Severe weather conditions and urban intensification are key factors affecting the response of combined sewer systems, especially during storm events. In this regard, the capacity assessment of combined sewer networks under the impact of rainfall storm events of different return periods was the focus of this work. The selected case study area was a mixed-use catchment in the city centre of Thessaloniki, Greece. The hydraulic performance of the examined sewer network was assessed using an InfoWorks ICM model. The results indicated that mitigation strategies, such as the application of nature-based solutions (NBSs) or low-impact developments (LIDs) are considered essential for controlling combined sewer overflows. A multicriteria analysis was conducted to select the most appropriate NBSs/LIDs to be located in the study area to enhance the system’s capacity. The results of this multicriteria analysis were used to propose a combined sewer overflow mitigation scenario, based on the installation of green roofs, as the most highly ranked solution in the analysis performed. Incorporating the proposed NBS/LID in the hydrologic-hydraulic model significantly increased the performance of the studied combined sewer network.

The study examines the impacts of climate change on the operation and capacity of the combined sewer network in the historic center of Thessaloniki, Greece. Rainfall data from three high-resolution Regional Climate Models (RCMs), namely (a) the Cosmo climate model (CCLM), (b) the regional atmospheric climate model (RACMO) and (c) the regional model (REMO), from the MED-CORDEX initiative with future estimations based on Representative Concentration Pathway (RCP) 4.5, are first corrected for bias based on existing measurements in the study area. Intensity–duration–frequency (IDF) curves are then constructed for future data using a temporal downscaling approach based on the scaling of the Generalized Extreme Value (GEV) distribution to derive the relationships between daily and sub-daily precipitation. Projected rainfall events associated with various return periods are subsequently developed and utilized as input parameters for the hydrologic–hydraulic model. The simulation results for each return period are compared with those of the current climate, and the projections from various RCMs are ranked according to their impact on the combined sewer network and overflow volumes. In the short term (2020–2060), the CCLM and REMO project a decrease in CSO volumes compared to current conditions, while the RACMO predicts an increase, highlighting uncertainties in short-term climate projections. In the long term (2060–2100), all models indicate a rise in combined sewer overflow volumes, with CCLM showing the most significant increase, suggesting escalating pressure on urban drainage systems due to more intense rainfall events. Based on these findings, it is essential to adopt mitigation strategies, such as nature-based solutions, to reduce peak flows within the network and alleviate the risk of flooding.

The study examines impacts of climate change on operation and capacity of the combined sewer network in the historic center of Thessaloniki, Greece. Rainfall data from three high-resolution Regional Climate Models (RCMs) from MED-CORDEX initiative with future estimations based on Representative Concentration Pathway (RCP) 4.5, are first corrected for bias based on existing measurements in the study area. Intensity-duration-frequency (IDF) curves are then constructed for the future data, using a temporal downscaling approach based on the scaling of the Generalized Extreme Value (GEV) distribution to derive the relationships between daily and sub-daily precipitation. Projected rainfall events associated with various return periods are subsequently developed and utilized as input parameters for the hydrologic-hydraulic model. The simulation results for each return period are compared with those of the current climate, and the projections from various RCMs are ranked according to their impact on the combined sewer network and overflow volumes.