Veranstaltungsprogramm

This study developed a simplified 1D hydraulic model to quantify field runoff entering a combined sewer network in a catchment in southwest England. This model uses the Green-Ampt model to represent the infiltration process and a reservoir routing model to represent the runoff routing. The modelled field runoff was input into the existing sewer network model as inflows in InfoWorks ICM to analyse the contributions of various components to storm overflows. The simulations revealed that storm overflow frequency is primarily driven by impermeable area surface runoff, overflow duration is mainly affected by ground infiltration, and field runoff significantly contributes to overflow volume. Nature Based Solutions (NBS) and Sustainable Drainage Systems (SuDS) were implemented within the model to evaluate their effectiveness in mitigating storm overflow through long-term simulations. Results indicated that together with the NBS, retrofitting 8% of impermeable surfaces with SuDS can reduce storm overflow frequency by 38%, overflow duration by 40%, and overflow volume by 77%, highlighting the potential of these interventions to minimise storm overflow impacts.

Three permeable car park systems were simulated with SWMM LID model. For the two vegetated permeable car parks (ECOVEGETAL Mousses and ECOVEGETAL Green), the choice was made to use the SWMM bioretention module while the permeable pavement module was used for a mineral permeable car park (ECOVEGETAL Minéral). One year of rainfall and potential evapotranspiration were used to simulated water flows through the structure of these parking lots. Calibration and sensibility analysis were conducted and quality of the simulations were estimated with a Nash–Sutcliffe efficiency coefficient and a water budget criterion. Good results were obtained for the mineral and ECOVEGETAL Mousses car parks. Bioretention module seems not suitable if the structure of the parking is too complex.

This study introduces a modelling framework integrating blue-green infrastructure modelling with demand-oriented irrigation management. By using Python-based applications, such as SWMM, SWMM-UrbanEVA and Smartin, the framework addresses key challenges, including insufficient representation of location- and plant-specific conditions or lack of integration for real-time control and model-predictive control. The framework supports dynamic irrigation control strategies, optimizing water use, enhancing evapotranspiration, and reducing urban runoff. In a case study in Münster, Germany, evapotranspiration increased by up to 60% for some BGI types, while sewer runoff decreased by up to 36%. The integration of rainwater harvesting and irrigation control demonstrates its capacity for resource efficiency. Flexible and adaptable, the framework enables practical applications across urban environments, allowing scenario analysis, efficient irrigation operations, and citizen engagement through real-time irrigation demand forecasting.

This study assesses the potential implementation of Bioretention Zones (BRZ) in the Bogota campus at the Universidad Nacional Colombia. The goal of the paper is to present a simplified methodology that considers a BRZ scenario for mitigating runoff peaks in the campus. The project methodology is three folded: (1) a suitability analysis for BRZ implementation, (2) configuration and calibration of a rainfall-runoff model, and (3) simulation and assessment of one BRZ scenario in the study area. The GIS-based suitability analysis revealed that at least 10% of the delineated urban catchment may be suitable for BRZ implementation. An 11-BRZ scenario that captures runoff from 11.9% of the catchment area resulted in a subcatchment’s peak-runoff reduction between 10% to 42%. However, the overall peak reduction may not achieve the 30% peak reduction required by Colombian regulations. Besides the potential location of BRZ, the potential subcatchment runoff is suggested as a planning variable to improve the assessment of this SUDS typology for peak-runoff reduction.

Stormwater engineers need to predict how Low Impact Development (LID) assets (e.g. green roofs and bioretention cells) respond to both routine and extreme rainfall events. Typically, the growing media of the LID assets will be in an unsaturated state, where percolation through the media is related to the media’s volumetric water content. This relationship can provide significant detention effects, particularly when moisture contents are at or near field capacity. Correctly representing these unsaturated flows is critical to ensuring robust long-term continuous simulations of bioretention hydrological performance. The US EPA’s Storm Water Management Model, SWMM, is the most well-known of the available open-source modelling tools. SWMM models the percolation rate in the growing media with an exponential function. The resulting percolation estimates have been observed to lead to poor modelled outflow responses during low flow conditions.

This study introduces a new power form Hydraulic Conductivity Function (HCF) that better represents observed percolation rates and yields improved modelled outflow responses. Crucially, the New HCF requires the same number of media specific variables as the current SWMM HCF. Even with these HCF improvements, modelled outflow timings are still compromised by the homogenous media moisture content assumed within the SWMM percolation model framework.

Bioretention cells (BRCs) are commonly used in urban areas to manage stormwater runoff and reduce pressure on drainage systems. However, their performance often differs from design expectations due to construction limitations and site-specific conditions. This study compares water retention in 31 BRCs located in Montreal, Canada, as simulated with the Storm Water Management Model (SWMM) and observed through field data collection. BRCs were selected for analysis based on their impervious-to-permeable (I/P) ratio and physical characteristics. The field data included water level measurements taken by pressure probes and rainfall data provided by the city, used to analyze the hydrological behaviour of the BRCs during the non-freezing season (May to November). Results for four randomly chosen BRCs are presented here. One of these showed close agreement between simulated and observed water retention, with a Nash-Sutcliffe efficiency value of 0.74 and a strong positive correlation. The other three exhibited differences between the modelled and observed data, attributed to discrepancies between the design (modelled) and field-built conditions, as confirmed by field visits. These findings underscore the importance of considering the physical limitations of BRCs in the field and their construction characteristics, such as elevated inlets or poorly directed street slopes, when evaluating their performance.