Guericke, L. , Caradot, N. , Del Punta, F. , Sonnenberg, H. , Daurat, A. , Hamou, Y. , Cherqui, F. (2026): Enhanced Sewer Condition Prediction Using Prior Defect Observations.

11th International Conference on Sewer Processes and Networks, Trondheim

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Caradot, N. (2026): Data driven sewer asset management.

Giornata Tecnica con A2A Ciclo Idrico, Brescia

Caradot, N. , Kramer, A. (2026): AI:LINER - Data driven sewer asset mangement - Project overview and selected technologies.

AI, Drones, Sensors and Robots for Smart Sewers and Urban Drainage 2026, Gelsenkirchen

DOI
Zusammenfassung

Nature-based solutions (NBSs) are often considered to be cure-all remedies for mitigating risks arising from climate change, among others. This study explores the failure modes of NBSs in stormwater management, and analyses challenges across the different stages of their life cycles, including planning, design, and operation. The PRISMA methodology was applied to carry out a systematic literature review to identify the main triggers, consequences and potential mitigation measures for different failure modes and challenges, with a view to enhancing the long-term performance of NBSs. Each identified failure mode was classified along the three typological dimensions of severity, origin and preventability, with sub-dimensions for qualitative and quantitative analysis. Based on 76 reviewed studies, it was concluded that preventable and intrinsic failures dominate the early stages (planning and design), whereas induced and extrinsic failures tend to manifest during operation and maintenance. The application of interdisciplinary and catchment-scale thinking in planning reduces the probability and severity of failure in the design and operation stages. Standardised and data-based approaches are needed to mitigate NBS failures throughout the life cycle.

Zusammenfassung

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.

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