Themed collection Data-intensive water systems management and operation
Editorial: Themed issue on data-intensive water systems management and operation
Branko Kerkez, Kris Villez and Eveline I. P. Volcke introduce the Environmental Science: Water Research & Technology themed issue on data-intensive water systems management and operation.
Environ. Sci.: Water Res. Technol., 2022,8, 2032-2033
https://doi.org/10.1039/D2EW90029G
Online monitoring of bromate in treated wastewater: implications for potable water reuse
An online bromate ion analyzer coupled with a nanofiltration membrane-based pre-treatment system can monitor bromate ion formation during wastewater ozonation.
Environ. Sci.: Water Res. Technol., 2022,8, 2034-2039
https://doi.org/10.1039/D1EW00634G
Application of data reconciliation to a dynamically operated wastewater treatment process with off-gas measurements
Data reconciliation was applied to a full-scale SHARON partial nitritation process. Adding off-gas analysis allowed to identify more key variables, facilitated gross error detection and led to more reliable information on N2O emissions.
Environ. Sci.: Water Res. Technol., 2022,8, 2114-2125
https://doi.org/10.1039/D2EW00006G
Automatic optimization of temporal monitoring schemes dealing with daily water contaminant concentration patterns
Online algorithms have been developed to automatically adjust monitoring schemes to sample instants characterized by maximum and/or minimum daily concentrations while reducing sampling costs with respect to traditional monitoring schemes.
Environ. Sci.: Water Res. Technol., 2022,8, 2099-2113
https://doi.org/10.1039/D2EW00089J
Including snowmelt in influent generation for cold climate WRRFs: comparison of data-driven and phenomenological approaches
A data-driven model was proposed for generating the influent flow and water temperature dynamics including the impact of snowmelt under cold climate conditions. The performance was compared with a phenomenological model.
Environ. Sci.: Water Res. Technol., 2022,8, 2087-2098
https://doi.org/10.1039/D1EW00646K
Reinforcement learning-based real-time control of coastal urban stormwater systems to mitigate flooding and improve water quality
Reinforcement learning agents can learn real-time stormwater system control strategies that balance the competing goals of flood mitigation and sediment capture in urban watersheds.
Environ. Sci.: Water Res. Technol., 2022,8, 2065-2086
https://doi.org/10.1039/D1EW00582K
Statistical and microbial analysis of bio-electrochemical sensors used for carbon monitoring at water resource recovery facilities
Real-time carbon monitoring of wastewater using bio-electrochemical sensors coupled with advanced data analysis methods provides WRRFs with an opportunity for efficient wastewater quality monitoring and an early warning tool for plant upsets.
Environ. Sci.: Water Res. Technol., 2022,8, 2052-2064
https://doi.org/10.1039/D1EW00653C
Turbidity informed real-time control of a dry extended detention basin: a case study
This research investigated the impact and use of real-time water quality data in a dry extended detention basin retrofitted with a controllable valve and a turbidity sensor with the goal of more consistently meeting water quality objectives.
Environ. Sci.: Water Res. Technol., 2022,8, 2040-2051
https://doi.org/10.1039/D1EW00654A
About this collection
Guest Edited by Branko Kerkez (University of Michigan, USA), Kris Villez (Oak Ridge National Laboratory, USA) and Eveline Volcke (Ghent University, Belgium) this themed collection reports on significant advances in the design and use of data-intensive methodologies for water systems management and operation.
The water sector increasingly looks at intensified instrumentation, data collection and automation as tools for daily use. Still, a massive opportunity remains in fully embracing emerging methods and technologies such as artificial intelligence, data analytics, machine learning, low-cost sensor hardware, and edge and cloud computing. Indeed, sensing and automation technology has already infiltrated many facets of society today. As such, the time is ripe to evaluate the role of novel technologies for systems monitoring, diagnostics, and automation of aquatic processes and large-scale water systems. When leveraged, the water sector will do more with less.