Modeling Water Quality of Chitgar Lake: Evaluation of the Effectiveness of Various Water Treatment Scenarios on Lake Water Quality

Document Type : Original Research Article

Authors

1 Department of Environmental Pollutants Research, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, Iran

2 Department of Geography and Urban Planning, Faculty of Humanities, Payame Noor University of Karaj, Alborz, Iran

3 Department of Environment, Natural Resources Faculty, Isfahan University of Technology, Isfahan, Iran

4 Department of Environmental Science, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

Abstract

Chitgar Lake in Tehran city faces challenges in maintaining water quality due to nutrient loading and potential eutrophication. A water treatment plant (WTP) established in 2016 plays a crucial role in improving Chitgar Lake's water quality. The treatment process involves screening, coagulation, filtration, and disinfection, reducing TP to below 0.02 mg/L before releasing the water into the lake. A water quality model was developed to assess the impacts of external and internal nutrient and organic loading on lake management. This study investigates the impact of different WTP operational scenarios on water quality parameters using a water quality model. The results show that the lake experiences water quality issues, with a minimum DO level of 3.96 mg/L and maximum TP and Chl-a levels exceeding standard levels. The river water undergoes significant improvements after treatment, with nutrient reductions, Chl-a, and turbidity. The study highlights the critical need for continuous monitoring and effective treatment strategies to maintain Chitgar Lake's water quality well above standard conditions. The model serves as a valuable tool for assessing management strategies and optimizing water treatment plant operations, helping to control eutrophication and preserve the lake's recreational value. The simulation scenarios indicate that the most effective strategy for maintaining water quality in Chitgar Lake is the continuous operation of the water treatment plant during both the refilling and recycling periods. This approach successfully keeps key parameters, such as Chl-a and TP, within acceptable limits, effectively preventing eutrophication and ensuring the lake's suitability for recreational activities.

