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

Abstract

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.

Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions

“…As can be seen from this figure, crowdsourcing techniques have been widely used to collect precipitation data (15% of the reviewed papers) and data for natural hazard management (17%). This is likely because precipitation data and data for natural hazard management are highly spatially distributed, and hence are more likely to benefit from crowdsourcing techniques for data collection (Eggimann et al, ). In terms of potential issues that exist within the applications of crowdsourcing approaches, project management, data quality, data processing, and privacy have been increasingly recognized as problems based on our review and hence they are considered (Figure ).…”

“…The availability of sufficient and high quality data is vitally important for activities in a broad range of areas within geophysics (Assumpção et al, ). As shown in Figure , data are used, either directly or via models, for a variety of purposes (Eggimann et al, ; Montanari et al, ; See et al, ), such as developing increased understanding of physical systems or processes (e.g., the weather); geophysical event prediction (e.g., rainfall, earthquakes); natural resources management (e.g., river systems); impact assessment (e.g., air pollution); infrastructure system planning, design, and operation (e.g., water supply systems); and the management of natural hazards (e.g., floods). In addition, they are also used in the model development process itself (See, Schepaschenko, et al, ), as well as to inform us about deficits in our models and thus foster an improved understanding/form the basis of scientific discovery (Del Giudice et al, ).…”

“…This problem has been exacerbated in recent years as real‐time water system operations and management are being adopted increasingly in many cities around the world. These real‐time systems require substantially increased amounts of precipitation data with high spatiotemporal resolution (Eggimann et al, ), which themselves are becoming more variable as a result of climate change (e.g., Berg et al, ; Wasko & Sharma, ; Zheng, Westra, et al, ).…”

A Systematic Literature Mining of Sponge City: What Has Been Done and The Challenges Standing Ahead

“…This statistical result also stresses the significance of this paper, which also belongs to review, covering the history of development of Sponge City, research trends and challenges in the future. The previous reviews also contribute in different aspects, such as different practices [68,69], effectiveness [70], technologies [71], challenges in the background of climate change and urbanization [72]. The type VI focuses on water quality, waste, and pollution control or management.…”

Leveraging Big Data Tools and Technologies: Addressing the Challenges of the Water Quality Sector

“…The development of a new generation of sensors, more accurate, smaller, cheaper to manufacture, and able to transmit the information in almost real time, is a contributing factor to the ubiquity of devices generating data of use for the water industry [59][60][61][62][63]. However, despite having access to a broad range of data sources and technical resources, the water utility sector appears to make very limited use of it for the improvement of water quality and source apportionment.…”