Performance of Green roof in stormwater management regarding high-resolution precipitation fields

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Performance of Green roof in stormwater management regarding high-resolution precipitation fields Pierre-Antoine Versini, Auguste Gires, Ioulia Tchiguirinskaia, D Schertzer To cite this version: Pierre-Antoine Versini, Auguste Gires, Ioulia Tchiguirinskaia, D Schertzer. Performance of Green roof in stormwater management regarding high-resolution precipitation fields. Urban Drainage Modelling 2015, Sep 2015, Mont-Saint-Anne, Canada. <hal-01239199> HAL Id: hal-01239199 https://hal.archives-ouvertes.fr/hal-01239199 Submitted on 7 Dec 2015 HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Versini et al. Performance of Green roof in stormwater management regarding highresolution precipitation fields Pierre-Antoine Versini 1, Auguste Gires 1, Ioulia Tchinguirinskaia 1 and Daniel Schertzer 1 1 LEESU, Ecole des Ponts Paristech, 6-8 avenue Blaise Pascal, 77455 Champs-sur-Marne, France (Email: pierreantoine.versini@leesu.enpc.fr, auguste.gires@leesu.enpc.fr, ioulia.tchinguirinskaia@leesu.enpc.fr, daniel.schertzer@leesu.enpc.fr) Abstract At the basin scale, green roofs can represent an efficient tool to manage stormwater in urbanized areas. Widely implemented and/or completed with additional sustainable urban drainage systems, they show a positive impact on urban runoff: decrease and slow-down of the peak discharge and decrease of runoff volume. To assess green roof performances at this scale, a specific module dedicated to simulate their hydrological behaviour has been developed in the Multi-Hydro rainfallrunoff model. Its distributed structure gives the opportunity to test the susceptibility of green roof response regarding spatial distributions of precipitation. Based on radar rainfall fields, an ensemble of 50 realistic downscaled rainfall fields with a resolution of 10 m in space has been generated by using multifractals downscaling technique. Simulations have been conducted on a small urban catchment close to Paris (France) where most of the buildings roofs are assumed to easily accept the implementation of green roof. Although green roof confirm their ability to reduce urban runoff, these results illustrate that peak discharge reduction seems to be clearly dependant of spatial distribution of precipitation. Implementation of green roof can also produce concomitance situations and higher peak discharges than those produced by impervious roofs. Keywords Green roof; precipitation; modelling INTRODUCTION Green roofs have become relatively commonplace over the last 20 years in urban areas for many reasons. Indeed, they can perform in: reduction of heat island through increasing evapotranspiration, improvement of the air quality, protection of biodiversity and stormwater management. Their use in urban runoff management is surely the most significant argument used to promote their implementation. At the building scale, the main performance of green roofs in quantitative management of storm water is known to be: (i) the reduction of runoff volume at the annual scale, and (ii) the peak attenuation and delay at the rainfall event depending on the green roof structure, the rainfall intensity and the antecedent soil moisture conditions (Simmons et al., 2008, Stovin et al., 2012, Versini et al., 2015). As roof areas represent a significant part of the surfaces of city centres where no space is available for new infrastructures, green roof can also appear as a useful tool to solve operational issue at the basin scale by reducing the runoff volume and/or attenuating peak discharge. Most of the work conducted for now on the hydrological impact of green roof were focused at the building scale: Voyde et al., 2010; Gregoire and Clausen, 2011; Stovin et al., 2012. These works usually present the results provided by an experimental monitored green roof, used to collect continuous runoff and precipitation data and also often to develop some specific (global) models (Šimůnek et al., 2008; 1

