111 citations as recorded by crossref.

1. Numerical modelling of rapid, flow-like landslides across 3-D terrains: a Tsunami Squares approach to El Picacho landslide, El Salvador, September 19, 1982 J. Wang et al. https://doi.org/10.1093/gji/ggv095
2. Las ecuaciones de Saint Venant para la modelización de avalanchas de nieve densa M. Sanz-Ramos et al. https://doi.org/10.4995/ia.2020.12302
3. Performance of Artificial Bed-Wetting Parameter in a 1D Coulomb-Type Debris Flow Numerical Model V. Pham https://doi.org/10.48084/etasr.10719
4. A vertically non-uniform temperature approach for the friction term computation in depth-averaged viscoplastic lava flows J. Ortega-Moya et al. https://doi.org/10.1016/j.jcp.2024.113378
5. A debris-flow simulation model for the evaluation of protection structures Y. Tsai https://doi.org/10.1007/s11629-007-0193-2
6. Modelling the 2012 Lahar in a Sector of Jamapa Gorge (Pico de Orizaba Volcano, Mexico) Using RAMMS and Tree-Ring Evidence O. Franco-Ramos et al. https://doi.org/10.3390/w12020333
7. Experimental study on rheologic behaviour of debris flow material R. Kaitna et al. https://doi.org/10.1007/s11440-007-0026-z
8. An integrated procedure to evaluate rheological parameters to model debris flows A. Pellegrino et al. https://doi.org/10.1016/j.enggeo.2015.07.002
9. A 2D finite volume model for bebris flow and its application to events occurred in the Eastern Pyrenees V. MEDINA et al. https://doi.org/10.1016/S1001-6279(09)60006-8
10. Initiation and Flow Conditions of Contemporary Flows in Martian Gullies T. de Haas et al. https://doi.org/10.1029/2018JE005899
11. Influence of flow resistance stresses on debris flow runout S. Lee & C. Song https://doi.org/10.1007/s12665-018-7604-2
12. 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
13. Rheological characteristics of marine sediments from the Ulleung Basin, East Sea to estimate the mobility of submarine landslides S. Jeong et al. https://doi.org/10.1007/s11001-022-09473-1
14. Learning Case Study of a Shallow-Water Model to Assess an Early-Warning System for Fast Alpine Muddy-Debris-Flow A. Pasculli et al. https://doi.org/10.3390/w13060750
15. Novel Discretization Strategies for the 2d Non-Newtonian Resistance Term in Geophysical Shallow Flows S. Martínez-Aranda et al. https://doi.org/10.2139/ssrn.4012414
16. Effect of Solid Volume Concentration on Rheological Properties of Chengdu Clay Slurry X. Ji et al. https://doi.org/10.3390/pr10020425
17. Modelling the Brumadinho tailings dam failure, the subsequent loss of life and how it could have been reduced D. Lumbroso et al. https://doi.org/10.5194/nhess-21-21-2021
18. A high resolution finite volume model for 1D debris flow J. Paik https://doi.org/10.1016/j.jher.2014.03.001
19. Volume estimation of small scale debris flows based on observations of topographic changes using airborne LiDAR DEMs H. Kim et al. https://doi.org/10.1007/s11629-013-2829-8
20. DFLOWZ: A free program to evaluate the area potentially inundated by a debris flow M. Berti & A. Simoni https://doi.org/10.1016/j.cageo.2014.02.002
21. Rheological properties of bauxite residue: the role of tailings gradation and solids concentration S. Kumar & B. Rao https://doi.org/10.1007/s41062-021-00691-x
22. Novel discretization strategies for the 2D non-Newtonian resistance term in geophysical shallow flows S. Martínez-Aranda et al. https://doi.org/10.1016/j.enggeo.2022.106625
23. Back-Analysis of the Abbadia San Salvatore (Mt. Amiata, Italy) Debris Flow of 27–28 July 2019: An Integrated Multidisciplinary Approach to a Challenging Case Study M. Amaddii et al. https://doi.org/10.3390/geosciences12100385
24. Driftwood deposition from debris flows at slit-check dams and fans B. Shrestha et al. https://doi.org/10.1007/s11069-011-9939-9
25. Modeling debris-flow runout patterns on two alpine fans with different dynamic simulation models K. Schraml et al. https://doi.org/10.5194/nhess-15-1483-2015
26. Modeling the effect of sediment concentration on the flow-like behavior of natural debris flow L. Schippa https://doi.org/10.1016/j.ijsrc.2020.03.001
27. Channel flow simulation of a mixture with a full-dimensional generalized quasi two-phase model K. Khattri & S. Pudasaini https://doi.org/10.1016/j.matcom.2019.03.014
28. Bayesian active learning for parameter calibration of landslide run-out models H. Zhao & J. Kowalski https://doi.org/10.1007/s10346-022-01857-z
