In increasingly expanding cities, roofs are still largely unused areas to counteract the negative impacts of urbanization on the water balance and to reduce flooding. To estimate the effect of green roofs as a sustainable low impact development (LID) technique on the building scale, different approaches to predict the runoff are carried out. In hydrological modelling, representing vegetation feedback on evapotranspiration (ET) is still considered challenging. In this research article, the focus is on improving the representation of the coupled soil–vegetation system of green roofs. Relevant data to calibrate and validate model representations were obtained from an existing field campaign comprising several green roof test plots with different characteristics. A coupled model, utilizing both the Penman–Monteith equation to estimate ET and the software EPA stormwater management model (SWMM) to calculate the runoff, was set up. Through the application of an automatic calibration procedure, we demonstrate that this coupled modelling approach (Kling–Gupta efficiency KGE = 0.88) outperforms the standard ET representation in EPA SWMM (KGE = −0.35), whilst providing a consistent and robust parameter set across all green roof configurations. Moreover, through a global sensitivity analysis, the impact of changes in model parameters was quantified in order to aid modelers in simplifying their parameterization of EPA SWMM. Finally, an improved model using the Penman–Monteith equation and various recommendations are presented.

Green roofs are a proven measure to increase evapotranspiration at the expense of runoff, thus complementing contemporary stormwater management efforts to minimize pluvial flooding in cities. This effect has been quantified by numerous studies, ranging from experimental field campaigns to modeling experiments and even combinations of both. However, up until now, most green roof studies consider standard types of green roof dimensions, thus neglecting varying flow length in the substrate. For the first time, we present a comprehensive investigation of green roofs that involves artificial rainfall experiments under laboratory conditions (42 experiments in total). We consider varying flow length and slope. The novelty lies especially in the consideration of flow lengths beyond 5 m and non-declined roofs. This experimental part is complemented by numerical modeling, employing the open-source Catchment Modeling Framework (CMF). This is set-up for Darcy and Richards flow in the green roof and calibrated utilizing a multi-objective approach, considering both runoff and hydraulic head. The results demonstrate that through maximizing flow length and minimizing slope, the runoff coefficient (i.e., percentage of rainfall that becomes runoff) for a 100 years design rainfall is significantly decreased: from ~30% to values below 10%. These findings are confirmed through numerical modeling, which proves its value in terms of achieved model skill (Kling-Gupta Efficiency ranging from 0.5 to 0.95 with a median of 0.78). Both the experimental data and the numerical model are published as open data and open-source software, respectively. Thus, this study provides new insights into green roof design with high practical relevance, whilst being reproducible.

<p>Green infrastructure plays a key role in contemporary concepts to mitigate flooding in urban environments. Concepts like water sensitive cities, sponge cities, and water sensitive urban design aim to mimic features of the natural water cycle even in highly urbanized districts. For instance, green roofs – as a key element of green infrastructure – reduce runoff due to their storage capacity. Hence, evapotranspiration is also increased at the expense of runoff, which better matches the characteristics of the natural water cycle. In this presentation, we demonstrate the added value of green roofs for stormwater mitigation. First, a green roof test plot with a slope of zero degrees and dimensions of 20 m in length and 1 m in width is built under laboratory conditions. The vertical extent is 0.08 m filled with a homogeneous substrate layer with a 300 g m<sup>-2</sup> drainage mat below. The runoff leaving the green roof at one of the 1 m edges is collected in tanks, which allows to continuously monitor the outflow. The water level in the green roof is observed using cameras. In this physical experiment, a sprinkler system is set up in order to generate an artificial rainfall event that mimics a design storm with a rainfall volume of 27 l m<sup>-2</sup> in total falling within 15 minutes. This corresponds to a return period of 100 years at the experimental site in Hanover, Germany. A numerical model utilizing the open source Catchment Modelling Framework (CMF) is developed to represent the green roof in a physically based model representation, which solves the Darcy flow along a 1D numerical grid with a grid spacing of 0.2 m. The model captures the dynamics of the green roof’s hydrological response very well. The comparison of observed and modelled runoff time series, each with a temporal resolution of 1 minute, suggest a Nash-Sutcliffe model efficiency of 0.64. The root mean square error (RMSE) of modelled water levels in the green roof amounts to 1.2 cm. Both the physical experiment and the model suggest a runoff coefficient of 9% after 15 minutes. At present, we also focus on analyzing other configurations of green roofs with altered dimensions and slope (50 experiments in total with up to three repetitions each). These results highlight that (i) CMF represents the hydrology of the green roof with high accuracy, and (ii) green roofs are a very efficient measure of green infrastructure that helps to reduce runoff even for design storms well beyond return periods usually considered in urban drainage planning. This is especially relevant in the process of transforming grey to green infrastructure in the light of climate change adaptation.</p><p> </p>

