135 citations as recorded by crossref.

1. Spatial transferability of the physically based model TRIGRS using parameter ensembles L. de Vugt et al. https://doi.org/10.1002/esp.5770
2. Geotechnical and geophysical property models of soil-covered slopes prone to landsliding. The case study of the Ischia Island (southern Italy) R. Di Maio et al. https://doi.org/10.1016/j.catena.2024.108509
3. Mapping method of rainfall-induced landslide hazards by infiltration and slope stability analysis N. Dolojan et al. https://doi.org/10.1007/s10346-020-01617-x
4. Coupled prediction of flood response and debris flow initiation during warm- and cold-season events in the Southern Appalachians, USA J. Tao & A. Barros https://doi.org/10.5194/hess-18-367-2014
5. Root Reinforcement in Slope Stability Models: A Review E. Masi et al. https://doi.org/10.3390/geosciences11050212
6. Understanding shallow landslides in Campos do Jordão municipality – Brazil: disentangling the anthropic effects from natural causes in the disaster of 2000 R. Mendes et al. https://doi.org/10.5194/nhess-18-15-2018
7. Updating EWS rainfall thresholds for the triggering of landslides A. Rosi et al. https://doi.org/10.1007/s11069-015-1717-7
8. A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale S. Zhang et al. https://doi.org/10.5194/nhess-18-969-2018
9. Formulation of landslide risk scenarios using underground monitoring data and numerical models: conceptual approach, analysis, and evolution of a case study in Southern Italy A. Segalini et al. https://doi.org/10.1007/s10346-019-01137-3
10. Analysis of Rainfall Infiltration and Improvement of the Analytical Solution of Safety Factors on Unsaturated Inner Dump Slopes: A Case Study Z. Wang et al. https://doi.org/10.3390/pr10112407
11. Deterministic Physically Based Distributed Models for Rainfall-Induced Shallow Landslides G. Sannino et al. https://doi.org/10.3390/geosciences14100255
12. Hazard prediction modeling for typhoon-triggered shallow landslides by integrating physically-based model and extreme rainfall analysis T. Zeng et al. https://doi.org/10.1007/s10064-025-04371-3
13. Brief communication "A prototype forecasting chain for rainfall induced shallow landslides" P. Mercogliano et al. https://doi.org/10.5194/nhess-13-771-2013
14. Spatio-temporal variability of landslides as indicator of climate change impact: Towards an Italian national scale integrated procedure for the rainfall role analysis in landslide dynamics M. Delchiaro et al. https://doi.org/10.1016/j.ijdrr.2026.106252
15. Technical Note: An operational landslide early warning system at regional scale based on space–time-variable rainfall thresholds S. Segoni et al. https://doi.org/10.5194/nhess-15-853-2015
16. Landslide hazard prediction under an extreme rainfall scenario by considering multiple timescale rainfalls and effective recharge Z. Guo et al. https://doi.org/10.1080/17499518.2025.2570863
17. FSLAM: A QGIS plugin for fast regional susceptibility assessment of rainfall-induced landslides Z. Guo et al. https://doi.org/10.1016/j.envsoft.2022.105354
18. Spatial modeling of pyroclastic cover deposit thickness (depth to bedrock) in peri‐volcanic areas of Campania (southern Italy) M. Del Soldato et al. https://doi.org/10.1002/esp.4350
19. Modeling the spatial occurrence of shallow landslides triggered by typhoons K. Chang et al. https://doi.org/10.1016/j.geomorph.2013.11.020
20. Extended Residual-State Creep Test and Its Application for Landslide Stability Assessment D. Bhat et al. https://doi.org/10.3390/ma14081968
21. A review on spatial, temporal and magnitude prediction of landslide hazard A. Tyagi et al. https://doi.org/10.1016/j.jaesx.2022.100099
22. 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
23. Indirect root distribution characterization using electrical resistivity tomography in different soil conditions Y. Giambastiani et al. https://doi.org/10.1016/j.ufug.2021.127442
