Pregled bibliografske jedinice broj: 1215158
Water Quality Index Prediction for Improvement of Treatment Processes on Drinking Water Treatment Plant
Water Quality Index Prediction for Improvement of Treatment Processes on Drinking Water Treatment Plant // Sustainability, 14 (2022), 18; 11481, 16 doi:10.3390/su141811481 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1215158 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Water Quality Index Prediction for Improvement of
Treatment Processes on Drinking Water Treatment
Plant
Autori
Volf, Goran ; Sušanj Čule, Ivana ; Žic, Elvis ; Zorko, Sonja
Izvornik
Sustainability (2071-1050) 14
(2022), 18;
11481, 16
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Water quality index ; prediction models ; machine learning ; water quality ; treatment processes improvement ; drinking water treatment plant ; Butoniga reservoir
Sažetak
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, KMnO4, NH4, Mn, Al and Fe, the calculation of WQI was conducted, while for the WQI prediction models, along with the mentioned parameters, O2, 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.
Izvorni jezik
Engleski
Znanstvena područja
Biologija, Građevinarstvo
POVEZANOST RADA
Projekti:
NadSve-uniri-tehnic-18-129 - Održivo upravljanje riječnim slivom implementacijom inovativnih metodologija, pristupa i alata (Karleuša, Barbara, NadSve ) ( CroRIS)
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-54 - Hidrologija vodnih resursa i identifikacija rizika od poplava i blatnih tokova na krškom području (Ožanić, Nevenka, NadSve - Sveučilište u Rijeci) ( CroRIS)
Ustanove:
Građevinski fakultet, Rijeka
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- Social Science Citation Index (SSCI)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
