42 citations as recorded by crossref.

1. Probabilistic rainfall thresholds of post-earthquake debris flows by integrating observed soil moisture content and calculated water runoff Z. Wei et al. https://doi.org/10.1007/s10346-025-02623-7
2. Constructing rainfall thresholds for debris flow initiation based on critical discharge and S-hydrograph Y. Li et al. https://doi.org/10.1016/j.enggeo.2020.105962
3. Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment S. Dixit et al. https://doi.org/10.5194/nhess-24-465-2024
4. Deep learning prediction of rainfall-driven debris flows considering the similar critical thresholds within comparable background conditions H. Jiang et al. https://doi.org/10.1016/j.envsoft.2024.106130
5. Scale-dependent transition in soil moisture memory and its environmental controls in complex mountain terrain J. Zhang et al. https://doi.org/10.5194/hess-30-3825-2026
6. Variability in the characteristics of extreme rainfall events triggering debris flows: a case study in the Chenyulan watershed, Taiwan J. Chen et al. https://doi.org/10.1007/s11069-020-03938-5
7. The Application of Numerical Simulation in Debris Flow Disaster Early Warning: A Case Study of Shiyang Gully, China H. Zheng et al. https://doi.org/10.3390/land14010181
8. Uncertainty analysis of a rainfall threshold estimate for stony debris flow based on the backward dynamical approach M. Martinengo et al. https://doi.org/10.5194/nhess-21-1769-2021
9. A systematic review on rainfall thresholds for landslides occurrence F. Gonzalez et al. https://doi.org/10.1016/j.heliyon.2023.e23247
10. A probabilistic modeling framework for data-driven forecasting of rainfall-induced debris flows S. Zhang et al. https://doi.org/10.1016/j.jhydrol.2026.135772
11. The twin catastrophic flows occurred in 2014 at Ambato Range (28°09′–28°20′S), Catamarca Province, Northwest Argentina D. Fernández et al. https://doi.org/10.1016/j.jsames.2020.103086
12. Preface: Landslide early warning systems: monitoring systems, rainfall thresholds, warning models, performance evaluation and risk perception S. Segoni et al. https://doi.org/10.5194/nhess-18-3179-2018
13. Influence of the mapping unit for regional landslide early warning systems: comparison between pixels and polygons in Catalonia (NE Spain) R. Palau et al. https://doi.org/10.1007/s10346-020-01425-3
14. Using Tabu Search Adjusted with Urban Sewer Flood Simulation to Improve Pluvial Flood Warning via Rainfall Thresholds H. Liao et al. https://doi.org/10.3390/w11020348
15. Urban pluvial flooding prediction by machine learning approaches – a case study of Shenzhen city, China Q. Ke et al. https://doi.org/10.1016/j.advwatres.2020.103719
16. Study on meteorological risk early warning for landslides based on analysis of extreme rainfall-induced clustering landslide events: a case of Bailong River Basin in China S. Liu et al. https://doi.org/10.1007/s11069-025-07926-5
17. Definition of Rainfall Thresholds for Landslides Using Unbalanced Datasets: Two Case Studies in Shaanxi Province, China S. Zhang et al. https://doi.org/10.3390/w15061058
18. Rainfall Warning Model for Rainfall-Triggered Channelized Debris Flow Based on Physical Model Test—A Case Study of Laomao Mountain Debris Flow in Dalian City Y. Wang et al. https://doi.org/10.3390/w13081083
19. Research Progress of Initial Mechanism on Debris Flow and Related Discrimination Methods: A Review J. Du et al. https://doi.org/10.3389/feart.2021.629567
20. Constructing regional catchment-specific triggering threshold for runoff-generated debris flows: a case study in the Bailong River Y. Huang et al. https://doi.org/10.1080/19475705.2025.2574301
21. Evaluation of Rainfall-Triggered Debris Flows under the Impact of Extreme Events: A Chenyulan Watershed Case Study, Taiwan J. Chen & W. Huang https://doi.org/10.3390/w13162201
