Water Quality Modelling with Industrial and Domestic Point Source Pollution: a Study Case of Cikakembang River, Majalaya District
Abstract
Rapid industrial development is one of the leading causes of environmental degradation. The textile industries and the domestic activities in Majalaya District produce wastewater directly discharged into the Cikakembang River. As a result, the Cikakembang Riverâs water quality has decreased to the point that the water quality cannot be used for daily needs. This study modeled three main parameters in water quality modelling, namely Dissolved Oxygen (DO), Biological Oxygen Demand (BOD), and Chemical Oxygen Demand (COD). Using MATLAB, the three-water quality governing equations originating from the Advection-Dispersion Equation were solved using the Runge Kutte-4 discretization scheme. The numerical modelling was carried out along 2.36 km of the Cikakembang River. All water quality coefficients, such as the DO Saturation (DOsat), the Reaeration Rate (ka), the Dispersion Coefficient (D), the Deoxygenation Rate (kd), and the Decomposition Rate (kc), for the Cikakembang River were estimated using equations developed by existing studies. The estimation of ka and D coefficients requires hydraulic parameters, which in this study were estimated using the HEC-RAS simulation. Meanwhile, kd and kc values were obtained from the calibration and verification process. The Relative Root Mean Square Error (RRMSE) objective function was used to evaluate the results of water quality modelling at three sampling points. In the calibration process, the results
of water quality modelling produced RRMSE values for the DO, BOD, and COD parameters of 1.99%, 0.36% and 0.92%, respectively. Meanwhile, for the verification process, the RRMSE values for the DO, BOD, and COD parameters are 1.95%, 1.02% and 1.86%. All water quality parameters produce small RRMSE values in the calibration and verification processes. Hence, the water quality model created has good accuracy and stability.
References
Benedini, M. and Tsakiris, G. (2013), Water Quality Modelling for Rivers and Streams, Springer Dordrecht, s.l. URL: https://doi.org/10.1007/978-94-007-5378-3
Deng, T., Chau, K.-w. and Duan, H. (2021), âMachine learning based marine water quality prediction for coastal hydro-environment managementâ, Journal of Environmental Management 284, 112051. URL: https://doi.org/10.1016/j.jenvman.2021.112051
Despotovic, M., Nedic, V., Despotovic, D. and Cve tanovic, S. (2016), âEvaluation of empirical models for predicting monthly mean horizontal diffuse solar radiationâ, Renewable and Sustainable Energy Reviews pp. 246â260. URL: https://doi.org/10.1016/j.rser.2016.11.064
Dey, S. and Islam, A. S. (2015), âA review on textile wastewater characterization in bangladeshâ, Resources and Environment 5(1), 15â44. URL: https://doi.org/10.5923/j.re.20150501.03
Fitriana, F. et al. (2023), âThe assessment of citarum river water quality in majalaya district, bandung regencyâ, Rekayasa Sipil 17(1), 37â46. URL: https://doi.org/10.14710/teknik.v17i1.45029
Haider, H., Ali, W. and Haydar, S. (2013), âEvaluation of various relationships of reaeration rate coefficient for modelling dissolved oxygen in a river with extreme flow variations in pakistanâ, Hydrological Processes pp. 3949â3963. URL: https://doi.org/10.1002/hyp.9501
Iqbal, M. M., Shoaib, M., Farid, H. U. and Lee, J. L. (2018), âAssessment of water quality profile using numerical modeling approach in major climate classes of asiaâ, International Journal of Environmental Research and Public Health 15(2258). URL: https://doi.org/10.3390/ijerph15102258
Iwasa, Y. and Aya, S. (1991), âTransverse mixing in a river with complicated channel geometryâ, Bulletin of the Disaster Prevention Research Institute 41 (3), 129â175. URL: https://doi.org/10.11408/suirikagaku.41.129
Jha, R., Ojha, C. S. P. and Bhatia, K. K. S. (2001), âRefinement a predictive reaeration equations for a typical indian riverâ, Hydrological Processes pp. 1047â1060. URL: https://doi.org/10.1002/hyp.122
Jha, R., Ojha, C. S. P. and Bhatia, K. K. S. (2004),âA supplementary approach for estimating reaeration rate coefficientsâ, Hydrological Processes 18(1), 65â79. URL: https://doi.org/10.1002/hyp.1289
