Assessing curve number uncertainty for green roofs in a stochastic environment

W. S.C. Huang, L. W. You, Y. K. Tung, Chulsang Yoo

Research output: Contribution to journalConference article

Abstract

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.

Original languageEnglish
Article number012002
JournalIOP Conference Series: Earth and Environmental Science
Volume191
Issue number1
DOIs
Publication statusPublished - 2018 Nov 5
Event4th International Conference on Water Resource and Environment, WRE 2018 - Kaohsiung City, Taiwan, Province of China
Duration: 2018 Jul 172018 Jul 21

    Fingerprint

ASJC Scopus subject areas

  • Environmental Science(all)
  • Earth and Planetary Sciences(all)

Cite this