Although it is widely accepted that the detention performance of green roofs is of interest to stormwater engineers and planners, no single metric allows detention to be unambiguously defined. Detention effects are highly sensitive to rainfall characteristics and antecedent conditions, and individual roofs typically exhibit wide variations in detention performance between storm events. This paper uses a straightforward hydrological model to explore two alternative approaches to describing detention performance: a probabilistic approach based on long time-series simulations; and a design storm approach. It is argued that the non-linear reservoir routing parameters (scale, k and exponent, n) provide fundamental descriptors of the detention process, with modelling enabling performance to be determined for specific rainfall inputs. The study utilises 30-year rainfall time-series predictions for four contrasting UK locations to demonstrate the utility of the two proposed design approaches and to comment on locational variations in detention performance.
Green roofs may make an important contribution to urban stormwater management. Rainfall-runoff models are required to evaluate green roof responses configuration, with the substrate or growing media providing both retention and detention of rainfall. The objective of the research described here is to quantify the detention effects due to green roof substrates, and to propose a suitable hydrological modelling approach.Laboratory results from experimental detention tests on green roof substrates are presented. It is shown that detention increases with substrate depth and as a result of increasing substrate organic content. Model structures based on reservoir routing are evaluated, and it is found that a one-parameter reservoir routing model coupled with a parameter that describes the delay to start of runoff best fits the observed data. Preliminary findings support the hypothesis that the reservoir routing
Green roofs have been adopted in urban drainage systems to control the total quantity and volumetric ow rate of runo . Modern green roof designs are multi-layered, their main components being vegetation, substrate and, in almost all cases, a separate drainage layer. Most current hydrological models of green roofs combine the modelling of the separate layers into a single process; these models have limited predictive capability for roofs not sharing the same design. An adaptable, generic, two-stage model for a system consisting of a granular substrate over a hard plastic "egg box"-style drainage layer and brous protection mat is presented. The substrate and drainage layer/protection mat are modelled separately by previously veri ed sub-models. Controlled storm events are applied to a green roof system in a rainfall simulator. The time-series modelled runo is compared to the monitored runo for each storm event. The modelled runo pro les are accurate (mean R t 2 = 0.971), but further characterization of the substrate component is required for the model to be generically applicable to other roof con gurations with di erent substrate.
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