Green roof seasonal variation: comparison of the hydrologic behavior of a thick and a thin extensive system in New York City

R M Elliott, R A Gibson, T B Carson, D E Marasco, P J Culligan, W R McGillis
2016 Environmental Research Letters  
Green roofs have been utilized for urban stormwater management due to their ability to capture rainwater locally. Studies of the most common type, extensive green roofs, have demonstrated that green roofs can retain significant amounts of stormwater, but have also shown variation in seasonal performance. The purpose of this study is to determine how time of year impacts the hydrologic performance of extensive green roofs considering the covariates of antecedent dry weather period (ADWP),
more » ... riod (ADWP), potential evapotranspiration (ET 0 ) and storm event size. To do this, nearly four years of monitoring data from two full-scale extensive green roofs (with differing substrate depths of 100 mm and 31 mm) are analyzed. The annual performance is then modeled using a common empirical relationship between rainfall and green roof runoff, with the addition of Julian day in one approach, ET 0 in another, and both ADWP and ET 0 in a third approach. Together the monitoring and modeling results confirm that stormwater retention is highest in warmer months, the green roofs retain more rainfall with longer ADWPs, and the seasonal variations in behavior are more pronounced for the roof with the thinner media than the roof with the deeper media. Overall, the ability of seasonal accounting to improve stormwater retention modeling is demonstrated; modification of the empirical model to include ADWP, and ET 0 improves the model R 2 from 0.944 to 0.975 for the thinner roof, and from 0.866 to 0.870 for the deeper roof. Furthermore, estimating the runoff with the empirical approach was shown to be more accurate then using a water balance model, with model R 2 of 0.944 and 0.866 compared to 0.975 and 0.866 for the thinner and deeper roof, respectively. This finding is attributed to the difficulty of accurately parameterizing the water balance model.
doi:10.1088/1748-9326/11/7/074020 fatcat:j4iyrvi3ofhshgxhksjiclnajy