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The Potential of Knowing More: A Review of Data-Driven Urban Water Management

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† Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
‡ Institute of Civil, Environmental and Geomatic Engineering, ETH Zürich, 8093 Zurich, Switzerland
*Phone: +41 58 765 6851; e-mail: [email protected]
Cite this: Environ. Sci. Technol. 2017, 51, 5, 2538–2553
Publication Date (Web):January 26, 2017
https://doi.org/10.1021/acs.est.6b04267
Copyright © 2017 American Chemical Society
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    Abstract

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    The promise of collecting and utilizing large amounts of data has never been greater in the history of urban water management (UWM). This paper reviews several data-driven approaches which play a key role in bringing forward a sea change. It critically investigates whether data-driven UWM offers a promising foundation for addressing current challenges and supporting fundamental changes in UWM. We discuss the examples of better rain-data management, urban pluvial flood-risk management and forecasting, drinking water and sewer network operation and management, integrated design and management, increasing water productivity, wastewater-based epidemiology and on-site water and wastewater treatment. The accumulated evidence from literature points toward a future UWM that offers significant potential benefits thanks to increased collection and utilization of data. The findings show that data-driven UWM allows us to develop and apply novel methods, to optimize the efficiency of the current network-based approach, and to extend functionality of today’s systems. However, generic challenges related to data-driven approaches (e.g., data processing, data availability, data quality, data costs) and the specific challenges of data-driven UWM need to be addressed, namely data access and ownership, current engineering practices and the difficulty of assessing the cost benefits of data-driven UWM.

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