Conference Agenda

Green walls have recently been adapted for urban water treatment, focusing on optimal media, plants, and system design. However, hydrodynamic studies on water balance and evapotranspiration (ET) capacity are lacking. This work introduces a novel continuous infiltration and ET model for green walls. A simplified process-driven model was developed and tested on experimental green walls in Sydney, Australia, with calibration and validation across multiple seasons and watering conditions. Calibration parameters include initial soil moisture, soil texture, and crop coefficient. Results show a good model fit for water flow, with Nash-Sutcliffe Efficiency (NSE) over 0.95 for individual events. Long-term ET simulations also performed well across seasons (average NSE 0.83 – 0.96). Continuous simulations of infiltration and ET showed good performance under various scenarios (NSE for flow and ET over 0.5 and 0.9, respectively). Initial moisture and soil texture were sensitive to the flow module, while crop coefficient significantly impacted long-term predictions. These models are useful for planning water balance in green walls and real-time monitoring, though future work should test them in different climate conditions.

Evapotranspiration (ET) plays a critical role in green stormwater infrastructures (GSI) management by reducing runoff and providing cooling benefit. This study quantitatively assesses seasonal and annual ET by simulating GSI performance including four experimental green roofs (GR) and one rain garden (RG) using the Hydrus-1D hydrological model. The model was calibrated using drainage and ET data from the GRs and the RG respectively. Long term simulations (six years for GRs and two years for the RG) revealed that GRs with a 15 cm substrate planted with sedum and/or grasses achieved interannual ET rates exceeding 50% of precipitation. In contrast, configurations with a 3 cm substrate, either bare or planted with sedum, exhibited ET rates ranging from 30 to 44% of precipitation. Similarly, the rain garden, with an impluvium four times its area, 80 cm silty clay substrate, herbaceous vegetation, and total drainage without internal water storage, demonstrated an annual ET equivalent to 35% of precipitation inputs.

Understanding the sensitivity of reference evapotranspiration(ET₀) to meteorological variables is critical for improving urban water management and climate adaptation strategies. This study analyzes the one-way and two-way sensitivity of ET₀ to maximum temperature(T_max), wind speed(u₂), solar radiation(Rs), and maximum relative humidity(RH_max) using the FAO-56 Penman-Monteith equation for multiple meteorological stations in Paris area. One-way sensitivity analysis revealed that T_max and Rs have the strongest influence on ET₀ in summer, while windspeed and RH_max show secondary notable effects, particularly in winter seasons. A two-way sensitivity analysis was conducted for T_max and RH_max, considering their joint influence on vapor pressure deficit(VPD). The results indicate a nonlinear relationship, where higher T_max and lower RHmax significantly increase VPD, amplifying ET₀, while increasing RHmax dampens this effect. Seasonal variations highlight stronger ET₀ sensitivity in summer and reduced impact of Rs in winter due to high humidity levels. Windspeed has its major role in shaping evapotranspiration in winter and in dense urban settings. These findings emphasize the need for climate-adaptive urban drainage models, integrating ET₀ variability to enhance stormwater retention, flood resilience, and green infrastructure efficiency under changing climate conditions. Future research should refine ET₀ modelling for urban microclimates, ensuring accurate water balance predictions in cities.

This research presents the results of field monitored green infrastructure Stormwater Management Practices (SMPs) constructed to mitigate urbanized stormwater runoff from an elevated highway in the urban environment. The SMPs were designed to capture and remove the first three to five centimetres of rainfall that falls on the highway and allow it to infiltrate rather than enter the combined sewer network, and to mitigate peak flows from larger events. Since 1997, Villanova University in partnership with Temple University has developed and is continuing a fundamental and applied research program using field monitored data coupled with calibrated computer SWMM models to advance the knowledge base of the profession, and to assist and inform stormwater management design and maintenance practices implemented as part of the project. The research team includes geotechnical and environmental researchers, though this presentation will focus on the lessons learned from field hydrologic monitoring coupled with the USEPA Stormw Water Mangagement Model.

Recommendations derived from this research address the stormwater capture and transport system, design of infiltration SMP’s, addressing design and construction challenges, and use of continuous simulation for design to meet regulatory requirements.

Monitoring the long-term performance of blue-green infrastructure (BGI) is underexplored in the published literature. This oversight risks overestimating its benefits in the long run and ignoring its maintenance requirements. To address this gap, a workflow is proposed to investigate temporal dynamics in BGI hydrological performance. The workflow utilises Time Series Data Mining (TSDM), combining clustering, segmentation, and dynamic time warping techniques with statistical tests. This workflow first identifies pairs of statistically similar rainfall events from different periods. Then, the corresponding BGI underdrain flows for these similar rainfall event pairs are analysed using the volume-based underdrain flow-to-rainfall ratio (UF-P ratio) and time-based metrics, which include centroid delay, cross-correlation, and DTW. When using the workflow in a green roof in Oslo, only six rainfall pairs were found to be statistically similar. The UF-P ratio for these pairs increased on average from 0% to around 6.6% over time, albeit with high variability (SD > 16%); the changes over time were not statistically significant. Although the change in the UF-P ratio was not statistically significant due to the small sample size, the results suggest performance drifts over time. This result also highlights the need to monitor BGI to track its hydrological performance.

As precipitation patterns change, so does the need for revised Blue-Green Infrastructure (BGI) design standards. Holistic hydrologic design and modelling are vital for addressing climate uncertainties and ensuring the long-term integrity of optimized BGI. Within that scope, two key design needs are what size storm event needs to be safely routed through a BGI practice, and what is the precipitation depth of a Water Quality (WQ) event? WQ events principally determine the surface area and storage depths of BGI. The investigation uses North Carolina, USA, as a case study to determine revised design standards for these hydrologic parameters. Of particular interest was the increase, usually substantially (up to 25%), required for the WQ event depth when focusing on the most recent decade of available precipitation data. These results will be used to inform design standards in NC, likely yielding larger, and more protective, BGI in the coming years.