Open Access This article is
- freely available
Water 2019, 11(5), 1055; https://doi.org/10.3390/w11051055
Stormwater Retention and Reuse at the Residential Plot Level—Green Roof Experiment and Water Balance Computations for Long-Term Use in Cyprus
Energy, Environment and Water Research Center, The Cyprus Institute, 20 Kostantinou Kavafi, 2121 Nicosia, Cyprus
KANA Hydrocontrol Ltd., P.O. Box 71044, 3840 Limassol, Cyprus
Dipartimento di Scienze della Terra ‘A. Desio’, Università degli Studi di Milano, Via Mangiagalli 34, 20133 Milano, Italy
Agricultural Research Institute, Ministry of Agriculture, Rural Development and Environment, P.O. Box 22016, 1516 Nicosia, Cyprus
Author to whom correspondence should be addressed.
Received: 26 April 2019 / Accepted: 17 May 2019 / Published: 21 May 2019
Green roofs can provide various benefits to urban areas, including stormwater retention. However, semi-arid regions are a challenging environment for green roofs as long dry weather periods are met with short but intense rainfall events. This requires green roofs to retain maximum volumes of stormwater, while being tolerant to minimal irrigation supplies. The objectives of this study are (i) to quantify the stormwater retention of two substrate mixtures with two plant species under natural rainfall; (ii) to assess the performance of two plant species under two levels of deficit irrigation; and (iii) to compute stormwater runoff reduction and reuse by green roofs and rooftop water harvesting systems for three standard residential plot types in urban Nicosia, Cyprus. A rooftop experiment was carried out between February 2016 and April 2017 and results were used to compute long-term performance. Average stormwater retention of the 16 test beds was 77% of the 371-mm rainfall. A survival rate of 88% was recorded for Euphorbia veneris and 20% for Frankenia laevis, for a 30% evapotranspiration irrigation treatment. A combination of a green roof, rainwater harvesting system and 20-m3 tank for irrigation and indoor greywater use reduced stormwater runoff by 47–53%, for the 30-year water balance computations.
Keywords:green roof; stormwater retention; deficit irrigation; water balance; rainwater harvesting; greywater use
Sustainable urban drainage systems are being strongly promoted for managing stormwater in cities, due to their reliance on natural catchment processes that reduce runoff and improve stormwater quality close to its source [1,2,3]. Green roofs are a sustainable urban drainage system that can offer additional benefits, such as energy savings, reduction of the urban heat island effect, improved air quality, increased biodiversity, as well as improved aesthetic value of urban environments [4,5,6].
Weather-related factors such as antecedent substrate moisture, rainfall depth and the intensity and duration of rainfall events affect green roof stormwater retention [1,7,8]. Green roof substrate composition and depth, the plants and roof slope also influence stormwater retention [9,10,11]. Various studies have examined the substrate composition to optimize stormwater management, minimize weight and support adequate plant growth [8,12,13]. However, few studies have investigated stormwater retention performance of different substrate mixtures under natural rainfall.
For arid and semi-arid environments, green roof plants should use high amounts of water post rainfall to reduce soil moisture and thereby runoff of subsequent precipitation events, but also persist and survive extended drought periods . Green roof plants should be selected by comparing the microclimate of the green roof with the climate of the native habitat of potential plant species . The identification of plants that are able to survive and grow under severe stress determines the success of a green roof’s establishment.
Various modelling studies have examined the irrigation of green roofs using stormwater harvesting and greywater reuse systems and investigated required storage volumes [16,17,18,19,20]. However, no studies have modelled the collection of stormwater at the residential plot scale and its reuse for greywater demand and green roof and garden irrigation.
Few studies have investigated green roof water management in semi-arid environments. With an average annual rainfall of 315 mm, a daily maximum of 86 mm and a reference evapotranspiration (ETo) of 1515 mm and daily maximum temperature averaging 37 °C in July (1980–2010), Nicosia, located in the center of Cyprus, is a challenging environment for green roof development. The specific objectives of this research are (i) to quantify the stormwater retention of two substrate mixtures with two plant species under natural rainfall; (ii) to assess the performance of the two plant species under two levels of deficit irrigation during the summer period; and (iii) to compute the reduction and reuse of stormwater runoff from green roofs and rooftop water harvesting systems for three standard residential plot types in urban Nicosia.
