Preprints
https://doi.org/10.5194/egusphere-2024-2267
https://doi.org/10.5194/egusphere-2024-2267
18 Sep 2024
 | 18 Sep 2024
Status: this preprint is open for discussion.

Use of simple analytical solutions in the calibration of Shallow Water Equations debris flow models

Riccardo Bonomelli, Marco Pilotti, and Gabriele Farina

Abstract. Modelling debris flow propagation requires numerical models able to describe the main characteristics of the flow, like velocity or inundation extent. Due to the complex physics involved, every numerical model is dependent from a set of parameters whose influence on the results is often not evident. In this contribution we propose simple analytical solutions based on the monophasic Shallow Water Equations for some of the most used rheological models (O'Brien & Julien, Voellmy, Bingham and Bagnold) implemented in monophasic (FLO-2D, RAMMS, HEC-RAS, TELEMAC-2D) and biphasic commercial software (TRENT2D). These simplified solutions and their asymptotic uniform-flow like relationship are useful on one hand to speed up the calibration process, limiting the need to perform multiple simulations with unrealistic set of parameters and on the other hand as a benchmark for existing numerical methods. To further guide the calibration, a Sobol's sensitivity analysis has been performed to highlight which parameters of the considered equations have the most influence on the flow velocity. Finally, as an example of application, the proposed methodology is validated on a real debris flow event occurred in Italy.

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Riccardo Bonomelli, Marco Pilotti, and Gabriele Farina

Status: open (extended)

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Riccardo Bonomelli, Marco Pilotti, and Gabriele Farina
Riccardo Bonomelli, Marco Pilotti, and Gabriele Farina

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Short summary
Debris flows are fundamental components of the hazard in mountain regions and numerical models must be used for the related risk computation. Most existing commercial software strongly conceptualizes the main characteristics of the flow, leading to an inevitable calibration process, that is time-consuming and difficult to accomplish. This contribution offers some physically based solutions to confine the calibration process and to better understand the implications of the selected choice.