TY - JOUR
T1 - Assessing curve number uncertainty for green roofs in a stochastic environment
AU - Huang, W. S.C.
AU - You, L. W.
AU - Tung, Y. K.
AU - Yoo, C. S.
N1 - Funding Information:
The study is supported under the Joint Research Cooperative Program for the National Research Foundation of Korea (2016K2A9A1A06922023) and the Ministry of Science & Technology of Taiwan (MOST 105–2923-E-009-004-MY2).
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2018/11/5
Y1 - 2018/11/5
N2 - 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 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.
AB - 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 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.
UR - http://www.scopus.com/inward/record.url?scp=85058114689&partnerID=8YFLogxK
U2 - 10.1088/1755-1315/191/1/012002
DO - 10.1088/1755-1315/191/1/012002
M3 - Conference article
AN - SCOPUS:85058114689
SN - 1755-1307
VL - 191
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
IS - 1
M1 - 012002
T2 - 4th International Conference on Water Resource and Environment, WRE 2018
Y2 - 17 July 2018 through 21 July 2018
ER -