2. Materials and Methods
2.1. Green Roof Experimental Setup and Water Balance Monitoring
A green-roof experiment was established on the roof of the three-story Cyprus Institute’s Guy Ourisson Building in Nicosia, Cyprus (latitude 35°08′26″, longitude 33°22′53″, elevation 180 m above sea level). The experimental design simulating a green roof comprised two substrate mixtures and two plant species (four replicates) and two irrigation treatments during the summer months. The experiment was carried out between February 2016 and April 2017.
Sixteen green roof test beds were setup in individual polypropylene plastic boxes (Figure 1). Each box consisted of a 2.5-cm drainage layer comprising gravel of 4 to 10 mm diameter, followed by a filter layer sheet of non-woven geotextile, which had a mass of 200 g/m2, an 0.06-mm aperture opening size (O90,w) and a cut through strength of 2.3 kN. This was overlaid by a substrate layer and plants. The test beds were individually given a 5% slope and each had an outlet at the bottom of the box for drainage, and a second outlet at the top of the substrate layer for surface runoff. Drainage and runoff were measured daily. A weather sensor (WS501; LUFFT, Fellbach, Germany) was installed next to the test beds and measurements were used to compute reference evapotranspiration (ETo) using the methodology of the Food and Agricultural Organization, referred to as (FAO)-56 approach . A tipping bucket rain gauge (16 mm diameter; 0.25 mm resolution; Davis, Hayward, CA, USA) and a manual rain gauge were placed next to the test beds. Thirteen 5TM capacitance soil moisture and temperature sensors (Decagon, Pullman, WA, USA) were installed in the test beds, seven in the Mix1 substrate and six in Mix2.
Two substrate mixtures, referred to as Mix1 and Mix2, were developed from locally-available materials, based on the green roof specifications . The main difference is the inclusion of the light-weight material perlite in Mix2, while keeping the load nearly the same. This allowed a depth of 17.5 cm for Mix2, compared to 15.5 cm for Mix1 (Table 1). The soil included in the substrate mixtures was 70% sand and 30% clay and silt (d < 0.063 mm). The compost components included 65.5% organic matter, 250 ppm Nitrogen-NO3 and 315 ppm Phosphorus (Olsen), all on a dry basis. The substrate characteristics fall in line with other studies [8,12,13].
The plant species examined were Euphorbia veneris (Euphorbiaceae) and Frankenia laevis (Frankeniaceae). Euphorbia veneris (E. veneris) is a perennial with several simple stems up to 35-cm long arising from woody stock and is endemic to Cyprus . Frankenia laevis (F. laevis), is a low prostrate shrub, minutely hairy, perennial with many branches, forming dense mats, with 2–5 mm long linear-lanceolate leaves . Each test bed was planted with either six E. veneris plants or 12 F. laevis plugs.
2.2. Deficit Irrigation and Plant Performance
The test beds were rainfed between February and June 2016. On 1 June 2016, all test beds were irrigated until steady drainage was observed (approximately maximum water capacity), before commencing a deficit irrigation period during the summer period (2 June and 31 October 2016). Following studies carried out in similar environments , two levels of deficit-irrigation were applied, equal to 15% and 30% of ETo, minus any rainfall, and were administered once every week. The low levels of irrigation were applied taking into account that the plants are adapted to the local environment and can survive without rain for long periods. Plant performance was assessed by measuring the number of surviving plants at the beginning and the end of the deficit irrigation period.
2.3. Stormwater Retention and Reuse for Residential Plots in Cyprus
2.3.1. Green Roof Water Balance Computations
A daily green roof water balance model was set up in Microsoft Excel, following the approach by . The water balance equation was:where SM is the soil moisture (mm), P is the precipitation (mm), IR is the irrigation (mm), Q is the drainage and surface runoff (mm), ETa is the actual evapotranspiration (mm), t is the current day and t + 1 the next day. The Q and ETa components were computed as follows:where FC is the soil moisture at field capacity (mm), Ks is the water stress coefficient, Kc the crop coefficient, ETo is the reference evapotranspiration (mm), LL (lower limit) is the substrate’s soil moisture level below which no evaporation occurs (mm) and UL (upper limit) is the soil moisture level below which ETo becomes constrained by available moisture (mm). Because of the shallow depths of the substrate, soil evaporation cannot be separated from plant transpiration. Therefore, no wilting point was established. The Kc parameter combines soil evaporation and plant transpiration and expresses the ratio between ETo and the evapotranspiration of a green roof without soil moisture stress, while Ks describes the effect of water stress on evapotranspiration.
