Wednesday Poster session- Starting projects

Since 2018, the City of Paris has implemented a rainwater zoning plan to manage stormwater at source and reduce flooding. Facing a lack of monitoring tools, the City of Paris developed two GIS systems: EPONGE (Project Evaluation and Operations for Rainwater Management), which ensures project compliance and OGEP (Rainwater Equipment Management Tool), which inventories and defines maintenance procedures for stormwater management facilities. These tools enhance traceability and coordination, thereby strengthening urban resilience. 

The design and dimensioning of urban stormwater management structures are becoming increasingly important in urban development projects. These projects involve a growing number of economic stakeholders. The issues raised concern stormwater and/or wastewater management, as well as the role of green spaces in urban areas in the face of multiple challenges related to the water cycle (rainwater drainage) and climate change (heat islands, loss of biodiversity, etc.). Numerous skills must therefore be mobilised to integrate these different aspects, but they are not always available within the companies or public services responsible for providing technical advice on preliminary projects. The Smart-Water Cities project offers a software solution that assesses the impact of a development project on its environment: rainwater management in terms of quantity and quality and quantification of the associated benefits in terms of ecosystem services. The software consists of a graphical interface that allows the various structures (hydraulic or hydrological) of the project to be located and connected to each other. Based on the location of the project, the software calculates a hydrological balance (quantity of water discharged, stored or infiltrated), assesses the quality of the water discharged into receiving environments and provides an assessment of the ecosystem services provided compared to the initial situation. 

Imperviousness is profoundly disrupting the hydrological cycle, increasing runoff and reducing infiltration, evapotranspiration, and groundwater recharge. Climate change is exacerbating these dynamics by increasing the frequency and intensity of extreme rainfall events, putting greater pressure on stormwater management systems. Among mineral infiltration systems, block pavers appear to be a promising solution, offering a permeable alternative to conventional mineral surfaces. Despite the infiltration potential of block pavers, several uncertainties remain regarding their hydrodynamic behavior, in particular the effect of the loads supported on the compaction of subsurface layers and on the hydrodynamic properties of the structures. Moreover, the gaps inherent in the design of these infiltration systems create preferential flows that govern surface infiltration. Characterizing the geometries of the different models of block pavers allows the study of the influence of these gaps on subsurface and underground flows. This study focuses on assessing the sensitivity of pavers to compaction caused by parking, analyzing infiltration and interaction with groundwater, and mapping preferential flows using hydrogeophysical methods, to better understand and optimize the use of block pavers for sustainable stormwater management. 

Urbanisation is rapidly converting permeable landscapes into impervious surfaces, increasing stormwater runoff and accelerating the transport of various contaminants including heavy metals into receiving waters. Permeable pavements are an important Water Sensitive Urban Design (WSUD) measure that support infiltration and decentralised stormwater management. At the same time, the disposal of waste tyres has become a major environmental concern, and their incorporation into permeable pavements offers a promising approach for resource recovery while enhancing stormwater control. However, the influence of waste tyre materials on pollutant behaviour and treatment performance remains insufficiently understood. Recent research shows that a variety of engineered adsorbents can improve the removal of heavy metals from stormwater, yet comparative assessments of different adsorbent materials and combinations, particularly in relation to waste tyre permeable pavements, are still limited. This study aims to evaluate several adsorbents through controlled laboratory experiments to determine their heavy metal removal efficiencies when used in conjunction with waste tyre permeable pavements. The outcomes of this research will support the development of innovative permeable pavement systems that make use of waste tyres while improving stormwater quality in urban environments. 

Four pilot-scale bioretention cells were built in the campus of the University of Iceland and subjected to synthetic runoff events in cold maritime conditions. One pair had a functionally diverse turf cover (shrubs and forbs) while the other used a grass dominated turf cover. Throughout the field campaign, synthetic events were performed in neutral, snow, and frost conditions. The performance metrics of each pair were calculated and compared against the other pair using statistical analysis. The preliminary results suggest a minor improvement in performance across all initial conditions as well as adequate infiltration capacity in winter. 

Over the past decades, climate change and urbanisation have increased flood risk and degraded stormwater quality, highlighting the need for Nature-Based Solutions such as Sustainable Drainage Systems (SuDS). The study focuses on a one-kilometre SuDS scheme in Bovisio Masciago (Lombardy, Italy), where bioretention systems and detention basins with infiltration trenches have been implemented along a residential street and in an adjacent park. The aim is to develop and test methods to evaluate both hydraulic–hydrologic performance and ecosystem services. A monitored bioretention area is instrumented with paired inflow–outflow automatic samplers, level sensors and soil-moisture probes, enabling controlled tanker tests and event-based monitoring of water quantity and quality. In parallel, vegetation surveys, microclimate measurements and questionnaire surveys will be used to assess biodiversity potential, contribution to urban heat island mitigation and cultural services such as aesthetics, contact with nature and perceived comfort. The integrated approach is intended to support a comprehensive evaluation of the multifunctional benefits of SuDS interventions. 

