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Water Quality Index Prediction for Improvement of Treatment Processes on Drinking Water Treatment Plant

Author

Listed:
  • Goran Volf

    (Department of Hydraulic Engineering, Faculty of Civil Engineering, University of Rijeka, 51000 Rijeka, Croatia)

  • Ivana Sušanj Čule

    (Department of Hydraulic Engineering, Faculty of Civil Engineering, University of Rijeka, 51000 Rijeka, Croatia)

  • Elvis Žic

    (Department of Hydraulic Engineering, Faculty of Civil Engineering, University of Rijeka, 51000 Rijeka, Croatia)

  • Sonja Zorko

    (Istarski Vodovod d.o.o., 52420 Buzet, Croatia)

Abstract

In order to improve the treatment processes of the drinking water treatment plant (DWTP) located near the Butoniga reservoir in Istria (Croatia), a prediction of the water quality index (WQI) was done. Based on parameters such as temperature, pH, turbidity, KMnO 4 , NH 4 , Mn, Al and Fe, the calculation of WQI was conducted, while for the WQI prediction models, along with the mentioned parameters, O 2 , TOC and UV254 were additionally used. Four models were built to predict WQI with a time step of one, five, ten, and fifteen days in advance, in order to improve treatment processes of the DWTP regarding the changes in raw water quality in the Butoniga reservoir. Therefore, obtained models can help in the optimization of treatment processes, which depend on the quality of raw water, and overall, in the sustainability of the treatment plant. Results showed that the obtained correlation coefficients for all models are relatively high and, as expected, decrease as the number of prediction days increases; conversely, the number of rules, and related linear equations, depends on the parameters set in the WEKA modelling software, which are set to default settings which give the highest values of correlation coefficient (R) for each model and the optimal number of rules. In addition, all models have high accuracy compared to the measured data, with a good prediction of the peak values. Therefore, the obtained models, through the prediction of WQI, can help to manage the treatment processes of the DWTP, which depend on the quality of raw water in the Butoniga reservoir.

Suggested Citation

  • Goran Volf & Ivana Sušanj Čule & Elvis Žic & Sonja Zorko, 2022. "Water Quality Index Prediction for Improvement of Treatment Processes on Drinking Water Treatment Plant," Sustainability, MDPI, vol. 14(18), pages 1-16, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11481-:d:913999
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    References listed on IDEAS

    as
    1. Volf, Goran & Atanasova, Nataša & Kompare, Boris & Precali, Robert & Ožanić, Nevenka, 2011. "Descriptive and prediction models of phytoplankton in the northern Adriatic," Ecological Modelling, Elsevier, vol. 222(14), pages 2502-2511.
    2. Tanaka Mandy Mbavarira & Christine Grimm, 2021. "A Systemic View on Circular Economy in the Water Industry: Learnings from a Belgian and Dutch Case," Sustainability, MDPI, vol. 13(6), pages 1-62, March.
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    Cited by:

    1. Samara Soares & Joel Vasco & Paulo Scalize, 2023. "Water Quality Simulation in the Bois River, Goiás, Central Brazil," Sustainability, MDPI, vol. 15(4), pages 1-21, February.

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