The collected experimental data were used to derive the values of FC, LL, UL and Kc. The parameters were fitted by minimizing the mean absolute error and bias between the observed (average of 13 sensors) and computed daily soil moisture, for the November 2016 to April 2017 period.
2.3.2. Plot-Level Stormwater Retention and Reuse Computations
The stormwater runoff for three types of residential plots was computed considering the inclusion of green roofs, roof-top rainwater harvesting, use of the harvested stormwater for garden and green roof irrigation, as well as for non-potable indoor water (greywater) use. Three typical urban plot types, with a standard Cypriot plot size of 520 m2, are used for the analysis . PlotType1 represents a residential plot with a single house and a large garden (340 m2), PlotType2 represents a semi-detached two-unit family complex with a small garden (140 m2) and PlotType3 represents a small-scale multi-storey residential complex with a 50-m2 garden.
For Cyprus, household water consumption is approximately 150 L/d per person, for an average household of four people. Excluding garden irrigation, average non-potable water demand per household member has been estimated to be 56 L/d, consisting of 28% for toilet flushing, 2% for car washing and 7% for other uses . Two tank sizes are considered for stormwater storage, a 10 or 20-m3 tank, based on the availability of tank sizes in the market.
Daily runoff and greywater use is computed using the daily rainfall and climate data from the Nicosia meteorological station, for the 31-year period 1 January 1980 to 31 December 2010. Daily runoff for roof and paved areas was computed using the Curve Number equation . A curve number of 98 was selected based on the value for impervious areas by the TR-55 manual on urban hydrology for small watersheds . The daily soil water balance model (Equation (1)) was used for computing total stormwater runoff (Q) from the green roof and gardens. Irrigation was applied based on soil moisture levels, preventing the too high levels of plant stress observed in the experiment. For green roofs, irrigation was applied when the stress level reached 30% of the total available water capacity (TAW = UL − LL). For the gardens, irrigation was applied when soil moisture reached 50% of TAW. During the wet winter months (November to February) 10-mm of irrigation was applied, while during the other months 80% of the available soil moisture storage (UL − SM) was filled up, as to leave some storage for rainfall.
Runoff from garden areas was assumed to occur when the soil moisture exceeds the TAW. The TAW for garden soils in Nicosia was assumed to be 100 mm, which represents a medium coarse or fine texture soil with 70-cm depth . Considering the highly variable conditions and management of residential gardens, the above equations and assumptions aim to give a general representation of the hydrology of private gardens.
3. Results and Discussion
3.1. Observed Stormwater Retention under Natural Rainfall
Total rainfall during the 15-month study period was 371 mm and ETo was 1704 mm. Rain and ETo for the 12-month period (May 2016–April 2017) were 316 mm and 1390 mm, respectively. The absolute maximum temperature was 41.7 °C (23 June 2016) and absolute daily minimum −0.4 °C (31 January 2017). The weather data fell in line with the long-term data from the nearby Athalassa station of the Cyprus Meteorological Service, which had an annual ETo ranging between 1405 and 1607 mm, for the 1980–2010 period.
Table 2 presents the combined drainage and surface runoff per treatment and the average retention, for all rainfall events that generated runoff. Total stormwater retention for the 15-month study period ranged between 74% and 79% of the rainfall for the four substrate and plant combinations. A 2-way analysis of variance showed that there were no statistically significant effects of the substrate (p = 0.639) and the plant species (p = 0.864) on stormwater retention. Surface runoff was observed for nine of the nineteen recorded drainage events. For seven of the nine events, surface runoff was less than 6% of the combined drainage and surface runoff of each event. For the other two events (17 December 2016 and 9 February 2017), the combined drainage and surface runoff was low but surface runoff was 0.01 mm (39%) and 0.11 mm (86%), respectively.
