49 citations as recorded by crossref.

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4. From back-analysis to run-out prediction: a case study in the Western Italian Alps M. Pirulli et al. https://doi.org/10.1007/s10346-010-0248-2
5. Comparison of two depth-averaged numerical models for debris flow runout estimation F. Vagnon et al. https://doi.org/10.1139/cgj-2017-0455
6. Granular and particle-laden flows: from laboratory experiments to field observations R. Delannay et al. https://doi.org/10.1088/1361-6463/50/5/053001
7. Coupling Depth-Averaged and 3D numerical models to study debris flow: Saint-Vincent event A. Pasqua et al. https://doi.org/10.1051/e3sconf/202341502015
8. Collapse of granular–cohesive soil mixtures on a horizontal plane L. Brezzi et al. https://doi.org/10.1007/s11440-018-0725-7
9. Modelling of flowslides and debris avalanches in natural and engineered slopes: a review S. Cuomo https://doi.org/10.1186/s40677-019-0133-9
10. A novel approach to evaluate and compare computational snow avalanche simulation J. Fischer https://doi.org/10.5194/nhess-13-1655-2013
11. Parameterization of a numerical 2-D debris flow model with entrainment: a case study of the Faucon catchment, Southern French Alps H. Hussin et al. https://doi.org/10.5194/nhess-12-3075-2012
12. Description and numerical modelling of the October 2000 Nora debris flow, Northwestern Italian Alps M. Pirulli & F. Marco https://doi.org/10.1139/T09-082
13. Extension of Iber for Simulating Non–Newtonian Shallow Flows: Mine-Tailings Spill Propagation Modelling M. Sanz-Ramos et al. https://doi.org/10.3390/w16142039
14. Predicting Debris Flow Runout with SFLOW Model: Case Study of Datong and Taicun Gullies, Lijiang, China Q. Mehmood et al. https://doi.org/10.1007/s10706-024-03020-y
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19. A multivariate statistical method for susceptibility analysis of debris flow in southwestern China F. Ji et al. https://doi.org/10.5194/nhess-20-1321-2020
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21. An overview of debris-flow mathematical modelling M. Trujillo-Vela et al. https://doi.org/10.1016/j.earscirev.2022.104135
22. An analysis of rheological models for lahar modelling with Iber M. Sanz-Ramos et al. https://doi.org/10.22201/igc.20072902e.2025.3.1882
23. Uniaxial compressive strength and crack propagation of debris-ice mixtures: Insights from experiments and particle-based modeling G. Cui et al. https://doi.org/10.1016/j.enggeo.2025.108253
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26. Comparison of depth-averaged and 3D models for dense granular flows A. Pasqua et al. https://doi.org/10.1088/1755-1315/833/1/012101
27. Combining Spatial Models for Shallow Landslides and Debris-Flows Prediction R. Gomes et al. https://doi.org/10.3390/rs5052219
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29. A robust debris-flow and GLOF risk management strategy for a data-scarce catchment in Santa Teresa, Peru H. Frey et al. https://doi.org/10.1007/s10346-015-0669-z
30. Continuum modelling of flow-structure interaction during the 2009 Cancia debris flow (Italian Dolomites) M. Pirulli et al. https://doi.org/10.1016/j.enggeo.2026.108971
31. Modeling the formation of bright slope deposits associated with gullies in Hale Crater, Mars: Implications for recent liquid water K. Kolb et al. https://doi.org/10.1016/j.icarus.2009.09.009
32. Geotechnical and rheological characteristics of waste rock deposits influencing potential debris flow occurrence at the abandoned Imgi Mine, Korea S. Jeong https://doi.org/10.1007/s12665-014-3991-1
33. Evaluation of different erosion–entrainment models in debris-flow simulation S. Lee et al. https://doi.org/10.1007/s10346-022-01901-y
34. A new data assimilation procedure to develop a debris flow run-out model L. Brezzi et al. https://doi.org/10.1007/s10346-015-0625-y
35. A multiscale framework for simulating landslide runout and impact with barriers A. Pasqua et al. https://doi.org/10.1139/cgj-2025-0034
36. Characterization of wood‐laden flows in rivers V. Ruiz‐Villanueva et al. https://doi.org/10.1002/esp.4603
37. Advance survey and modelling technologies for the study of the slope stability in an Alpine basin A. Ferrero et al. https://doi.org/10.1007/s11069-014-1490-z
38. Modeling the runout behavior of the July 23rd, 2015 Cancia debris-flow event using two numerical models Z. Qiao et al. https://doi.org/10.1051/e3sconf/202341505019
39. El rol de los términos de fricción y cohesión en la modelización bidimensional de fluidos no Newtonianos: avalanchas de nieve densa M. Sanz-Ramos et al. https://doi.org/10.4995/ia.2023.20080
40. Debris flow simulation 2D (DFS 2D): Numerical modelling of debris flows and calibration of friction parameters M. Abraham et al. https://doi.org/10.1016/j.jrmge.2022.01.004
41. Deciphering controls for debris‐flow erosion derived from a LiDAR‐recorded extreme event and a calibrated numerical model (Roßbichelbach, Germany) A. Dietrich & M. Krautblatter https://doi.org/10.1002/esp.4578
42. Rainfall-induced runoff and debris flows: modelling the Cervinara 1999 cascade flow-like mass movements S. Cuomo et al. https://doi.org/10.1007/s10064-025-04283-2
43. A two‐phase mechanical model for rock‐ice avalanches S. Pudasaini & M. Krautblatter https://doi.org/10.1002/2014JF003183
44. Debris flow-induced topographic changes: effects of recurrent debris flow initiation C. Chen & Q. Wang https://doi.org/10.1007/s10661-017-6169-y
45. Numerical modelling of dense snow avalanches with a well-balanced scheme based on the 2D shallow water equations M. Sanz-Ramos et al. https://doi.org/10.1017/jog.2023.48
46. Runout modeling and calibration of friction parameters of Kurichermala debris flow, India M. Abraham et al. https://doi.org/10.1007/s10346-020-01540-1
47. Solid-liquid interaction caused by minor wetting in gravel-ice mixtures: A key factor for the mobility of rock-ice avalanches Y. Ren et al. https://doi.org/10.1016/j.enggeo.2021.106072
48. A new method for evaluating stony debris flow rainfall thresholds: the Backward Dynamical Approach G. Rosatti et al. https://doi.org/10.1016/j.heliyon.2019.e01994
49. Evaluation of probabilistic snow avalanche simulation ensembles with Doppler radar observations J. Fischer et al. https://doi.org/10.1016/j.coldregions.2013.09.011