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Chabokpour, Jafar. (1403). Estimating Total Sediment Load Using Water Quality Parameters in the Sufi Chay River, Iran: A Comparative Analysis of Soft Computing and Dimensionless Approaches. , (), -. doi: 10.22077/jwhr.2025.8174.1154
Jafar Chabokpour. "Estimating Total Sediment Load Using Water Quality Parameters in the Sufi Chay River, Iran: A Comparative Analysis of Soft Computing and Dimensionless Approaches". , , , 1403, -. doi: 10.22077/jwhr.2025.8174.1154
Chabokpour, Jafar. (1403). 'Estimating Total Sediment Load Using Water Quality Parameters in the Sufi Chay River, Iran: A Comparative Analysis of Soft Computing and Dimensionless Approaches', , (), pp. -. doi: 10.22077/jwhr.2025.8174.1154
Chabokpour, Jafar. Estimating Total Sediment Load Using Water Quality Parameters in the Sufi Chay River, Iran: A Comparative Analysis of Soft Computing and Dimensionless Approaches. , 1403; (): -. doi: 10.22077/jwhr.2025.8174.1154

Estimating Total Sediment Load Using Water Quality Parameters in the Sufi Chay River, Iran: A Comparative Analysis of Soft Computing and Dimensionless Approaches

Water Harvesting Research
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 24 دی 1403
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22077/jwhr.2025.8174.1154
نویسنده
Jafar Chabokpour*
Civil engineering department, University of Maragheh
چکیده
The sediment transport and the relation to water quality parameters and hydrological characteristics in the Sufi Chay River in Iran were investigated in this study using long-term data. Traditional statistical methods, dimensionless parameter analysis, and advanced soft computing techniques are combined within the scope of presented comprehensive analysis. Sediment discharge is the dependent variable, while the independent variables include flow rate, total dissolved solids (TDS), electrical conductivity (EC), pH, total anions, total cations, anion hardness, and cation hardness. Strong correlations were observed between sediment discharge and flow rate (r = 0.82), total dissolved solids (r = 0.68), and electrical conductivity (r = 0.65). The dimensionless equation developed related sediment concentration to Reynolds number, Froude number, and normalized water quality parameters. The performance was quite good as revealed by the R2 value of 0.82. Comparison of performances using three soft computing methods, namely Artificial Neural Networks, Adaptive Neuro-Fuzzy Inference System, and Support Vector Regression, are performed. The highest R2 value of 0.91 and RMSE of 53.2 tons/ day were obtained with ANFIS model. Sensitivity analyses indicated that flow rate and TDS were the most sensitive parameters to predict sediment discharge. Generally, a seasonal variability in sediment transport, showing that the maximum discharges happened in the spring season with the mean of 187.3 tons/day, while the minimum discharges happened in the summer season with the mean of 42.8 tons/day. Besides, a nonlinear relationship between flow rate and both sediment concentration and discharge in this catchment reflects a complex erosion and transport process.
کلیدواژه‌ها
Total sediment load؛ Water quality؛ Soft computing؛ Dimensionless analysis؛ River management
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تعداد مشاهده مقاله: 46


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