Articles | Volume 24, issue 6
https://doi.org/10.5194/hess-24-3189-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-3189-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Jun 2020
Research article |
| 19 Jun 2020
| 19 Jun 2020
Multi-objective calibration by combination of stochastic and gradient-like parameter generation rules – the caRamel algorithm
EDF R&D LNHE – Laboratoire National d'Hydraulique et Environnement, Chatou, 78400, France
Fabrice Zaoui
EDF R&D LNHE – Laboratoire National d'Hydraulique et Environnement, Chatou, 78400, France
Nicolas Le Moine
UMR 7619 Metis (SU/CNRS/EPHE), Sorbonne Université, 4 Place Jussieu, Paris, 75005, France
Frédéric Hendrickx
EDF R&D LNHE – Laboratoire National d'Hydraulique et Environnement, Chatou, 78400, France
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Latest update: 21 Nov 2024
Short summary
Environmental modelling is complex, and models often require the calibration of several parameters that are not able to be directly evaluated from a physical quantity or a field measurement. Based on our experience in hydrological modelling, we propose combining two algorithms to obtain a fast and accurate way of calibrating complex models (many parameters and many objectives). We built an R package, caRamel, so that this multi-objective calibration algorithm can be easily implemented.
Environmental modelling is complex, and models often require the calibration of several...