29. 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
30. Wave Riemann description of friction terms in unsteady shallow flows: Application to water and mud/debris floods J. Murillo & P. García-Navarro https://doi.org/10.1016/j.jcp.2011.11.014
31. New Numerical Simulation Procedure for Large-scale Debris Flows (Kanako-LS) T. UCHIDA et al. https://doi.org/10.13101/ijece.6.58
32. Rheological behavior of dredged slurries at high water contents G. Xu et al. https://doi.org/10.1080/1064119X.2016.1173747
33. Landslide prediction, monitoring and early warning: a concise review of state-of-the-art B. Chae et al. https://doi.org/10.1007/s12303-017-0034-4
34. Evaluation of approaches to calculate debris-flow parameters for hazard assessment M. Hürlimann et al. https://doi.org/10.1016/j.enggeo.2008.03.012
35. Emulator-based global sensitivity analysis for flow-like landslide run-out models H. Zhao et al. https://doi.org/10.1007/s10346-021-01690-w
36. A novel depth-averaged model of landslide over erodible bed using (b, s) coordinates V. Pham et al. https://doi.org/10.1016/j.compgeo.2025.107105
37. Analytic Back Calculation of Debris Flow Damage Incurred to a Masonry Building: The Case of Scaletta Zanclea 2009 Event H. Soleimankhani et al. https://doi.org/10.1051/e3sconf/20160704007
38. GIS-based numerical modelling of debris flow motion across three-dimensional terrain J. Wu et al. https://doi.org/10.1007/s11629-013-2486-y
39. Evaluation of different erosion–entrainment models in debris-flow simulation S. Lee et al. https://doi.org/10.1007/s10346-022-01901-y
40. Numerical modeling of subaerial and submarine landslide-generated tsunami waves—recent advances and future challenges S. Yavari-Ramshe & B. Ataie-Ashtiani https://doi.org/10.1007/s10346-016-0734-2
41. A Variable-Mass Shallow Water SPH framework for debris flow simulation with erosion and entrainment N. Dolojan et al. https://doi.org/10.1016/j.compgeo.2026.108338
42. Empirical prediction of debris‐flow mobility and deposition on fans C. Scheidl & D. Rickenmann https://doi.org/10.1002/esp.1897
43. A multi-source data fusion modeling method for debris flow prevention engineering Q. Xu et al. https://doi.org/10.1007/s11629-020-6332-8
44. An overview of debris-flow mathematical modelling M. Trujillo-Vela et al. https://doi.org/10.1016/j.earscirev.2022.104135
45. Application of FLATModel, a 2D finite volume code, to debris flows in the northeastern part of the Iberian Peninsula V. Medina et al. https://doi.org/10.1007/s10346-007-0102-3
46. Risk Assessment and Control of Geological Hazards in Towns of Complex Mountainous Areas Based on Remote Sensing and Geological Survey W. Ding et al. https://doi.org/10.3390/w15183170
47. A debris-flow alarm system for the Alpine Illgraben catchment: design and performance A. Badoux et al. https://doi.org/10.1007/s11069-008-9303-x
48. Numerical Simulation of Subaerial and Submarine Landslides Using the Finite Volume Method in the Shallow Water Equations with (<i>b</i>, <i>s</i>) Coordinate V. Pham et al. https://doi.org/10.9765/KSCOE.2019.31.4.229
49. Application of Sensitivity Analysis for Process Model Calibration of Natural Hazards C. Chow et al. https://doi.org/10.3390/geosciences8060218
50. Deterministic Landslide Risk Assessment at a Past Landslide Site M. Xie et al. https://doi.org/10.1007/s10706-008-9232-1
51. Assessment and mapping of debris-flow risk in a small catchment in eastern Sicily through integrated numerical simulations and GIS G. Aronica et al. https://doi.org/10.1016/j.pce.2012.04.002
52. Kinematics of flow mass movements on inclined surfaces I. Rendina et al. https://doi.org/10.1007/s00162-019-00486-y
53. Sensitivity and identifiability of rheological parameters in debris flow modeling G. Zegers et al. https://doi.org/10.5194/nhess-20-1919-2020
54. CONSTRUCTION OF A ONE-DIMENSIONAL NUMERICAL MODEL FOR DEBRIS FLOW USING THE FLUX-DIFFERENCE SPLITTING METHOD M. SHIGE-EDA & Y. SOGO https://doi.org/10.2208/jscejj.25-15045
55. Ice-avalanche scenario elaboration and uncertainty propagation in numerical simulation of rock-/ice-avalanche-induced impact waves at Mount Hualcán and Lake 513, Peru Y. Schaub et al. https://doi.org/10.1007/s10346-015-0658-2
56. Fluidization Process in Submarine Landslides: Physical and Numerical Considerations S. Jeong et al. https://doi.org/10.1080/1064119X.2012.676155
57. Back calculation and hazard prediction of a debris flow in Wenchuan meizoseismal area, China B. Liu et al. https://doi.org/10.1007/s10064-021-02127-3