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References

 Afshar, A. & Saadatpour, M., 2008. Reservoir eutrophication modeling, sensitivity analysis, and assessment; application to Karkheh Reservoir, Iran. Journal of Environmental Engineering and Science, 26(7), 1227-1238.
 Bayat, J., Hashemi, S.H., Nikzad, M.F. & Talakesh, S.M.R., 2021. Necessity of water treatment to meet lake water quality goals in Chitgar Lake. Lake and Reservoir Management, 37(2), 160-169.
 Bayat, J., Zolfagharian, M., Hashemi, S.H., Emam, A. & Zeranki Nooshabadi, E., 2019. Water quality management of a man-made lake: case study Persian Gulf Martyrs Lake. ICOLD 2019 Annual Meeting/Symposium, June 9-14, Ottawa, Canada.
Bueche, C.J., 2008. Water quality monitoring of five major tributaries in the Otsego Lake watershed. 40th Annual Report, SUNY Oneonta Biological Field Station, SUNY Oneonta.
Calamita, E., Vanzo, D., Wehrli, B. & Schmid, M., 2021. Lake modeling reveals management opportunities for improving water quality downstream of transboundary tropical dams. Water Resources Research, 57(4), e2020WR027465.
Das, A., 2025. Prediction of Urban Surface Water Quality Scenarios Using Water Quality Index (WQI), Multivariate Techniques, and Machine Learning (ML) Models in Water Resources, in Baitarani River Basin, Odisha: Potential Benefits and Associated Challenges. Earth Systems and Environment, 1-37.
Duc, N.H., Avtar, R., Kumar, P. & Lan, P.P., 2021. Scenario-based numerical simulation to predict future water quality for developing robust water management plan: a case study from the Hau River, Vietnam. Mitigation and Adaptation Strategies for Global Change, 26, 1-38.
 Emam, A., Zolfagharian, M., Binazadeh, K., Alavi Deilami, H., Eslaminia, A. & Bayat, J., 2016. Construction of the Chitgar Dam’s artificial lake: social and environmental impact assessment. Paper presented at the International Symposium on Appropriate Technology to Ensure Proper Development, Operation, and Maintenance of Dams in Developing Countries, Johannesburg, South Africa.
 Evtimova, V.V. & Donohue, I. 2014. Quantifying ecological responses to amplified water level fluctuations in standing waters: an experimental approach. Journal of Applied Ecology, 51, 1282-1291.
 Fewtrell, L. & Kay, D., 2015. Recreational water and infection: a review of recent findings. Current Environmental Health Reports, 2(1), 85-94. DOI: 10.1007/s40572-014-0036-6.
 Hughes, D. & Slaughter, A., 2016. Disaggregating the components of a monthly water resources system model to daily values for use with a water quality model. Environmental Modelling & Software, 80, 122-131.
 Isazadeh, S., Tajrish, M., Abrishamchi, A. & Ahmadi, M., 2005. Application of phosphorous simulation models to Latian Reservoir. Water and Wastewater, 54, 3-16.
 Li, S., Liu, W., Gu, S., Cheng, X., Xu, Z. & Zhang, Q., 2009. Spatio-temporal dynamics of nutrients in the upper Han River basin, China. Journal of Hazardous Materials, 162(2-3), 1340-1346.
 Lindim, C., Becker, A., Grüneberg, B. & Fischer, H., 2015. Modelling the effects of nutrient loads reduction and testing the N and P control paradigm in a German shallow lake. Ecological Engineering, 82, 415-427.
 Lindim, C., Pinho, J. & Vieira, J., 2011. Analysis of spatial and temporal patterns in a large reservoir using water quality and hydrodynamic modeling. Ecological Modelling, 222(14), 2485-2494. DOI: 10.1016/j.ecolmodel.2010.07.019.
Liu, Y., Wang, Y., Sheng, H., Dong, F., Zou, R., Zhao, L. & He, B., 2014. Quantitative evaluation of lake eutrophication responses under alternative water diversion scenarios: a water quality modeling based statistical analysis approach. Science of the Total Environment, 468, 219-227.
 Meng, X., Zhang, Y., Yu, X., Zhan, J., Chai, Y., Critto, A., Li, Y. & Li, J., 2015. Analysis of the temporal and spatial distribution of lake and reservoir water quality in China and changes in its relationship with GDP from 2005 to 2010. Sustainability, 7(2), 2000-2027.
 Naselli-Flores, L. & Barone, R., 2005. Water-level fluctuations in Mediterranean reservoirs: setting a dewatering threshold as a management tool to improve water quality. Hydrobiologia, 548, 85-99.
 Rubel, M., Chowdhury, D.A., Ahmed, M.J.U. & Uddin, M.H., 2019. Physico-chemical characterization of Kaptai Lake and Foy’s Lake water quality parameters in Chittagong, Bangladesh. American Journal of Pure and Applied Sciences, 1(6), 49-58.
 Sadeghian, A., Chapra, S.C., Hudson, J., Wheater, H. & Lindenschmidt, K.-E., 2018. Improving in-lake water quality modeling using variable chlorophyll a/algal biomass ratios. Environmental Modelling & Software, 101, 73-85.
 Sudha, R. & Sangeetha, T., 2017. Comparative study of water quality parameters of lake water Chinna Eri with surrounding bore well water samples Thuraiyur Tk Tiruchirappalli Dt Tamil Nadu. International Journal of Current Research in Chemistry and Pharmaceutical Sciences, 4(7), 14-18.
 Sullivan, A.B. & Rounds, S.A., 2005. Modeling hydrodynamics, temperature, and water quality in Henry Hagg Lake, Oregon 2000-2003. USGS Scientific Investigations Report 2004-5261. Available at: http://pubs.usgs.gov/sir/2004/5261.
 Xie, G., Zhang, J., Tang, X., Cai, Y. & Gao, G., 2011. Spatio-temporal heterogeneity of water quality (2010-2011) and succession patterns in Lake Bosten during the past 50 years. Journal of Lake Sciences, 23, 837-846.
Xing, Z., Chua, L. H. & Imberger, J., 2014. Evaluation of management scenarios for controlling eutrophication in a shallow tropical urban lake. International Journal of Environmental Pollution and Remediation (IJEPR), 2(1), 66-72.
Zhang, Q. & You, X.Y., 2024. Recent advances in surface water quality prediction using artificial intelligence models. Water Resources Management, 38(1), 235-250.
 Zhang, W., Li, H. & Li, Y., 2019. Spatio-temporal dynamics of nitrogen and phosphorus input budgets in a global hotspot of anthropogenic inputs. Science of the Total Environment, 656, 1108-1120.

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