## 2 Materials and Methods  
The general framework of the proposed methodology is outlined in Figure 1.  
The proposed methodology is based on the following key principles. 1. Identify urban boundaries and catchment areas. It is necessary to identify the urban boundaries and the catchment areas in which they are located. This requires the collection of spatial information on urban boundaries and the creation of an elevation model in order to accurately delineate watercourses and their respective catchment areas. 2. Establish the hydrological baseline. To do this, hydrological models need to be developed, parameterised, and supported by relevant data. Our focus is on peak flows and aggregated annual runoff and infiltration values to assess the effectiveness of SUDSs in managing extreme floods and restoring the natural water balance, ensuring runoff to natural watercourses and aquifer recharge through infiltration. 3. Hydrological modelling approach. We used a custom-built conceptual hydrological model based on curve number (CN), developed in Python (version 3.7), for which we required data on catchment land use, precipitation (both daily aggregates and individual storm events), and evapotranspiration. 4. Climate change projections. Information on the projected evolution of weather variables is crucial for evaluating the effectiveness of SUDSs in a changing climate. Understanding how weather variables are expected to change is essential for evaluating the performance of SUDSs in future climate scenarios. To this end, we employed CMIP6 climate projections, focusing particularly on precipitation and surface maximum/minimum temperatures. These data were obtained from the Climate Change Knowledge Portal in the 'Climate Projections' section. The downloaded CSV data were processed to extract the daily mean, maximum, and minimum precipitation and temperature values for all the selected CMIP6 scenarios. In the CMIP6 framework, the transition year between historical simulations and future projections typically occurs around 2015. From this point onwards, climate model projections are driven by a set of standardised scenarios known as shared socio-economic pathways (SSPs), which describe different possible futures based on various levels of socio-economic development, energy use, land use, and greenhouse gas emissions. These SSPs were developed through a comprehensive, community-led process, and are a key component of CMIP6 scenario-based projections [34; 35]. Each SSP combines qualitative storylines with quantitative data to characterise future challenges to mitigation and adaptation. For instance, SSP1 depicts a'sustainability' pathway involving minimal challenges to both adaptation and mitigation, whereas SSP5 corresponds to a 'fossil-fuelled development' pathway involving significant challenges due to elevated emissions and energy demand. These narratives are supported by sector-specific studies on energy systems [36], land use [37], GHG emission trajectories [38], and air pollution implications [39]. Figure 1: General flowchart of the methodology for assessing the impact of climate change scenarios on SUDS provision. This study incorporates SSP-based projections of precipitation and temperature provided by CMIP6 to simulate future runoff scenarios in urban areas under different potential climate futures. 5. Develop future scenarios for SUDS implementation. Future scenarios for SUDS implementation need to be developed. In our study, we assumed that SUDSs could be represented by variations in the number of representative curves in the catchment area. We selected the city of Bari (Puglia, Italy) as a case study, as it is a coastal urban area facing specific challenges related to climate and urbanisation. Historical rainfall records were collected to establish baseline conditions, and future projections were integrated to simulate the expected evolution of the hydrological systems. Simulations were conducted under different storm event scenarios using aggregated daily rainfall data.