Design and construction of urban drainage systems has to be done in a predictive way, as the average lifespan of such investments is several decades. The design engineer has to predict many influencing factors and scenarios for future development of a system (e.g. change in land use, population, water consumption and infiltration measures). Furthermore, climate change can cause increased rain intensities which leads to an additional impact on drainage systems. In this paper we compare the behaviour of different performance indicators of combined sewer systems when taking into account long-term environmental change effects (change in rainfall characteristics, change in impervious area and change in dry weather flow). By using 250 virtual case studies this approach is--in principle--a Monte Carlo Simulation in which not only parameter values are varied but the entire system structure and layout is changed in each run. Hence, results are more general and case-independent. For example the consideration of an increase of rainfall intensities by 20% has the same effect as an increase of impervious area of +40%. Such an increase of rainfall intensities could be compensated by infiltration measures in current systems which lead to a reduction of impervious area by 30%.

Traditional urban water management relies on central organised infrastructure, the most important being the drainage network and the water distribution network. To meet upcoming challenges such as climate change, the rapid growth and shrinking of cities and water scarcity, water infrastructure needs to be more flexible, adaptable and sustainable (e.g., sustainable urban drainage systems, SUDS; water sensitive urban design, WSUD; low impact development, LID; best management practice, BMP). The common feature of all solutions is the push from a central solution to a decentralised solution in urban water management. This approach opens up a variety of technical and socio-economic issues, but until now, a comprehensive assessment of the impact has not been made. This absence is most likely attributable to the lack of case studies, and the availability of adequate models is usually limited because of the time- and cost-intensive preparation phase. Thus, the results of the analysis are based on a few cases and can hardly be transferred to other boundary conditions. VIBe (Virtual Infrastructure Benchmarking) is a tool for the stochastic generation of urban water systems at the city scale for case study research. With the generated data sets, an integrated city-scale analysis can be performed. With this approach, we are able to draw conclusions regarding the technical effect of the transition from existing central to decentralised urban water systems. In addition, it is shown how virtual data sets can assist with the model building process. A simple model to predict the shear stress performance due to changes in dry weather flow production is developed and tested.

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Throughout the past years, governments, industries, and researchers have shown increasing interest in incorporating smart techniques, including sensor monitoring, real-time data transmitting, and real-time controlling into water systems. However, the design and construction of such a smart water system are still not quite standardized for massive applications due to the lack of consensus on the framework. The major challenge impeding wide application of the smart water network is the unavailability of a systematic framework to guide real-world design and deployment. To address this challenge, this review study aims to facilitate more extensive adoption of the smart water system, to increase effectiveness and efficiency in real-world water system contexts. A total of 32 literature pieces including 1 international forum, 17 peer-reviewed papers, 10 reports, and 4 presentations that are directly related to frameworks of smart water system have been reviewed. A new and comprehensive smart water framework, including definition and architecture, was proposed in this review paper. Two conceptual metrics (smartness and cyber wellness) were defined to evaluate the performance of smart water systems. Additionally, three pieces of future research suggestions were discussed, calling for broader collaboration in the community of researchers, engineers, and industrial and governmental sectors to promote smart water system applications.

Urban water infrastructure, i.e., water supply and sewer networks, are underground structures, implying that detailed information on their location and features is not directly accessible, frequently erroneous, or missing. For public use, data is also not made available due to security concerns. This lack of quality data, especially for research purposes, requires substantial effort when such data is sought for both statistical and model-based analyses. An alternative to gathering data from archives and observations is to extract the information from surrogate data sources (e.g., the street network). The key for such an undertaking is to identify the common characteristics of all urban infrastructure network types and to quantify them. In this work, the network correlations of the street, water supply, and sewer networks are systematically analyzed. The results showed a strong correlation between the street networks and urban water infrastructure networks, in general. For the investigated cases, on average, 50% of the street network length correlates with 80%-85% of the total water supply/sewer network. A correlation between street types and water infrastructure properties (e.g., pipe diameter) cannot be found. All analyses are quantified in the form of different geometric-and graph-based indicators. The obtained results improve the understanding of urban network infrastructure from an integrated point of view. Moreover, the method can be fundamental for different research purposes, such as data verification, data completion, or even the entire generation of feasible datasets.

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Analyses of case studies are used to evaluate new or existing technologies, measures or strategies with regard to their impact on the overall process. However, data availability is limited and hence, new technologies, measures or strategies can only be tested on a limited number of case studies. Owing to the specific boundary conditions and system properties of each single case study, results can hardly be generalized or transferred to other boundary conditions. virtual infrastructure benchmarking (VIBe) is a software tool which algorithmically generates virtual case studies (VCSs) for urban water systems. System descriptions needed for evaluation are extracted from VIBe whose parameters are based on real world case studies and literature. As a result VIBe writes Input files for water simulation software as EPANET and EPA SWMM. With such input files numerous simulations can be performed and the results can be benchmarked and analysed stochastically at a city scale. In this work the approach of VIBe is applied with parameters according to a section of the Inn valley and therewith 1,000 VCSs are generated and evaluated. A comparison of the VCSs with data of real world case studies shows that the real world case studies fit within the parameter ranges of the VCSs. Consequently, VIBe tackles the problem of limited availability of case study data.

[1] Building theories from case studies is a common research approach that can also be applied to the analysis of networks. Although case studies of real systems bridge the gap between theory and practice, they are nevertheless investigations of a subset of cases, each with specific characteristics. To tackle this problem, a multitude of networks with diverging characteristics are generated using the graph-theory-based Modular Design System (MDS). In this paper the application of this MDS is demonstrated by generating a set of 2280 virtual Water Supply Systems. The layout and the properties of these systems are representative of typical examples encountered in practice. Scatterplots, density, and cumulative distribution functions are used to characterize several network parameters. A comparison of the virtual set with three real-world case studies shows similar characteristics. Finally, the potential of the methodology is demonstrated by analyzing the impact of increased water demand on hydraulic performance. It can be shown that the allowed maximum and minimum diameters envelop a range of impacts on mean values for nodal pressure.