Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 23, issue 9
Articles | Volume 23, issue 9
https://doi.org/10.5194/hess-23-3787-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-3787-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 9
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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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.
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