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dc.contributor.authorHuang, W. S. C.en_US
dc.contributor.authorYou, L. W.en_US
dc.contributor.authorTung, Y. K.en_US
dc.contributor.authorYoo, C. S.en_US
dc.date.accessioned2019-06-03T01:09:17Z-
dc.date.available2019-06-03T01:09:17Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn1755-1307en_US
dc.identifier.urihttp://dx.doi.org/10.1088/1755-1315/191/1/012002en_US
dc.identifier.urihttp://hdl.handle.net/11536/152025-
dc.description.abstractCurve number (CN) is well-known by hydrologists for estimating rainfall induced runoff from a catchment. It can also be used as an indicator for measuring the impact of engineering or non-engineering measures on the runoff production in a catchment. In this study, a method is presented to quantify the uncertainty of CN for hydrologic performance of a green roof system. Latin hypercube sampling approach, coupled with the antithetic variate technique, is used to achieve efficient and accurate quantification of the uncertainty features of CN for a green roof system. Elements in green roofs subject to uncertainty considered are rainfall characteristics (i.e. amount and inter-event dry period), soil-plant-climate factors (i.e. field capacity, wilting point, interception, evapotranspiration rate), and model error in SCS I-a-S relation. Numerical study shows that model error in SCS I-a-S relation has the dominant effect on the uncertainty features of CN for green roof performance.en_US
dc.language.isoen_USen_US
dc.titleAssessing curve number uncertainty for green roofs in a stochastic environmenten_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1088/1755-1315/191/1/012002en_US
dc.identifier.journal4TH INTERNATIONAL CONFERENCE ON WATER RESOURCE AND ENVIRONMENT (WRE 2018)en_US
dc.citation.volume191en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department防災與水環境研究中心zh_TW
dc.contributor.departmentDisaster Prevention and Water Environment Research Centeren_US
dc.identifier.wosnumberWOS:000467867600002en_US
dc.citation.woscount0en_US
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