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Quality management of Zarrineh Rud river for agricultural irrigation using QUAL2K simulation model

    Armin Jalalzadeh Affiliation
    ; Hamid Reza Rabieifar Affiliation
    ; Hamid Reza Vosoughifar Affiliation
    ; Arash Razmkhah Affiliation
    ; Ebrahim Fataei Affiliation

Abstract

Zarrineh Rud river is one of the most important rivers in northwest of Iran. In this study, QUAL2K simulation model was used. The simulation parameters in this study were collected from 5 sampling stations. The results showed that the amount of oxygen saturated solution of Zarrineh Rud river varied between 7–8 mg / l, which is higher than the maximum standard value required. The results showed that BOD could increase by 16%, respectively, and should decrease by 70%. The station S5 at the river downstream with 3.53 mg/L DO deficit was the most critical point, and the 26th kilometer of the river with a DO deficit of 2.05 mg/L was the most critical point for maintaining the aquatic life; therefore, some scenario must be developed for waste load reduction at this station. In order to improve the quality of Zarrineh Rud river, construction of a wastewater treatment plant is necessary for Miandoab sugar factory.

Keyword : water quality, modeling, QUAL2K, Zarrineh Rud river, aquatic, Iran

How to Cite
Jalalzadeh, A., Rabieifar, H. R., Vosoughifar, H. R., Razmkhah, A., & Fataei, E. (2022). Quality management of Zarrineh Rud river for agricultural irrigation using QUAL2K simulation model. Journal of Environmental Engineering and Landscape Management, 30(4), 457–471. https://doi.org/10.3846/jeelm.2022.17631
Published in Issue
Nov 24, 2022
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References

Abdilzadeh, M. (2015). Application of computer models in qualitative simulation of rivers (Case study: Godarchay river). In 10th International Seminar on River Engineering, Tehran, Iran.

Babakhani, Z., Tabrizi, M. S., & Babazadeh, H. (2019). Determination of river self-purification capacity using QUAL2Kw mode case study: Divandare River, Iran. Iranian Journal of Echohydrology, 8(3), 673–684.

Carney, E. (2009). Relative influence of lake age and watershed land use on tropic state and water quality of artificial lakes in Kansas. Lake and Reservoir Management, 25, 199–207. https://doi.org/10.1080/07438140902905604

Chang, H. (2004). Water quality impacts of climate and land use changes on Southeastern Pennsylvania. The Professional Geo­grapher, 56, 240–257.

Chapra, S. C., Pelletier, G. J., & Tao, H. (2008). QUAL2K: A modeling framework for simulating river and stream water quality (Version 2.11: Documentation and user’s manual). Civil and Environmental Engineering Department, Tufts University, Medford.

Devi, K. (2017). Self-purification capacity of Bhavani River. Research Journal of Engineering Science, 6(3), 1–4.

Ebadati, N. (2017). Statistical analysis of Dez river water quality, South west of Iran. Journal of Anthropogenic Pollution, 1(1), 46–60.

Fataei, E., Donya, A. M., & Fatemeh, N. (2014). Prediction of thermal stratification of Seymareh Dam using CE-QUAL-W2 model. Advances in Bioresearch, 5(1), 150–159.

Fataei, E., Monavari, S. M., Hasani, A. H., Mirbagheri, S. A., & Karbasi, A. (2011). Surface water quality assessment using cluster analysis: A case study of the Gharasou River Basin, Iran. Iranian Journal of Environmental Sciences, 8(2), 137–146.

Ghorbani, Z., Amanipoor, H., & Battaleb-Looie, S. (2022). Water quality simulation of Dez River in Iran using QUAL2KW model. Geocarto International, 37(4), 1126–1138. https://doi.org/10.1080/10106049.2020.1762763

Gonzales, S. O., Almeida, C. A., Calderone, M., Mallea, M. A., & Gonzalea, P. (2014). Assessment of the water self-purification capacity on a river affected by organic pollution: Application of chemo metrics in spatial and temporal variations. Environmental Science and Pollution Research International, 21(18), 10583–10593. https://doi.org/10.1007/s11356-014-3098-y

Hakimpour, K. (2005). A study of practical methods and strategies for prevention and control of water resources pollution and restoration of their lost capacity (Applied research project, Final report, Vol. 1). Iran Water Resources Management Company.