No clear patterns could be established between retention and rainfall intensity, rainfall depth or the substrate’s antecedent moisture. However, for all events with high antecedent soil moisture, retention was low. Antecedent soil moisture did influence retention during events with high intensity. In the case of the 36.7-mm rainfall event with a high maximum 15-minute intensity (25.6 mm/h) and high antecedent soil moisture (19%) on 24 December 2017, low retention (32%) was observed. On the contrary, the 63.5-mm event with high maximum 15-minute intensity (34.4 mm/h) but very low antecedent soil moisture (3%) led to high retention (80%) on 14 April 2017. The high rainfall intensity of both events also led to the generation of surface runoff, irrelevant of the antecedent soil moisture.
Figure 2 presents the soil moisture and water balance components between 26 November 2016 and 30 April 2017. The increase in soil moisture at the end of April was due to a 9-mm irrigation application. The average soil moisture observed by the seven sensors in Mix1 and the six sensors in Mix2 reached a maximum of 24% and 27%, respectively, both observed on 24 December 2016 at 23:00, after 113 mm rain during the previous 25 days. The soil moisture of the individual sensors at this time ranged between 13.4% and 43.5%. The absolute maximum soil moisture recorded by the 10-minute readings during the study period for the 13 sensors ranged between 15.3% and 43.6%. The large range could be due to preferential flow paths in the substrate. Soil moisture after drainage (field capacity) during the December and January rainfall events was around 20 to 22%. Total retention for the 16 test beds ranged between 71% and 87% of the 371 mm rainfall for the 15-month period.
There was no clear relation between the observed drainage and the average soil moisture of the test beds during the November 2016 to April 2017 period. In a similar study, a maximum water capacity of 63% was observed on samples from a field-installed green roof substrate, using tension plates, after rainfall exceeded laboratory-derived water storage potential . The relatively low maximum water capacity values observed in the current study can be attributed to the test beds starting to drain before a homogeneous soil moisture level is obtained, due to preferential flow paths. Thus, this indicates that green roofs may not reach the maximum water capacity observed on samples tested in the laboratory, after 24 h submergence, as defined by green roof guidelines . The reduction of substrate water storage capacity has also been suggested to be due to plant roots. For larger events (>25 mm), it has been shown that some plant species (S. glauca) had (36%) lower retention than unplanted modules or low-water using succulent species (S. pachyphyllum), even though these species would have higher ET rates . The root structure of these plants potentially results in a greater number of macropores and sub-surface channels causing uneven and rapid water movement through unsaturated parts of the substrate.
3.2. Deficit Irrigation and Plant Performance
After a five-day heatwave from 19 to 23 June 2016 (daily maximum temperatures between 40 and 42 °C) 74% of the F. laevis plants appeared severely stressed. Therefore, only the 30%-ETo irrigation treatment was applied thereafter to all F. laevis test beds. The survival rate for the 30%-ETo irrigation treatment was 20%. The survival rate for the E. veneris plant species was 88% for the 30%-ETo treatment and 38% for the 15%-ETo treatment. Thus, it is evident that a 15%-ETo irrigation treatment is insufficient for either species. These results fall in line with a similar study , where a 30% survival rate was reported for F. laevis in a rainfed green roof treatment, under 640 mm rain and 925 mm ETo in Barcelona, Spain, while a 100% survival rate was noted for a 20% and 40%-ETo irrigation treatment.
The soil moisture sensors showed that 15%-ETo irrigation did not substantially increase soil moisture, especially for Mix2 and towards the end of the deficit irrigation period. The soil evidently became so dry that water did not reach the sensor at 9-cm depth. This supports the finding that weekly irrigation applications at 15%-ETo may not be sufficient to sustain green roof plants in this environment.
3.3. Stormwater Retention and Reuse for Residential Plots in Cyprus
Considering that the difference in the observed stormwater drainage of the two substrates was not statistically significant and their properties were nearly the same, the experimental results were averaged to determine the parameter values of the green roof water balance model. The fitted soil physical characteristics were 4% (7 mm) for LL, 16% (27 mm) for UL, and 22% (36 mm) for FC, with a Kc value of 1.0. The absolute mean error between the observed and modelled daily soil moisture was 3.2 mm and the bias was 0.02 mm.
