Academic Journal
Python-Based Model Emulation Workflows with PEST.
| Τίτλος: | Python-Based Model Emulation Workflows with PEST. |
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| Συγγραφείς: | Hugman R, White J; INTERA Incorporated, Fort Collins, CO. |
| Πηγή: | Ground water [Ground Water] 2026 May 28. Date of Electronic Publication: 2026 May 28. |
| Publication Model: | Ahead of Print |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Blackwell Publishing Country of Publication: United States NLM ID: 9882886 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1745-6584 (Electronic) Linking ISSN: 0017467X NLM ISO Abbreviation: Ground Water Subsets: MEDLINE |
| Imprint Name(s): | Publication: 2005- : Malden, MA : Blackwell Publishing Original Publication: Worthington, Ohio : Water Well Journal Pub. Co. |
| Περίληψη: | Computational demands for uncertainty quantification and optimization often exceed available resources for high-fidelity environmental models. While surrogate modeling (or model emulation) offers a pragmatic solution, widespread adoption is hindered by a significant "implementation gap": practitioners often lack standardized, robust tools to integrate emulation techniques directly into existing modeling workflows, relying instead on bespoke implementations. To bridge this gap, we present the Emulator module within the open-source pyEMU package. This framework provides a "plug-and-play" architecture for deploying Gaussian Process Regression (GPR), Data-Space Inversion (DSI) and other model emulation approaches. The framework automates the complex "plumbing" of emulation-based workflows, including non-Gaussian data transformation and the generation of PEST interface files, allowing trained surrogates to serve as drop-in replacements for physics-based models. We believe this one-to-one correspondence between physics-based model and emulator-based workflows will facilitate direct comparisons between the two so that the community in general can build up the knowledge of when and how to effectively and appropriately deploy emulation. We demonstrate the utility of these tools through a benchmarking optimization problem and a history-matching application on a synthetic groundwater model. (© 2026 National Ground Water Association.) |
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| Entry Date(s): | Date Created: 20260528 Latest Revision: 20260528 |
| Update Code: | 20260528 |
| DOI: | 10.1111/gwat.70082 |
| PMID: | 42207131 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1745-6584 |
|---|---|
| DOI: | 10.1111/gwat.70082 |