Detention-based green roofs for stormwater management under extreme precipitation due to climate change

Abstract Rooftops cover a large percentage of land area in urban areas, which can potentially be used for stormwater purposes. Seeking adaptation strategies, there is an increasing interest in utilising green roofs for stormwater management. However, the impact of extreme rainfall on the hydrological performance of green roofs and their design implications remain challenging to quantify. In this study, a method was developed to assess the detention performance of a detention-based green roof (underlaid with 100 mm of expanded clay) for current and future climate conditions under extreme precipitation using an artificial rainfall generator. The green roof runoff was found to be more sensitive to the initial water content than the hyetograph shape. The green roof outperformed the black roof in terms of all performance indicators (time of concentration, centroid delay, T50 or peak attenuation). While the time of concentration for the reference black roof was within 5 minutes independently of rainfall intensity, for the green roof was extrapolated between 30 and 90 minutes with intensity from 0.8 to 2.5 mm/min. Adding a layer of expanded clay under the green roof substrate provided a significant improvement to the detention performance under extreme precipitation in current and future climate conditions.

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Addressing the Water–Energy–Food Nexus through Enhanced Green Roof Performance

Sustainability ◽

10.3390/su13041972 ◽

2021 ◽

Vol 13 (4) ◽

pp. 1972

Author(s):

Jeremy Wright ◽

Jeremy Lytle ◽

Devon Santillo ◽

Luzalen Marcos ◽

Kristiina Valter Mai

Keyword(s):

Climate Change ◽

Performance Optimization ◽

Urban Areas ◽

Stormwater Management ◽

Green Roof ◽

Green Roofs ◽

Management Tool ◽

Contributing Factors ◽

Rainwater Runoff ◽

Rain Events

Urban densification and climate change are creating a multitude of issues for cities around the globe. Contributing factors include increased impervious surfaces that result in poor stormwater management, rising urban temperatures, poor air quality, and a lack of available green space. In the context of volatile weather, there are growing concerns regarding the effects of increased intense rainfalls and how they affect highly populated areas. Green roofs are becoming a stormwater management tool, occupying a growing area of urban roof space in many developed cities. In addition to the water-centric approach to the implementation of green roofs, these systems offer a multitude of benefits across the urban water–energy–food nexus. This paper provides insight to green roof systems available that can be utilized as tools to mitigate the effects of climate change in urbanized areas. A new array of green roof testing modules is presented along with research methods employed to address current issues related to food, energy and water performance optimization. Rainwater runoff after three rain events was observed to be reduced commensurate with the presence of a blue roof retention membrane in the testbed, the growing media depth and type, as well as the productive nature of the plants in the testbed. Preliminary observations indicate that more productive green roof systems may have increasingly positive benefits across the water–energy–food nexus in dense urban areas that are vulnerable to climate disruption.

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Is Smart Growth a smart adaptation strategy?: Examining Ontario's proposed growth under climate change

Ekistics and the new habitat - India and Jugaad: The Impact of Innovation by the Resilient Indian Mind on Habitat ◽

10.53910/26531313-e200471424-426224 ◽

2004 ◽

Vol 71 (424-426) ◽

pp. 57-62

Author(s):

Brad Bass

Keyword(s):

Climate Change ◽

Energy Consumption ◽

Urban Areas ◽

Green Roof ◽

Smart Growth ◽

Green Roofs ◽

Adaptation Strategy ◽

University Of Toronto ◽

Conducting Research ◽

The Impact

The author is a member of Environment Canada's Adaptation and Impact Research Group, located in the Centre for Environment at the University of Toronto. His primary research interests include the use of ecological technologies in adapting urban areas to atmospheric change, the impacts of climate change on the energy sector, and the characteristics of adaptable systems. His current work on ecological technologies includes green roofs, vertical gardens and living machines. Dr Bass has been involved in two major projects, in Ottawa and Toronto, to evaluate the impact of green roofs on the urban heat island, energy consumption, stormwater runoff and water quality. Currently, Dr Bass is conducting research on integrating green roof infrastructure with other vegetation strategies at a community scale, simulating the impact of a green roof on the energy consumption of individual buildings.

