Garofalo, G.

Piro, P.

Principato, F.

I-Revues

NOVATECH 2016 
1 
Hydrologic performance of an extensive green roof 
under different climate conditions 
Performance hydrologique d’une toiture végétalisée 
extensive sous différentes conditions climatiques 
 
Principato Francesca1,2, Garofalo Giuseppina2, Piro Patrizia2  
 
1: Dept. of Civil, Chemical and Environmental Engineering, University of Genoa, 
Via Montallegro 1, 16145 Genova, Italy 
2: Department of Civil Engineering, University of Calabria,  
Ponte P. Bucci, Cubo 42 B, 87036 Rende (CS), Italy  
Emails: francesca.principato@unical.it;  
             giuseppina.garofalo@unical.it;  
             patrizia.piro@unical.it 
 
RÉSUMÉ 
Les toitures végétalisées (TV) représentent une solution durable pour atténuer le ruissellement pluvial 
dans l’environnement urbain. Sur la base de l'hypothèse que la capacité de rétention d'eau dépend 
principalement des conditions météorologiques et que chaque événement de pluie influence 
différemment la réponse d'une TV en termes de débit, cette étude analyse l'influence des paramètres 
hydrologiques sur l'efficacité d’une TV expérimentale, installée à l'Université de Calabre (Unical), à 
Cosenza dans le sud de l'Italie. 
Dans la première phase d'étude, le modèle conceptuel "Sigma Drain" (SD), préalablement calé et 
validé, a été utilisé pour évaluer le ruissellement de la TV, avec les données de pluie enregistrées en 
deux régions climatiques différentes : Cosenza (Italie) et Lyon (France). Le coefficient de 
ruissellement, et donc la rétention, pour chaque événement pluvieux a été calculé avec les valeurs 
obtenues par SD : les deux scénarios ont retenu en moyenne 60 % des volumes précipités.  
Dans la deuxième phase, les données de pluie de Cosenza ont été utilisées pour une analyse de 
régression linéaire multiple; la validation de l'équation a été effectuée en utilisant les pluies de Lyon. 
Les premiers résultats confirment que la TV installée à Unical, en climat méditerranéen, est également 
efficace hydrologiquement sous un autre régime climatique tel que celui tempéré de la ville de Lyon.  
 
ABSTRACT 
In urban environment, green roofs (GRs) represent a sustainable solution to mitigate stormwater 
runoff. Based on the assumption that water retention capacity mainly depends on weather conditions 
and that each rainfall event will differently affect the response in terms of outflow from a GR, this study 
analyzes the influence of the hydrologic parameters on the efficiency for a specific experimental GR, 
installed at University of Calabria (Unical), Cosenza in south Italy.  
In the first phase of the study, using a Conceptual Model “Sigma Drain” (SD), previously calibrated and 
validated, the runoff from the GR was evaluated using two rainfall datasets, recorded in two different 
climatic zones: Cosenza (Italy) and Lyon (France). Based on the values obtained from SD, it was 
possible to obtain the subsurface runoff coefficient and consequently, the retention for each rainfall 
event. By comparing the results, both scenarios showed similar behaviors: estimating an average 
retention capacity of about 60% for both data sets.  
In the second phase, using rainfall data collected at Unical, a multiple linear regression analysis was 
evaluated; the validation procedure made for the equation was performed by using the rainfall data of 
Lyon. First results show how the GR, installed at Unical, under Mediterranean climate condition, is 
also hydrologically efficient in another climate condition as the Temperate of the city of Lyon. 
 
