Department Urban Water Management

Urban water systems are being redefined for a digital age, promising substantial advantages for service users and providers, and for society as a whole. However, beside the much-discussed benefits of smart urban water systems in future smart cities, the transition will also bring unique challenges, particularly with respect to privacy and cybersecurity. A preemptive delineation of these risks and providing appropriate recommendations will help to guide digital transformations of urban water towards sustainable solutions. Faced with emerging risks of digitalization, urban water management needs to look beyond technology while recognizing the central and multifaceted role of research.
In smart city initiatives, urban water systems remain largely out of the digitalization spotlight compared to other types of infrastructure. Oftentimes, the management and planning of urban water systems still follow traditional, steel and concrete-based approaches that treat used water as waste and not as a resource [1]. The need for innovation, however, is significant: the infrastructure, operation, and maintenance cost of urban water systems around the world already ranges in the hundred billion dollars annually and water-related stresses are expected to continue rising. Digitalization could not only increase the flexibility and effectiveness of existing urban water systems, but could also allow for the provisions of new services to society. The envisioned transformation, as outlined for example in the literature [2–4], entails novel data collection and transmission techniques, analytical methods, models, and automation. For example, smart water meter data can be combined with noise loggers to detect and roughly locate leaks in water mains. Together with automated control infrastructure, pressure can be regulated to reduce water losses [4]. By this and numerous other smart solutions, not only water distribution but also sewers and wastewater treatment will be transformed. In particular, digitalization facilitates large-scale implementation of disruptive technologies like decentralized wastewater treatment [5] and direct potable reuse, which will help cities to cope with climate change and urbanization.
However, we argue that as the benefits of smart urban water systems are increasingly explored and showcased in literature, it is time to also give attention to potential risks that might emerge. Recurring data breaches and the growing use of cyber-attacks for geopolitical ends are a reminder that the digitalization of society indeed carries risks. Given the critical role of water services in society and within the water-energy-food nexus, these risks must be identified and managed pro-actively. In the following, we raise awareness and suggest ways forward in approaching the unique privacy and security issues that accompany the digitalization of urban water systems. Finally, we highlight the central role of researchers in assessing and mitigating the potential risks of the smart urban water solutions they propose.

Ubiquitous sensing will create many opportunities and threats for urban water management, which are only poorly understood today. To identify the most relevant trends, we conducted a horizon scan regarding how ubiquitous sensing will shape the future of urban drainage and wastewater management. Our survey of the international urban water community received an active response from both the academics and the professionals from the water industry. The analysis of the responses demonstrates that emerging topics for urban water will often involve experts from different communities, including aquatic ecologists, urban water system engineers and managers, as well as information and communications technology professionals and computer scientists. Activities in topics that are identified as novel will either require (i) cross-disciplinary training, such as importing new developments from the IT sector, or (ii) research in new areas for urban water specialists, for example, to help solve open questions in aquatic ecology. These results are, therefore, a call for interdisciplinary research beyond our own discipline. They also demonstrate that the water management community is not yet prepared for the digital transformation, where we will experience a data demand, i.e. a “pull” of urban water data into external services. The results suggest that a lot remains to be done to harvest the upcoming opportunities. Horizon scanning should be repeated on a routine basis, under the umbrella of an experienced polling organization.

Sensor maintenance is time-consuming and is a bottleneck for monitoring on-site wastewater treatment systems. Hence, we compare maintained and unmaintained sensors to monitor the biological performance of a small-scale sequencing batch reactor (SBR). The sensor types are ion-selective pH, optical dissolved oxygen (DO), and oxidation-reduction potential (ORP) with platinum electrode. We created soft sensors using engineered features: ammonium valley for pH, oxidation ramp for DO, and nitrite ramp for the ORP. Four soft sensors based on unmaintained pH sensors correctly identified the completion of the ammonium oxidation (89–91 out of 107 cycles), about as many times as soft sensors based on a maintained pH sensor (91 out of 107 cycles). In contrast, the DO soft sensor using data from a maintained sensor showed slightly better (89 out of 96 cycles) detection performance than that using data from two unmaintained sensors (77, respectively 82 out of 96 correct). Furthermore, the DO soft sensor using maintained data is much less sensitive to the optimisation of cut-off frequency and slope tolerance than the soft sensor using unmaintained data. The nitrite ramp provided no useful information on the state of nitrite oxidation, so no comparison of maintained and unmaintained ORP sensors was possible in this case. We identified two hurdles when designing soft sensors for unmaintained sensors: i) Sensors’ type- and design-specific deterioration affects performance. ii) Feature engineering for soft sensors is sensor type specific, and the outcome is strongly influenced by operational parameters such as the aeration rate. In summary, the results with the provided soft sensors show that frequent sensor maintenance is not necessarily needed to monitor the performance of SBRs. Without sensor maintenance monitoring smalls-scale SBRs becomes practicable, which could improve the reliability of unstaffed on-site treatment systems substantially.