Session xxx UDM2015 Palla et al., 2009). To our knowledge, very few studies (Carter and Jackson, 2007; Palla, 2008; Versini et al., 2015b) have been conducted at the basin scale and even less by using a distributed rainfall-runoff model able to take into account the spatial distribution of green roof and precipitation. It is the originality of this paper, which is focussed on the hydrological impact of green roof at the basin scale regarding precipitation fields characterized by high spatio-temporal resolution. METHODOLGY AND CASE STUDY To assess green roof impact at the basin scale regarding distributed precipitation, the Multi-Hydro (El Tabach, 2009; Giangola-Murzyn et al., 2012; Gires et al., 2014) distributed rainfall-runoff model has been used. It is a numerical platform that makes interact several models representing a specific portion of the water cycle in an urban environment: surface runoff and infiltration depending on a land use classification, sub-surface processes and sewer network drainage. A specific module dedicated to simulate green roof behaviour has been added in Multi-Hydro (inspired from that presented in Versini et al., 2015a, and detailed in Versini et al., 2015c). It has been calibrated to simulate the hydrological behaviour of a green roof structure comprising an extensive vegetation layer (sedum), a growing medium layer (thickness of 3 cm) and a drainage layer. Distributed structure of the Multi-Hydro model enables to analyse the impact of the spatial variability of precipitation and land use, and especially the precise location of green roof. Multi-Hydro has been applied on the Loup basin (0.5 km 2 ) in a highly populated and urbanized city (Villepinte, France) located close to Paris. 20% of the basin area is occupied by buildings dedicated to industrial activities. It has been assumed that green roof can be implemented on these roofs which are all flat. Note that Multi-Hydro was previously applied on the Loup basin with satisfactory results in Gires et al. (2013). Figure 1. Loup basin: land use spatial distribution with pixel of size 10 m x 10 m, and sewer network inputted on Multi-Hydro In order to test the impact of spatial variability of precipitation, an ensemble of 50 realistic downscaled rainfall fields with a resolution of 10 m in space was generated from Radar data (1 km- 2

Versini et al. resolution). The downscaling process relies on the framework of Universal Multifractals (Schertzer and Lovejoy, 1987). It is assumed that rainfall is generated through a space-time multiplicative cascade process characterized by two parameters (the mean intermittency and the multifractality index). More details on the downscaling process can be found in Gires et al. (2012). The process was applied on two complex events on the studied basin for which radar data was available: (i) a common event (9 February 2009) characterized by a total rainfall depth of 8.3 mm and a duration of approximately 6 h (return period estimated to 1 month), (ii) a severe event (15 August 2010) characterized by a total rainfall depth of 25 mm and a duration of 6h (return period estimated to 2 years). RESULTS AND DISCUSSION Multi-Hydro simulations have been carried out for both rainfall events. The results obtained with green roof implementation have been compared to those obtained for the current situation (without any green roof implemented). Related hydrographs are illustrated in Figure 2. Green roof performances on peak discharge and volume runoff have particularly been studied. First of all, it has to be noticed that current basin response can significantly be modified depending on the spatial variability of rainfall distribution. Peak discharge for the impervious scenario varies between 0.10 and 0.15 m 3 /s for the first event and between 0.5 and 0.9 m 3 /s for the second one. When green roofs are implemented, this variation is still significant: between 0.06 and 0.11 m 3 /s, and between 0.5 and 1.4 m 3 /s for both events respectively. Green roofs appear to impact urban runoff in terms of peak discharge and volume depending on precipitation total amount and intensity- and initial substrate saturation: the higher the precipitation, the more saturated the substrate, and the lower the reduction in terms of stormwater. Results are less pronounced than those usually observed at the building scale because they depend on the green roof area, representing here only 20% of the basin area. At the roof scale, this low event would be completely retained by the substrate (in dry conditions). The reduction of volume runoff can reach more than 36% as it can be noticed for the more common event. This reduction is only about 12% for the 2-year return period event characterized by a higher amount of precipitation. Note that the variation of