Table 3 presents the average annual runoff from the three plot types with and without the inclusion of a green roof and a greywater reuse system for the 30-year computation period. For the cases without greywater use and without tank, a green roof reduces average annual stormwater runoff by 15–17%. These reductions become smaller with the addition of a 10- or 20-m3 tank. For the cases with greywater use, the effect of a green roof on runoff reduction is negligible. This is because the daily greywater use leaves sufficient space in the tank to store the runoff from the roof that would otherwise be captured by the green roof. Average yearly stormwater runoff from paved areas was 5.1, 25.6 and 41 m3/yr for PlotType1, 2 and 3, respectively. For garden areas this was 23.1, 9.5 and 3.4 m3/yr for PlotType1, 2 and 3.
Table 4 shows the water requirements for each case and the savings that can be achieved with a 10 or 20-m3 tank. The requirement for greywater use is equivalent to the number of residents for each plot type and is 81, 164 and 409 m3/yr for PlotType1, 2 and 3, respectively. Green roof irrigation water requirements are slightly less for PlotType1 (104 m3/yr) than for PlotType2 and 3 (159 m3/yr) as the roof area is smaller. Water requirements for garden irrigation decreased from 390 m3/yr for PlotType1 to 161 and 57 m3/yr for PlotType2 and 3, respectively. For PlotType3, savings of up to 48% can be achieved with the installation of a 20-m3 tank for the case without greywater use and without a green roof, as the collected stormwater will be used for the small garden area. However, for all other cases the inclusion of collected stormwater will allow for limited savings in residential plots (2–19%).
The best case for reduction of average annual stormwater runoff, for all plot types, is the inclusion of a 20-m3 tank and greywater use. The inclusion of a green roof did not influence the reduction in stormwater runoff in this case. However, the inclusion of a green roof made a difference in the average annual stormwater runoff when no greywater use was included. It also made a difference for the cases with a 10-m3 tank and greywater use, reducing runoff from 28.2 to 25.7 m3/day for PlotType1, 27.4 to 24.8 m3/day for PlotType2 and 30 to 27.6 m3/day for PlotType3.
For a 1963-m2 building in Athens, Greece, a combination of a green roof, rain water harvesting (200-m3 tank) and greywater use was found to be the most preferable flood reduction option (average annual runoff 369 m3/yr), compared to combinations of a green roof with greywater use (600 m3/yr) and rainwater harvesting with greywater use (874 m3/yr) . In the current Nicosia study for the inclusion of a green roof only the case without a water-harvesting tank or without greywater use provides a significant difference (15–17%) in the retention of annual rain.
The use of a daily time step in calculations for the performance of rainwater tanks has been found to underestimate roof runoff yields compared to a 6-min time step . Moreover, the water quality of the collected runoff may reduce the volume that can be used for indoor greywater use. Thus, further research can optimize the availability of collected runoff for greywater use and irrigation.
- A 15.5-cm deep green roof substrate made up of pumice, zeolite, soil and compost and a 17.5-cm deep substrate, which contained lightweight perlite aggregates in addition to the above, achieved an average retention of 77% of the 371 mm rainfall for a 15-month study period in Nicosia, Cyprus.
- A 30%-ETo irrigation treatment during the dry June to October summer months gave an 88% survival rate for the stalky, endemic succulent E. veneris and a 20% survival rate for the groundcover species F. laevis. Thus, a higher irrigation rate should be tested, while the combination of the two species could improve the water use efficiency and greenness of the roof.
- The substrate type and plant species had no statistically significant effect on stormwater retention. The observed variabilities in soil moisture and drainage showed that the substrates start draining before they reach a homogeneous field capacity soil moisture level, indicating the importance of in situ testing of green roof performance.
- The water balance computations showed that the combination of a green roof with a rainwater harvesting system, a 20-m3 tank, and use of the collected water for outdoor irrigation and indoor greywater use reduced long-term average annual stormwater runoff up to 47–53%, for three types of standard 520-m2 residential plots in Nicosia. For the cases where collected runoff was used for indoor greywater demand, the inclusion of a green roof did not affect the reduction of stormwater runoff. The use of a 20-m3 tank for storage of stormwater runoff, for green roof, garden irrigation and indoor greywater use, provides an average annual water saving of 3–5% for urban plots in Nicosia.