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A Comparison between Conceptual and Physically Based Models in Predicting the Hydrological Behavior of Green Roofs

Proceedings ◽

10.3390/ecws-4-06450 ◽

2019 ◽

Vol 48 (1) ◽

pp. 8

Author(s):

Mirka Mobilia ◽

Antonia Longobardi

Keyword(s):

Urban Areas ◽

Goodness Of Fit ◽

Green Roof ◽

Green Roofs ◽

Storm Events ◽

Climate Conditions ◽

Hourly Data ◽

Test Beds ◽

Fit Indexes ◽

Flooding Risk

The evolving climate conditions contribute to increase flooding risk in urban areas. Green roofs are effective tools for controlling and managing stormwater runoff. With the aim to prevent these damaging events, an accurate modelling of the response of green roofs to storm events becomes essential. The goal of this research is to compare the accuracy of two hydrological models in predicting the behavior of two green roof test beds in terms of runoff production. The test beds are located in the campus of University of Salerno, in a typical Mediterranean climate and they differ in the composition of the drainage layer. The selected models are the Storm Water management model (SWMM) model and the Nash model. They have been calibrated against hourly data of 25 rainfall-runoff events observed at the experimental site and compared using a number of goodness of fit indexes. The Nash cascade model aims to be a very simple but effective approach. No substantial differences were observed in the behavior of the two green roof plots, though they differ in their design characteristics. Finally, the existence of a relationship between the errors and the rainfall characteristics has been found.

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Influence of environmental factors on retention of extensive green roofs with different substrate composition

E3S Web of Conferences ◽

10.1051/e3sconf/20198600026 ◽

2019 ◽

Vol 86 ◽

pp. 00026 ◽

Cited By ~ 1

Author(s):

Anna Baryła ◽

Agnieszka Karczmarczyk ◽

Agnieszka Bus ◽

Edyta Hewelke

Keyword(s):

Environmental Factors ◽

Green Infrastructure ◽

Urban Areas ◽

Green Roof ◽

Green Roofs ◽

Statistical Regression ◽

Climate Conditions ◽

Factors Affecting ◽

Organic Mineral ◽

Local Ecosystem

Increasing recognition is being given to the adaption of green roofs in urban areas to enhance the local ecosystem. Green roofs may bring several benefits to urban areas including flood mitigation Analysis of environmental factors affecting the outflow of green roofs is the subject of many studies. The work assessed how environmental factors moisture of structural layers and antecedent dry weather period influence the retention on two types of green roof substrates. The monitoring of environmental factors and amount of runoff was carried out on two models of green roofs covered by extensive vegetation (mosssedum-herbs) with substrates of an organic-mineral and mineral composition for 8 months. A statistical regression approach identified potential antecedent meteorological factors and moisture indicators of extensive green-roof retention. Continuous field monitoring data revealed the combined effects of rainfall depth and antecedent dry weather period to explain the measured stormwater retention under a moderate climate conditions regime. It is important to incorporate site-specific planning and assessment prior to green infrastructure design.

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Robust Vegetation Parameterization for Green Roofs in the EPA Stormwater Management Model (SWMM)

Hydrology ◽

10.3390/hydrology8010012 ◽

2021 ◽

Vol 8 (1) ◽

pp. 12

Author(s):

Ronja Iffland ◽

Kristian Förster ◽

Daniel Westerholt ◽

María Herminia Pesci ◽

Gilbert Lösken

Keyword(s):

Stormwater Management ◽

Low Impact Development ◽

Green Roof ◽

Green Roofs ◽

Management Model ◽

Model Parameters ◽

Vegetation Feedback ◽

Stormwater Management Model ◽

The Impact ◽

Monteith Equation

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.

