Parameter sensitivity and uncertainty analysis of a stormwater runoff model

摘要: AbstractIn this study, Generalized Likelihood Uncertainty Estimation (GLUE) methodology was used to perform uncertainty analysis of a stormwater model, which randomly generates parameter sets and identifies behavioral ones with higher likelihood. Latin Hypercube Sampling (LHS) is generate sets. The Model for Urban Stormwater Improvement Conceptualization chosen as an appropriate model runoff. Prediction limits are determined by selecting the cutoff threshold likelihood function. Study area Goonja Drainage Basin located in city Seoul, Korea. From results, maximum value calibration 0.78 0.73 validation. p-factors validation 87 83%, respectively. p-factor all storm events 85%. These acceptable values results considered good when 60% or more observed data bracketed prediction limits. Overall, it shown that, using GLUE LHS, mod...