24. Critical Continuous Rainfall Map for Forecasting Shallow Landslide Initiations in Busan, Korea J. Park et al. https://doi.org/10.3390/w12092404
25. Soil characterization for shallow landslides modeling: a case study in the Northern Apennines (Central Italy) V. Tofani et al. https://doi.org/10.1007/s10346-017-0809-8
26. A simplified semi-quantitative procedure based on the SLIP model for landslide risk assessment: the case study of Gioiosa Marea (Sicily, Italy) M. Gatto et al. https://doi.org/10.1007/s10346-023-02040-8
27. Landslides Triggered by the 2016 Heavy Rainfall Event in Sanming, Fujian Province: Distribution Pattern Analysis and Spatio-Temporal Susceptibility Assessment S. Ma et al. https://doi.org/10.3390/rs15112738
28. Spatio-Temporal Prediction of Three-Dimensional Stability of Highway Shallow Landslide in Southeast Tibet Based on TRIGRS and Scoops3D Coupling Model J. Mao et al. https://doi.org/10.3390/w16091207
29. Insights Gained from the Review of Landslide Susceptibility Assessment Studies in Italy S. Segoni et al. https://doi.org/10.3390/rs16234491
30. Event-Based Landslide Modeling in the Styrian Basin, Austria: Accounting for Time-Varying Rainfall and Land Cover R. Knevels et al. https://doi.org/10.3390/geosciences10060217
31. Department of Earth Sciences, University of Florence N. Casagli & V. Tofani https://doi.org/10.1007/s10346-019-01226-3
32. SHIA_Landslide: a distributed conceptual and physically based model to forecast the temporal and spatial occurrence of shallow landslides triggered by rainfall in tropical and mountainous basins E. Aristizábal et al. https://doi.org/10.1007/s10346-015-0580-7
33. Web data mining for automatic inventory of geohazards at national scale A. Battistini et al. https://doi.org/10.1016/j.apgeog.2013.06.012
34. Towards a National-Scale Dataset of Geotechnical and Hydrological Soil Parameters for Shallow Landslide Modeling P. Vannocci et al. https://doi.org/10.3390/data7030037
35. Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility P. Lima et al. https://doi.org/10.1007/s11629-021-7254-9
36. ALICE (Assessment of Landslides Induced by Climatic Events): A single tool to integrate shallow and deep landslides for susceptibility and hazard assessment R. Vandromme et al. https://doi.org/10.1016/j.geomorph.2020.107307
37. Insight from a Physical-Based Model for the Triggering Mechanism of Loess Landslides Induced by the 2013 Tianshui Heavy Rainfall Event S. Ma et al. https://doi.org/10.3390/w15030443
38. Towards a landslide early warning system for South Africa: Model coupling and evaluation J. van Tol & J. Kotzé https://doi.org/10.17159/sajs.2026/22201
39. Application of a physically based model to forecast shallow landslides at a regional scale T. Salvatici et al. https://doi.org/10.5194/nhess-18-1919-2018
40. A Tool for the Automatic Aggregation and Validation of the Results of Physically Based Distributed Slope Stability Models M. Bulzinetti et al. https://doi.org/10.3390/w13172313
41. PHyL v1.0: A parallel, flexible, and advanced software for hydrological and slope stability modeling at a regional scale G. Chen et al. https://doi.org/10.1016/j.envsoft.2023.105882
42. Space-time prediction of rainfall-induced shallow landslides through Artificial Neural Networks in comparison with the SLIP model M. Gatto et al. https://doi.org/10.1016/j.enggeo.2024.107822
43. Early warning of snow-caused disasters in pastoral areas on the Tibetan Plateau W. Wang et al. https://doi.org/10.5194/nhess-13-1411-2013
44. Strategies to improve the explanatory power of a dynamic slope stability model by enhancing land cover parameterisation and model complexity E. Schmaltz et al. https://doi.org/10.1002/esp.4570
45. Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale V. Medina et al. https://doi.org/10.1016/j.catena.2021.105213