58. Evaluation of Debris Properties Using Numerical Analysis for USGS Debris Flume Tests H. Shin https://doi.org/10.9798/KOSHAM.2015.15.3.215
59. Hydraulic Characteristics of Dam Break Flow by Flow Resistance Stresses and Initial Depths C. Song & S. Lee https://doi.org/10.3741/JKWRA.2014.47.11.1077
60. A landscape scale model to predict post-fire debris flow impact zones T. Keeble et al. https://doi.org/10.1016/j.geomorph.2024.109175
61. Runout and deposit morphology of Bingham fluid as a function of initial volume: implication for debris flow modelling L. Calvo et al. https://doi.org/10.1007/s11069-014-1334-x
62. Limits of sediment transfer in an alpine debris-flow catchment, Illgraben, Switzerland F. Schlunegger et al. https://doi.org/10.1016/j.quascirev.2008.10.025
63. 2D Runout Modelling of Hillslope Debris Flows, Based on Well-Documented Events in Switzerland F. Zimmermann et al. https://doi.org/10.3390/geosciences10020070
64. Dynamic characteristics and erosion effect of a landslide-induced debris flow which occurred in Pingwu, southwest China B. Liu et al. https://doi.org/10.1007/s10064-023-03480-1
65. Detailed observations reveal the genesis and dynamics of destructive debris-flow surges J. Aaron et al. https://doi.org/10.1038/s43247-025-02488-7
66. GIS-based numerical simulation of Amamioshima debris flow in Japan J. Wu et al. https://doi.org/10.1007/s11709-013-0198-6
67. Topographic uncertainty quantification for flow-like landslide models via stochastic simulations H. Zhao & J. Kowalski https://doi.org/10.5194/nhess-20-1441-2020
68. Tsunami Squares modeling of landslide tsunami generation considering the ‘Push Ahead’ effects in slide/water interactions: Theory, experimental validation, and sensitivity analyses J. Wang et al. https://doi.org/10.1016/j.enggeo.2021.106141
69. Comparison of debris flow observations, including fine-sediment grain size and composition and runout model results, at Illgraben, Swiss Alps D. Bolliger et al. https://doi.org/10.5194/nhess-24-1035-2024
70. Debris flow damage incurred to buildings: an in situ back analysis F. Jalayer et al. https://doi.org/10.1111/jfr3.12238
71. Experimental observations of water‐like behavior of initially fluidized, dam break granular flows and their relevance for the propagation of ash‐rich pyroclastic flows O. Roche et al. https://doi.org/10.1029/2008JB005664
72. Visco‐Collisional Scaling Law of Flow Resistance and Its Application in Debris‐Flow Mobility Q. Chen et al. https://doi.org/10.1029/2022JF006712
73. Analysis of debris flow behavior with a one dimensional run-out model incorporating entrainment B. Luna et al. https://doi.org/10.1016/j.enggeo.2011.04.007
74. Depth Averaged Models for Fast Landslide Propagation: Mathematical, Rheological and Numerical Aspects M. Pastor et al. https://doi.org/10.1007/s11831-014-9110-3
75. Experimental study on impact and deposition behaviours of multiple surges of channelized debris flow on a flexible barrier D. Tan et al. https://doi.org/10.1007/s10346-020-01378-7
76. A 1D shallow-flow model for two-layer flows based on FORCE scheme with wet–dry treatment S. Martínez-Aranda et al. https://doi.org/10.2166/hydro.2020.002
77. Experimental investigation on debris flow resistance and entrainment characteristics: effects of the erodible bed with discontinuous grading P. Li et al. https://doi.org/10.1007/s11629-022-7365-y
78. A Simple Deposition Model for Debris Flow Simulation Considering the Erosion–Entrainment–Deposition Process S. Lee et al. https://doi.org/10.3390/rs14081904
79. Predictive simulation of concurrent debris flows: How slope failure locations affect predicted damage K. Yamanoi et al. https://doi.org/10.1111/jfr3.12776
80. SPH model for fluid–structure interaction and its application to debris flow impact estimation Z. Dai et al. https://doi.org/10.1007/s10346-016-0777-4
81. Triggering factors, behavior, and social impact of the January 2021 hail-debris flows at the Central Valley of Chile J. Romero et al. https://doi.org/10.1007/s10346-021-01830-2
82. Modeling the effects of sediment concentration on the propagation of flash floods in an Andean watershed M. Contreras & C. Escauriaza https://doi.org/10.5194/nhess-20-221-2020
83. Numerical Modeling of Downstream Morphological Evolution during Mount Polley Tailings Dam Failure U. Sreekumar et al. https://doi.org/10.1061/JHEND8.HYENG-13497