- Green roofs can reduce stormwater runoff but are not as effective as rainwater harvesting systems with large storage tanks. However, the environmental benefits of green roofs, aside from stormwater management, support the importance of implementing them. Further research could examine the environmental trade-offs between green roofs with various irrigation levels and plant species and the heating and cooling requirements of buildings.
K.C. and A.B. conceptualized the research and designed the methodology; L.V. advised on the selection of plants to be tested; M.E. and C.C. helped with the experimental setup and installed the weather station and sensors; K.C. carried out the experiment and processed the results; K.C. and A.B. developed the water balance model and computed green roof long-term performance; K.C. prepared the manuscript, while the review and editing were carried out by A.B., C.C. and M.E.
This study has received funding from the European Union Seventh Framework Programme (GA 612385) BEWATER project.
The authors would like to thank Agapios Agapiou, Christos Zoumides, Elias Giannakis, Hakan Djuma and Despina Papacharalambous of the Cyprus Institute, as well as Loizos Kyritsopoulos and Roberto Schiffo, for their help with the design and setup of the test beds.
Conflicts of Interest
The authors declare no conflict of interest.
- Wong, T.H.F.; Brown, R.R. The water sensitive city: Principles for practice. Water Sci. Technol. 2009, 60, 673–682. [Google Scholar] [PubMed]
- Stovin, V. The potential of green roofs to manage urban stormwater. Water Environ. J. 2010, 24, 192–199. [Google Scholar]
- Zhou, Q. A review of sustainable urban drainage systems considering the climate change and urbanization impacts. Water 2014, 6, 976–992. [Google Scholar] [CrossRef]
- Sfakianakis, A.; Pagalou, E.; Pavlou, K.; Santamouris, M.; Assimakopoulos, M.N. Theoretical and experimental analysis of the thermal behaviour of a green roof system installed in two residential buildings in Athens, Greece. Int. J. Energy Res. 2009, 33, 1059–1069. [Google Scholar] [CrossRef]
- Rowe, B.D.; Kolp, M.R.; Greer, S.E.; Getter, K.L. Comparison of irrigation frequency efficiency and plant health of overhead, drip, and sub-irrigation for extensive green roofs. Ecol. Eng. 2014, 64, 306–313. [Google Scholar]
- Cirkel, D.G.; Voortman, B.R.; van Veen, T.; Bartholomeus, R.P. Evaporation from (blue-) green roofs: Assessing the benefits of a storage and capillary irrigation system based on measurements and modeling. Water 2018, 10, 1253. [Google Scholar] [CrossRef]
- Berndtsson, J.C. Green roof performance towards management of runoff water quantity and quality: A review. Ecol. Eng. 2010, 36, 351–360. [Google Scholar] [CrossRef]
- Fassman, E.; Simcock, R. Moisture measurements as performance criteria for extensive living roof substrates. J. Environ. Eng. U.S. 2012, 138, 841–851. [Google Scholar] [CrossRef]
- Graceson, A.; Hare, M.; Monaghan, J.; Hall, N. The water retention capabilities of growing media for green roofs. Ecol. Eng. 2013, 61, 328–334. [Google Scholar] [CrossRef]
- Peczkowski, G.; Kowalczyk, T.; Szawernoga, K.; Orzepowski, W.; Zmuda, R.; Pokladek, R. Hydrological performance and runoff water quality of experimental green roofs. Water 2018, 10, 1185. [Google Scholar] [CrossRef]
- Liu, W.; Feng, Q.; Chen, W.; Wei, W.; Deo, R.C. The influence of structural factors on stormwater runoff retention of extensive green roofs: new evidence from scale-based models and real experiments. J. Hydrol. 2019, 569, 230–238. [Google Scholar] [CrossRef]