46. Forecasting the time of failure of landslides at slope-scale: A literature review E. Intrieri et al. https://doi.org/10.1016/j.earscirev.2019.03.019
47. Field and numerical investigations on triggering mechanism in typical rainfall-induced shallow landslides: a case study in the Ren River catchment, China X. Wei et al. https://doi.org/10.1007/s11069-020-04075-9
48. Shifting from traditional landslide occurrence modeling to scenario estimation with a “glass-box” machine learning F. Caleca et al. https://doi.org/10.1016/j.scitotenv.2024.175277
49. Assessment of rainfall-induced landslide susceptibility at the regional scale using a physically based model and fuzzy-based Monte Carlo simulation H. Park et al. https://doi.org/10.1007/s10346-018-01125-z
50. Applicability and performance of deterministic and probabilistic physically based landslide modeling in a data-scarce environment of the Colombian Andes R. Marin et al. https://doi.org/10.1016/j.jsames.2021.103175
51. Influence of subsurface flow by Lidar DEMs and physical soil strength considering a simple hydrologic concept for shallow landslide instability mapping S. Kim et al. https://doi.org/10.1016/j.catena.2019.104137
52. Mapping the susceptibility of rain-triggered lahars at Vulcano island (Italy) combining field characterization, geotechnical analysis, and numerical modelling V. Baumann et al. https://doi.org/10.5194/nhess-19-2421-2019
53. Assessment of a Dynamic Physically Based Slope Stability Model to Evaluate Timing and Distribution of Rainfall-Induced Shallow Landslides J. Thomas et al. https://doi.org/10.3390/ijgi12030105
54. Development of shallow landslide hazard maps by combining continuous rainfall scenarios with physically based model J. Park et al. https://doi.org/10.14770/jgsk.2022.58.4.489
55. Decoding vegetation's role in landslide susceptibility mapping: An integrated review of techniques and future directions Y. Li & W. Duan https://doi.org/10.1016/j.bgtech.2023.100056
56. Breaking Limits of Remote Sensing by Deep Learning From Simulated Data for Flood and Debris-Flow Mapping N. Yokoya et al. https://doi.org/10.1109/TGRS.2020.3035469
57. Snow accumulation/melting model (SAMM) for integrated use in regional scale landslide early warning systems G. Martelloni et al. https://doi.org/10.5194/hess-17-1229-2013
58. Research on the Impact of Regional-Scale Soil Mechanics Parameter Disturbances on Rainfall Landslides Warning K. Wang et al. https://doi.org/10.3390/geosciences15120449
59. Requirements for Flood-Driven Forecasting Systems for Small and Medium-Sized Catchments in Germany J. Leandro et al. https://doi.org/10.3390/w17223283
60. Rainfall-induced landslide prediction models, part ii: deterministic physical and phenomenologically models K. Ebrahim et al. https://doi.org/10.1007/s10064-024-03563-7
61. Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico R. Baum et al. https://doi.org/10.5194/nhess-24-1579-2024
62. A 3D model for rain-induced landslides based on molecular dynamics with fractal and fractional water diffusion G. Martelloni et al. https://doi.org/10.1016/j.cnsns.2017.03.014
63. Physically Based and Data-Driven Models for Landslide Susceptibility Assessment: Principles, Applications, and Challenges C. Ye et al. https://doi.org/10.3390/rs17132280
64. Efficient probabilistic assessment of rainfall-induced landslides involving complex hydrological simulations Z. Deng et al. https://doi.org/10.1016/j.jrmge.2026.03.032
65. Slope stability models for rainfall-induced lahars during long-lasting eruptions V. Baumann et al. https://doi.org/10.1016/j.jvolgeores.2018.06.018
66. Integrated multihazard study combining qualitative and quantitative analyses of floods, landslides, and debris flows: A case study on the impacts of Typhoon Yun-Yeung on Iwaki City, Fukushima N. Dolojan et al. https://doi.org/10.1016/j.ijdrr.2025.105647
67. State-of-the-art: parametrization of hydrological and mechanical reinforcement effects of vegetation in slope stability models for shallow landslides A. DiBiagio et al. https://doi.org/10.1007/s10346-024-02300-1
