Validation of the Shallow Landslide Model, SHALSTAB, for forest management

Author(s):  
William E. Dietrich ◽  
Dino Bellugi ◽  
Raphael Real de Asua
2010 ◽  
Vol 36 (1) ◽  
pp. 27-32
Author(s):  
Yasuhiro SHUIN ◽  
Keigo MATSUE ◽  
Kazuhiro ARUGA ◽  
Toshiaki TASAKA ◽  
Norifumi HOTTA

2009 ◽  
Vol 34 (6) ◽  
pp. 867-881 ◽  
Author(s):  
Sekhar L. Kuriakose ◽  
L. P. H. van Beek ◽  
C. J. van Westen

2013 ◽  
Vol 10 (7) ◽  
pp. 9761-9798 ◽  
Author(s):  
D. Penna ◽  
M. Borga ◽  
G. T. Aronica ◽  
G. Brigandì ◽  
P. Tarolli

Abstract. This work evaluates the predictive power of the quasi-dynamic shallow landslide model QD-SLaM to simulate shallow landslide locations in a small-scale Mediterranean landscape: the Giampilieri catchment located in Sicily (Italy). The catchment was impacted by a sequence of high-intensity storms over the years 2007–2009. The effect of high resolution Digital Terrain Models (DTMs) on the quality of model predictions is tested by considering four DTM resolutions: 2 m, 4 m, 10 m and 20 m. Moreover, the impact of the dense forest road network on the model performance is evaluated by considering separately road-related landslides and natural landslides. The landslide model does not incorporate the description of road-related failures. The model predictive power is shown to be DTM-resolution dependent. When assessed over the sample of mapped natural landslides, better model performances are reported for 4 m and 10 m DTM resolution, thus highlighting the fact that higher DTM resolution does not necessarily mean better model performances. Model performances over road-related failures are, as expected, lower than for the other cases. These findings show that shallow landslide predictive power can benefit from increasing DTM resolution only when the model is able to describe the physical processes emerging at the smaller spatial scales resolved by the digital topography. Model results show also that the combined use of high DTM resolution and a model capable to deal with road-related processes may lead to substantially better performances in landscapes where forest roads are a significant factor of slope stability.


2014 ◽  
Vol 18 (6) ◽  
pp. 2127-2139 ◽  
Author(s):  
D. Penna ◽  
M. Borga ◽  
G. T. Aronica ◽  
G. Brigandì ◽  
P. Tarolli

Abstract. This work evaluates the predictive power of the quasi-dynamic shallow landslide model QD-SLaM to simulate shallow landslide locations in a small-scale Mediterranean landscape, namely, the lower portion (2.6 km2) of the Giampilieri catchment, located in Sicily (Italy). The catchment was impacted by a sequence of high-intensity storms over the years 2007–2009, resulting in widespread landsliding, with a total landslide initiation area amounting to 2.6% of the basin area. The effect of high-resolution digital terrain models (DTMs) on the quality of model predictions is tested by considering four DTM resolutions: 2, 4, 10 and 20 m. Moreover, the impact of the dense forest road network on the model performance is evaluated by separately considering road-related landslides and natural landslides. The landslide model does not incorporate the description of road-related failures and is applied without calibration of the model parameters. The model predictive power is shown to be DTM-resolution dependent. Use of coarser resolution has a smoothing effect on terrain attributes, with local slope angles decreasing and contributing areas becoming larger. The percentage of watershed area represented by the model as unconditionally unstable (i.e. failing even without the addition of water from precipitation) ranges between 6.3% at 20 m DTM and 13.8% at 2 m DTM, showing an overestimation of the mapped landslide area. We consider this prediction as an indication for likely failing sites in future storms rather than areas proved stable during previous storms. When assessed over the sample of mapped non-road-related landslides, better model performances are reported for 4 and 10 m DTM resolution, thus highlighting the fact that higher DTM resolution does not necessarily mean better model performances. Model performances over road-related failures are lower than for the natural cases, and slightly increase with decreasing DTM resolution. These findings indicate that to realize the full potential of high-resolution topography, more extensive work is needed aiming more specifically to identify the extent of the artificial structures and their impact on shallow landsliding processes.


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