volume regarding the 50 downscaled scenarios is not significant (standard deviation of 1%) as the amount of precipitation falling on the basin is usually always the same for the 50 members of the ensemble. Peak discharge can also be significantly affected by green roof implementation depending on the rainfall event. Regarding the common event, average peak discharge decrease is about 35% and ranges between 10% and 56% depending on the downscaled scenario, illustrating the influence of spatial variability of precipitation. These satisfactory results are most of all concentrated on the first rainfall peak. Here, basin response to the main rainfall intensity is clearly attenuated but likewise dispersed. Conversely, the response to the second rainfall peak is systematically increased by green roofs (from 0 to 33% with an average value of 10%). The range of simulated values is also more dispersed, increasing the sensitivity of the basin regarding precipitation. First peak decreases and second peak increases are quite correlated, meaning attenuation of the first one seems to cause gain 3

Session xxx UDM2015 of the second one. In this case, the substrate stores precipitation during the first part of the event, before releasing it simultaneously with the second rainfall peak. Figure 2. Simulation results obtained by using the 50 downscaled rainfall fields for the 09/02/2009 (top) event and the 15/08/2010 (bottom): current situation (without any green roof) is depicted in black and green roofing scenario in blue. The same kind of situation is noticed and even more pronounced for the 2010 event. Although green roof can reduce the first peak discharge for most of the downscaled scenarios (between -9% to 65% with an average value of 32%), the response to the second large rainfall peak is systematically increased (average increase of 60%). In a general way, green roof response to 4

Versini et al. successive rainfall peaks can alternatively increase or decrease peak discharge at the basin outlet depending on the spatio-temporal distribution of precipitation. These examples represent concomitance situations. For some events characterized by several rainfall peaks, the fast response of the saturated substrate generated by the second peak of the rainfall coincides with the slow response of the green roof produced by the initial portion of the rainfall event. These situations are related to both the spatio-temporal distribution of precipitation and the specific configuration of the studied basin (especially on the basin geometry and land cover, and the sewage network arrangement). The superposition in space and time of responses from impervious and a green roofed areas to a complex rainfall event (composed by several rainfall peaks for example) can generate a peak discharge higher than that produced by the current (impervious) situation. CONCLUSION The Multi-Hydro distributed rainfall-runoff model has been used to assess green roof performances in stormwater management regarding high-resolution precipitation fields. Regarding the presented examples and additional works, green roof implementation appears to reduce urban runoff in terms of peak discharge and volume depending on rainfall event characteristics (in terms on intensity and duration) and the initial state of the substrate saturation. The wide implementation of green roof should be useful to avoid some flooding (or sewer combined overflows) issues in several cases depending on the initial conditions. They will particularly perform to mitigate the effects of common rainfall events and/or very short (but sometimes intense) rainfalls that are expected to be more often in Paris area under climate change. Nevertheless an important point has to be carefully considered: concomitance situations that can occur for a particular basin configuration and/or a rainfall event. As illustrated with the Loup basin, depending on the considered downscaled rainfall scenario, the combination of basin configuration and precipitation can produce higher peak discharge than that produced in the current situation (impervious roofs). Finally, spatial variability of rainfall fields seem to influence the basin response as peak reduction can increase/decrease of about +/- 25% regarding the average response. This demonstrates the interest to use high-resolution precipitation data (as those provided by X-band radar for instance) in stormwater management. ACKNOWLEDGEMENT This work is part of the Climate-KIC funded Blue Green Dream project (http://bgd.org.uk/) that aims to move forward a new paradigm for efficient planning and management of new urban developments and retrofitting of existing ones. For this purpose, it promotes the implementation of blue and green infrastructures to maximize ecosystem services and increase resilience to climate change. Authors would like to thank Jean-Baptiste Abbes who initially implemented the Multi- Hydro on the Loup catchment. REFERENCES Carter, T. and Jackson C. R. (2007). Vegetated roofs for stormwater management at multiple spatial scales. Landscape 5