KEYWORDS 
Green roof, Rainfall-Runoff, Regression Analysis, Retention, Stormwater management 
SESSION 
2 
1 INTRODUCTION 
The use of LIDs (Low Impact Developments) as storm water management techniques has 
assumed increased importance in recent years (Sitzenfrei et al., 2013). Despite the benefits are large 
and well known, the transition to sustainable urban drainage systems is very slow (Piro et al., 2012). 
The lack of adequate modeling and analysis tools for is a limiting factor in the diffusion of such 
systems (Elliott & Trowsdale, 2007).  
Green roofs represent one of the most diffused LIDs, but due to their morphological complexity, 
green roof’s analysis requires specific modeling techniques that take into account the complex 
physical phenomena involved. Storm water management performance of a green roof may differ in 
various climatic regions due to the specific precipitation climatology, building practices and GR 
materials. 
This study will analyze the influence of the hydrologic parameters on the hydraulic efficiency for a 
specific experimental GR, installed at University of Calabria (Unical), Cosenza. In the first phase of the 
study, using a Conceptual Model “Sigma Drain” (SD), previously calibrated and validated (Principato et 
al., 2016), the runoff from the GR was evaluated using rainfall data recorded in two different climatic 
zones: Cosenza (Italy) and Lyon (France). In the second phase, using rainfall data collected at Unical, 
a multiple linear regression analysis was evaluated; the validation procedure made for the equation 
was performed by using the rainfall data of Lyon.  
2 METHODOLOGY 
2.1 Experimental Site and Data Analysis 
The study was performed on the experimental site at the Cube 46/C of University of Calabria 
(Unical), Italy. The test site, situated on a fifth-floor terrace of a campus’s building, is located in a 
Mediterranean climate region, characterized by a hot-dry summers and cool-wet winters a strongly 
seasonal rainfall with an annual average of 1000 mm. High temperatures during the summer average 
27°C (Carbone et al. 2015). The GR consists of four compartments, each one with an equal area of 
around 50 m
2
 and a slope of 1%, which vary in their stratigraphy, composition elements and the 
presence, or not, of vegetation species. Precipitation data, consisting of rainfall depth recorded with 
minute frequency, were collected from two different sites: Green Roof of Unical (Italy) and GR of the 
Lyon Congress Center (France), located respectively in Mediterranean and Temperate climate 
conditions. In order to analyze the influence of hydrologic parameters on the efficiency of the green 
roof, under different climate conditions, it was needed to define each rainfall event in the data sets with 
time resolution of 1 minute. 
For both sites, despite having both rain gauge a resolution of 0.2 mm, only events with rainfall 
depth greater than 2 mm were selected, based on the assumption that rainfall events less than 2 mm 
are unlike to produce runoff from a conventional roof (Voyde et al., 2010; Stovin et al., 2012). In this 
study, individual events were defined as being separated by continuous dry periods of at least two 
hours; rainfall events separated by less than 2 hours were merged and considered as single event. 
From this assumptions, a number of rainfall events were selected from each datasets. In specific, 
under these conditions, a total of 70 and 50 rainfall events, recorded respectively at Unical and Lyon 
site, were identified and then used in the analysis. Since the experimental site is installed in an area 
with a Mediterranean climate, characterized by precipitations which mostly result distributed in the 
autumn and winter season, the data collected in the period between September and April were 
considered. 
2.2 The SIGMA DRAIN Conceptual Model 
The SIGMA DRAIN conceptual model (Principato et al., 2016), is a new tool developed to simulate 
the hydraulic response of the extensive green roof installed at the University of Calabria, realized 
using the calculation engine of EPA-SWMM (Storm Water Management Model) software (Rossman, 
2010) for the simulation of the hydrological and hydraulic phenomena, while being completely 
independent of the user interface. The SIGMA DRAIN model idealizes the green roof as a system 
consisting of three individual components in series, each of them corresponding to the main 
technological modules of the GR. The surface layer, exposed to the atmosphere and covered by 
vegetation, is conceptualized as sub-catchment; it is defined by the real size of the vegetated roof 
surface (area and % slope), and is characterized by a specific permeability of the soil dependent on 
fraction of vegetation coverage. The following soil and drainage layers are schematized through two 
NOVATECH 2016 
3 
reservoir elements, which describe respectively the percolation in the substrate and the transport 
through the drainage layer. A mass balance equation is applied to each block, taking into account the 
specific physical phenomena that occur in each module and the flow is instead regulated by the 
Richard’s equation. 
2.3 Multi-linear Regression Analysis 
In this study, the Multiple Linear Regression Analysis was used in order to:  
 statistically define the most influencing hydrological factors on the hydraulic efficiency of the 
experimental green roof located at University of Calabria; 
 get regression equations that an engineer could use for a preliminary study on the 
performance of the green roof, without the implementation of the conceptual model. 
The Multiple Linear Regression Analysis is used to assess the association between two or more 
independent variables and a single continuous dependent variable. The multiple linear regression 
equation is as follows: 
                                                                                                Eq. 1 
where Y is the predicted or expected value of the dependent variable, X1 through Xp are p distinct 
independent or predictor variables, β0 is the value of Y when all of the independent variables (X1 through 
Xp) are equal to zero, β1 through βP are the estimated regression coefficients, and ε is the residual term 
which translates the inability of the model to accurately reproduce the observed reality. In this study the 
independent variables are the hydrological parameters, such as precipitation depth, rainfall duration and 
rainfall intensity, while the dependent variable is the runoff depth and the retention capacity. 
In order to evaluate the significance of each regression coefficient a t-test was used. A p-value of 
0.05 was considered in this study. To define how close the data are to the fitted regression line, the R
2
 
coefficient is used.  
This analysis is carried out by firstly defining the runoff depth at event scale, by using 1-minute 
rainfall data as input data in the SIGMA DRAIN conceptual model. The rainfall data set from Unical 
(Italy), and the model runoff, are used to obtain the multi-regression relationships, which were, then, 
validated with the data set from Lyon, France. 
3 RESULTS AND DISCUSSION 
A multiple linear regression analysis, using the rainfall data collected from the experimental site at 
University of Calabria, was evaluated. The results of the multiple linear regression analysis are 
summarized in Table 1, where the t-statistics (significant at p = 0.05) are presented in the same order 
as the parameters in the equation.  
Table 1 - Multiple Linear Regression Analysis for rainfall data collected at University of Calabria 
Regression equation R
2 
  T-statistic 
RD = - 4.10 + 0.71PD                                                   (EQ. 1) 
lnVR%= - 4.92 - 0.18 lnPD – 0.02d                               (EQ. 2) 
VR= 1.13 - 0.03d – 0.03i                                               (EQ. 3) 
0.9 
0.7 
0.7 
24.7
 
