Sewer rehabilitation is a costly challenge for cities like Berlin, with annual investments exceeding €100 million, compounded by aging infrastructure and low replacement rates. Traditional CCTV inspections, used since the 1980s, face limitations in data completeness, accuracy and automation. To address this, Kompetenzzentrum Wasser Berlin and Berliner Wasserbetriebe developed SEMAplus, a suite of data-driven tools modernizing sewer asset management. The system uses machine learning to prioritize inspections and forecast long-term network conditions. This abstract highlights advancements in deterioration modeling and innovation pathways for the digitalization of sewer management. As workforce shortages, budget constraints, and sustainability goals intensify, these innovations are crucial for optimizing investments and strengthening sewer system resilience.

Leaks and bursts in water supply networks can cause significant infrastructure damage and pose contamination risks. Even utilities with robust rehabilitation strategies are not immune to the costly consequences of major bursts. A key question is whether such events can be prevented by detecting and localizing them while they are still small (i.e., leakage flows below 3 L/s). The model-based algorithm Dual Model has demonstrated both simplicity and precision, securing first place among 18 algorithms in the Battle of the Leakage Detection and Isolations Methods. However, mismatches of around 10% between the hydraulic model and the real network can hinder its performance, particularly in detecting and locating small leaks. In this work, we enhance the Dual Model by incorporating source inflows, allowing discrepancies between the real and simulated networks to be expressed as residual virtual flows. These residuals are integrated into the model as demand patterns, enabling the detection of leaks as small as 2–3 L/s even under perturbations of roughness and base demand exceeding 35%. Additionally, this approach calibrates nodal pressures without requiring manual adjustments to roughness or demand values.

Understanding the residential end uses of water is helpful for the sustainable management of water resources and the implementation of water conservation strategies. In this study, over one hundred studies were systematically reviewed to provide a comprehensive overview of the state-of-the-art research on end-use water consumption. Each study was reviewed, clustered, and subjected to a multilevel analysis aimed at quantitatively comparing the characteristics of the end uses of water available in the literature. The findings of this work support water utilities, researchers, policy makers, and consumers in identifying the key aspects of water end uses and exploring their main features across different geographical, socioeconomic, and cultural regions of the world.

This paper investigates the robustness of one innovative model-based method for leak detection, namely the Dual Model. We evaluate the algorithm’s performance under various leakage scenarios in the L-Town network, despite uncertainties and model mismatches in (i) base demand, (ii) pipe roughness, (iii) the number of sensors, and (iv) network topology. Our investigation results indicate that the Dual Model is highly sensitive to discrepancies in the first three parameters. However, the impact can be mitigated through sensor-specific calibration, such as adjusting sensor elevations. Moreover, the Dual Model has demonstrated robustness to minor topology mismatches, like those introduced by closed valves.

This research report addresses the current uncertainties regarding the technical service life and aging behavior of the most common sewer rehabilitation method, Cured-in-Place Pipe (CIPP) lining. The goal of this study is to develop a robust data foundation for a CIPP liner survival curve for use in aging models. The methodological approach includes (i) a literature review, (ii) interviews with sewer rehabilitation experts, and (iii) an analysis of data from Berliner Wasserbetriebe to create an updated and suitable data basis for the calibration of survival curves. The literature review and expert interviews predominantly estimate the service life of CIPP liners to exceed 50 years. However, the study also reveals that this lifespan is influenced by numerous factors and that there is a lack of reliable data. Further investigations of long-used CIPP liners are therefore essential. The installation process, particularly the curing phase, has been identified as the primary factor contributing to defects and deficiencies in CIPP liners. Standardizing damage assessment and condition evaluation for liner-specific defects, as well as establishing non-destructive inspection methods, is necessary to improve the understanding of aging behavior in the future. Recommendations include improving data collection during the operation, installation, and removal of CIPP liners, enhancing quality assurance during installation, investigating the impact of damage on service life, and promoting knowledge exchange among operators.

Addressing Europe's current challenges of aging sewer networks, the presented research focuses on the uncertainties in service life and aging behavior of the most used renovation technique, Cured in Place Pipe (CIPP) lining. Examining its aging behavior, common defects and deficiencies were analyzed through literature review and expert interviews. The findings influenced the proposition of a calibration setting for a deterioration model using survival curves. Identified defects stress the need for precise installation and curing processes. The study recommends a thorough review of the initially specified 50-year service life, acknowledging uncertainties during the installation process.

Extending the AI-driven Software SEMAplus with a risk prioritization module.

Selection and analysis of risk criteria as preliminary part of decision making.

Analysis of multicriteria decision approaches and choice of ELECTRE TRI.