Huang, J., Zhou, P., Zhou, Z., & Huang, Y. (2013). Assessing the influence of land use and land cover datasets with different points in time and levels of detail on watershed modeling in the North River watershed, China. International Journal of Environmental Research and Public Health, 10, 144–157. https://doi.org/10.3390/ijerph10010144

Jalili, S. (2020). Water quality assessment based on HFB I& BMWP Index in Karoon River, Khouzestan Provience (Northwest of Persian Gulf). Anthropoghenic Pollution, 4(1), 35–49.

Kerachian, R. (2012). Study of seasonal changes in self-purification of Karun River. Amirkabir Civil Engineering Journal, 49(4), 621–634.

Lai, Y. C., Tu, Y. T., & Yang, C. P. (2013). Development of a water quality modeling system for river pollution index and suspended oil loading evaluation. Journal of Hydrology, 478, 89–101. https://doi.org/10.1016/j.jhydrol.2012.11.050

Lee, I., Hwang, H., Lee, J., Yu, N., Yun, J., & Kim, H. (2017). Modeling approach to evaluation of environmental impacts on river water quality: A case study with Galing River, Kuantan, Pahang, Malaysia. Ecological Modelling, 353(10), 167–173. https://doi.org/10.1016/j.ecolmodel.2017.01.021

Melo, R. H., Benetti, M., & Melo, R. R. (2020). Surface Water Quality Modeling of a watershednin the north of Rio Grande do Sul. International Journal of Advanced Engineering Research and Science, 7(9), 306–310. https://doi.org/10.22161/ijaers.79.36

Miri, M. (2010). Ghareh Aghaj River quality simulation using QUAL2K model [Unpublished Master of Science thesis]. University of Tehran.

Moghimi Nezad, S., Ebrahimi, K., & Kerachian, R. (2017). Investigation of seasonal self-purification variations of Karun River. Amirkabir Civil Engineering Journal, 49(4), 621–634.

Najafi, H., & Mahmoudpour, T. (2012). Qualitative modeling of Qarasu River using QUAL2K model [Conference presentation]. First National Conference on Flow and Water Pollution, Tehran, University of Tehran, Water Institute.

Nugraha, W. D., Sarminingsih, A., & Alfisya, B. (2020). The study of self purification capacity based on Biological Oxygen Demand (BOD) and Dis-solved Oxygen (DO) parameters. IOP Conference Series: Earth and Environmental Science, 448, 012105. https://doi.org/10.1088/1755-1315/448/1/012105

Oliveira, J., Bola, P., Quinteiro, H., & Nadais, L. (2013). Application of Qual2Kw model as a tool for water quality management: Cértima River as a case study. Environmental Monitoring and Assessment, 184(10), 6197–6210. https://doi.org/10.1007/s10661-011-2413-z

Privette, C. V., & Smink, J. (2017). Assessing the potential impacts of WWTP effluent reductions within the Reedy River watershed. Ecological Engineering, 98, 11–16. https://doi.org/10.1016/j.ecoleng.2016.10.058

Saily, R., & Setiawan, B. (2021). Determination of carrying and load capacity using QUAL2Kw modeling simulation. IOP Conference Series: Earth and Environmental Science, 737, 012022. https://doi.org/10.1088/1755-1315/737/1/012022

Sajjadi, N., Davoodi, M., & Jozi, S. A. (2019). The quality assessment of Kan River’s resources in terms of agricultural and drinking purposes. Anthropoghenic Pollution, 3(1), 46–53.

Semenov, M. Y., Semenov, Y. M., Silaev, A. V., & Begunova, A. (2019). Assessing the self-purification capacity of surface waters in Lake Baikal Watershed. Water, 11(7), 1505. https://doi.org/10.3390/w11071505

Tajrishi, A. (2001). Zoning of river pollution by fuzzy classification technique (Applied research project). Iran Water Resources Management Company.

Tian, Sh., Wang, Z., & Shang, H. (2011). Study on the Self-purification of Juma River. Procedia Environmental Sciences, 11, 1328–1333. https://doi.org/10.1016/j.proenv.2011.12.199

Yustiani, Y. M. (2021). Deoxygenation rate coefficient in modeling the quality of urban rivers in Indonesia. IOP Conference Series: Earth and Environmental Science, 802, 012022. https://doi.org/10.1088/1755-1315/802/1/012022