Recognition method for mid- to long-term runoff forecasting factors based on global sensitivity analysis in the Nenjiang River Basin

2012 ◽  
Vol 26 (18) ◽  
pp. 2827-2837 ◽  
Author(s):  
Hongyan Li ◽  
Miao Xie ◽  
Shan Jiang
Keyword(s):  
Sensitivity Analysis ◽  
River Basin ◽  
Global Sensitivity Analysis ◽  
Recognition Method ◽  
Global Sensitivity ◽  
Runoff Forecasting ◽  
Nenjiang River Basin

scholarly journals Time-Dependent Global Sensitivity Analysis for Long-Term Degeneracy Model Using Polynomial Chaos

2014 ◽  
Vol 6 ◽  
pp. 719825 ◽  
Author(s):  
Jianbin Guo ◽  
Shaohua Du ◽  
Yao Wang ◽  
Shengkui Zeng
Keyword(s):  
Sensitivity Analysis ◽  
Polynomial Chaos ◽  
Global Sensitivity Analysis ◽  
Time Dependent ◽  
Accurate Information ◽  
Test Case ◽  
Sobol Indices ◽  
Global Sensitivity ◽  
Mechanism Model

Global sensitivity is used to quantify the influence of uncertain model inputs on the output variability of static models in general. However, very few approaches can be applied for the sensitivity analysis of long-term degeneracy models, as far as time-dependent reliability is concerned. The reason is that the static sensitivity may not reflect the completed sensitivity during the entire life circle. This paper presents time-dependent global sensitivity analysis for long-term degeneracy models based on polynomial chaos expansion (PCE). Sobol’ indices are employed as the time-dependent global sensitivity since they provide accurate information on the selected uncertain inputs. In order to compute Sobol’ indices more efficiently, this paper proposes a moving least squares (MLS) method to obtain the time-dependent PCE coefficients with acceptable simulation effort. Then Sobol’ indices can be calculated analytically as a postprocessing of the time-dependent PCE coefficients with almost no additional cost. A test case is used to show how to conduct the proposed method, then this approach is applied to an engineering case, and the time-dependent global sensitivity is obtained for the long-term degeneracy mechanism model.

Sign in / Sign up

Export Citation Format

Share Document