Impacts of variation of river geometry on flowing water quality (Case Study: Ghezel Ozan River)

Document Type : Research Article


1 Department of Irrigation and Reclamation Engineering, University of Tehran, Iran

2 Associate Professor, Department of Irrigation & Reclamation Engineering, University of Tehran, IRAN


Introduction: Rivers are generally receiving wastewater from agriculture, industrial and urban areas. Population growth, urban development and human activities have always been a threat to the quantity and quality of river water flows. In general the purer the water, the more valuable and useful it is for riverine ecology and for abstractions to meet human demands such as irrigation, drinking and industry. Conversely, the more polluted the water, the more expensive it is to treat to satisfactory levels. This leads to disruption of natural food chains and the loss of riverine lives. Protecting and improving the quality of river flows is a priority.
The changing hydrological regime associated with the developing water demand schemes may alter the capacity of the environment to assimilate water soluble pollution. In particular, reductions in low flows result in increased pollutant concentrations already discharged into the water course either from point sources, such as industry, irrigation drains and urban areas, or from non-point sources, such as agrochemicals leaking into groundwater and soil erosion. Reduced flood flows may remove beneficial flushing, and reservoirs may cause further concentration of pollutants. Monitoring of water quality in different reaches of rivers depends on the purposes of water uses and requires a long-time and high-cost planning. Numerical simulator models are useful tools for a rapid and low-cost assessment and prediction of water quality in the present and in the future conditions of the rivers reaches. Different scenarios can be tested for determining and evaluating the effects of point and non-points sources of pollutants discharging into the river, and for predicting the effectiveness of alternative restoration plans in the management of water-based lives instream and in riverine riparian areas. In the present study, the effects of discharging pollutants on water quality in a long river reach have been investigated under the present condition and in different scenarios of river training schemes.
Methodology: In this study, the 51-km Diwandra-Bijar Reach of the Ghezel Ozan River was selected. Modeling of the existing conditions of river quality was performed using existing geometric-hydraulic and river water quality data. Two mathematical models QUAL2KW and WASP were used to simulate the water quality. Simulation of different parameters (such as: DO, BOD, COD, Norg, NH3, Q, h, V, T and pH) were considered. In order to calibrate these models, RMSE and MAPE statistical indices were used. Using the QUAL2KW model, five river training schemes (variation of 1- river width, 2- side slope, 3- longitudinal slope, 4-coefficient of roughness; and 5- width and longitudinal slope of the river) were considered.
Results and discussion: Comparison of river conditions simulation with two models of QUAL2KW and WASP with observational data showed that both models have the proper ability to simulate water quality. The study of river conditions showed that the river flow increased during the study area due to the entry of the sub branch. Due to changes in geometry and river flow, depth and flow velocity are changing along the path. Changes in river water temperature to 35 km are decreasing and then rising. The concentration of dissolved oxygen from the upstream to downstream of the river is decreasing. BOD concentration is rising from kilometer 19. The concentration of nitrate in kilometer 32 has increased due to the arrival of the Cham Zard River. The concentration of Norg has increased from Kilometer 19. This is due to changes in the river section and a decrease in sedimentation due to the increase of flow and entry of pollutants into the river. Ammonia concentration also increased at Kilometer 19 with the arrival of the Cham Zard River, and finally decreased by the arrival of the Yol Gashti river. Investigating scenarios showed that, in decreasing river width, flow velocity increased, resulting in an increase in the concentration of dissolved oxygen that increased the amount of river self-purification capacity. The concentration of NO3, BOD and COD parameters also increased slightly in high Discharge. The effect of the scenario of the Side slope on the water quality and hydraulic performance of the river is very small and has the least impact on the water quality of the river. By reducing the slope of the river bed, the flow rate is reduced, so the dissolved oxygen decreases. And the concentration of BOD and COD parameters has increased and the concentration of nitrate has decreased. This scenario is appropriate for the condition where the river needs to reduce the BOD. By the roughness increases, the flow velocity decreases. Consequently, the concentration of quality parameters (such as: BOD, DO and COD) are decreased.
Conclusion: The results indicated that both models are capable of simulating the qualitative status of the river reach. The results of the five river training scenarios prove that wherever the dissolved oxygen (DO) is insufficient in the flowing water, the decrease in the channel width has the greatest effect. Implementation of both the decrease in channel slope and the increase in the channel width is effective in the reduction of BOD and COD, while does not result in a significant reduction in DO. Nitrate variations are almost negligible in all scenarios, indicating a low susceptibility of this parameter to the changes the channel geometry. However, wherever the concentration of Nitrate is a major treat, the increase in the channel width together with the decrease in the channel slope would be an alternative training solution.
Keywords: River training, Water quality, QUAL2KW model, WASP model, Ghezel Ozan River.


