Abstract:Low-impact development (LID) structures are combined with traditional measures to manage stormwater and cope with increased runoff rates originating from heavy urbanization and climate change. As the use of LIDs for climate adaptation increases, practitioners need more knowledge on LID performance in future climates for successful planning and implementation. In this study, temporal downscaling of regional climate projections for three cities in Norway is performed, using the concept of scale invariance to dow… Show more
“…Secondly, these DDF curves were multiplied by a climate factor of 1.4 to estimate expected rainfall in the period between 2071 and 2100, including a worst-case scenario with Representative Concentration Pathway (RCP) 8.5 for shortterm events. The use of this factor was also suggested in other studies (Kristvik et al 2018;Kristvik et al 2019).…”
Section: Rainfall Simulator and Future Climate Scenariosmentioning
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.
“…Secondly, these DDF curves were multiplied by a climate factor of 1.4 to estimate expected rainfall in the period between 2071 and 2100, including a worst-case scenario with Representative Concentration Pathway (RCP) 8.5 for shortterm events. The use of this factor was also suggested in other studies (Kristvik et al 2018;Kristvik et al 2019).…”
Section: Rainfall Simulator and Future Climate Scenariosmentioning
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.
“…These disasters cause enormous social and economic losses, and they severely threaten the safety and property of residents [4][5][6]. Frequent and serious urban rainstorms require the extensive adoption of low-impact development (LID) to supplement the traditional drainage infrastructures [7,8]. LID is a storm water management strategy based on distributed management and localized practices for controlling the runoff and pollution caused by storms in order to enhance the capacity for absorption, storage, and purification, and the recovery of the urban resilience system [9].…”
Urban flooding now occurs frequently and low impact development (LID) has been widely implemented as an effective resilience strategy to improve storm water management. This study constructed the inundation curve to dynamically simulate the disaster, and established an inundation severity indicator (ISI) and cost-effectiveness indicator (CEI) to quantify the severity and cost effectiveness at each site. The study set 10 different density scenarios using a zonal approach. The results showed that LID could reduce the overall ISI value, but as the construction increased, the CEI exhibited a downward trend, showing that there is a marginal utility problem in LID. However, the performance of CEI differed slightly in areas of different severity. In the vulnerable resilience zone, the CEI increased initially and then decreased, and the optimal cost–benefit combination was 60% permeable pavement +20% green roof +50% vegetative swale. The mutual effects of LID measures in different zones led to synergistic or antagonistic effects on LID. This study explored the tradeoff between the resilience enhancement effect and strategy transformation cost, and determined the optimal combination of the LID strategy, thereby providing a new analytical perspective for the sustainable development of sponge cities.
“…In order to conclude on the applicability of downscaled time-series to predict the future performance of green infrastructure, the methods were compared to the current recommended practice in Norway: the use of the variational method (Alfieri et al, 2008) with the use of a climate factors (CF) (Kristvik et al, 2019;Trondheim Kommune, 2015). The results presented, for the city of Trondheim and 2, 5 and 10-year return period rainfall and runoff events, include: i) peaks runoff of runoff events based on an observed precipitation time-series, ii) the peak runoff or rainfall events based on variational method with and without climate factor and, iii) an hybrid approach based on downscaling 10 5 rainfall events with a daily depth based on to the return period curves with and without climate factors (Figure 8).…”
Abstract. A strategy to simulate rainfall by the means of different Multiplicative random Cascades (MRC) was developed to evaluate their applicability to produce inputs for green roof infrastructures models taking into account climate change. The MRC reproduce a (multi)fractal distribution of precipitation through an iterative and multiplicative random process. The initial model was improved with a temperature dependency and an additional function to improve its capability to reproduce the temporal structure of rainfall. The structure of the models with depth and temperature dependency was found to be applicable in eight locations studied across Norway (N) and France (F). The resulting time-series from both reference period and projection based on RCP 8.5 were applied to two green roofs (GR) with different properties. The different models lead to a slight change in the performance of GR, but this was not significant compared to the range of outcomes due to ensemble uncertainty in climate modelling and the stochastic uncertainty due to nature of the process. The moderating effect of the green infrastructure was found to decrease in most of the Norwegian cities, especially Bergen (N), while increasing in Lyon (F).
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