Articles | Volume 58
https://doi.org/10.5194/adgeo-58-67-2022
https://doi.org/10.5194/adgeo-58-67-2022
22 Nov 2022
 | 22 Nov 2022

Environmental hazard quantification toolkit based on modular numerical simulations

Morgan Tranter, Svenja Steding, Christopher Otto, Konstantina Pyrgaki, Mansour Hedayatzadeh, Vasilis Sarhosis, Nikolaos Koukouzas, Georgios Louloudis, Christos Roumpos, and Thomas Kempka

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Cited articles

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Chen, T. and Guestrin, C.: XGBoost: A Scalable Tree Boosting System, in: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '16, ACM, New York, NY, USA, 785–794, https://doi.org/10.1145/2939672.2939785, 2016. a, b
Géron, A.: Hands-on Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, O'Reilly Media, ISBN 9781491962268, 2017. a
Goldsim Technology Group: GoldSim User's Guide (Version 14.0), Tech. rep., 2021. a
Short summary
The quantification of the impacts on the environment and human health is a crucial prerequisite for geological sub-surface utilisation projects. With the presented approach, the shortcomings of using conceptually simplified models are substantially reduced, since subsurface complexities are accounted for. The transparency of the assessment basis should generally increase the acceptance of geoengineering projects, considered one of the crucial aspects for geological subsurface utilisation.