Khalish, M., Utami, A., Lukito, H. and Herlambang, S (2022), âEvaluation of textile industry waste water treatment as an effort to control river water pollution in central javaâ, KnE Life Sciences pp. 48â61.URL: https://doi.org/10.18502/kls.v8i1.10565
Lin, L., Yang, H. and Xu ,X.(2022),âEffects of water pollution on human health and disease heterogeneity: A reviewâ, Frontiers in Environmental Science 10. URL: https://doi.org/10.3389/fenvs.2022.846520
Liyanage, C. P. and Yamada, K.(2017),âImpact of population growth on the water quality of natural waterbodiesâ, Sustainability 9(8), 1405. URL: https://doi.org/10.3390/su9081405
Menendez, A., LecertĂșa, E., Badano, N. and GarcĂa, P. (2016), âNumerical modeling to define remediation actions for water quality in streamsâ, Journal of Applied Water Engineering and Research pp. 67â81. URL: https://doi.org/10.1016/j.jaer.2016.03.004
Nasrollahi, Z., Hashemi, M., Bameri, S. and Taghvaee, V. M. (2020), âEnvironmental pollution, economic growth, population, industrialization, and technology in weak and strong sustainability: using stirpat modelâ, Environment, Development and Sustainability 22, 1105â1122. URL: https://doi.org/10.1007/s10668-019-00352-0
Nogare, M. A. and Bauer, B. O. (2022), âA field-based evaluation of the reliability of empirical formulae for quantifying the longitudinal dispersion coefficient in small channelsâ, geosciences 12(281). URL: https://doi.org/10.3390/geosciences12120281
Polisar, A. (2023), âStudy of the impacts of domestic and textile industry wastewater discharge in cikakembang river, majalaya, bandung regencyâ, Parahyangan Catholic University. URL: https://doi.org/10.13140/RG.2.2.10236.33924
Popescu, I. (2014), Computational Hydraulics Numerical Methods and Modelling, IWA Publishing, London. URL: https://doi.org/10.2166/9781780404996
Schnoor, J. L. (1996), Environmental modeling: Fate and transport of pollutants in water, air, and soil, Wiley, Iowa. URL: https://doi.org/10.1002/9781119116469
Srinivas, T. A. S. et al. (2023), âUnlocking the power of matlab: A comprehensive surveyâ, IJARSCT 3(1), 20â31. URL: https://doi.org/10.47595/IJARSCT.2023.3710
Sun, L. et al. (2020), âA review of applications of fractional advectionâdispersion equations for anomalous solute transport in surface and subsurface waterâ, WIREs Water. URL: https://doi.org/10.1002/wat2.1448
Tabari, H. (2020), âClimate change impact on food and extreme precipitation increases with water availabilityâ, Scientific Reports 10, 13768. URL: https://doi.org/10.1038/s41598-020-70895-w
Tang, W. et al. (2022), âTwenty years of chinaâs water pollution control: Experiences and challengesâ, Chemosphere p. 133875. URL: https://doi.org/10.1016/j.chemosphere.2022.133875
Wang, X., Jiang, J. and Gao, W. (2022), âReviewing textile waste water produced by industries: characteristics environmental impacts, and treatment strategiesâ, Water Sci Technol pp. 2076â2096. URL: https://doi.org/10.2166/wst.2022.098
Wikiandy, N., Rosidah and Herawati, T. (2013), âThe impact of textile industry waste pollution on damage to the structural organs of fish living in the upper section of the citarum river flow (das)â, Journal of Fisheries and Marine Affairs (Jurnal Perikanan dan Kelautan) pp. 215â225. URL: https://doi.org/10.14710/jpk.5.3.215-225
Worldwide, C. (2019), âCdp global water report: Are companies responding to the risks and opportunitiesâ, CDPWorldwide. URL: https://doi.org/10.46755/cdp.2019.011
Yan, B., Yu, F., Xiao, X. and Wang, X. (2019), âGround water quality evaluation using a classification model: a case study of jilin city, chinaâ, Natural Hazards 99 (2), 735â751. URL: https://doi.org/10.1007/s11069-019-03654-3
Yu, X., Shen, J. and Du, J. (2020), âA machineâlearning based model for water quality in coastal waters, taking dissolved oxygen and hypoxia in chesapeake bay as an exampleâ, Water Resources Research p. 56. URL: https://doi.org/10.1029/2020WR027227,
Zeng, Y. H. and Huai, W. X. (2014),âEstimation of longitudinal dispersion coefficient in riversâ, Journal of Hydro-environment Research pp. 2â8. URL: https://doi.org/10.1016/j.jher.2014.05.001
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