Globally, urbanization, climate change, and ageing assets affect urban water management. One potential solution is recognized in smart urban water systems, which rely on monitoring data from infrastructure elements, e.g., combined sewer overflows (CSOs). Such monitoring data provides evidence on system functioning and performance and allows a dynamic control to exploit all existing infrastructure capacities, for example during heavy rainfalls. As a result, smart urban water systems hold the potential to improve performance outcomes, to reduce environmental impacts on surface waters, and to manage infrastructures more efficiently.
However, despite the availability of digital technologies for monitoring, data transfer, and control, only few examples of smart urban water systems exist. Where monitoring data is already obtained, it is often not optimally handled. Potential reasons cannot be found at the technical level only, but require an understanding of smart urban water systems in their social and socio-technical dimensions. To achieve smart urban water systems, not only technical innovation, but also adaptations of the surrounding social system are needed. [...]

A network perspective to urban water governance provides a useful analytical perspective. Network approaches allow systematic descriptions and analysis of the structure of interactions among actors and technical elements. This chapter presents conceptual approaches, theoretical elements, and methodological tools related to actor networks in urban water governance. The chapter starts by presenting theoretical aspects and related research questions at the intersection of network governance and urban water governance. After an introduction to the main concepts and measures of Social Network Analysis, the chapter focuses on how network approaches can help in analyzing processes of digitalization and decentralization, not least with the concept of sociotechnical network approaches that combine actor networks with technical networks.

Networked infrastructure systems - including energy, transportation, water, and wastewater systems — provide essential services to society. Globally, these services are undergoing major transformative processes such as digitalization, decentralization, or integrated management. Such processes not only depend on technical changes in infrastructure systems but also include important social and socio-technical dimensions. In this article, we propose a socio-technical network perspective to study the ensemble of social actors and technical elements involved in an infrastructure system, and their complex relations. We conceptualize structurally explicit socio-technical networks of networked infrastructure systems based on methodological considerations from network analysis and draw on concepts from socio-technical system theories and social-ecological network studies. Based on these considerations, we suggest analytical methods to study basic network concepts such as density, reciprocity, and centrality in a socio-technical network. We illustrate socio-technical motifs, i.e., meaningful sub-structures in socio-technical networks of infrastructure management. Drawing on these, we describe how infrastructure systems can be analyzed in terms of digitalization, decentralization, and integrated management from a socio-technical network perspective. Using the example of urban wastewater systems, we illustrate an empirical application of our approach. The results of an empirical case study in Switzerland demonstrate the potential of socio-technical networks to promote a deeper understanding of complex socio-technical relations in networked infrastructure systems. We contend that such a deeper understanding could improve management practices of infrastructure systems and is becoming even more important for enabling future data-driven, decentralized, and more integrated infrastructure management.

Digital technologies can be important to policy-makers and public servants, as these technologies can increase infrastructure performance and reduce environmental impacts. For example, utilizing data from sensors in sewer systems can improve their management, which in turn may result in better surface water quality. Whether such big data from sensors is utilized is, however, not only a technical issue, but also depends on different types of social and institutional conditions. Our article identifies individual, organizational, and institutional barriers at the level of sub-states that hinder the evaluation of data from sewer systems. We employ fuzzy-set Qualitative Comparative Analysis (fsQCA) to compare 23 Swiss sub-states and find that two barriers at different levels can each hinder data evaluation on their own. More specifically, either a lack of vision at the individual level or a lack of resources at the organizational level hinder the evaluation of data. Findings suggest that taking into account different levels is crucial for understanding digital transformation in public organizations.

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.

Mit der fortschreitenden Digitalisierung gilt es heute als Stand der Technik, Messdaten über das Abwassersystem zu erheben, auszuwerten und zu archivieren. Wie der Wert von Messdaten für Betrieb, Planung und Leistungsüberprüfung ausgeschöpft werden kann, ist jedoch unklar. Um einen einheitlichen Einsatz von Messtechnik, z.B. an Regenüberlaufbecken, sowie einen guten Umgang mit erfassten Messdaten in der Schweizer Praxis zu schaffen, sind Anpassungen auf organisatorischer Ebene notwendig.