Hydraulic and water quality simulation in steep-slope rivers: a case study of Dohezar river, Tonekabon

Document Type : Research Paper

Authors

Department of Civil Engineering, Faculty of Civil Engineering and Environment, Shahid Beheshti University, Tehran, Iran.

10.22059/jwim.2025.384294.1186

Abstract

The growth of pollutants in surface water resources has significantly increased, causing adverse effects on the environment and human communities. As a result, the use of mathematical models to simulate river water quality and evaluate various scenarios has become essential. This study utilizes the HEC-RAS model to assess the spatial and temporal distribution of pollutants in mountainous rivers with steep slopes and a step-pool structure, as well as to examine changes in pollutants at sections above and below the step. Four main sections on the Dohezar River in Tonekabon, located upstream, downstream, upstream of the step, and downstream of the step, were studied. Qualitative samples for dissolved oxygen, nitrate, inorganic phosphorus, and water temperature were collected and tested over an eight-month period. The simulation results during calibration and validation periods showed that the mean minimum and maximum total relative errors were 1.05 percent for temperature and 10.18 percent for inorganic phosphorus, respectively, indicating acceptable accuracy of the HEC-RAS model in simulating water quality parameters. Overall, due to stable flow and reduced turbulence, errors were lower in upstream and downstream sections, while error increased in areas downstream of the step due to enhanced turbulence and movement of settled quality parameters. Another reason for increased error in these areas is the model's use of hydrostatic pressure instead of hydrodynamic pressure, which reduces accuracy in turbulent flows. The results indicate that the HEC-RAS model performs well in simulating water quality in mountainous rivers, and improving the simulation of settled quality parameters and nitrate and phosphorus processes can further enhance the model's accuracy.

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