The influence of substrate and vegetation configuration on green roof hydrological performance

A four-year record of rainfall and runoff data from nine different extensive (80 mm substrate) green roof test beds has been analysed to establish the extent to which the substrate composition and vegetation treatment affect hydrological performance. The test beds incorporated three different substrate components with different porosity and moisture retention characteristics, and three different vegetation treatments (Sedum, Meadow Flower and unvegetated). Consistent differences were observed, with the vegetated beds showing higher levels of rainfall retention and better detention compared with unvegetated beds. The seasonal Meadow Flower beds had similar hydrological performance to Sedum-vegetated beds. There was a 27% performance reduction in annual volumetric retention attributable to differences in substrate and vegetation. The beds with the most porous/permeable substrates showed the lowest levels of both retention and detention. As with previous studies, retention efficiency in all nine beds showed a strong dependency on rainfall depth (P), with retention typically >80% for events where P < 10 mm, but significantly lower when P > 10 mm. The effects of vegetation and substrate were most evident for rainfall events where P > 10 mm, with the mean per-event retention varying between beds from 26.8% to 61.8%. On average, the test beds were able to retain the first 5 mm of rainfall in 65% of events where P > 5 mm, although this ranged from 29.4% to 70.6% of events depending on configuration. In terms of detention, all but one of the test beds could achieve runoff control to a green field runoff equivalent of 2 l/s/ha for more than 75% of events. Detention was also characterised via the calibration of a reservoir-routing modelthatlinked net rainfall to the measured runoff response. The parameter values identified here – when combined with a suitable evapotranspiration/retention model – provide a generic mechanism for predicting the runoff response to a time-series or design rainfall for any unmonitored system with comparable components, permitting comparison against local regulatory requirements

Parameters influencing the regeneration of a green roof’s retention capacity via evapotranspiration

The extent to which the finite hydrological capacity of a green roof is available for retention of a storm event largely determines the scale of its contribution as a Sustainable Drainage System (SuDS). Evapotranspiration (ET) regenerates the retention capacity at a rate that is variably influenced by climate, vegetation treatment, soil and residual moisture content. Experimental studies have been undertaken to monitor the drying cycle behaviour of 9 different extensive green roof configurations with 80 mm substrate depth. A climate-controlled chamber at the University of Sheffield replicated typical UK spring and summer diurnal cycles. The mass of each microcosm, initially at field capacity, was continuously recorded, with changes inferred to be moisture loss/gain (or ET/dew). The ranges of cumulative ET following a 28 day dry weather period (ADWP) were 0.6–1.0 mm/day in spring and 0.7–1.25 mm/day in summer. These ranges reflect the influence of configuration on ET. Cumulative ET was highest from substrates with the greatest storage capacity. Significant differences in ET existed between vegetated and non-vegetated configurations. Initially, seasonal mean ET was affected by climate. Losses were 2.0 mm/day in spring and 3.4 mm/day in summer. However, moisture availability constrained ET, which fell to 1.4 mm/day then 1.0 mm/day (with an ADWP of 7 and 14 days) in spring; compared to 1.0 mm/day and 0.5 mm/day in summer. A modelling approach, which factors Potential Evapotranspiration (PET) according to stored moisture content, predicts daily ET with very good accuracy (PBIAS = 2.0% [spring]; −0.8% [summer])

Moisture content behaviour in extensive green roofs during dry periods: the influence of vegetation and substrate characteristics

Evapotranspiration (ET) is a key parameter that influences the stormwater retention capacity, and thus the hydrological performance, of green roofs. This paper investigates how the moisture content in extensive green roofs varies during dry periods due to evapotranspiration. The study is supported by 29 months continuous field monitoring of the moisture content within four green roof test beds. The beds incorporated three different substrates, with three being vegetated with sedum and one left unvegetated. Water content reflectometers were located at three different soil depths to measure the soil moisture profile and to record temporal changes in moisture content at a five-minute resolution. The moisture content vertical profiles varied consistently, with slightly elevated moisture content levels being recorded at the deepest substrate layer in the vegetated systems. Daily moisture loss rates were influenced by both temperature and moisture content, with reduced moisture loss/evapotranspiration when the soil moisture was restricted. The presence of vegetation resulted in higher daily moisture loss. Finally, it is demonstrated that the observed moisture content data can be accurately simulated using a hydrologic model based on water balance and two conventional Potential ET models (Hargreaves and FAO56 Penman–Monteith) combined with a soil moisture extraction function. Configuration-specific correction factors have been proposed to account for differences between green roof systems and standard reference crops

The champion of urban water resources management in the Chinese city — the case of Ningbo

Ningbo is a coastal megacity located at the East Coast of China and developing rapidly with proactive trading and export economic activities. The city owns a ranked top ten international port and it is the major strategic spot of 21st century maritime Silk Road from the “Belt and Road” policy established for promoting further international trades and developments. In future, populations and economy in Ningbo are expected continuously growing in the next few decades. The demand of quality freshwater resources thus is enormously increasing. Ningbo municipal government has established the “Five water management” (五水共治) policy in 2013 that aims to manage (i) sewage discharge; (ii) flooding; (iii) surface water; (iv) water conservation and (v) freshwater supply. Indeed, the municipal government also liaised and initiated the “Sponge City Program” after 2015 that Ningbo was selected as one of the pilot city; these policies and practices are successful up to now. This article adopts the case study of Ningbo to investigate the reasons of municipal government to promote the policy, to understand the public perception of this water management policy in Ningbo through conducted semi-structured interviews. During the 2017 and 2019, we conducted a questionnaire (N = 110) and interviews (N = 10) that follow up for justification of the public perception with the local communities. Our findings indicated that the communities had not been engaged closely with these practices, but generally supporting these two urban water management practices; and agreed that the urban water conditions (urban floods and pollution) had been improved. Also, the article discusses whether these (5 Water and SCP) practices can be extensively applied in other Chinese cities. We will provide recommendations at the end of the article

Defining green roof detention performance

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

A modelling study of long term green roof retention performance

This paper outlines the development of a conceptual hydrological flux model for the long term continuous simulation of runoff and drought risk for green roof systems. A green roof's retention capacity depends upon its physical configuration, but it is also strongly influenced by local climatic controls, including the rainfall characteristics and the restoration of retention capacity associated with evapotranspiration during dry weather periods. The model includes a function that links evapotranspiration rates to substrate moisture content, and is validated against observed runoff data. The model's application to typical extensive green roof configurations is demonstrated with reference to four UK locations characterised by contrasting climatic regimes, using 30-year rainfall time-series inputs at hourly simulation time steps. It is shown that retention performance is dependent upon local climatic conditions. Volumetric retention ranges from 0.19 (cool, wet climate) to 0.59 (warm, dry climate). Per event retention is also considered, and it is demonstrated that retention performance decreases significantly when high return period events are considered in isolation. For example, in Sheffield the median per-event retention is 1.00 (many small events), but the median retention for events exceeding a 1 in 1 yr return period threshold is only 0.10. The simulation tool also provides useful information about the likelihood of drought periods, for which irrigation may be required. A sensitivity study suggests that green roofs with reduced moisture-holding capacity and/or low evapotranspiration rates will tend to offer reduced levels of retention, whilst high moisture-holding capacity and low evapotranspiration rates offer the strongest drought resistance