Sensitivity analysis of correlated outputs and its application to a dynamic model

Liyang Xu, Zhenzhou Lu*, Luyi Li, Shi Yan Shi, Gang Zhao

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

2 Citations (Scopus)


Risk assessment and decision making in ecology, hydrology and biology often employ dynamic models with multiple calibrations. The global sensitivity analysis of models is usually completed at each time step of a single output. However, due to the enormous volume of data and model complexity, a single index cannot give a full-scale analysis of such models. The purposes of this paper are: (1) to apply T-pooling for analysing multiple outputs at a lower computational cost; (2) to consider the influence of the correlations among the outputs and the output dimensions on sensitivity analysis; and (3) to propose a procedure that combines the Sobol' index for a single output and the generalised sensitivity method and T-pooling index for multiple outputs to analyse dynamic models comprehensively. The proposed procedure and index are applied to a Hydrologiska Byråns Vattenbalansavdelning (HBV) model with three calibrations to provide an uncertainty analysis across time periods ranging from a single time step to the entire time period.

Original languageEnglish
Pages (from-to)39-53
Number of pages15
JournalEnvironmental Modelling and Software
Early online date9 Apr 2018
Publication statusPublished - 1 Jul 2018


  • Dynamic model
  • Hydrologiska Byråns Vattenbalansavdelning (HBV) model
  • Multivariate outputs
  • Probability integral transformation (PIT)
  • Sensitivity analysis
  • T-pooling


Dive into the research topics of 'Sensitivity analysis of correlated outputs and its application to a dynamic model'. Together they form a unique fingerprint.

Cite this