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Experimental Winter Monitoring of a Light-Weight Green Roof Assembly for Building Retrofit

Sustainability ◽

10.3390/su13094604 ◽

2021 ◽

Vol 13 (9) ◽

pp. 4604

Author(s):

Fabiana Frota de Albuquerque Landi ◽

Claudia Fabiani ◽

Anna Laura Pisello

Keyword(s):

Urban Areas ◽

Green Roof ◽

Green Roofs ◽

Cold Season ◽

Positive Energy ◽

Light Weight ◽

Building Retrofit ◽

Island Effect ◽

Urban Heat ◽

The Impact

Green roofs are a recurrent solution for improving environmental quality in buildings. Such systems can, among other things, reduce the urban heat island effect, improve indoor thermal comfort and visual quality, and reduce energy consumption in buildings, therefore promoting human comfort. This work presents the winter monitoring of a light-weight green roof assembly with the potential to be implemented in extensive urban areas. The green roof monitoring was compared to those of previous bituminous and cool-coating applications. Results show that the system was able to decrease heat losses maintaining a positive energy flow from solar radiation gains and a more constant indoor temperature. In a well-insulated construction, the impact during the cold season was discreet. However, compared to the reference building, a slightly lower indoor air temperature (about 1 °C) was registered.

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Estimating Carbon Sequestration of Green Roof Plants in Tropical Climate

International Journal of Integrated Engineering ◽

10.30880/ijie.2021.13.03.024 ◽

2021 ◽

Vol 13 (3) ◽

Author(s):

Mohamad Norfekry Md. Yacob ◽

◽

Hartini Kasmin ◽

Muhammad Iqbal Hakeem Hashim ◽

◽

...

Keyword(s):

Urban Areas ◽

Greenhouse Gas Emission ◽

Green Roof ◽

Co2 Reduction ◽

Green Roofs ◽

Co2 Uptake ◽

Test Bed ◽

Reduce Carbon Dioxide ◽

Carbon Dioxide Co2 ◽

The Impact

A green roofs is one of the recommended methods of practice in improving the sustainability of urban areas. Green roofs can be used as a passive technique to reduce carbon dioxide (CO2) emissions from the atmosphere. This is due to the role of green roof layers which are vegetation and soil to process the photosynthesis activities and to capture CO2 from the atmosphere. The objective of this paper is to quantify and to compare the amount of CO2 sequestration by ten potential green roof plants, in order to estimate the CO2 reduction within the surrounding atmosphere. It is found that, by planting the Alternanthera Paronychioides (Alternanthera P.) on the roof surface could reduce the indoor air temperature as well as the CO2, thus enhance the quality of air. This study also revealed that the Alternanthera P. generates the highest photosynthesis rate or CO2 uptake compared to the other nine plants, as high as 23.59 μmol CO2 m-2s-1. It is predicted that if the Alternanthera P. is to be installed on a 0.64 m2 test bed roof, the CO2 could be reduced almost 0.010 tonnes, annually. This suggested that by planting Alternanthera P. on the roof surfaces may potentially give advantages on mitigating the greenhouse gas emission, particularly CO2, and reducing the impact of global warming.

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Seismic Performance of a Green Roof Structure

Sustainability ◽

10.3390/su13084278 ◽

2021 ◽

Vol 13 (8) ◽

pp. 4278

Author(s):

Svetlana Tam ◽

Jenna Wong

Keyword(s):

Green Roof ◽

Time History ◽

Green Roofs ◽

Moment Frame ◽

Steel Moment Frame ◽

Roof Structure ◽

Nonlinear Time History Analyses ◽

Vegetated Roofs ◽

Nonlinear Time History ◽

The Impact

Sustainability addresses the need to reduce the structure’s impact on the environment but does not reduce the environment’s impact on the structure. To explore this relationship, this study focuses on quantifying the impact of green roofs or vegetated roofs on seismic responses such as story displacements, interstory drifts, and floor level accelerations. Using an archetype three-story steel moment frame, nonlinear time history analyses are conducted in OpenSees for a shallow and deep green roof using a suite of ground motions from various distances from the fault to identify key trends and sensitivities in response.