68. Modeling shallow landslides and root reinforcement: A review I. Murgia et al. https://doi.org/10.1016/j.ecoleng.2022.106671
69. Landslide hazard assessment in parts of upper Bhagirathi Basin: a comparative study using earth observation and machine learning based initiatives in perspective of slope instability P. Mohan et al. https://doi.org/10.1007/s10064-025-04544-0
70. Prediction of the instability probability for rainfall induced landslides: the effect of morphological differences in geomorphology within mapping units K. Wang et al. https://doi.org/10.1007/s11629-022-7789-4
71. Characterizing the Distribution Pattern and a Physically Based Susceptibility Assessment of Shallow Landslides Triggered by the 2019 Heavy Rainfall Event in Longchuan County, Guangdong Province, China S. Ma et al. https://doi.org/10.3390/rs14174257
72. Rainfall thresholds for rainfall-induced landslides in Slovenia A. Rosi et al. https://doi.org/10.1007/s10346-016-0733-3
73. Study on the influence of spatial variability of soil strength parameters on reliability and slip surfaces of cofferdam slope reinforced by geosynthetic reinforcement Y. Wan et al. https://doi.org/10.1080/1064119X.2023.2169650
74. Development and validation of the terrain stability model for assessing landslide instability during heavy rain infiltration A. Gutiérrez-Martín et al. https://doi.org/10.5194/nhess-19-721-2019
75. Simulation of Debris-Flow Runout Near a Construction Site in Korea B. Chae et al. https://doi.org/10.3390/app10176079
76. Landslide Susceptibility Mapping Using Machine Learning: A Danish Case Study A. Ageenko et al. https://doi.org/10.3390/ijgi11060324
77. 土体-大气相互作用下土质边坡稳定性研究 C. Sun et al. https://doi.org/10.3799/dqkx.2022.275
78. Bridging data gaps in landslide early warning: Physics-derived rainfall thresholds under rainfall uncertainty H. Zou et al. https://doi.org/10.1016/j.enggeo.2026.108608
79. Landslides in the Mountain Region of Rio de Janeiro: A Proposal for the Semi-Automated Definition of Multiple Rainfall Thresholds A. Rosi et al. https://doi.org/10.3390/geosciences9050203
80. Development of a coupled hydrological-geotechnical framework for rainfall-induced landslides prediction X. He et al. https://doi.org/10.1016/j.jhydrol.2016.10.016
81. Geotechnical and hydrological characterization of hillslope deposits for regional landslide prediction modeling G. Bicocchi et al. https://doi.org/10.1007/s10064-018-01449-z
82. Temporal prediction modeling for rainfall-induced shallow landslide hazards using extreme value distribution J. Lee et al. https://doi.org/10.1007/s10346-020-01502-7
83. LAND-SUITE V1.0: a suite of tools for statistically based landslide susceptibility zonation M. Rossi et al. https://doi.org/10.5194/gmd-15-5651-2022
84. A comparison of linear and nonlinear model performance of shia_landslide: a forecasting model for rainfall-induced landslides E. Aristizábal-Giraldo et al. https://doi.org/10.17533/udea.redin.n80a09
85. Physically Based Susceptibility Assessment of Rainfall-Induced Shallow Landslides Using a Fuzzy Point Estimate Method H. Park et al. https://doi.org/10.3390/rs9050487
86. Generating soil thickness maps by means of geomorphological-empirical approach and random forest algorithm in Wanzhou County, Three Gorges Reservoir T. Xiao et al. https://doi.org/10.1016/j.gsf.2022.101514
87. Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management Z. Guo et al. https://doi.org/10.1016/j.gsf.2021.101249
88. Landslide Geomorphology: Pattern, Process and Stability H. Qiu & Y. Wei https://doi.org/10.1007/s12583-024-0131-z
89. Probabilistic landslide ensemble prediction systems: lessons to be learned from hydrology E. Canli et al. https://doi.org/10.5194/nhess-18-2183-2018
90. Effects of soil heterogeneity on susceptibility of shallow landslides E. Oguz et al. https://doi.org/10.1007/s10346-021-01738-x