- Papafotiou, M.; Pergialioti, N.; Tassoula, L.; Massas, I.; Kargas, G. Growth of native aromatic xerophytes in an extensive Mediterranean green roof as affected by substrate type and depth and irrigation frequency. HortScience 2013, 48, 1327–1333. [Google Scholar] [CrossRef]
- Nektarios, P.A.; Ntoulas, N.; Nydrioti, E.; Kokkinou, I.; Bali, E.-A.; Amountzias, I. Drought stress response of Sedum sediforme grown in extensive green roof systems with different substrate types and depths. Sci. Hortic. 2015, 151, 52–61. [Google Scholar] [CrossRef]
- Razzaghmanesh, M.; Beecham, S.; Brien, C.J. Developing resilient green roofs in a dry climate. Sci. Total Environ. 2014, 490, 579–589. [Google Scholar] [CrossRef]
- Farrell, C.; Szota, C.; Williams, N.S.G.; Arndt, S.K. High water users can be drought tolerant: Using physiological traits for green roof plant selection. Plant Soil 2013, 372, 177–193. [Google Scholar] [CrossRef]
- Hardin, M.; Wanielista, M.; Chopra, M. A mass balance model for designing green roof systems that incorporate a cistern for re-use. Water 2012, 4, 914–931. [Google Scholar] [CrossRef]
- Rozos, E.; Makropoulos, C.; Maksimović, Č. Rethinking urban areas: an example of an integrated blue-green approach. Water Sci. Technol. Water Supply 2013, 13, 1534–1542. [Google Scholar] [CrossRef]
- Chao-Hsien, L.; En-Hao, H.; Yie-Ru, C. Designing a rainwater harvesting system for urban green roof irrigation. Water Sci. Technol. Water Supply 2015, 15, 271–277. [Google Scholar] [CrossRef]
- Stratigea, D.; Makropoulos, C. Balancing water demand reduction and rainfall runoff minimization: modelling green roofs, rainwater harvesting and greywater reuse systems. Water Sci. Technol. Water Supply 2015, 15, 248–255. [Google Scholar] [CrossRef]
- Pradhan, S.; Al-Ghamdi, S.G.; Mackey, H.R. Greywater recycling in buildings using living walls and green roofs: A review of the applicability and challenges. Sci. Total Environ. 2019, 652, 330–344. [Google Scholar] [CrossRef]
- Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements; Irrigation and Drainage Paper 56; FAO: Rome, Italy, 1998. [Google Scholar]
- Forschungsgesellschaft Landschaftsentwicklung Landschaftsbau (FLL). Guidelines for the Planning, Execution and Upkeep of Green-Roof Sites; Forschungsgesellschaft Landschaftsentwicklung Landschaftsbau: Bonn, Germany, 2002. [Google Scholar]
- Meikle, R.D. Flora of Cyprus; The Bentham-Moxon Trust: Kew, UK, 1985; Volume 2. [Google Scholar]
- Blamey, M.; Grey-Wilson, C. Wild Flowers of the Mediterranean; A & Black Publishers: London, UK, 2004; p. 147. [Google Scholar]
- Ioannou, B. Town planning, development patterns and the reduction of private gardens in the suburbia of Cyprus. In Growing in Cities–Interdisciplinary Perspectives on Urban Gardening, Proceedings of the COST-Action 1201 Urban Allotment Gardens in European Cities Conference, Basel, Austria, 8–10 September 2016; University of Applied Sciences and Arts Northwestern Switzerland & ILS Research Institute for Regional and Urban Development: Basel, Austria, 2016; pp. 167–179. [Google Scholar]
- Water Development Department (WDD), Water Use and Saving in Cyprus. Available online: http://www.moa.gov.cy/moa/WDD/wdd.nsf/All/A8C797C0428AC8FFC22582030037F34A/$file/10_Page1_17.pdf?OpenElement (accessed on 6 December 2018).
- United States Department of Agriculture (USDA). Urban Hydrology for Small Watersheds, 2nd ed.; Government Printing Office: Washington, DC, USA, 1986.
