Water and Irrigation Management

Water and Irrigation Management

Assesment of water quality of Haraz river with IRWQI, NSFWQI, CCMEWQI indices and optimization using response surface methodology -RSM

Document Type : Research Paper

Authors
Yasaman Tajabadi
Homayoun Motiee
Ali Moridi
Department of Water, Wastewater and Environmental Engineering, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran.
10.22059/jwim.2025.398878.1247
Abstract
Rivers, as one of the main sources of water supply, play a vital role in meeting environmental, agricultural, and  human needs. Assessing the water quality of these resources is essential for sustainable management and reducing environmental risks. Selecting an appropriate index for evaluating surface water quality is one of the  key challenges in water resources management. In this study, in order to compare three widely used water  quality indices, the Iranian National Water Quality Index (IRWQI), the National Sanitation Foundation Water  Quality Index (NSFWQI), and the Canadian Council of Ministers of the Environment Water Quality Index (CCMEWQI), data collected from the Haraz River (nine stations during two seasons: winter and summer)  were used as a case study. The results showed that all three indices were able to classify water quality  relatively well; however, differences were observed in their sensitivity and discriminatory capability, with the NSFWQI generally providing more optimistic results. Furthermore, Response Surface Methodology (RSM)  was employed to analyze the influence of different parameters on each index and to optimize water quality  modeling. The findings indicated that in summer, nitrate, phosphate, dissolved oxygen, and ammonium were  the most influential parameters, accounting for a total of 83%, while in winter, biochemical oxygen demand,  chemical oxygen demand, total hardness, and pH were the most influential, accounting for 82%. Water quality  based on the NSFWQI was lower in summer than in winter; during winter, all stations fell within the medium  to good categories, whereas only about 34% of the stations were in this range in summer. A decreasing trend in  water quality along the river was also observed in both seasons. This study demonstrates that the choice of  index can significantly affect the interpretation of water quality status, and that integrating indices with  statistical methods such as RSM can provide an effective tool for surface water quality management in other rivers.
Keywords
CCMEWQI
IRWQI
NSFWQI
Indices RSM
Water quality assessment
Subjects
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Water and Irrigation Management
Volume 15, Issue 3
Autumn 2025
Pages 607-630