Antunesa, I.M.H.R, Albuquerqueb, M.T.D, Oliveirab, S.F. and Sánzc, G. (2018). Predictive scenarios for surface water quality simulation - A watershed case Study, Catena 170, 283–289
Biglari, M.R., Sima, S. and Saadatpour, M. (2019). Modeling and Management of the River Water Quality for Aquatic Habitat Health Using a Source Control Approach (Case Study: Zarrineh-rud River). Iran-Water Resources Research. 14(5), 54-70. (in Persian).
Bowie, G.L; Mills, W.B; Porcella, D.B; Campbell, C.L; Pagenkopf, J.R; Rupp, G.L; et al. (1985). Rates, constants, and kinetics formulations in surface water quality modeling. EPA. 600,3-85.
Canu, D; Ginevra, R. (2017). Long-term scenarios of mercury budgeting and exports for a Mediterranean hot spot (Marano-Grado Lagoon, Adriatic Sea), Estuarine, Coastal and Shelf Science. 198, 518-528.
Cox, B.A.A. (2003). A review of dissolved oxygen modelling techniques in low land rivers. The Science of the Total Environment, NCBI, 314-316.
Kannel, P.R., Leea, S., Lee, Y.S., Kanel, S.R. and Pelletier, G.J. (2007). Application of automated QUAL2KW for water quality modeling and management in the Bagmati River, Nepal. Journal of Ecological Modeling. 202, 503517.
Karamoz, M. and Karachian, R. (2013). Planning And quality management of water resource systems. 2nd ed. Tehran: Amirkabir University of Technology. (in Persian).
Khajehpour, M.E., Karimi, L., Shiasi Arani, M. and Ansari, H. (2014). Eutrophication Check of Reservoirs with CE-QUAL-W2(Case study: Shirin Darre dam reservoir). Iranian Journal of lrrigation and Drainage. 1(8), 96-107. (in Persian).
Mathew, M., Yao, Y., Cao, Y., Shodan, K.H., Ghosh, I., Bucci,V., Leatao, C.H., Njokaand, D. and Hellweger, L. (2011). Anatomy of an urban waterbody: A case study of Boston’s muddy river. Environmental Pollution. 159,1996-2002.
Mesbah, M. (2008). The quality management of the river system through the trade license for the discharge of pollution through fuzzy logic. Master's thesis, Department of Environmental Engineering, Tehran University. (in Persian).
Milovanovic, M. (2007) Water quality assessment and determination of pollution sources along the Axios/Vardar river, Southeastern Europe. Desalinization. 213(1-3), 159-173
Oliveira, B., Bola, J., Quinteiro, P., Nadais, H, and Arroja, L. (2012). Application of QUAL2KW model as a tool for water quality management: Certima River as a case study. Environmental monitoring and assessment. 184(10), 6197-6210.
Pelletier, G.J. and Chapra, S.C. (2008). QUAL2Kw, theory and documentation (version 5.1); A modeling framework for simulating river and stream water quality. Department of Ecology Publications Distributions Office. Publication. 08-03.
Privette, C.V. and Smink, J. (2017). Assessing the potential impacts of WWTP effluent reductions within the Reedy River watershed. Ecological Engineering, 98, 11-16.
Rafiee, M., Ali, A., Mohammad, A., Moazed, H., Lyon, S.W. and Jaafarzadeh, N. (2014). A Case Study of Water Quality Modeling of the Gargar River. Iran. Journal of Hydraulic Structures, 1(2), 10-22. (in Persian).
Rajabizadeh Y. and Sayari N. (2017). Investigation of river water quality parameters using WASP software (case study: Baft river, Kerman province). 14th National Conference on Irrigation and Evaporation of Shahid Bahonar University of Kerman. (in Persian).
Rezaei Moghadam, M.H., Sarvati, M.R. and Asghari Sareskanroodi, S. (2011). Compared Investigation Meandering Pattern by Fractal GeometricalAnalysis and Central Angles and Sinuosity Ratio Indices. Journal of Watershed Management, 2(3). (in Persian).
Sharma, D., Kansal, A. and Pelletier, G. (2017). Water quality modeling for urban reach of Yamuna river, India (1999–2009), using QUAL2Kw. Applied Water Science, 7, 1535–1559.
Tajrishi, M., Abrishamchi, A., Ahmadi, M. and Turkian, A. (2009). Standard No. 481. Guide to the self-purification capacity of rivers, The Ministry of Energy, Technical report (in Persian).
Streeter, M.W., Phelps, E.E. (1925) A study of the pollution and natural purification of the Ohio River. U.S. Department of Health, Education, & Welfare. pp 146.
  • Receive Date: 04 July 2019
  • Revise Date: 02 October 2019
  • Accept Date: 07 October 2019
  • First Publish Date: 20 February 2020