SENSITIVITY ANALYSIS OF DISTRIBUTED RAINFALL-RUNOFF MODELS

摘要：

Two Monte Carlo based methods were applied in a mountainous watershed. The methods covered were the Generalized Likelihood Uncertainty Estimation Technique (GLUE) and the variance based Sobol technique. The former assess the likelihood of a model to describe a system recognizing that model and data are subject to uncertainty; the latter statistically evaluates the uncertainty in the estimation of model parameter values. Both are commonly used in model predictive uncertainty. This paper analyzed their applicability to distributed rainfall-runoff schemes. The methods were found to be complimentary: GLUE technique contributed the criteria for rejection/acceptance of behavioral models, and Sobol indices described the relative variance contribution of model parameters on total discharge. Bayesian updating within GLUE, and the spatial distribution of sensitivity indices were not covered, and can be the key to extend the analysis into fully distributed schemes.

关键词： Monte Carlo ezperiments variance based methods generalized likelihood uncertainty estimation

作者: Freddy Soria So Kazama Masaki Sawamoto

作者单位: Tohoku University, Graduate School of Engineering, Sendai -Japan Tohoku University, Graduate School of Environmental Sciences, Sendal -Japan

会议类型: 国际会议

会议名称: 第16届亚太地区国际水利学大会暨第3届水工水力学国际研讨会(16th IAHR-APD Congress and 3rd Symoposium of IAHR-ISHS)

会议地点: 南京

会议语种:英文

页码: 24-28

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）