Session xxx UDM2015 and urban planning, 80, 84-94. El Tabach, E., Tchiguirinskaia, I., Mahmood, O., and Schertzer, D., (2009). Multi-Hydro: a spatially distributed numerical model to assess and manage runoff processes in peri-urban watersheds. In: E. Pasche, N. Evelpidou, C. Zevenbergen, R. Ashley and S. Garvin, eds. Final Conference of the COST Action C22, Road map towards flood resilient Urban Environment, Paris, France. Hamburger Wasserbau-Schriften. Giangola-Murzyn A., Gires A., Hoang C.T., Tchiguirinskaia I. and Schertzer D. (2012). Multi-Hydro: physically based modelling to assess flood resilience across scales, case studies in Paris region. Proceedings of 10th Urban Dranaige conference, Belgrade 3-7 Sept. 2012, Serbia. Gires, A., Tchiguirinskaia, I., Schertzer, D., and Lovejoy, S. (2012). Multifractal analysis of an urban hydrological model on a Seine-Saint-Denis study case. Urban Water Journal, 10 (3), 195 208. Gires A., Giangola-Murzyn A., Abbes J.B., Tchinguirinskaia I., Schertzer D., Lovejoy.S. (2013). Impacts of small scale rainfall variability in urban areas: a case study with 1D and 1D/2D hydrological models in a multifractal framework. Urban water journal, DOI:10.1080/1573062X.2014.923917 Gires, A., Giangola-Murzyn, A., Abbes, J.B., Tchiguirinskaia, I., Schertzer, D., and Lovejoy, S. (2014). Impacts of small scale rainfall variability in urban areas: a case study with 1D and 1D/2D hydrological models in a multifractal framework. Urban Water Journal. DOI: 10.1080/1573062X.2014.923917 Gregoire, B.G., Clausen, J.C. (2011). Effect of a modular extensive green roof on stormwater runoff and water quality. Ecological Engineering, 37, 963 969 Palla, A., Berreta., C, Lanza, L.G.and La Barbera, P. (2008). Modelling storm water control operated green roofs at the urban catchment scale. 11th International Conference on Urban Drainage, Edinburgh, (Scotland). Palla, A., Gnecco I., Lanza L.G. (2009). Unsaturated 2D modelling of subsurface water flow in the coarse-grained porous matrix of a green roof. Journal of Hydrology, 379, 193-204 Schertzer, D. and Lovejoy, S. (1987). Physical modelling and analysis of rain and clouds by anisotropic scaling and multiplicative processes. Journal of Geophysical Research, 92 (D8), 9693 9714. Simmons, M.T., Gardiner, B., Windhager, S., Tinsley, J., (2008). Green roofs are not created equal: the hydrologic and thermal performance of six different extensive green roofs and reflective and non-reflective roofs in a subtropical climate. Urban Ecosyst. 11 (4), 339 348. Šimůnek, J., van Genuchten, M.T. and Šejna, M. (2008). Development and applications of the HYDRUS and STANMOD software packages, and related codes. Vadose Zone Journal, 7(2): 587-600. Stovin, V., Vesuviano, G. and Kasmin, H. (2012). The hydrological performance of a green roof test bed under UK climatic conditions. Journal of Hydrology, 414-415: 148-161. Versini, P.-A., Ramier, D., Berthier, E., de Gouvello, B. (2015a). Assessment of the hydrological impacts of green roof: from building scale to basin scale. Journal of Hydrology, 524: 562-575. Versini, P.A., Jouve, P., Ramier, D., Berthier, E. and de Gouvello, B. (2015b). Use of green roofs to solve storm water issues at the basin scale - Study in the Hauts-de-Seine county (France). Urban Water Journal. http://dx.doi.org/10.1080/1573062x.2014.993993 Versini, P.A., Gires, A., Tchinguirinskaia, I., and Schertzer, D. (2015c). Toward an operational tool to simulate green roof hydrological impact at the basin scale: a new version of the distributed rainfall-runoff model Multi-Hydro. Water Science and Technology, submitted Voyde, E., Fassman, E. and Simcock, R. (2010). Hydrology of an extensive living roof under sub-tropical climate conditions in Auckland, New Zealand. Journal of Hydrology, 394(3-4): 384-395 6