Articles | Volume 23, issue 9
Hydrol. Earth Syst. Sci., 23, 3787–3805, 2019
https://doi.org/10.5194/hess-23-3787-2019
Hydrol. Earth Syst. Sci., 23, 3787–3805, 2019
https://doi.org/10.5194/hess-23-3787-2019

Research article 18 Sep 2019

Research article | 18 Sep 2019

Global sensitivity analysis and adaptive stochastic sampling of a subsurface-flow model using active subspaces

Daniel Erdal and Olaf A. Cirpka

Viewed

Total article views: 2,048 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,102 928 18 2,048 92 25 21
  • HTML: 1,102
  • PDF: 928
  • XML: 18
  • Total: 2,048
  • Supplement: 92
  • BibTeX: 25
  • EndNote: 21
Views and downloads (calculated since 24 Apr 2019)
Cumulative views and downloads (calculated since 24 Apr 2019)

Viewed (geographical distribution)

Total article views: 1,694 (including HTML, PDF, and XML) Thereof 1,672 with geography defined and 22 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 07 Dec 2021
Download
Short summary
Assessing how sensitive uncertain model parameters are to observed data can be done by analyzing an ensemble of model simulations in which the parameters are varied. In subsurface modeling, this involves running heavy models. To reduce time wasted simulating models which show poor behavior, we use a fast polynomial model based on a simple parameter decomposition to approximate the behavior prior to full-model simulation. This largely reduces the cost for the global sensitivity analysis.