84. Debris-Flow Hazard Assessment and Methods Applied in Engineering Practice D. RICKENMANN https://doi.org/10.13101/ijece.9.80
85. Coupling Depth-Averaged and 3D numerical models for the simulation of granular flows A. Pasqua et al. https://doi.org/10.1016/j.compgeo.2022.104879
86. Spatial differentiation and risk zonation of debris flow hazards in Tajikistan W. JIA et al. https://doi.org/10.1016/j.regsus.2026.100299
87. Phase classification of laboratory debris flows over a rigid bed based on the relative flow depth and friction coefficients N. HOTTA & K. MIYAMOTO https://doi.org/10.13101/ijece.1.54
88. Numerical simulation of debris-flow behavior incorporating a dynamic method for estimating the entrainment Z. Han et al. https://doi.org/10.1016/j.enggeo.2015.02.009
89. Subaerial sediment-water flows on hillslopes D. Germain & M. Ouellet https://doi.org/10.1177/0309133313507943
90. Influence of the Parameters in Resistance Models for 2D Shallow Water Debris Flow Simulation –A Case Study in Atami City, Japan— R. Nomura et al. https://doi.org/10.20965/jdr.2025.p1062
91. Investigation of accidents in the infrastructure triggered by debris flows in Russia E. Petrova https://doi.org/10.1007/s11069-022-05518-1
92. A Modular, Model, Library Framework (DebrisLib) for Non-Newtonian Geophysical Flows I. Floyd et al. https://doi.org/10.3390/geosciences15070240
93. A modeling methodology to study the tributary-junction alluvial fan connectivity during a debris flow event A. Garcés et al. https://doi.org/10.5194/nhess-22-377-2022
94. Flow resistance variability in debris flows: evaluating equations, critical stress, and scaling from high-resolution field data T. Schöffl et al. https://doi.org/10.1007/s10346-025-02611-x
95. Probabilistic Analysis of Floods from Tailings Dam Failures: A Method to Analyze the Impact of Rheological Parameters on the HEC-RAS Bingham and Herschel-Bulkley Models M. Melo & J. Eleutério https://doi.org/10.3390/w15162866
96. Application of Fuzzy Logic and Fractal Modeling Approach for Groundwater Potential Mapping in Semi-Arid Akka Basin, Southeast Morocco F. Echogdali et al. https://doi.org/10.3390/su141610205
97. Laboratory investigations of the role of biofilms on stream‐bed surfaces in debris‐flow runout Y. Tang et al. https://doi.org/10.1002/esp.4794
98. Debris flow run-out simulation and analysis using a dynamic model R. Melo et al. https://doi.org/10.5194/nhess-18-555-2018
99. Hydrodynamic and topography based cellular automaton model for simulating debris flow run-out extent and entrainment behavior Z. Han et al. https://doi.org/10.1016/j.watres.2021.116872
100. Unravelling the multiphase run-out conditions of a slide-flow mass movement T. van Asch et al. https://doi.org/10.1016/j.geomorph.2014.11.014
101. Hierarchical Statistics-Based Nonlinear Vertical Velocity Distribution of Debris Flow and Its Application in Entrainment Estimation Z. Han et al. https://doi.org/10.3390/w14091352
102. The Application of the Risk Concept to Debris Flow Hazards S. Fuchs et al. https://doi.org/10.1002/geot.200800013
103. Experimental Research on the Dam‐Break Mechanisms of the Jiadanwan Landslide Dam Triggered by the Wenchuan Earthquake in China F. Xu et al. https://doi.org/10.1155/2013/272363
104. Flow Resistance of Inertial Debris Flows D. Berzi & E. Larcan https://doi.org/10.1061/(ASCE)HY.1943-7900.0000664
105. Field Measurements and Numerical Simulation of Debris Flows from Dolomite Slopes Destabilized during the 2005 Kashmir Earthquake, Pakistan Z. Kazmi et al. https://doi.org/10.1080/13632469.2013.873372
106. Characterization of wood‐laden flows in rivers V. Ruiz‐Villanueva et al. https://doi.org/10.1002/esp.4603
107. 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
108. Evaluation concepts to compare observed and simulated deposition areas of mass movements M. Heiser et al. https://doi.org/10.1007/s10596-016-9609-9
109. Characteristics and influencing factors of rainfall-induced landslide and debris flow hazards in Shaanxi Province, China K. Zhang et al. https://doi.org/10.5194/nhess-19-93-2019
110. The failure of the Stava Valley tailings dams (Northern Italy): numerical analysis of the flow dynamics and rheological properties M. Pirulli et al. https://doi.org/10.1186/s40677-016-0066-5
111. Numerical simulation for run-out extent of debris flows using an improved cellular automaton model Z. Han et al. https://doi.org/10.1007/s10064-016-0902-6