22. A review of recent earthquake-induced landslides on the Tibetan Plateau B. Zhao et al. https://doi.org/10.1016/j.earscirev.2023.104534
23. Early warning of debris flow using optimized self-organizing feature mapping network X. Wang et al. https://doi.org/10.2166/ws.2020.142
24. Validation and potential forecast use of a debris-flow rainfall threshold calibrated with the Backward Dynamical Approach M. Martinengo et al. https://doi.org/10.1016/j.geomorph.2022.108519
25. Torrential Hazard Prevention in Alpine Small Basin through Historical, Empirical and Geomorphological Cross Analysis in NW Italy L. Turconi et al. https://doi.org/10.3390/land11050699
26. Modelamiento numérico de un flujo de escombros asociado a una rotura de presa en la subcuenca Quillcay, Áncash, Perú A. Díaz-Salas et al. https://doi.org/10.54139/revinguc.v28i1.4
27. Frequent dry-wet cycles promote debris flow occurrence: Insights from 40 years of data in subtropical monsoon region of Sichuan, China J. Li et al. https://doi.org/10.1016/j.catena.2024.107888
28. Assessment of Potential Landslide Scenarios Using Morphometry, Geomorphological Constraints, and Run-Out Analysis: A Case Study from Central Apennines (Italy) G. Paglia et al. https://doi.org/10.3390/land14112109
29. Quantitative assessment of the complexity of talus slope morphodynamics using multi-temporal data from terrestrial laser scanning (Tatra Mts., Poland) Z. Rączkowska & J. Cebulski https://doi.org/10.1016/j.catena.2021.105792
30. Quantifying Debris Flood Deposits in an Alaskan Fjord Using Multitemporal Digital Elevation Models M. Balazs et al. https://doi.org/10.3390/s21061966
31. Evaluating the thresholds for predicting post-earthquake debris flows: Comparison of meteorological, hydro-meteorological and critical discharge approaches Z. Wei et al. https://doi.org/10.1016/j.enggeo.2024.107773
32. Development of Nomogram for Debris Flow Forecasting Based on Critical Accumulated Rainfall in South Korea D. Nam et al. https://doi.org/10.3390/w11102181
33. Experimental study on debris flow initiation X. Liu et al. https://doi.org/10.1007/s10064-019-01618-8
34. Information Entropy Embedded Back Propagation Neural Network Approach for Debris Flows Hazard Assessment Y. Yu & J. Wang https://doi.org/10.1088/1755-1315/453/1/012015
35. Statistical analysis of the relationship between catchment morphometric parameters and debris-flow-triggering rainfall intensity J. Huo et al. https://doi.org/10.1007/s11069-025-07434-6
36. Debris Flow Risk Assessment Based on a Water–Soil Process Model at the Watershed Scale Under Climate Change: A Case Study in a Debris-Flow-Prone Area of Southwest China Q. Li et al. https://doi.org/10.3390/su11113199
37. Identification of rainfall thresholds for debris-flow occurrence through field monitoring data E. Ioriatti et al. https://doi.org/10.5194/nhess-25-4941-2025
38. Application of a fuzzy verification framework for the evaluation of a regional-scale landslide early warning system during the January 2020 Gloria storm in Catalonia (NE Spain) R. Palau et al. https://doi.org/10.1007/s10346-022-01854-2
39. A Regional-Scale Landslide Warning System Based on 20 Years of Operational Experience S. Segoni et al. https://doi.org/10.3390/w10101297
40. Parameter Sensitivity Analysis of a Korean Debris Flow-Induced Rainfall Threshold Estimation Algorithm K. Choo et al. https://doi.org/10.3390/w16060828
41. Temporal changes in the debris flow threshold under the effects of ground freezing and sediment storage on Mt. Fuji F. Imaizumi et al. https://doi.org/10.5194/esurf-9-1381-2021
42. Shredding post-fire debris flow likelihood: A field-constrained catchment-scale model of wood-shred surface treatment effectiveness M. Harrison et al. https://doi.org/10.1016/j.geomorph.2026.110343