This study analyzed stormwater runoff from a green roof to evaluate different storm definitions. Data from one year showed 79 rainfall events with a maximum depth of 58.3mm and average retention of 79%. Preliminary analysis using a common definition identified relationships between retention and rainfall depth/duration between storms. Specifically, smaller rainfall depths and longer dry periods between storms corresponded to higher retention rates. However, more data is needed to clarify these relationships and establish a standardized storm definition for comparing green roof performance across studies.

1. Green Roof Hydrologic Performance and the Influence of Storm Definition
Christopher Weiman, Xiao Yang, Mallory Squier, Professor Davidson
Department of Civil and Environmental Engineering, Syracuse University
Introduction
•Stormwater overflow from urban roofs is influenced heavily by runoff
•Green infrastructure will assist in dealing with storm water runoff
especially for extreme rain events by decreasing chance of overflow
•Green roof research lacks a standard storm definition, limiting
comparison between studies and sites elsewhere
•In order to understand the hydrologic performance of the OnCenter
Green Roof, an analysis of the storms experienced at the OnCenter and
storm definitions from various other sites were undertaken. Using this
data, two factors were taken into account:
1 .When does a storm begin and end?
2. What minimum precipitation is necessary to define a storm event?
Objective
Through analysis of the storm event data and an expanded review of
literature, certain factors of the “storm definition” will be evaluated to
be more suitable for the OnCenter Green Roof and for roofs reported
in the literature.
Study Details
•Our study site, the Nicholas J. Pirro Convention Center Roof is a 5,600
m2 green roof completed in the Fall of 2011 as a retrofit to the existing
building.
•Data was collected using a Badger M-2000 electromagnetic flow
meter and a Campbell Scientific TE 525W tipping bucket.
•Using this data, various parameters were identified which included
antecedent dry weather periods, rain duration, rainfall depth, mean
intensity, and peak intensity.
•Literature review was undertaken to observe any trends with other
existing sites and storm event definitions that were followed.
Data Analysis
Preliminary analysis using one definition commonly cited in the literature (6 hour dry period following precipitation and
a minimum of 0.6 mm rainfall) identified 79 rainfall events from 17 July 2014 to 15 July 2015. The rainfall distribution
data shows in Graph 1 below
Graph 1, Rainfall distribution graph
Graph 1 shows all the storm from 17 July 2014 to 15 July 2015. The highest rainfall is 58.3 mm the lowest rainfall is 0.6
mm. The average rain duration is 8.76 hours with an average rainfall depth of 8.39mm. Also, the average runoff
retention percentage for the roof is 79%.
Discussion & Conclusion
• It is apparent that there is a relationship between the
magnitude of precipitation that occurs to the amount
that is retained by the roof, with the smaller rainfall
depth resulting in a higher retention rate
• There is also a relationship with the duration between
each storm event and the amount of precipitation that
is retained from the roof, where events that are
separated for longer periods of time the roof is able to
retain more of the precipitation
• As for literature review, several publications followed
the 6-hour Antecedent Dry Weather Period (ADWP)
and combined storms that were separated by fewer
than 6 hours (Voyde et al., 2010, Stovin et al., 2012,
VanWoert et al., 2005)
• There were also multiple publications that organized
the storms by small, medium, and large events which
could effect the retention efficiency of the roof when
comparing the smaller events to the larger ones
(VanWoert et al., 2005, Carpenter et al., 2011)
• More data needs to be collected before any concrete
conclusions are met, since there is only one year of
data being observed the relationships that are starting
to surface have to be researched more thoroughly
Sources
• 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(3-4), 384-395.
• Stovin, V., Vesuviano, G., & Kasmin, H. (2012). The hydrological
performance of a green roof test bed under UK climatic conditions.
Journal of Hydrology, 414-415, 148-161.
• VanWoert, N.D., Rowe, D.B., Andersen, J.A., Rugh, C.L.,
Future Work
• Further data needs to be evaluated so that
relationships between rain duration, dry period
duration, and retention rates can be more apparent
• More research has to be done to establish a
standardized storm definition that will allow more
green roof sites to be able to be more comparable.
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
0.00 10.00 20.00 30.00 40.00 50.00 60.00
Retention(%)
Rainfall Depth (mm)
Graph 2, Rainfall Depth vs. Retention (%)
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
0 50 100 150 200 250 300 350
Retention(%)
ADWP (Hour)
Graph 3, ADWP vs Retention (%)
0.00
10.00
20.00
30.00
40.00
50.00
60.00
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77
Depth(mm)
Number of rainfall
Rainfall Distribution Graph
Rainfall depth (mm) Retention depth (mm)
Graph 2 shows that
retention% has some
relationship with
rainfall depth. It is
clearly that when
rainfall depth increase,
the rentention% is
decreasing. However,
there are still lots of
point are scattered. Its
shows there are still
other factors influence
the retention%
Graph 3 shows the
relationship between
retention% and
ADWP(The dry period).
For general trend, when
ADWP is increasing, the
retention% is
increasing.