| publications-2461 |
Peer reviewed articles |
2022 |
12.J Gao, K Li, Wenyan Wu, J Chen, T Zhang, L Deng and P Xin |
Innovative Water Supply Network Pressure Management MethodâThe Establishment and Application of the Intelligent Pressure-Regulating Vehicle |
Energies |
10.3390/en15051870 |
AI & Machine Learning |
Natural Water Bodies |
|
The development of many intelligent technologies, such as artificial intelligence and the Internet of Things, has brought new opportunities for water industry intelligence. Based on intelligent pressure regulation technology, this paper built an intelligent management platform, designed an intelligent pressure-regulating device, and combined both to form an intelligent pressure-regulating vehicle (IPRV). The IPRV has the functions of developing a pressure-regulating scheme, equipment selection, pressure reduction potential analysis, etc. It can bring convenience to the field test of the water supply network. In the field test, an intelligent pressure-regulating device was used to obtain the network data in the pilot site called S-cell. After utilizing the intelligent management platform to analyze the measured data, the water usage pattern and pressure reduction potential of the S-cell were obtained, and an optimal pressure-regulating strategy was formulated. The water pressure at the critical node always met the water demand at the critical node during the field test. In addition, no complaints were received from other users. The results show that the IPRV is not only convenient for utility managers to make decisions on building pressure-reducing stations, but also meets user needs, realizing a winâwin situation for both users and companies. |
765921 |
|
|
|
| publications-2462 |
Peer reviewed articles |
2021 |
Magdalena Matusiak; Krzysztof Dragon; JĂłzef GĂłrski; Roksana Kruc-Fijalkowska; Jan PrzybyĆek |
Surface water and groundwater interaction at long-term exploited riverbank filtration site based on groundwater flow modelling (Mosina-Krajkowo, Poland) |
Journal of Hydrology: Regional Studies |
10.1016/j.ejrh.2021.100882 |
Uncategorized |
Wastewater Treatment Plants |
|
No abstract available |
689450 |
|
|
|
| publications-2463 |
Peer reviewed articles |
2022 |
Roksana KruÄ-FijaĆkowska; Krzysztof Dragon; Dariusz DroĆŒdĆŒyĆski; JĂłzef GĂłrski |
Seasonal variation of pesticides in surface water and drinking water wells in the annual cycle in western Poland, and potential health risk assessment |
Scientific Reports |
10.1038/s41598-022-07385-z |
Control Systems |
Wastewater Treatment Plants |
|
AbstractDrinking water wells on a riverbank filtration sites are exposed to contamination from farmlands (like pesticides) that had migrated from the contaminated river. In this study, pesticide contamination of the Warta River and riverbank filtration water at the Mosina-Krajkowo well field (Poland) were examined during the annual cycle. Among the 164 pesticides analysed, 25 were identified. The highest concentrations occurred in the river water and decreased along the flow path from the river to wells. Only the most persistent substances were detected at the farthest points. During the study, seasonal changes in pesticide concentrations and differences in the types of occurring substances were observed. Most substances and the highest concentrations were detected in May 2018, while the lowest number and the lowest concentrations were detected in February 2018. Spring is the period of increased exposure of water to pollution, which is correlated with increased pesticides use and increased rainfall. Seven toxic and persistent pesticides were found with the highest concentrations in water: isoproturon, nicosulfuron, imidacloprid, terbuthylazine, chlorotoluron, S-metalachlor, and prometryn. Pesticides are widely used in the study area; therefore, a potential health risk assessment was performed. The hazard quotient (HQ) values did not exceed one, which indicated a less significant health risk. |
689450 |
|
|
|
| publications-2464 |
Peer reviewed articles |
2021 |
Daniel Sauter; Claudia Stange; Vera Schumacher; Andreas Tiehm; R. Gnirss; Thomas Wintgens; Thomas Wintgens |
Impact of ozonation and biological post-treatment of municipal wastewater on microbiological quality parameters |
Environ. Sci.: Water Res. Technol. |
10.1039/d1ew00312g |
Uncategorized |
Uncategorized |
|
Biological post-treatment after ozonation in tertiary municipal wastewater treatment significantly improves the abatement of several microbiological quality parameters. |
689450 |
|
|
|
| publications-2465 |
Peer reviewed articles |
2022 |
Munthali, E., Marcé, R., Farré, M.J. |
Drivers of variability in disinfection by-product formation potential in a chain of thermally stratified drinking water reservoirs |
Environmental Science: Water Research & Technology |
10.1039/d1ew00788b |
AI & Machine Learning |
Groundwater |
|
Increasing hydraulic residence time (HRT) along a chain of interconnected reservoirs enhances the formation potential of carbonaceous disinfection by-products (DBPs) and reduces the formation potential of nitrogenous DBPs, particularly N-nitrosodimethylamine (NDMA). |
722518 |
|
|
|
| publications-2466 |
Peer reviewed articles |
2021 |
