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Environmental Analysis & Ecology Studies

The Relationship between Surface Water Quality and Watershed Characteristics

  • Open or Close Mehdi Vafakhah*

    Faculty of Natural Resources, Tarbiat Modarres University, Iran

    *Corresponding author: Mehdi Vafakhah DR, Associate Professor in Water Resources and Hydrology Department of Watershed Management, Faculty of Natural Resources, Tarbiat Modarres University, P.O.Box 46417-76489, Noor, Mazandaran Province, Iran

Submission: December 16, 2017;Published: February 27, 2018

DOI: 10.31031/EAES.2018.01.000514

ISSN: 2578-0336
Volume1 Issue3


The healthy water resources are necessary and essential prerequisite for environmental protection and economic development, political, social and cultural rights of Iran. In this research, water quality parameters i.e. total dissolved solids (TDS), sodium absorption rate (SAR), electrical conductivity (EC), Na+, Cl-, CO3 2-, K+, Mg2+, Ca2+, pH, HCO3- and SO4 2- during 2010-2011 were obtained from Iranian Water Resources Research Institute in water quality measurement stations on Mazandaran province, Iran. Then, the most important catchment characteristics (area, mean slope, mean height, base flow index, annual rainfall, land cover, and geology) were determined on water quality parameters using stepwise regression via backwards method in the 63 selected rivers. The results showed that sodium absorption rate (SAR), total dissolved solids (TDS), electrical conductivity (EC), Na+ and Cl- parameters are strongly linked to geology characteristics, while K+, Mg2+ and Ca2+ cations is linked to rainfall and geology characteristics. pH and HCO3- are related to area, rainfall, land cover and geology characteristics, CO3 2- is related to area, rainfall, rangeland area and geology characteristics and SO4 2- is related to area, rainfall, range and bar land area and geology characteristics. Adaptive Neuro-Fuzzy Inference System (ANFIS) was used for modeling the selected catchment characteristics and water quality parameters. The ANFIS models have a low Nash–Sutcliffe model efficiency coefficient (NSE) and high root mean squares error (RMSE) to estimate water quality parameters except EC, Cl- and Ca2+ parameters.

Keywords: pH; TDS; EC; Water quality; Water cautions; Water anions; Modeling; Mazandaran province

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