91. A prototype adaptive mesh generator for enhancing computational efficiency and accuracy in physically-based modeling of flood-landslide hazards G. Chen et al. https://doi.org/10.1016/j.envsoft.2025.106458
92. Exploring the Use of Pattern Classification Approaches for the Recognition of Landslide-Triggering Rainfalls A. Rosi https://doi.org/10.3390/su152015145
93. Constructing physical-based rainfall landslides prediction model: insights from rainfall threshold curves database of slope units K. Wang et al. https://doi.org/10.5194/nhess-26-2367-2026
94. Hydrologic-geotechnical modelling of shallow landslide and flood hazards caused by heavy rainfall N. Dolojan et al. https://doi.org/10.1016/j.enggeo.2023.107184
95. Identification of Potential Landslide Susceptible Area in the Lesser Himalayan Terrain of Nepal K. Pokhrel & B. Bhandari https://doi.org/10.4236/gep.2019.711003
96. Double-threshold validation tool (DTVT): From landslide hazard maps to operational early warning systems N. Nocentini et al. https://doi.org/10.1016/j.ijdrr.2025.105786
97. Shallow landslides and vegetation at the catchment scale: A perspective C. Phillips et al. https://doi.org/10.1016/j.ecoleng.2021.106436
98. State-of-the-art on development and operation of landslide early warning system for climate change response Y. Song & J. Park https://doi.org/10.14770/jgsk.2022.58.4.509
99. Inclusion of Nature-Based Solution in the Evaluation of Slope Stability in Large Areas L. Zedek et al. https://doi.org/10.3390/land13030372
100. Quantitative comparison between two different methodologies to define rainfall thresholds for landslide forecasting D. Lagomarsino et al. https://doi.org/10.5194/nhess-15-2413-2015
101. Exploiting the land use to predict shallow landslide susceptibility: A probabilistic implementation of LAPSUS-LS A. Giarola et al. https://doi.org/10.1016/j.catena.2024.108437
102. Preparing first-time slope failures hazard maps: from pixel-based to slope unit-based G. Domènech et al. https://doi.org/10.1007/s10346-019-01279-4
103. Quantification of climate change impact on rainfall-induced shallow landslide susceptibility: a case study in central Norway E. Oguz et al. https://doi.org/10.1080/17499518.2023.2283848
104. Slope stability modelling of shallow landslides at a regional scale N. Brilli et al. https://doi.org/10.1186/s40677-025-00323-x
105. Integration of rainfall thresholds and susceptibility maps in the Emilia Romagna (Italy) regional-scale landslide warning system S. Segoni et al. https://doi.org/10.1007/s10346-014-0502-0
106. A field-based thickness measurement dataset of fallout pyroclastic deposits in the peri-volcanic areas of Campania (Italy): statistical combination of different predictions for spatial estimation of thickness P. Ebrahimi et al. https://doi.org/10.5194/essd-16-4161-2024
107. Optimising landslide initiation modelling with high-resolution saturation prediction based on soil moisture monitoring data T. Halter et al. https://doi.org/10.1007/s10346-024-02304-x
108. Applications of UAV in landslide research: a review B. Chen et al. https://doi.org/10.1007/s10346-025-02547-2
109. Combining Spatial Models for Shallow Landslides and Debris-Flows Prediction R. Gomes et al. https://doi.org/10.3390/rs5052219
110. The effect of DEM resolution on the computation of the factor of safety using an infinite slope model M. Fuchs et al. https://doi.org/10.1016/j.geomorph.2014.07.015
111. Evolution and critical evaluation of deterministic physically based rainfall-induced landslide susceptibility mapping: a mixed review R. Sachinthaka et al. https://doi.org/10.1007/s11069-025-07634-0
112. Combined influence of rainfall and groundwater on the stability of an inner dump slope Z. Wang et al. https://doi.org/10.1007/s11069-023-06052-4