-4.7, - 4.0 
-10.9, -4.2 
The first relationship (Eq. 1) correlates the runoff depth (RD) with the rainfall depth (PD) and 
presents a R
2
 equal to 0.9. The second equation (Eq. 2) was defined by considering how the 
Retention capacity (%) could be express as a function of rainfall depth (PD) and rainfall duration (d). 
Although this relationship exhibits a R
2
 equal to 0.7, the t-statistic of both parameters were 
characterized by a low significance level. In the regression equation (Eq. 3), the retention capacity 
(VR) was obtained by using the rainfall duration (d) and intensity (i), with an R
2
 equal to 0.7. In 
agreement with Stovin et al. (2012), the antecedent dry weather period (ADWP) was not found to be a 
good predictor of retention. The multi-regression relationships, reported in Table 1, are validated by 
using the rainfall data recorded at Congress Center in Lyon. In the validation process, the SIGMA 
DRAIN model was used as a reference to verify the soundness of the data obtained from the statistical 
relationship. One of the result obtained for Eq. 1, is compared with those obtained from the SIGMA 
DRAIN model - loaded with the 1-minute rainfall data as well - are shown in the Figure below (Fig. 1).  
SESSION 
4 
 
Figure 1 – Runoff Depth predicted by the Eq. 28 and modelled with SIGMA DRAIN model, with Lyon dataset. 
The runoff obtained from the regression relationship (Eq. 1), for the entire data set is similar to the 
runoff provided through SIGMA DRAIN model, corresponding to a NS value equal to 0.9. In particular 
is possible to notice how the runoff depth obtained by the Eq. 1, generally overestimates the SIGMA 
DRAIN values, except for events with a rainfall depth higher than 40 mm. 
4 CONCLUSION 
In this study, the model SIGMA DRAIN was loaded with datasets collected in two different sites 
(Unical, in Italy and Lyon, in France), in order to analyze the influence of the hydrologic parameters on 
the green roof efficiency. A similar behavior for both scenarios (Unical and Lyon) is evident by 
comparing the results provided by SIGMA DRAIN in terms of runoff: the two sites area follow the same 
trend, suggesting that this GR package, developed at University of Calabria, under Mediterranean 
climate conditions, has a good hydraulic performance also in a different climate, as the Temperate 
one, in which the Lyon data were recorded. 
Furthermore, to statistically determine the significance of the hydrological parameters on the 
performance of the GR, the multiple linear regression analysis was applied. The investigation revealed 
that the most influencing parameters on the retention capacity of the green roof are the rainfall depth, 
the duration and intensity, according to which, the substrate moisture condition changes. The 
relationships founded and validated with Lyon dataset, can be used to preliminarily predict the runoff 
depth and the retention capacity, for a given rainfall event, when more advanced model are not 
available.  
Acknowledgments 
The study was developed and co-funded from the Italian National Operative Project (PON) - Research and 
Competitiveness for the convergence regions 2007/2013: PON01_02543 “Integrated and Sustainable 
Management service of water-energy cycle in urban drainage systems”. 
LIST OF REFERENCES 
Carbone M., Garofalo G., Nigro G., Piro, P., 2015a. Green roofs in the Mediterranean area: Interaction between 
native plant species and sub-surface runoff. Applied Mechanics and Materials, Vol. 737, pp. 749-753. 
Elliott A.H., Trowsdale S.A., 2007. A review of models for low impact urban stormwater drainage. Environmental 
Modelling & Software, 22(3), pp. 394-405. 
Piro P., Carbone M., Sansalone J., 2012. Delivery and Frequency Distributions of Combined Wastewater 
Collection System Wet and Dry Weather Loads. Water Environment Research, 84(1), pp. 65-75  
Principato F., Carbone M., Piro P., 2016. Modeling Stormwater runoff from extensive green roof using the 
Conceptual Model “Sigma Drain”. Submitted to the 9
th
 International Conference Novatech 2016, Lyon, France. 
Rossman L. A., 2010. Storm water management model user's manual, version 5.0. Cincinnati: National Risk 
Management Research Laboratory, Office of Research and Development, US Environmental Protection 
Agency. 275 p. 
Sitzenfrei R., Möderl M., Rauch W., 2013. Assessing the impact of transitions from centralized to decentralised 
water solutions on existing infrastructures - Integrated city-scale analysis with VIBe. Water Research, 47(20), 
pp. 7251-7263. 
Stovin V., Vesuviano G., Kasmin H., 2012. The hydrological performance of a green roof test bed under UK 
NS = 0.9 
1 
NOVATECH 2016 
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climatic conditions. Journal of Hydrology, 414, pp. 148-161 
Voyde E., Fassman E., Simcock, R., 2010. Hydrology of an extensive living roof under sub-tropical climate 
conditions in Auckland, New Zealand. Journal of Hydrology, 394(3), pp. 384-395. 


Performance hydrologique d’une toiture végétalisée extensive sous différentes conditions climatiques

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Performance hydrologique d’une toiture végétalisée extensive sous différentes conditions climatiques

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