Urban stormwater management is a major challenge for cities in the context of climate change adaptation. The ALLAGUI project (2025–2028) aims to promote a long-term shift in professional engineering practices by developing and disseminating innovative methods and tools for the design of integrated stormwater management systems. The project first proposes an integrated methodology to simulate the performance of vegetated infrastructures (green roofs, infiltration swales) under future climate conditions (2070–2099), while incorporating environmental and social criteria. These tools will then be tested by external partner municipalities and engineering companies to identify the drivers and barriers to their adoption and to better understand the social and behavioural dynamics of practice change. Finally, a user manual and training modules will be developed to support the use of the methods and tools and the practical implementation of nature-based solutions. The communication will present the first technical and methodological developments of the project, as well as the observation protocol for monitoring tool appropriation by external testers and their first feedback. 

Process‑based catchment models are valuable tools for informing urban water quality management, but often struggle to capture extremes, non‑linear dynamics, and contaminant levels in data‑sparse regions. Knowledge‑guided machine learning models combine the scientific foundation of process‑based models with the strengths of machine learning to enhance predictive accuracy while maintaining physical consistency. We aim to develop a knowledge guided machine learning model for estimating total suspended solid concentrations of river systems in the Port Phillip Bay–Western Port Region of Victoria, Australia, a heterogeneous region, characterised by diverse land use, climate, streamflow regimes, soil typologies, and topography. The model will employ a long-short-term memory network constrained by the law of conservation of mass. The study will evaluate model performance across three scenarios: existing monitoring sites, ungauged catchments, and infrequent hydrological conditions such as droughts and extreme rainfall. Finally, the study will assess and investigate the interpretability and explainability of the model to improve the trustworthiness of using machine learning models for water quality management. By Novatech 2026, a first iteration of the knowledge guided machine learning model is anticipated. 

Blue–Green Infrastructure (BGI) supports urban runoff control but is vulnerable to structural failures. Insufficient maintenance is a main driver amplifying these failures and reducing design performance. This study assesses risk of insufficient performance in BGI under relevant maintenance scenarios using a structured risk-interpretation matrix that combines the risk of structural failure (RSF) and the risk of no maintenance (RNM) for four BGIs - dry detention basins, stormwater ponds, bioretention systems, and stormwater vaults (EcoVault®). Likelihood and consequence scores for both RSF and RNM were assigned using expert-informed criteria to evaluate how each failure condition affects overall risk. Results showed that outlet blockages in stormwater ponds and hidden underdrain malfunctions in bioretention systems, produced the highest risk classes. Cumulative processes such as sediment accumulation also generated elevated risks in infiltration-based BGIs like bioretention systems, whereas similar failures were more manageable in storage-based systems like dry detention basins. The assessment further highlights practical differences in maintenance motivation, with (especially very frequent and/or labour-intensive) tasks concentrated at single end-of-pipe assets (e.g., sediment removal in ponds) being more feasible than equivalent tasks across multiple decentralised units. Ongoing work will extend the assessment to additional BGIs and water-quality performance. 

Sustainable Drainage Systems (SuDS) are increasingly promoted as an alternative or complement to conventional combined and separate sewer systems to manage urban stormwater, reduce peak flows and improve effluent quality. However, pilot-scale performance data under Mediterranean climate conditions remain limited, especially for treatment trains combining several devices. This paper presents the CEIC experimental SuDS facility in Meco (Spain), designed to test different sustainable drainage techniques under real rainfall conditions. The pilot plant includes several representative units (e.g. swales, permeable pavements, filter drains and bioretention systems) arranged in a treatment train. The site is instrumented to continuously monitor rainfall, flows and water quality at inlet and outlet control points. Preliminary results indicate a significant attenuation of peak discharges and a clear improvement of stormwater quality, particularly for particulate-bound pollutants. Operational experience from the first monitoring campaigns is used to identify key design, operation and maintenance aspects that are critical for SuDS performance in semi-arid and Mediterranean contexts. The CEIC facility provides a robust platform to support future optimisation of SuDS design guidelines and to promote their wider implementation in Spanish cities.