Assessing curve number uncertainty for green roofs in a stochastic environment

• Published in: IOP conference series. Earth and environmental science Vol. 191; no. 1; pp. 12002 - 12009
• Main Authors: Huang, W S C, You, L W, Tung, Y K, Yoo, C S
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 05.11.2018
• Subjects: Evapotranspiration; Field capacity; Green buildings; Green roofs; Hydrology; Hypercubes; Interception; Latin hypercube sampling; Rainfall; Roofing; Roofs; Runoff; Uncertainty; Wilting; Wilting point
• ISSN: 1755-1307; 1755-1315; 1755-1315
• DOI: 10.1088/1755-1315/191/1/012002

Curve 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 Ia-S relation. Numerical study shows that model error in SCS Ia-S relation has the dominant effect on the uncertainty features of CN for green roof performance.