Für das Wassermanagement urbaner Gewässersysteme werden schnelle und zugleich ausreichend belastbare Modellansätze benötigt, um beispielsweise Stoffeinträge, Abwasseranteile oder Auswirkungen zukünftiger Randbedingungen bewerten zu können. Am Beispiel Berlins wurde hierfür das Berlin Water Model als vereinfachtes dynamisches Mischungsmodell entwickelt, das für 35 Gewässerabschnitte Durchflüsse, Stoffkonzentrationen sowie Anteile von gereinigtem Abwasser, Regenabfluss und Mischwasserüberläufen in stündlicher oder täglicher Auflösung berechnet. Die Validierung mit Ergebnissen hydrodynamischer Modelle und Messdaten zeigt eine gute Übereinstimmung, auch bei Sonderfällen wie Fließumkehr. Mit dem Modell können Hotspots und Überschreitungshäufigkeiten identifiziert und die Ergebnisse als Karte dargestellt werden. Das Modell eignet sich somit für Substanzmapping und Szenarien-rechnungen zur Unterstützung des Berliner Wassermanagements.

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.

The "Toolbox Fate & Transport Modelling of PMTs in the Environment" is a key deliverable from the H2020 PROMISCES project. This toolbox is a demonstrator that includes a collection of models developed in the PROMISCES project which are designed to assess the fate and transport of persistent, mobile, and toxic substances (PMTs) across various scales (local, regional) and conditions (e.g., urban run-off, bank filtration, unsaturated zone, groundwater).
This toolbox presents the basic information with links to the software and model input files with which the models can be run. This deliverable is intended for qualified modellers. It is complementary with the Guidance document, deliverable D2.4 (Zessner et al., 2025) which describes how to apply modelling tools in a tiered way as part of predictive risk assessment.

The scope of this document, produced as part of the H2020 PROMISCES project, is to provide guidance for applications of models with a specific focus on model trains for the assessment of exposure to PMTs as part of the predictive risk assessment related to surface and groundwater. This document explains the basic concepts of specific models and how best to use them in model
trains in the framework of a tiered approach. The intention is to inform users and interested stakeholders about what needs to be considered when using different methods, what is the best use of specific models, what are the best combinations in model trains and what are their current limitations.