Green stormwater infrastructure (GSI) is growing in popularity to reduce combined sewer overflows (CSOs) and hydrologic simulation models are a tool to assess their reduction potential. Given the numerous and interacting water flows that contribute to CSOs, such as evapotranspiration (ET) and groundwater (GW), these models should ideally account for them. However, due to the complexity, simplified models are often used, and it is currently unknown how these assumptions affect estimates of CSOs, GSI effectiveness, and ultimately planning guidance. This study evaluates the effect on estimates of CSOs and GSI effectiveness when different flows and hydrologic processes are neglected. We modified an existing EPA SWMM model of a combined sewer system in Switzerland to include ET, GW, and upstream inflows. Historical rainfall data over 30 years are used to assess volume and duration of CSOs with and without three types of GSI (bioretention basins, permeable pavements and green roofs). Results demonstrate that neglect of certain flows in modelling can alter CSO volumes from -15 % to 40 %. GSI effectiveness also varies considerably, resulting in differences in simulated percent of CSO volume reduced from 8 % to 35 %, depending on the GSI type and modeled flow or process. Representation of GW within models is particularly crucial when infiltrating GSI are present, as CSOs could increase in certain subcatchments due to higher GW levels from increased infiltration. When basing GSI planning decisions on modeled estimates of CSOs, all relevant hydrologic processes should be included to the extent possible, and uncertainty and assumptions should always be considered.

Due to their cooling ability, sustainable roofing configurations, such as green and cool roofs, have the potential to increase solar panel yield, which is temperature dependent. However, the influence of sustainable roofing configurations on panel yield is not yet considered in rooftop photovoltaic (PV) planning models; thus, the significance of these integrated systems cannot be evaluated. In order to quantify the potential benefits of sustainable rooftops on solar energy, the first goal of this study is to develop a method that systematically accounts for roof surface characteristics in the simulation of PV panel energy yield. To do so, a rooftop energy balance model is linked with a physically-based solar energy model (the System Advisor Model, SAM) to quantify the energy yield of PV installations on sustainable roofing configurations. Roof surface temperatures are first estimated using non-linear energy balance equations, then integrated into a revised version of SAM to simulate energy yield. This new method improves the accuracy of PV yield simulations, compared to prior assumptions of roof surface temperature equal to ambient temperature. This updated model is used for the second goal of the study, to understand how four roofing configurations (black membrane, rock ballasted, white membrane, and vegetated) influence PV panel yield, which is currently not well understood in cooler climates. For a flat rooftop PV installation near Zurich, Switzerland (temperate climate), results show that, compared to a conventional roof, green roofs can increase annual PV energy yield, on average, by 1.8%, whereas cool roofs can increase it by 3.4%. For the case-study installation, an inverse correlation between the 95th-quantile roof surface temperature and the PV energy yield was identified; an increase of 1 °C leads to a 71 kWh reduction in energy yield per year. Overall, cool roofs outperform green roofs in terms of increases in PV energy yield; however, potential improvements of both systems are non-negligible, even in relatively cooler climate regions like Switzerland. By providing a systematic method to evaluate the influence of the roofing configuration on PV energy yield, solar energy planners are able to differentiate between the benefits of traditional and sustainable rooftop configurations - the first step towards the coupling of distributed energy and sustainable building systems. In the future, this integrated method could be used as part of a holistic evaluation of the environmental, economic, and social objectives of green and cool roofs, as well as, other infrastructure systems.