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

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Status: closed
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (06 Aug 2019) by Alberto Guadagnini
AR by Daniel Erdal on behalf of the Authors (06 Aug 2019)  Author's response    Manuscript
ED: Publish as is (09 Aug 2019) by Alberto Guadagnini
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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.