Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4713-2021
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

Related authors

POET (v0.1): speedup of many-core parallel reactive transport simulations with fast DHT lookups
Marco De Lucia, Michael Kühn, Alexander Lindemann, Max Lübke, and Bettina Schnor
Geosci. Model Dev., 14, 7391–7409, https://doi.org/10.5194/gmd-14-7391-2021,https://doi.org/10.5194/gmd-14-7391-2021, 2021
Short summary
Reactive transport model of kinetically controlled celestite to barite replacement
Morgan Tranter, Maria Wetzel, Marco De Lucia, and Michael Kühn
Adv. Geosci., 56, 57–65, https://doi.org/10.5194/adgeo-56-57-2021,https://doi.org/10.5194/adgeo-56-57-2021, 2021
Short summary
Geochemical and reactive transport modelling in R with the RedModRphree package
Marco De Lucia and Michael Kühn
Adv. Geosci., 56, 33–43, https://doi.org/10.5194/adgeo-56-33-2021,https://doi.org/10.5194/adgeo-56-33-2021, 2021
Short summary
A coupling alternative to reactive transport simulations for long-term prediction of chemical reactions in heterogeneous CO2 storage systems
M. De Lucia, T. Kempka, and M. Kühn
Geosci. Model Dev., 8, 279–294, https://doi.org/10.5194/gmd-8-279-2015,https://doi.org/10.5194/gmd-8-279-2015, 2015

Related subject area

Hydrology
GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications
Guoqiang Tang, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, and Simon Michael Papalexiou
Geosci. Model Dev., 17, 1153–1173, https://doi.org/10.5194/gmd-17-1153-2024,https://doi.org/10.5194/gmd-17-1153-2024, 2024
Short summary
GEMS v1.0: Generalizable Empirical Model of Snow Accumulation and Melt, based on daily snow mass changes in response to climate and topographic drivers
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024,https://doi.org/10.5194/gmd-17-911-2024, 2024
Short summary
mesas.py v1.0: a flexible Python package for modeling solute transport and transit times using StorAge Selection functions
Ciaran J. Harman and Esther Xu Fei
Geosci. Model Dev., 17, 477–495, https://doi.org/10.5194/gmd-17-477-2024,https://doi.org/10.5194/gmd-17-477-2024, 2024
Short summary
rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
Lele Shu, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li
Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024,https://doi.org/10.5194/gmd-17-497-2024, 2024
Short summary
GLOBGM v1.0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model
Jarno Verkaik, Edwin H. Sutanudjaja, Gualbert H. P. Oude Essink, Hai Xiang Lin, and Marc F. P. Bierkens
Geosci. Model Dev., 17, 275–300, https://doi.org/10.5194/gmd-17-275-2024,https://doi.org/10.5194/gmd-17-275-2024, 2024
Short summary

Cited articles

Altmann, R.: Index reduction for operator differential-algebraic equations in elastodynamics, J. Appl. Math. Mech., 93, 648–664, https://doi.org/10.1002/zamm.201200125, 2013. a
Altmann, R. and Heiland, J.: Finite element decomposition and minimal extension for flow equations, ESAIM Math. Model. Numer. Anal., 49, 1489–1509, https://doi.org/10.1051/m2an/2015029, 2015. a
Appelo, C. A. J., Parkhurst, D. L., and Post, V. E. A.: Equations for calculating hydrogeochemical reactions of minerals and gases such as CO2 at high pressures and temperatures, Geochim. Cosmochim. Ac., 125, 49–67, https://doi.org/10.1016/j.gca.2013.10.003, 2013. a, b
Beisman, J. J., Maxwell, R. M., Navarre-Sitchler, A. K., Steefel, C. I., and Molins, S.: ParCrunchFlow: an efficient, parallel reactive transport simulation tool for physically and chemically heterogeneous saturated subsurface environments, Comput. Geosci., 19, 403–422, https://doi.org/10.1007/s10596-015-9475-x, 2015. a
Chen, T. and Guestrin, C.: XGBoost: A Scalable Tree Boosting System, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, https://doi.org/10.1145/2939672.2939785, 2016. a
Download
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.