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.

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.

The objective of the report is to identify enabling and hindering factors for the uptake of ICT solutions to water governance, through the analysis of the process of development and the introduction of three digital applications in three different contexts of water management.
This final deliverable builds on a preliminary (deliverable 3.4) for WP3 which was submitted in November 2020. The report applies the structure proposed in the Guiding Protocol (Deliverable 3.1).