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Bias correction of extreme values of high resolution climate simulations for risk analysis.

10.21203/rs.3.rs-264479/v1 ◽

2021 ◽

Author(s):

luis Augusto sanabria ◽

Xuerong Qin ◽

Jin Li ◽

Robert Peter Cechet

Keyword(s):

Climate Change ◽

Bias Correction ◽

Extreme Values ◽

The Body ◽

Future Climate ◽

Return Periods ◽

Climate Conditions ◽

Mitigation And Adaptation ◽

Climate Simulations ◽

The Impact

Abstract Most climatic models show that climate change affects natural perils' frequency and severity. Quantifying the impact of future climate conditions on natural hazard is essential for mitigation and adaptation planning. One crucial factor to consider when using climate simulations projections is the inherent systematic differences (bias) of the modelled data compared with observations. This bias can originate from the modelling process, the techniques used for downscaling of results, and the ensembles' intrinsic variability. Analysis of climate simulations has shown that the biases associated with these data types can be significant. Hence, it is often necessary to correct the bias before the data can be reliably used for further analysis. Natural perils are often associated with extreme climatic conditions. Analysing trends in the tail end of distributions are already complicated because noise is much more prominent than that in the mean climate. The bias of the simulations can introduce significant errors in practical applications. In this paper, we present a methodology for bias correction of climate simulated data. The technique corrects the bias in both the body and the tail of the distribution (extreme values). As an illustration, maps of the 50 and 100-year Return Period of climate simulated Forest Fire Danger Index (FFDI) in Australia are presented and compared against the corresponding observation-based maps. The results show that the algorithm can substantially improve the calculation of simulation-based Return Periods. Forthcoming work will focus on the impact of climate change on these Return Periods considering future climate conditions.

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Evaporation from (Blue-)Green Roofs: Assessing the Benefits of a Storage and Capillary Irrigation System Based on Measurements and Modeling

Water ◽

10.3390/w10091253 ◽

2018 ◽

Vol 10 (9) ◽

pp. 1253 ◽

Cited By ~ 4

Author(s):

Dirk Cirkel ◽

Bernard Voortman ◽

Thijs van Veen ◽

Ruud Bartholomeus

Keyword(s):

Energy Balance ◽

Urban Areas ◽

Evaporation Rate ◽

Climate Adaptation ◽

Irrigation System ◽

Green Roof ◽

Green Roofs ◽

C3 Plants ◽

Rapid Decline ◽

Air Temperatures

Worldwide cities are facing increasing temperatures due to climate change and increasing urban density. Green roofs are promoted as a climate adaptation measure to lower air temperatures and improve comfort in urban areas, especially during intensive dry and warm spells. However, there is much debate on the effectiveness of this measure, because of a lack of fundamental knowledge about evaporation from different green roof systems. In this study, we investigate the water and energy balance of different roof types on a rooftop in Amsterdam, the Netherlands. Based on lysimeter measurements and modeling, we compared the water and energy balance of a conventional green roof with blue-green roofs equipped with a novel storage and capillary irrigation system. The roofs were covered either with Sedum or by grasses and herbs. Our measurements and modeling showed that conventional green roof systems (i.e., a Sedum cover and a few centimeters of substrate) have a low evaporation rate and due to a rapid decline in available moisture, a minor cooling effect. Roofs equipped with a storage and capillary irrigation system showed a remarkably large evaporation rate for Sedum species behaving as C3 plants during hot, dry periods. Covered with grasses and herbs, the evaporation rate was even larger. Precipitation storage and capillary irrigation strongly reduced the number of days with dry-out events. Implementing these systems therefore could lead to better cooling efficiencies in cities.

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