Articles | Volume 14, issue 7
Geosci. Model Dev., 14, 4713–4730, 2021
https://doi.org/10.5194/gmd-14-4713-2021
Geosci. Model Dev., 14, 4713–4730, 2021
https://doi.org/10.5194/gmd-14-4713-2021

Model evaluation paper 29 Jul 2021

Model evaluation paper | 29 Jul 2021

DecTree v1.0 – chemistry speedup in reactive transport simulations: purely data-driven and physics-based surrogates

Marco De Lucia and Michael Kühn

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2020-445', Anonymous Referee #1, 08 Mar 2021
    • AC3: 'Reply on RC1', Marco De Lucia, 26 May 2021
  • RC2: 'Comment on gmd-2020-445', Glenn Hammond, 31 Mar 2021
    • AC1: 'Reply on RC2', Marco De Lucia, 26 May 2021
  • RC3: 'Comment on gmd-2020-445', P. Trinchero, 06 Apr 2021
    • AC2: 'Reply on RC3', Marco De Lucia, 26 May 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Marco De Lucia on behalf of the Authors (26 May 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (10 Jun 2021) by Havala Pye
RR by P. Trinchero (28 Jun 2021)
ED: Publish as is (28 Jun 2021) by Havala Pye
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Short summary
DecTree evaluates a hierarchical coupling method for reactive transport simulations in which pre-trained surrogate models are used to speed up the geochemical subprocess, and equation-based full-physics simulations are called only if the surrogate predictions are implausible. Furthermore, we devise and evaluate a decision tree surrogate approach designed to inject domain knowledge of the surrogate by defining engineered features based on law of mass action or stoichiometric reaction equations.