 9, 7, 11, 11, 11, 10, 7, 10, 10, 10, and 11, respectively. In order to validate the proposed network, by comparing the entropy of the proposed network with the entropy of random networks with the number of stations based on the 12 mentioned parameters in each year, the efficiency of the selected network was confirmed. Also, among the 12 evaluated quality indicators, chloride showed the highest entropy of weight. Therefore, chloride had the maximum entropy and was selected as the superior index.