During the last decades, municipalities have increasingly invested in new approaches for rehabilitating sewerage networks. With the increasing number of rehabilitation techniques, objectives and constraints, the number of rehabilitation scenarios rises exponentially. This article proposes an asset management approach to create long-term rehabilitation plans where different budget allocations for rehabilitation techniques are considered every year depending on performance and cost indicators. It builds long-term strategies through multiobjective black-box optimization where the impact of the budget allocations over the network life cycle is part of the decision process. It employs a pipe deterioration model based on Markov chains whose transition matrices are estimated by survival curves for different pipe cohorts. The proposed approach seeks to determine the appropriate investment (CAPEX) and operational expenses (OPEX) levels in the coming decades. It was tested with real-world data from a sewerage network in Sofia, Bulgaria, and the results show that it provides efficient long-term rehabilitation plans.

This report presents the findings from task 2.1 of the SafeCREW project, which aimed to monitor seasonal microbial quality changes in source waters of near-natural treatment systems, such as managed aquifer recharge (MAR). Two case study locations, Hamburg and Berlin, were examined to understand microbial dynamics over time. Microbial cell counts in source waters were monitored using flow cytometry (FCM), which enables the analysis of bacteria, protozoa, and viruses. In addition, organic matter in source waters and during near-natural treatment was analyzed using techniques such as Liquid Chromatography-Organic Carbon Detection (LC-OCD), fluorescence spectroscopy, and absorption measurements. These methods provided detailed insights into the type and quantity of organic substances, which influence microbial growth. Notably, biopolymers—organic substances produced during microbial degradation—were identified as indicators of microbial activity and surface water influence. By combining microbiological and organic analyses, a comprehensive monitoring system can be developed that provides extensive information not only on seasonal changes in microbial quality, but also on the underlying causes and influencing factors. This enables targeted and effective control of water treatment processes and helps to ensure high water quality.

Smart water management is acknowledged as a key component of the solutions to address climate change impact and secure water resources availabilities in the context of Sustainable Development Goals. Over the last decades, digital solutions have become an essential part of water management. Numerous initiatives have been developed to explore hybrid and new AI modeling with concrete approaches such as digital twins. The ambition is to provide water managers with tailored IT solutions that can be implemented in their current management system. These developments raise a wide range of questions in terms of sensors’ approach, interoperable open data models, reference architecture, and cybersecurity that are presented in this chapter. Additionally, IT innovation, as groundbreaking as it may be, requires additional dimensions such as governance, capacity building, and economics to ensure its adoption by water managers. These aspects are also presented in the latest sections of this chapter.

D7.4 describes the innovation and Intellectual Property Rights (IPR) management procedures within DWC. It introduces the concepts of Intellectual Property (IP), the types of protection rights as well as the IPR rules in the project. It summarizes the key procedures introduced in the Grant Agreement and Consortium Agreement documents. Finally, it explains the role of the innovation and IPR manager and the detailed activities that will be carried out to foster innovation and secure the protection of our key results. Compared to the previous versions, the IPR repository has been updated.