Articles | Volume 22, issue 8
https://doi.org/10.5194/nhess-22-2611-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-22-2611-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Aug 2022
Research article |
| 15 Aug 2022
| 15 Aug 2022
Introducing SlideforMAP: a probabilistic finite slope approach for modelling shallow-landslide probability in forested situations
Feiko Bernard van Zadelhoff
CORRESPONDING AUTHOR
HAFL, Bern University of Applied Sciences, Länggasse 85, CH-3052 Zollikofen, Switzerland
Adel Albaba
HAFL, Bern University of Applied Sciences, Länggasse 85, CH-3052 Zollikofen, Switzerland
Denis Cohen
CoSci LLC, Placitas, NM 87043, USA
Chris Phillips
Manaaki Whenua – Landcare Research, Lincoln, New Zealand
Bettina Schaefli
Institute of Geography (GIUB) & Oeschger Centre for Climate Change Research (OCCR), University of Bern, 3012 Bern, Switzerland
Luuk Dorren
HAFL, Bern University of Applied Sciences, Länggasse 85, CH-3052 Zollikofen, Switzerland
International EcorisQ Association, P.O. Box 2348, 1211 Geneva 2, Switzerland
Massimiliano Schwarz
HAFL, Bern University of Applied Sciences, Länggasse 85, CH-3052 Zollikofen, Switzerland
International EcorisQ Association, P.O. Box 2348, 1211 Geneva 2, Switzerland
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Cited
15 citations as recorded by crossref.
- Inclusion of Nature-Based Solution in the Evaluation of Slope Stability in Large Areas L. Zedek et al. 10.3390/land13030372
- Current progress in quantifying and monitoring instream large wood supply and transfer in rivers V. Ruiz‐Villanueva et al. 10.1002/esp.5765
- Accelerating Effect of Vegetation on the Instability of Rainfall-Induced Shallow Landslides J. Zhang et al. 10.3390/rs14225743
- Comparing physical and statistical landslide susceptibility models at the scale of individual trees R. Spiekermann et al. 10.1016/j.geomorph.2023.108870
- Exploring the influence of alfalfa root reinforcement on the loess slopes reliability analysis J. Li et al. 10.1007/s11069-024-06997-0
- GIS-based prediction method of shallow landslides induced by heavy rainfall in large mountainous areas X. Luo et al. 10.1007/s11629-023-8535-2
- A Computationally Efficient Method to Determine the Probability of Rainfall-Triggered Cut Slope Failure Accounting for Upslope Hydrological Conditions E. Robson et al. 10.1007/s00603-023-03694-5
- Influence of Root Reinforcement on Shallow Landslide Distribution: A Case Study in Garfagnana (Northern Tuscany, Italy) L. Marzini et al. 10.3390/geosciences13110326
- Effects of Land Cover Changes on Shallow Landslide Susceptibility Using SlideforMAP Software (Mt. Nerone, Italy) I. Murgia et al. 10.3390/land13101575
- Analysis of Poplar’s (Populus nigra ita.) Root Systems for Quantifying Bio-Engineering Measures in New Zealand Pastoral Hill Country H. Ngo et al. 10.3390/f14061240
- State-of-the-art: parametrization of hydrological and mechanical reinforcement effects of vegetation in slope stability models for shallow landslides A. DiBiagio et al. 10.1007/s10346-024-02300-1
- Using global sensitivity analysis to quantify the uncertainty of root reinforcement in vegetated slope stability J. Xian et al. 10.1007/s11104-024-07162-z
- Vegetation-induced modifications in hydrological processes and the consequential dynamic effects of slope stability Z. Deng et al. 10.1016/j.catena.2025.108793
- Predicting the thickness of shallow landslides in Switzerland using machine learning C. Schaller et al. 10.5194/nhess-25-467-2025
- Introducing SlideforMAP: a probabilistic finite slope approach for modelling shallow-landslide probability in forested situations F. van Zadelhoff et al. 10.5194/nhess-22-2611-2022
14 citations as recorded by crossref.
- Inclusion of Nature-Based Solution in the Evaluation of Slope Stability in Large Areas L. Zedek et al. 10.3390/land13030372
- Current progress in quantifying and monitoring instream large wood supply and transfer in rivers V. Ruiz‐Villanueva et al. 10.1002/esp.5765
- Accelerating Effect of Vegetation on the Instability of Rainfall-Induced Shallow Landslides J. Zhang et al. 10.3390/rs14225743
- Comparing physical and statistical landslide susceptibility models at the scale of individual trees R. Spiekermann et al. 10.1016/j.geomorph.2023.108870
- Exploring the influence of alfalfa root reinforcement on the loess slopes reliability analysis J. Li et al. 10.1007/s11069-024-06997-0
- GIS-based prediction method of shallow landslides induced by heavy rainfall in large mountainous areas X. Luo et al. 10.1007/s11629-023-8535-2
- A Computationally Efficient Method to Determine the Probability of Rainfall-Triggered Cut Slope Failure Accounting for Upslope Hydrological Conditions E. Robson et al. 10.1007/s00603-023-03694-5
- Influence of Root Reinforcement on Shallow Landslide Distribution: A Case Study in Garfagnana (Northern Tuscany, Italy) L. Marzini et al. 10.3390/geosciences13110326
- Effects of Land Cover Changes on Shallow Landslide Susceptibility Using SlideforMAP Software (Mt. Nerone, Italy) I. Murgia et al. 10.3390/land13101575
- Analysis of Poplar’s (Populus nigra ita.) Root Systems for Quantifying Bio-Engineering Measures in New Zealand Pastoral Hill Country H. Ngo et al. 10.3390/f14061240
- State-of-the-art: parametrization of hydrological and mechanical reinforcement effects of vegetation in slope stability models for shallow landslides A. DiBiagio et al. 10.1007/s10346-024-02300-1
- Using global sensitivity analysis to quantify the uncertainty of root reinforcement in vegetated slope stability J. Xian et al. 10.1007/s11104-024-07162-z
- Vegetation-induced modifications in hydrological processes and the consequential dynamic effects of slope stability Z. Deng et al. 10.1016/j.catena.2025.108793
- Predicting the thickness of shallow landslides in Switzerland using machine learning C. Schaller et al. 10.5194/nhess-25-467-2025
Latest update: 01 Apr 2025
Short summary
Shallow landslides pose a risk to people, property and infrastructure. Assessment of this hazard and the impact of protective measures can reduce losses. We developed a model (SlideforMAP) that can assess the shallow-landslide risk on a regional scale for specific rainfall events. Trees are an effective and cheap protective measure on a regional scale. Our model can assess their hazard reduction down to the individual tree level.
Shallow landslides pose a risk to people, property and infrastructure. Assessment of this hazard...
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