Document Type : Research Paper

Authors

• Hemen Mahmoudpour ¹
• Esfandiar Abbasnovinpour ¹
• Homayoun Moghimi ²

¹ Department of Geology, Faculty of Sciences, Urmia University, Urmia, Iran.

² Department of Geology, Payame Noor University, Tehran, Iran.

Abstract

Assessing water quality is an important step toward the optimal and appropriate use of drinking water resources. Therefore, the necessity of studying water quality characteristics in water resource management programs has been highly considered. Ambiguity and lack of inherent certainty governing water resources in the evaluation of goals, criteria, and decision-making units, as inconsistency and carelessness in the opinions and judgments of decision-makers have led to the tendency towards theories of fuzzy sets and, as a result, fuzzy logic as an efficient and useful tool for planning and making decisions. In the present underground water quality water was first classified by international standard methods (definitive evaluation method) for drinking purposes. Then classification was modeled and compared using Mamdani fuzzy inference. For this purpose, the four-year average of quality parameters of underground water sources related to 33 sources including 10 well rings, 22 spring mouths, and an aqueduct in operation in Sardasht Cityre used as inputs in two cases. In the deterministic evaluation method (Schoeller diagram), the characteristics and the water quality determination diagram were determined. In the four-year average fuzzy inference model, eight water quality parameters were classified into three groups, in the first group the parameters of Na⁺, Ca⁺², and Mg⁺², in the second group the parameters of HCO3^-, SO4^-2, and Cl^- were placed in the third group of two TH and TDS parameters. After determining each group with two input parameters, each input parameter was considered including three membership functions, so that the rules considered for it were estimated as nine (3x3). The results based on the deterministic method showed that all the studied samples were in the good to acceptable group. But Mamdani's fuzzy findings showed that two samples with a confidence level of 50% were in the acceptable category and other samples with a confidence level of 83-87% were placed in the desirable category for drinking.

Keywords

• Drinking water optimization
• Fuzzy inference system
• Sardasht city
• Water quality

20.1001.1.20087764.1402.76.1.11.2