Probabilistic assessment of hydrologic retention performance of green roof considering aleatory and epistemic uncertainties

Abstract

Green roofs (GRs) are well known for source control of runoff quantity in sustainable urban stormwater management. By considering the inherent randomness of rainfall characteristics, this study derives the probability distribution of rainfall retention ratio R-r and its statistical moments. The distribution function of R-r can be used to establish a unique relationship between target retention ratio R-r,R- T, achievable reliability AR, and substrate depth h for the aleatory-based probabilistic (AP) GR design. However, uncertainties of epistemic nature also exist in the AP GR model that makes AR uncertain. In the paper, the treatment of epistemic uncertainty in the AP GR model is presented and implemented for the uncertainty quantification of AR. It is shown that design without considering epistemic uncertainties by the AP GR model yields about 50% confidence of meeting R-r,R- T. A procedure is presented to determine the design substrate depth having the stipulated confidence to satisfy R-r,R- T and target achievable reliability AR(T).