Towards reproducible environmental modeling for decision support: a worked example
June 1, 2021
Supporting datasets for the associated journal publication "Towards reproducible environmental modeling for decision support: a worked example". Includes source codes for the version of PEST++ and MODFLOW-2005 used, the pyEMU and FloPy python modules and the driver script "eaa.py". Also included are the existing MODFLOW-2005 models supplied the Edwards Aquifer Authority
Citation Information
| Publication Year | 2021 |
|---|---|
| Title | Towards reproducible environmental modeling for decision support: a worked example |
| DOI | 10.5066/P9AUZMI7 |
| Authors | Jeremy White, Linzy Foster, Michael N Fienen, Matthew J. Knowling, Brioch Hemmings, James R. Winterle |
| Product Type | Data Release |
| Record Source | USGS Asset Identifier Service (AIS) |
| USGS Organization | Oklahoma-Texas Water Science Center – Austin, TX Office |
| Rights | This work is marked with CC0 1.0 Universal |
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Towards reproducible environmental modeling for decision support: A worked example Towards reproducible environmental modeling for decision support: A worked example
A fully worked example of decision-support-scale uncertainty quantification (UQ) and parameter estimation (PE) is presented. The analyses are implemented for an existing groundwater flow model of the Edwards aquifer, Texas, USA, and are completed in a script-based workflow that strives to be transparent and reproducible. High-dimensional PE is used to history-match simulated outputs to...
Authors
Jeremy White, Linzy Foster, Michael N. Fienen, Matthew Knowling, Brioch Hemmings, James Winterle
Related
Towards reproducible environmental modeling for decision support: A worked example Towards reproducible environmental modeling for decision support: A worked example
A fully worked example of decision-support-scale uncertainty quantification (UQ) and parameter estimation (PE) is presented. The analyses are implemented for an existing groundwater flow model of the Edwards aquifer, Texas, USA, and are completed in a script-based workflow that strives to be transparent and reproducible. High-dimensional PE is used to history-match simulated outputs to...
Authors
Jeremy White, Linzy Foster, Michael N. Fienen, Matthew Knowling, Brioch Hemmings, James Winterle