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

Lingwan You, Yeou Koung Tung, Chulsang Yoo

Research output: Contribution to journalArticlepeer-review

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 Rr and its statistical moments. The distribution function of Rr can be used to establish a unique relationship between target retention ratio Rr,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 Rr,T. A procedure is presented to determine the design substrate depth having the stipulated confidence to satisfy Rr,T and target achievable reliability ART.

Original languageEnglish
Pages (from-to)1377-1396
Number of pages20
JournalHydrology Research
Volume51
Issue number6
DOIs
Publication statusPublished - 2020 Dec 1

Keywords

  • Green roof
  • Probabilistic-based design
  • Probability
  • Retention ratio
  • Uncertainty analysis

ASJC Scopus subject areas

  • Water Science and Technology

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