113. Analysing the relationship between rainfalls and landslides to define a mosaic of triggering thresholds for regional-scale warning systems S. Segoni et al. https://doi.org/10.5194/nhess-14-2637-2014
114. Probabilistic prediction of shallow landslides through a generalized linear mixed-effects model integrating geological and rainfall factors Z. Liao et al. https://doi.org/10.1080/19475705.2025.2575356
115. Physically-based catchment-scale prediction of slope failure volume and geometry B. Van den Bout et al. https://doi.org/10.1016/j.enggeo.2020.105942
116. X-SLIP: A SLIP-based multi-approach algorithm to predict the spatial–temporal triggering of rainfall-induced shallow landslides over large areas M. Placido Antonio Gatto & L. Montrasio https://doi.org/10.1016/j.compgeo.2022.105175
117. Optimization of rainfall thresholds for landslide early warning through false alarm reduction and a multi-source validation N. Nocentini et al. https://doi.org/10.1007/s10346-023-02176-7
118. Estimating rainfall threshold and temporal probability for landslide occurrences in Darjeeling Himalayas A. Dikshit et al. https://doi.org/10.1007/s12303-020-0001-3
119. Effects of roots cohesion on regional distributed slope stability modelling E. Masi et al. https://doi.org/10.1016/j.catena.2022.106853
120. Technical Note: Use of remote sensing for landslide studies in Europe V. Tofani et al. https://doi.org/10.5194/nhess-13-299-2013
121. MAT.TRIGRS (V1.0): A new open-source tool for predicting spatiotemporal distribution of rainfall-induced landslides S. Ma et al. https://doi.org/10.1016/j.nhres.2021.11.001
122. A Landslide Monitoring System for Natural Terrain in Korea: Development and Application in Hazard Evaluations Y. Song et al. https://doi.org/10.3390/s21093040
123. Multi-failure numerical analysis of rainfall-triggered landslides at the basin-scale D. Calpa et al. https://doi.org/10.1016/j.compgeo.2025.107622
124. A satellite-based global landslide model A. Farahmand & A. AghaKouchak https://doi.org/10.5194/nhess-13-1259-2013
125. Incorporating Rainfall Forecast Data in X-SLIP Platform to Predict the Triggering of Rainfall-Induced Shallow Landslides in Real Time M. Gatto https://doi.org/10.3390/geosciences13070215
126. Combination of Rainfall Thresholds and Susceptibility Maps for Dynamic Landslide Hazard Assessment at Regional Scale S. Segoni et al. https://doi.org/10.3389/feart.2018.00085
127. A grid-based physical model to analyze the stability of slope unit S. Zhang et al. https://doi.org/10.1016/j.geomorph.2021.107887
128. Multiseasonal probabilistic slope stability analysis of a large area of unsaturated pyroclastic soils S. Cuomo et al. https://doi.org/10.1007/s10346-020-01561-w
129. Landslides triggered by rainfall: A semi-automated procedure to define consistent intensity–duration thresholds S. Segoni et al. https://doi.org/10.1016/j.cageo.2013.10.009
130. Site-specific to local-scale shallow landslides triggering zones assessment using TRIGRS M. Bordoni et al. https://doi.org/10.5194/nhess-15-1025-2015
131. A coupled hydrological-geotechnical framework for forecasting shallow landslide hazard—a case study in Halong City, Vietnam N. Ha et al. https://doi.org/10.1007/s10346-020-01385-8
132. A novel approach for the computation of soil slope stability in distributed hydrologic applications R. Bonomelli et al. https://doi.org/10.1002/esp.70122
133. Calibration scenarios for physically based rainfall-induced landslide modelling at regional scale. Application to Vall d’Aran (Central Pyrenees, Spain) F. Asurza et al. https://doi.org/10.1007/s10064-025-04697-y
134. Validation of landslide hazard models using a semantic engine on online news A. Battistini et al. https://doi.org/10.1016/j.apgeog.2017.03.003
135. Regional hazard assessment of excavation-disturbed translational rockslides in monoclinal strata: a probabilistic framework integrating failure extent and runout L. Yang et al. https://doi.org/10.1007/s10064-026-05273-8