Role of drainage layer on green roofs in limiting the runoff of rainwater from urbanized areas

Baryła, Anna

doi:10.2478/jwld-2019-0022

Cited by 7 publications

(3 citation statements)

References 34 publications

(40 reference statements)

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“…On the other hand, however, they reported not statistically significant correlation between ADWP and retention, but their research was conducted in natural conditions and they have taken into account all precipitations having diversified depths and intensities [40]. In another publication Baryla [41] found that the volume of precipitation, the initial moisture substrate, and ADWP have a significant effect on green roof retention. But she reported the higher correlation of retention with moisture content than with the ADWP.…”

Section: Resultsmentioning

confidence: 97%

Impact of the Hydrogel Amendment and the Dry Period Duration on the Green Roof Retention Capacity

Deska

Mrowieć

Ociepa

et al. 2020

Ecological Chemistry and Engineering S

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Climate changes as well as the urbanisation and economic development influence the characteristics of the stormwater runoff in the cities. The sealing of drainage basin surface leads to an increase of the runoff intensity, thereby decreasing the rainwater infiltration. This situation can lead to the risk of flooding in urban areas. Therefore, especially in great cities there is a need for application of such solutions that will support the operation of the sewage systems. The examples of such solutions are, among others, the green roofs. The paper presents the results of investigation of the water retention capacity of 4 green roof models containing following growing media: (1) the typical green roof substrate without any amendments, (2) the substrate with addition of about 1 % by weight of hydrogel (the cross-linked potassium polyacrylate), (3) the substrate containing about 0.25 % by weight of hydrogel, (4) the substrate with addition of expanded clay and perlite. The models were not vegetated in order to investigate only the water retention capacity of drainage elements and substrates. The water retention capacity of green roof models was investigated in the laboratory conditions with use of artificial precipitations simulated after diverse antecedent dry weather periods (ADWP) amounting to: 1, 2, 5, 7, and 12 days. The intensities of artificial precipitations were relatively high and ranged from 1.14 to 1.27 mm/min, whereas their durations ranged from 7.75 to 12.56 min. These values of intensities and durations corresponded to the design rainfall intensities calculated using Blaszczyk’s equation for annual rain depth equal to 600 mm and the return periods ranged from 5 to 15 years. The obtained results indicate that the water retention capacity of green roof models, expressed as the volumes (or depths) of rainwater retained within their structures, increases with an increase of ADWP. Results indicate that the relation between ADWP and the amount of water retained in the layers of green roofs in the case of relatively short antecedent dry weather periods provided for the analysis (from 1 to 7 days) may be approximately linear. The results of the one-way ANOVA indicate that in the case of all models there is a statistically significant difference between the values of retention depth for specified ADWP (p < 0.001). During more than half of simulated precipitations, especially in the case of longer ADWPs lasting 5, 7, and 12 days the best water retention capacity had Model 3, with substrate containing about 0.25 % by weight of hydrogel. On the other hand, the results show that the weakest retention capacity had Model 2 (with substrate containing 1 % by weight of hydrogel). In the case of longer ADWPs (lasting 7 and 12 days) relatively weak water retention capacity had Model 4 (with substrate containing the addition of expanded clay and perlite). It can be concluded that too large amount of hydrogel added to the substrate can have an unfavourable impact on the water retention capacity of green roofs.

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Section: Resultsmentioning

confidence: 97%

Impact of the Hydrogel Amendment and the Dry Period Duration on the Green Roof Retention Capacity

Deska

Mrowieć

Ociepa

et al. 2020

Ecological Chemistry and Engineering S

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“…Baryla [49] monitored six test stands for column studies to compare the retention capacity of two different types of green roof drainage layer: Leca® and quartzite grit. Each type has 10 cm and 5cm drainage layer columns.…”

Section: Substrate Layermentioning

confidence: 99%

Detection of Green Roofs through Satellite Imagery Using Faster R-CNN

Marcos

2024

Preprint

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<p>With the threat of global warming, there is a need to implement sustainable solutions. Due to urbanization, forests and other natural resources that could have helped reduce carbon emissions are being depleted. Thus, cities, like Toronto, experience urban heat island effects, food shortages and increased carbon emissions. To help solve this, Green Roofs are encouraged to be implemented in Toronto to help reduce the mentioned issues. In addition, green roofs are difficult to maintain and COVID-19 making it more difficult for urban farmers to physically go and check the green roofs. Hence, this study proposes to use deep learning in detecting green roofs from satellite imagery. The approach uses NDVI values and Toronto Building data to obtain green roof locations. From here, satellite images were taken from map services such as Google Earth Pro and ArcGIS Pro. The images were preprocessed and fed into Faster R-CNN model to detect green roofs. Since this is a first step in creating a system that can monitor the Green Roof Food-Energy-Water nexus, in the future, the behaviour of Faster R-CNN with Toronto Roof Satellite Images was observed. It was shown that the Faster R-CNN provided a higher validation accuracy and higher confidence score than the Fast R-CNN. Additionally, it is suggested that the current Faster R-CNN model needs to be improved, to precisely detect green roofs in different image resolutions and dimensions.</p>

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“…A properly constructed GR system serves two primary functions related to stormwater management; a GR can reduce the amount of stormwater runoff through its water retention capacity, as well as delay the peak flow of runoff, alleviating the pressures on stormwater infrastructures. These characteristics and effects of GR substrate layers and drainage materials have been extensively studied [2,3].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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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Role of drainage layer on green roofs in limiting the runoff of rainwater from urbanized areas

Cited by 7 publications

References 34 publications

Impact of the Hydrogel Amendment and the Dry Period Duration on the Green Roof Retention Capacity

Impact of the Hydrogel Amendment and the Dry Period Duration on the Green Roof Retention Capacity

Detection of Green Roofs through Satellite Imagery Using Faster R-CNN

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

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