- Camera, C.; Zomeni, Z.; Noller, J.S.; Zissimos, A.M.; Christoforou, I.C.; Bruggeman, A. A high resolution map of soil types and physical properties for Cyprus: A digital soil mapping optimization. Geoderma 2017, 285, 35–49. [Google Scholar] [CrossRef]
- Zhang, Z.; Szota, C.; Flether, T.D.; Williams, N.S.G.; Farrell, C. Green roof storage capacity can be more important than evapotranspiration for retention performance. J. Environ. Manag. 2019, 232, 404–412. [Google Scholar] [CrossRef] [PubMed]
- Vestrella, A.; Savé, R.; Biel, C. An experimental study in simulated green roof in Mediterranean Climate. J. Agric. Sci. 2015, 7. [Google Scholar] [CrossRef]
- Coombes, P.J.; Barry, M.E. The effect of selection of time steps and average assumptions on the continuous simulation of rainwater harvesting strategies. Water Sci. Technol. 2007, 55, 125–133. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Setup of a green roof test bed (top), layout of the 16 green roof test beds (bottom).
Figure 2. Water balance components and soil moisture (SM) for four green roof treatments, consisting of two substrate mixtures (Mix1, Mix2) and two plant species (EU = E. veneris, FR = F. Laevis) from 26 November 2016 to April 2017.
Table 1. Substrate component fractions by volume (v/v) for Mix1 and Mix2, depth of substrate, load, dry and saturated (Sat.) bulk density.
|Substrate Mix||Substrate Components (v/v)||Depth||Load||Dry Bulk Density||Sat. Bulk Density|
|Perlite||Pu1 a||Pu2 b||Zeo c||Soil||Com d||cm||kg/m2||g/cm3||g/cm3|
a Pumice1, with particle size range 5–8 mm; b Pumice2, with particle size range 0–8 mm, c Zeolite, with particle size range 0.8–2.5 mm; d Compost.
Table 2. Rain; maximum 15-minute rainfall intensity (Max int.); combined drainage and surface runoff (average of four replicates) for four green roof treatments, consisting of two substrate mixtures (Mix1, Mix2) and two plant species (EU = E. veneris, FR = F. Laevis); and average retention (Ret.) of the 16 test beds, for all rainfall events with drainage between 1 February 2016 and 30 April 2017 (total rain 371 mm).
|Date||Rain||Max int.||Combined Drainage and Surface Runoff||Ret.|
|30/11, 1–2/12/16 a||41.3||7.4||6.7||14.6||3.6||6.4||81|
|10–12/03/2017||20||11.6||0.51 b||0.6||N/A||0.72 c||98|
a surface runoff observed, b average of 3 replicates, c average of 2 replicates.
Table 3. Average stormwater runoff from the three residential plot types with and without green roof, indoor greywater (GW) use and storage tank for 1980–2010; Dif. is the percentage difference between the case with and without green roof.
No Green Roof
No GW Use
No GW Use
No Green Roof
|10 m3 tank||35.6||33.5||6.1||29.2||29.2||0.1|
|20 m3 tank||30.2||29.7||1.8||28.2||28.2||0.0|
|10 m3 tank||53.3||47.2||11.4||38.5||38.4||0.2|
|20 m3 tank||44.2||40.7||7.8||35.2||35.3||−0.2|
|10 m3 tank||65.5||56.7||13.4||46.3||46.0||0.7|
|20 m3 tank||56.2||50.1||10.9||44.4||44.4||0.0|
a 150 m2 roof, 30 m2 paved area, 340 m2 garden, 4 residents; b 230 m2 roof, 150 m2 paved area, 140 m2 garden, 8 residents; c 230 m2 roof, 240 m2 paved area, 50 m2 garden, 20 residents.
Table 4. Average annual water requirements for irrigation and greywater (GW) use and savings that can be achieved with the installation of a 10 and 20-m3 tank, for 1980–2010.
|Water Requirements and Savings||No Green Roof|
No GW Use
No GW Use
|No Green Roof|
|Savings—10 m3 tank||18.1||11.9||24.6||16.3|
|Savings—20 m3 tank||23.5||15.7||25.6||17.2|
|Savings—10 m3 tank||21.0||14.2||35.9||23.1|
|Savings—20 m3 tank||30.1||20.7||39.1||26.2|
|Savings—10 m3 tank||18.0||14.0||37.3||24.7|
|Savings—20 m3 tank||27.3||20.6||39.3||26.4|
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).