Effective decision-making in urban water management requires integrating outputs from specialized models. Berlin’s drinking water supply relies on induced bank filtration and managed aquifer recharge from the Spree and Havel rivers. However, river inflows into Berlin are declining -e.g., in summer 2019, the Spree’s inflow was half that of an average dry summer year- and are expected to decrease further over the next decade due to the ending of coal sump water discharge into the Spree. Long-term impacts from climate change are anticipated to exacerbate this trend. Additionally, an analysis of streamflow data and bank filtrate rate-corrected groundwater extraction has identified regions where maximum monthly extractions from drinking water wells already exceed the lowest monthly river flows in Berlin. This imbalance, combined with increasing water demand driven by population growth, leads to a higher proportion of treated wastewater in Berlin’s streams. As a result, risks to drinking water quality intensify, and the complexity and costs of water and wastewater treatment escalate. Furthermore, higher extraction levels are associated with increased bank filtrate fractions, amplifying system stress and emphasizing the need for sustainable water management practices.

In collaboration with the Belin Waterworks (Berliner Wasserbetriebe), we applied a well-calibrated FEFLOW© model of the Berlin-Friedrichshagen waterworks to simulate bank filtrate rates under various recharge and groundwater extraction scenarios. The model was run under three historical well configurations (2010, 2015, and 2019) and then well pumping rates were adjusted in the same relative configuration under three groundwater recharge scenarios.

A review of prior investigations revealed groups of well galleries exhibiting similar changes in bank filtrate fractions in response to extraction levels; our results complement these former investigations. Bank filtrate behavior across well galleries was found to depend on several factors, including well depth, distance to the riverbanks, the presence of opposing riverbanks, and regional groundwater heads. Relating bank filtrate change groups to site characteristics and bank filtrate fractions in other Berlin develops a city-wide understanding of changes in bank filtrate.

Future FEFLOW© modeling scenarios, including commissioning and decommissioning of well galleries, and implementing managed aquifer recharge will be essential to address remaining uncertainties. Outputs from this modeling effort contribute to regional dynamic water balance modeling for Berlin’s semi-closed water cycle in order to support sustainable water management decision-making amid evolving climatic and regulatory challenges.

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.

This deliverable presents the implementation progress and results of the innovative technologies
demonstrated across the IMPETUS demo sites during the period M1-M49 of the project (01/10/2021–
30/09/2025). It covers the full set of activities carried out under WP4 Tasks 4.5.1 to 4.12, which together
form Bundle 2: Innovative Technologies Implementation.
Bundle 2 aims to demonstrate a suite of advanced technical solutions that increase climate resilience
across diverse geographic, hydrological, and socio-economic contexts. The bundle includes
decentralised water reuse systems, digital modelling tools, pathogen monitoring technologies, sediment
transport modelling, multi-agent water balance models, decision-support systems for heat and flood risk,
and early-warning technologies for geological hazards. These solutions collectively reinforce the
broader WP4 objective of testing and validating multi-benefit adaptation innovations that can be scaled
across Europe.
The 15 tasks reported in this deliverable demonstrate substantial progress toward climate-resilient water
management, environmental protection, and risk reduction. Task 4.5.1 deployed a hybrid decentralised
fit-for-use water reclamation system in the Coastal demo site (Catalonia), producing high-quality
reclaimed water for irrigation and cleaning within a touristic complex and validating decentralised reuse
under highly variable seasonal demand. Task 4.5.2 implemented a Sewer Mining unit in East Attica
(Mediterranean demo site), integrating real-time data, energy-autonomous operation, and co-created
adaptation services. Task 4.5.3 developed a water-energy simulation and optimisation model, enabling
the operator of the East Attica system to explore climate-proof operation strategies and circulareconomy pathways.
Across several additional tasks, advanced modelling and monitoring capabilities were demonstrated.
Tasks 4.6 and 4.7.1 developed computational tools for sediment transport and regional water balance
simulation, supporting adaptation measures under hydrological and demographic pressures. Tasks
4.7.2 and 4.10.1 - 4.10.3 delivered decision-support systems that integrate multi-layer data for WEFEnexus planning, heat stress management, and flood risk visualisation, many of which are connected to
digital twin environments. Tasks 4.8.1 and 4.8.2 tackled climate-exacerbated water quality risks by
improving bathing water management during storm events and assessing drinking water resilience to
pathogens. Finally, Tasks 4.11 and 4.12 implemented technologies for urban climate proofing in coastal
settings facing sea-level rise and for geological and avalanche early-warning systems in the Arctic and
mountainous demo sites.
Together, the technologies demonstrated under Bundle 2 provide actionable, scalable, and evidencebased adaptation options. The solutions directly support regional water resilience, enable cross-sectoral
decision-making, and reduce exposure to climate-related risks. Their integration into the Resilience
Knowledge Boosters, digital twins, and participatory processes strengthens the IMPETUS vision of
empowering local stakeholders and decision-makers with robust, technology-driven adaptation
pathways.

The trophic index is often used to monitor the primary production of lakes. In Brandenburg, Germany, lakes are sampled several times every three years between April and October. The trophic index is then calculated from the values for phosphorus concentration, turbidity and chlorophyll-a content. This is usually only done for lakes that are monitored according to the Water Framework Directive (area > 50 ha). The low temporal resolution in combination with natural annual variations makes trend analysis of trophic levels very difficult and a high proportion of lakes are excluded from this monitoring.
Satellite images can be used to obtain information on chlorophyll-a and turbidity. Phosphorus, as a nutrient for algae, also has an indirect effect on water color. There are already many indices based on the Copernicus Sentinel-2 program, such as the Normalized Difference Chlorophyll Index, which can be used for real-time water monitoring. In addition, annual data are essential for lake management to identify long-term trends. The trophic index is a widely used and easily interpreted indicator in this regard.
The AD4GD project explored i) which bands of the Sentinel-2 images are best suited for estimating trophic state, ii) how the data can be temporally aggregated within a season, and iii) whether one pixel within a lake is sufficient to reliably describe the trophic state of the lake. Especially the latter was necessary to apply the method to small lakes where regular monitoring is not available.
The developed Normalized Difference Trophic Index (NDTI), aggregated over the months of April to October, best represented the trophic index based on measured values. It was developed and validated using 294 lakes in Brandenburg with trophic data between 2018 and 2022 and is defined for a satellite image as
NDTI_image=(B5-B2)/(B5+B2)
Band 5 describes the near infrared reflectance at 705 nm, band 2 the reflectance of blue light at 490 nm. In oligotrophic lakes, band 2 reflectance usually dominates and the index is below zero. The trophic index based on in-situ measurements is best calculated from monthly values. Similarly, NDTIimage is first averaged monthly and then seasonally (April to October in Germany).
The resulting NDTIseason was found to be highly correlated with the in-situ data for the available years (Pearson correlation coefficient between 0.83 and 0.92). Thus, it allows a comparison of the trophic state of lakes in the Brandenburg region. The data are available at an annual resolution, which is three times more frequent than the conventional analysis. This allows a much more reliable trend analysis, which can be used to monitor the success of water quality improvement measures or to identify water quality problems more quickly. Small lakes can be included in the monitoring without much effort.
A first sensitive analysis has shown that the classification of eutrophic water bodies is more reliable than that of oligotrophic water bodies. Further factors influencing the accuracy of the method will be investigated in a subsequent sensitivity analysis.