<p>While the added value of green roofs for mitigating rainfall extremes in urban drainage systems has been addressed in numerous studies, the microscale spatial redistribution of rainfall by solar panels (photovoltaic modules) mounted on green roofs and its impact on hydrology has hardly been studied so far. However, considering both green roofs and rooftop photovoltaic installations are emerging topics relevant for decision makers, since their combination supports both climate change adaptation (transforming grey to green infrastructure in order to cope with extreme rainfall in urban areas) and climate change mitigation (energy transformation). In the framework of an experimental study, we shed light on the hydrological and hydrodynamic effects of rooftop photovoltaic installations mounted on green roofs and how this contributes to the development of sustainable solutions in an interdisciplinary setting. Since solar panels redirect rainfall to the “green” fraction of the roof not covered by solar panels, the green roof part is in effect subject to higher rainfall and hence intensified surface runoff generation. Promising results were still obtained in a first investigation, where a photovoltaic green roof has been irrigated by a 100 years design storm with 27 mm over 15 minutes: the runoff coefficient (i.e., the percentage of rainfall that becomes runoff) at the end of the rainfall event amounts to only 23%, even though surface runoff occurred after 13 minutes. Based on this first investigation, a systematic measurement campaign has been launched to scrutinize the impact of the microscale spatial rainfall redistribution by solar panels on the runoff coefficient. In this presentation, we show the results of the first investigation along with results achieved in the systematic measurement campaign, which considers different vertical layer structures as well as various flow lengths and slopes of the photovoltaic green roof. In parallel, green roofs without photovoltaic rooftop installations are investigated alongside as a benchmark. In essence, our results suggest to consider both green roofs and photovoltaic rooftop installations to support both climate change mitigation and adaptation, which are important questions that decision makers are simultaneously confronted with. This way, this presentation highlights how experimental hydrology and interdisciplinary collaboration can contribute to address policy-related emerging research. Given that an obligation to install solar panels is expected in numerous countries, this kind of research might endorse new design approaches in future green roof design guidelines relevant for practitioners.</p><p> </p>

<p>Green roofs are particularly effective means of nature-based solutions (NBS) in urban areas: They increase evapotranspiration at the expense of surface runoff and thus effectively reduce heat islands. Thus, they provide important ecosystem services, similar to other NBS. This way, green roofs are a key feature in transforming grey to green cities in the light of climate change adaptation. However, there is an urgent need for climate change mitigation efforts, requesting a transformation of energy production, which also suggests a massive increase of rooftop photovoltaic installations. The last decade has seen numerous studies demonstrating the successful combination of both green roofs and rooftop photovoltaic installations. However, in many cases preference is given to either green roofs or rooftop photovoltaic installations. One question that has been little studied so far, is how the runoff coefficient changes due to solar panels, as they spatially redistribute rainfall. Therefore, we scrutinize the impact of solar panels on (sub-) surface hydrology under extreme rainfall conditions in laboratory experiments and a subsequent numerical modelling study. Finally, some recommendations are given on suitable green roof geometries – including rooftop photovoltaic installations – that still have particularly high retention effects.</p>