30 citations as recorded by crossref.

1. Predisposing Factors for Shallow Landslides in Alpine and Hilly/Apennines Environments: A Case Study from Piemonte, Italy E. Fedato et al. https://doi.org/10.3390/geosciences13080252
2. Short range tracking of rainy clouds by multi-image flow processing of X-band radar data L. Mesin https://doi.org/10.1186/1687-6180-2011-67
3. Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data E. Leonarduzzi et al. https://doi.org/10.1002/2017WR021044
4. Predictive Power Evaluation of a Physically Based Model for Shallow Landslides in the Area of Oltrepò Pavese, Northern Italy R. Valentino et al. https://doi.org/10.1007/s10706-014-9758-3
5. 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
6. Failure characteristics of soft rock and overlying soil after excavation of adjacent hard rock considering the rainfall K. Li et al. https://doi.org/10.1007/s10064-025-04267-2
7. Probabilistic landslide ensemble prediction systems: lessons to be learned from hydrology E. Canli et al. https://doi.org/10.5194/nhess-18-2183-2018
8. 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
9. Modelling catchment‐scale shallow landslide occurrence and sediment yield as a function of rainfall return period C. Bovolo & J. Bathurst https://doi.org/10.1002/hyp.8158
10. Hydrological and geotechnical investigations of mass movements in an equatorial city (Yaoundé, Cameroon) B. Ngounou Ngatcha et al. https://doi.org/10.1007/s12665-010-0654-8
11. Sediment modelling with fine temporal and spatial resolution for a hilly catchment A. Elliott et al. https://doi.org/10.1002/hyp.8445
12. Spatial patterns of rainfall and shallow landslide susceptibility J. Minder et al. https://doi.org/10.1029/2008WR007027
13. Spatially distributed rainfall information and its potential for regional landslide early warning systems E. Canli et al. https://doi.org/10.1007/s11069-017-2953-9
14. Rainfall-induced landslides assessment in the Fengjie County, Three-Gorge reservoir area, China K. Wang & S. Zhang https://doi.org/10.1007/s11069-021-04691-z
15. 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
16. aiNet- and GIS-based regional prediction system for the spatial and temporal probability of rainfall-triggered landslides C. Li et al. https://doi.org/10.1007/s11069-009-9351-x
17. A prototype system for space–time assessment of rainfall-induced shallow landslides in Italy L. Montrasio et al. https://doi.org/10.1007/s11069-014-1239-8
18. Statistical modelling of rainfall-induced shallow landsliding using static predictors and numerical weather predictions: preliminary results V. Capecchi et al. https://doi.org/10.5194/nhess-15-75-2015
19. Numerical Analysis of the Effect of Subgrid Variability in a Physically Based Hydrological Model on Runoff, Soil Moisture, and Slope Stability E. Leonarduzzi et al. https://doi.org/10.1029/2020WR027326
20. Preliminary establishment of a mass movement warning system for Taiwan using the soil water index C. Chen et al. https://doi.org/10.1007/s10346-021-01844-w
21. Spatial variations of landslide severity with respect to meteorological and soil related factors K. Dutta et al. https://doi.org/10.1007/s11069-024-06930-5
22. 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
23. Rainfall-induced shallow landslides: a model for the triggering mechanism of some case studies in Northern Italy L. Montrasio et al. https://doi.org/10.1007/s10346-009-0154-7
24. Comparison between different approaches to modeling shallow landslide susceptibility: a case history in Oltrepo Pavese, Northern Italy D. Zizioli et al. https://doi.org/10.5194/nhess-13-559-2013
25. Different Time-Increment Rainfall Prediction Models: a Machine Learning Approach Using Various Input Scenarios A. Rahimi et al. https://doi.org/10.1007/s11269-024-04040-2
26. Shallow landslides triggered by rainfalls: modeling of some case histories in the Reggiano Apennine (Emilia Romagna Region, Northern Italy) L. Montrasio et al. https://doi.org/10.1007/s11069-011-9906-5
27. Rainfall-induced shallow landslides and soil wetness: comparison of physically based and probabilistic predictions E. Leonarduzzi et al. https://doi.org/10.5194/hess-25-5937-2021
28. 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
29. Assessment of Landslide Susceptibility of Physically Based Model Considering Characteristics of the Unsaturated Soil J. Kim & H. Park https://doi.org/10.9719/EEG.2014.47.1.49
30. Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides R. Greco & L. Pagano https://doi.org/10.5194/nhess-17-2213-2017