Articles | Volume 15, issue 6
Geosci. Model Dev., 15, 2423–2439, 2022
https://doi.org/10.5194/gmd-15-2423-2022
Geosci. Model Dev., 15, 2423–2439, 2022
https://doi.org/10.5194/gmd-15-2423-2022
Model description paper
21 Mar 2022
Model description paper | 21 Mar 2022

Flow-Py v1.0: a customizable, open-source simulation tool to estimate runout and intensity of gravitational mass flows

Christopher J. L. D'Amboise et al.

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Cited articles

Ancey, C., Meunier, M., and Richard, D.: Inverse problem in avalanche dynamics models, Water Resour. Res., 39, 1099, https://doi.org/10.1029/2002WR001749, 2003. a
Bakkehøi, S., Domaas, U., and Lied, K.: Calculation of snow avalanche runout distance, Ann. Glaciol., 4, 24–29, 1983. a, b
Barbolini, M., Gruber, U., Keylock, C. J., Naaim, M., and Savi, F.: Application of statistical and hydraulic-continuum dense-snow avalanche models to five real European sites, Cold Reg. Sci. Technol., 31, 133–149, 2000. a
Barbolini, M., Pagliardi, M., Ferro, F., and Corradeghini, P.: Avalanche hazard mapping over large undocumented areas, Nat. Hazards, 56, 451–464, 2011. a, b, c
Brenning, A.: Spatial prediction models for landslide hazards: review, comparison and evaluation, Nat. Hazards Earth Sys., 5, 853–862, 2005. a
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The term gravitational mass flow (GMF) covers various natural hazard processes such as snow avalanches, rockfall, landslides, and debris flows. Here we present the open-source GMF simulation tool Flow-Py. The model equations are based on simple geometrical relations in three-dimensional terrain. We show that Flow-Py is an educational, innovative GMF simulation tool with three computational experiments: 1. validation of implementation, 2. performance, and 3. expandability.