Preprints
https://doi.org/10.5194/egusphere-2024-1191
https://doi.org/10.5194/egusphere-2024-1191
27 May 2024
 | 27 May 2024
Status: this preprint is open for discussion.

Introducing Iterative Model Calibration (IMC) v1.0: A Generalizable Framework for Numerical Model Calibration with a CAESAR-Lisflood Case Study

Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard

Abstract. In geosciences, including hydrology and geomorphology, the reliance on numerical models necessitates the precise calibration of their parameters to effectively translate information from observed to unobserved settings. Traditional calibration techniques, however, are marked by poor generalizability, demanding significant manual labor for data preparation and the calibration process itself. Moreover, the utility of machine learning-based and data-driven approaches is curtailed by the requirement for the numerical model to be differentiable for optimization purposes, which challenges their generalizability across different models. Furthermore, the potential of freely available geomorphological data remains underexploited in existing methodologies. In response to these challenges, we introduce a generalizable framework for calibrating numerical models, with a particular focus on geomorphological models, named Iterative Model Calibration (IMC). This approach efficiently identifies the optimal set of parameters for a given numerical model through a strategy based on a Gaussian neighborhood algorithm. We demonstrate the efficacy of IMC by applying it to the calibration of the widely-used Landscape Evolution Model, CAESAR-Lisflood, achieving high precision. Once calibrated, this model is capable of generating geomorphic data for both retrospective and prospective analyses at various temporal resolutions, and retrospective and prospective analyses at various temporal resolutions, specifically tailored for scenarios such as gully catchment landscape evolution.

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Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard

Status: open (until 22 Jul 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard

Model code and software

IMC calibration codes Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard https://drive.google.com/file/d/1o2Le5Lxf8hDyWmpD9BWeylyQGGzumg8e/view?usp=drive_link

Video supplement

Demonstration videos Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard https://drive.google.com/file/d/1v6JIj8lQ2uIKuglzVByZfF7fJAp0L8oH/view?usp=drive_link

Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard

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Short summary
In geosciences, the reliance on numerical models necessitates the precise calibration of their parameters to effectively translate information from observed to unobserved settings. We introduce a generalizable framework for calibrating numerical models, with a case study of the geomorphological model CAESAR-Lisflood. This approach efficiently identifies the optimal set of parameters for a given numerical model, enabling retrospective and prospective analyses at various temporal resolutions.