Session B2 - Modelling the resilience of SCMs to climate change and extreme events

Rapid urbanization and climate change have increasingly challenged conventional drainage systems in cities like Bogotá, prompting the adoption of Sustainable Drainage Systems (SuDS). This study proposes the development of a flexible methodology for the design of SuDS, aimed at mitigating various impacts of climate change. The methodology was applied to a case study in Bogotá, focused on the design of bioretention trenches under future climate scenarios in an urban catchment located in Teusaquillo (Bogotá). Historical records (1981–2009) and CMIP6 projections were integrated, applying a daily water balance model and a Monte Carlo stochastic simulation. Results indicate a decrease in performance under warmer and drier scenarios, although optimized configurations reach efficiencies close to 30%, significantly outperforming the baseline model (<1%). The proposed methodology demonstrates the feasibility and resilience of SuDS under climate change, providing a replicable framework for their evaluation and design in Latin American cities with similar urban and data constraints.

The research activity aims at evaluating the role of Stormwater Nature Based Solutions (NBS-Sw) in addressing the urban resilience in a changing climate. The continuous simulation of the hydrologic hydraulic response of an urban catchment is undertaken using EPA SWMM at a sub-hourly time resolution. At this aim, the case study of the Sampierdarena district in Genoa, northern Italy has been selected; the case study area (143 ha) and the corresponding drainage system is schematized by means of 90 sub-catchments and 137 conduit links where no NBS-Sws are implemented (reference scenario) while the widespread deployment of NBS-Sw (including bio-retention systems, dry swales and green roofs) represents the NBS-Sw scenario. The past and future climate are simulated over the ALP3 domain, and the bias correction was performed on both daily minimum and maximum temperatures and hourly precipitation, the latter further statistically downscaled to 5-minute resolution. Long-term hydrological results (series of 5 years) confirm that the NBS-Sw scenario contributes to partially restore evapotranspiration and infiltration processes and to significantly reduce the flood volume equal to 90% and 56% in the current and future climate respectively.

This study evaluates how well IDF-based design storms represent the hydrologic and water-quality impacts produced by actual storm events of equivalent return periods. Using a 44-year rainfall record, actual storms corresponding to different return periods were identified using the Weibull distribution and compared against three IDF-derived storm configurations: (i) 24-hour standardized storms, (ii) fixed-duration storms using IDF rainfall depth, and (iii) fixed-depth storms using IDF-based duration. Storm responses were assessed in SWMM using three threshold-based performance metrics: street flooding depth, shear stress at the outlet and TSS concentration. Results show that fixed-duration storms most closely reproduce the exceedance durations observed during actual storms for flooding and shear stress. Fixed-depth storms better matched actual TSS exceedance behavior, whereas the 24-hour standardized storms, because of their smoother intensity pattern, produced more cautious and lower exceedance estimates across indicators. Although no single IDF-based configuration fully replicated the system response of actual storms, the fixed-duration storms provided the most consistent approximation across metrics, while the 24-hour storm served as a conservative, regulation-friendly option for preliminary design.

Soil moisture data are essential for describing hydrological processes of natural surfaces. They play a minor role in the modelling of impervious urban drainage systems, but the expanding presence of green areas in urban environments opens up the possibility of using them also for the improvement of urban drainage models. In this work, the impact of soil moisture data in the optimization process of a peri-urban catchment model in SWMM was investigated. Using a generalized likelihood uncertainty estimation (GLUE) approach, two calibration scenarios were carried out. In the first scenario only flow data were used to optimize the model, in the second flow and soil moisture data were used. The two scenarios were then compared during a validation period. Results revealed a slight improvement in the accuracy of the soil moisture predictions for the second scenario, but no improvement for flow rate predictions was observed. However, a reduction of the prediction uncertainty was found for the second scenario for all the outputs. More detailed investigations are necessary, but the preliminary results of this study showed the potential for soil moisture data to reduce model uncertainty and improve soil moisture predictions when using them in the optimization of urban drainage models.