Probabilistic assessment of hydrologic retention performance of green roof considering aleatory and epistemic uncertainties
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 and its statistical moments. The distrib...
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doaj-d451e547e3d4480f995434962159ee152020-12-17T06:45:14ZengIWA PublishingHydrology Research1998-95632224-79552020-12-015161377139610.2166/nh.2020.086086Probabilistic assessment of hydrologic retention performance of green roof considering aleatory and epistemic uncertaintiesLingwan You0Yeou-Koung Tung1Chulsang Yoo2 Disaster Prevention and Water Environment Research Center, National Chiao Tung University, Hsinchu, Taiwan Disaster Prevention and Water Environment Research Center, National Chiao Tung University, Hsinchu, Taiwan Department of Civil, Environment, and Architecture, Korea University, Seoul, South Korea 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 and its statistical moments. The distribution function of can be used to establish a unique relationship between target retention ratio , 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 . A procedure is presented to determine the design substrate depth having the stipulated confidence to satisfy and target achievable reliability . HIGHLIGHTS Derive the probability distribution of the rainfall retention ratio of green roof (GR) and its statistical moments.; Present an aleatory-based probabilistic (AP) model for GR design.; The paper shows that the design without considering epistemic uncertainties by the AP GR model yields about 50% confidence of meeting target retention ratio.; Propose a methodology to treat epistemic uncertainty in the AP model for the uncertainty quantification of achievable reliability.; Demonstrate the analysis procedures via a numerical example to determine GR substrate depth having the stipulated confidence to satisfy target retention ratio and target reliability.;http://hr.iwaponline.com/content/51/6/1377green roofprobabilistic-based designprobabilityretention ratiouncertainty analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lingwan You Yeou-Koung Tung Chulsang Yoo |
spellingShingle |
Lingwan You Yeou-Koung Tung Chulsang Yoo Probabilistic assessment of hydrologic retention performance of green roof considering aleatory and epistemic uncertainties Hydrology Research green roof probabilistic-based design probability retention ratio uncertainty analysis |
author_facet |
Lingwan You Yeou-Koung Tung Chulsang Yoo |
author_sort |
Lingwan You |
title |
Probabilistic assessment of hydrologic retention performance of green roof considering aleatory and epistemic uncertainties |
title_short |
Probabilistic assessment of hydrologic retention performance of green roof considering aleatory and epistemic uncertainties |
title_full |
Probabilistic assessment of hydrologic retention performance of green roof considering aleatory and epistemic uncertainties |
title_fullStr |
Probabilistic assessment of hydrologic retention performance of green roof considering aleatory and epistemic uncertainties |
title_full_unstemmed |
Probabilistic assessment of hydrologic retention performance of green roof considering aleatory and epistemic uncertainties |
title_sort |
probabilistic assessment of hydrologic retention performance of green roof considering aleatory and epistemic uncertainties |
publisher |
IWA Publishing |
series |
Hydrology Research |
issn |
1998-9563 2224-7955 |
publishDate |
2020-12-01 |
description |
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 and its statistical moments. The distribution function of can be used to establish a unique relationship between target retention ratio , 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 . A procedure is presented to determine the design substrate depth having the stipulated confidence to satisfy and target achievable reliability . HIGHLIGHTS
Derive the probability distribution of the rainfall retention ratio of green roof (GR) and its statistical moments.;
Present an aleatory-based probabilistic (AP) model for GR design.;
The paper shows that the design without considering epistemic uncertainties by the AP GR model yields about 50% confidence of meeting target retention ratio.;
Propose a methodology to treat epistemic uncertainty in the AP model for the uncertainty quantification of achievable reliability.;
Demonstrate the analysis procedures via a numerical example to determine GR substrate depth having the stipulated confidence to satisfy target retention ratio and target reliability.; |
topic |
green roof probabilistic-based design probability retention ratio uncertainty analysis |
url |
http://hr.iwaponline.com/content/51/6/1377 |
work_keys_str_mv |
AT lingwanyou probabilisticassessmentofhydrologicretentionperformanceofgreenroofconsideringaleatoryandepistemicuncertainties AT yeoukoungtung probabilisticassessmentofhydrologicretentionperformanceofgreenroofconsideringaleatoryandepistemicuncertainties AT chulsangyoo probabilisticassessmentofhydrologicretentionperformanceofgreenroofconsideringaleatoryandepistemicuncertainties |
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1724380079591522304 |