Ribalta M, Mateu C, Bejar R, RubiĂłn E, Echeverria L, Varela Alegre FJ, Corominas L |
Sediment Level Prediction of a Combined Sewer System Using Spatial Features |
Sustainability |
10.3390/su13074013 |
Data Management & Analytics |
Water Distribution Networks |
|
The prediction of sediment levels in combined sewer system (CSS) would result in enormous savings in resources for their maintenance as a reduced number of inspections would be needed. In this paper, we benchmark different machine learning (ML) methodologies to improve the maintenance schedules of the sewerage and reduce the number of cleanings using historical sediment level and inspection data of the combined sewer system in the city of Barcelona. Two ML methodologies involve the use of spatial features for sediment prediction at critical sections of the sewer, where the cost of maintenance is high because of the dangerous access; one uses a regression model to predict the sediment level of a section, and the other one a binary classification model to identify whether or not a section needs cleaning. The last ML methodology is a short-term forecast of the possible sediment level in future days to improve the ability of operators to react and solve an imminent sediment level increase. Our study concludes with three different models. The spatial and short-term regression methodologies accomplished the best results with Artificial Neural Networks (ANN) with 0.76 and 0.61 R2 scores, respectively. The classification methodology resulted in a Gradient Boosting (GB) model with an accuracy score of 0.88 and an area under the curve (AUC) of 0.909. |
820751 |
|
|
|
| publications-2467 |
Peer reviewed articles |
2021 |
M.Escolà Casas, N.S.Schröter, I.Zammit, M.Castaño-Trias, S.Rodriguez-Mozaz, P.Gago-Ferrero and Ll.Corominas |
Showcasing the potential of wastewater-based epidemiology to track pharmaceuticals consumption in cities: Comparison against prescription data collected at fine spatial resolution |
Environment International |
10.1016/j.envint.2021.106404 |
Hydrological modeling |
River Basins |
|
No abstract available |
820751 |
|
|
|
| publications-2468 |
Peer reviewed articles |
2022 |
Pathak, D., Hutchins, M., Brown, L.E., Loewenthal, M., Scarlett, P., Armstrong, L., Nicholls, D., Bowes, M., Edwards, F., Old, G. |
High-resolution water-quality and ecosystem-metabolism modelling in lowland rivers |
Limnology & Oceanography |
10.1002/lno.12079 |
Data Management & Analytics |
River Basins |
|
AbstractHighâresolution monitoring of water quality and ecosystem functioning over large spatial scales in expansive lowland river catchments is challenging. Therefore, we need modeling tools to predict these processes at locations where observations are absent. Here, we present a new approach to estimate ecosystem metabolism underpinned by a highâresolution, processâbased model of inâstream flows and water quality. The model overcomes the current challenges in metabolism modeling by accounting for oxygen transport under varying flows and oxygen transformations due to biogeochemical processes. We implement the model in a 62âkmâlong stretch of the River Thames, England, using observations spanning 2 yr. Model outputs suggest that the river is primarily autotrophic from midâspring to midâsummer due to high biomass during lowâflow periods, and is heterotrophic during the rest of the year. Ecosystem respiration in upstream reaches is driven mainly by biochemical oxygen demand, autotrophic respiration, and nitrification processes, whereas downstream sites also show a control of benthic oxygen demand in addition to the aforementioned processes. Using empirical modeling, we analyze the sensitivity of our estimated metabolism rates to multiple environmental stressors. Results demonstrate that empirical models could be useful for rapid river health assessments, but need improvements to reproduce peak metabolism rates. The processâbased model, although more complex than existing in situ approaches to metabolism quantification, allows inference when gaps in continuous observations are present. The model offers additional benefits for predicting metabolism rates under future scenarios of environmental change incorporating multiple stressor effects. |
765553 |
|
|
|
| publications-2469 |
Peer reviewed articles |
2022 |
Zhan, Q., Teurlincx, S., van Herpen, F., Raman, N.V., LĂŒrling, M., Waajen, G. and de Senerpont Domis, L.N. |
Towards climate-robust water quality management: Testing the efficacy of different eutrophication control measures during a heatwave in an urban canal. |
Science of the Total Environment |
10.1016/j.scitotenv.2022.154421 |
Uncategorized |
Natural Water Bodies |
|
No abstract available |
722518 |
|
|
|
| publications-2470 |
Peer reviewed articles |
2021 |
Foglia, Alessia; Andreola, Corinne; Cipolletta, Giulia; Radini, Serena; Akyol, ĂaÄrı; Eusebi, Anna Laura; Stanchev, Peyo; Katsou, Evina; Fatone, Francesco |
Comparative life cycle environmental and economic assessment ofanaerobic membrane bioreactor and disinfection for reclaimed waterreuse in agricultural irrigation: A case study in Italy |
Journal of Cleaner Production |
10.5281/zenodo.4543511 |
Simulation & Modeling |
Water Distribution Networks |
|
No abstract available |
820954 |
|
|
|