Conference Agenda

This study aims to test the robustness of a physical based bioretention cell model, given the inaccuracies inherent to our knowledge of the systems’ hydrodynamic. Field monitoring data on a pilot bioretention cell is compared to HYDRUS 1D modelling results for a range of possible soil properties and bottom condition scenarios. The uncertainties in the hydrodynamic properties of the filtration and transition medias as well as the bottom boundary conditions (BCs) are found to significantly affect modelling results for water content dynamics in the filtration media but have limited impact on the long-term water balance of the system.

Large scale implementation of green infrastructure, such as bioretention, has become increasingly common. The goal of these installations moves beyond reducing downstream peak flows, also aiming to provide more natural hydrology in receiving streams. Thus, the partitioning of runoff to infiltration, drainage, and overflow; and the timing of these hydrologic pathways becomes critical to holistically evaluating implementations. In this study, DRAINMOD-Urban (a robust drainage model) is coupled with SWMM to provide a watershed scale model that can also perform fine scale modeling of bioretention (and proper hydrologic partitioning). This combined model is tested in a watershed with three bioretention areas in Columbus, Ohio, to evaluate its performance. Initial results show the combined model performs well for the test watershed (NSE = 0.66 for hydrograph representation). Further, the performance for hydrograph representation, mean flow, and volume was found to exceed that of a model representing the system using SWMM LID tools. The results suggest that the model chosen for site scale representation of green infrastructure can make a difference in modeling watershed scale performance.

Blue-Green Infrastructure (BGI) has become a vital component of urban stormwater management, offering hydrological benefits and ecosystem services. However, incomplete data on the long-term performance, operation and maintenance of BGI poses challenges for their sustainable asset management. This study proposes an agent-based model (ABM) to address these gaps by integrating hydrological and ecological aspects as well as stakeholders’ opinions. The ABM conceptual model incorporates agents representing utilities, maintenance practices, failure events, and BGI components, simulating their interactions over time. Data for the model is currently derived from a Fault Tree Analysis (FTA) and a survey of French BGI managers, with plans to expand to an international scope. FTA results help in identifying BGI failures and assessing their effects on BGI components, while survey data offers insights into maintenance practices and their frequency. ABM’s capacity to model emergent behaviours and simulate management strategies offers a promising path toward optimizing BGI performance. This study advances the understanding of BGI deterioration and supports the development of proactive, data-driven management frameworks to sustain the long-term benefits of these critical infrastructures.

The Olympluie project investigates the modelled hydrological performance of green roofs under varying climatic conditions in eight cities in the world, through long-term simulations (13–29 years) for both historical and future climate data. It also examines performance metrics (e.g. evapotranspiration efficiency) for different green roof designs (varying substrate depths, underlying storage capacities, etc.). Simulations revealed that green roof performance varies significantly with geography, while the analysis of future climate scenarios (2071–2099) for the city of Lyon, France, projected a moderate drop in green roof performance. However, the variability across 12 future climate rainfall timeseries was substantial. These results highlight the necessity of site-specific designs to optimize green roof efficiency under both current and future conditions and confirms the potential of green roofs to mitigate urban runoff. However, in a context of climate change, uncertainty surrounding future rainfall patterns is high and must be accounted for in future design.

This study uses the SWMM-UrbanEVA model to investigate the performance of seven Blue-Green Infrastructure (BGI) systems across seven European cities under current and future climates. Anticipating that climate change will intensify irrigation demand, the study evaluates key hydrological metrics (water balance, drought stress, runoff) for BGIs designed using national guidelines.

Results show that BGI performance is fundamentally dictated by design. Infiltration-focused systems like dry swales that receive external inflow demonstrated minimal irrigation needs and effectively eliminated runoff in most climates. In contrast, isolated systems like green roofs generated substantial runoff (up to 68%) and were more vulnerable to drought. Water balance partitioning also differed, with evapotranspiration dominating vegetated systems while groundwater recharge was the primary pathway for infiltration-based BGIs.

Future work will assess the effectiveness of national design guidelines against climate impacts like drought and urban flooding, providing recommendations for resilient BGI design. This research offers valuable insights for urban planners adapting BGI strategies to evolving climate challenges in Europe.

Highly urbanized areas pose the most significant challenge for stormwater management due to limited opportunities for implementing sustainable urban drainage systems (SUDS). A SUDS termed Toronto Exfiltration System (TES) was developed to utilize the pore space within the storm sewer trench for stormwater retention and detention. A full-scale model of TES (46m x 2.3m x 1.7 m) was built and used to evaluate the associated runoff control performance. Both steady-state and unsteady-state hydrologic performances were tested using the model (with underlying sandy and clay soil environments). For the 12 m section of TES with clay underlying soil, the steady-state inflows (3 and 10 L/s) were reduced by 47% and 56%, respectively, and the unsteady-state inflow peak flows and volume (5-year and 10-year hydrographs) were reduced about 94% and 45%. For the 12 m section of TES with sandy underlying soil, the steady-state inflows (5, 10, and 15 L/s) were reduced by 71%, 92%, and 83%, respectively, and the unsteady-state inflow peak flows and volume (10-year abd 50-year hydrographs) were decreased about 98% and 50% respectively. Results indicate that TES can be an effective SUDS for highlighted urbanized areas.