Sensitivity and Uncertainty Analyses of ACRONYM Model

• Main Authors: Chia-Cheng Wang, 汪嘉誠
• Other Authors: Keh-Chia Yeh; Yeou-Koung Tung
• Format: Others
• Language: zh-TW
• Published: 1993
• Online Access: http://ndltd.ncl.edu.tw/handle/87221795867852306409

碩士 === 國立交通大學 === 土木工程研究所 === 81 === The purpose of this study is to use suitable sets of input parameters generated by Latin Hypercubic Sampling (LHS) method, and to apply the current analytic technique to evaluate sensitivity and uncertainty of model outputs from ACRONYM. In sensitivity analysis, various model outputs at different times and locations are used to develop multiple regression relationships with model inputs. Based on the developed regression equations the sensitivity of input parameters and input groups on model outputs can be quantified. Information from the sensitivity analysis can be utilized to enhance the efficiency for model parameters calibration. In uncertainty analysis, the procedures are almost the same as that in sensitivity analysis, except that the synthesized data for model input parameters are somewhat different. When the regression equations between model input parameters and model outputs are obtained, the theories associated with type I SS and type II SS are adopted to perform the uncertainty analysis of input groups and input parameters, respectively. From the uncertainty analysis, model output uncertainty can be quantified and important model input parameters can be identified. Furthermore, analysis such as this provides important information on the degree of reliability of simulated results from the model which is useful to model users.