On the influence of temporal change on the validity of landslide susceptibility maps

Abstract

Abstract. The consideration of non-stationary landslide causal factors in statistical landslide susceptibility assessments is still problematic. The latter may lead to erroneous model predictions, especially in times of dramatic environmental change. In this case study in the Central Swiss Alps, we aim to evaluate the effect of dynamic change of landslide causal factors on the validity of landslide susceptibility maps. Logistic regression models were produced for two points in time, 1959 and 2000. Both models could correctly classify >70% of the independent spatial validation dataset. By subtracting the 1959 susceptibility map from the 2000 susceptibility map a deviation susceptibility map was obtained. Our interpretation was that these susceptibility deviations indicate the effect of the change of dynamic causal factors on the landslide probability. The deviation map explained 85% of new landslides occurring after 2000. We believe it to be a suitable tool to add a time element to the susceptibility map pointing to areas with changing susceptibility due to recently changing environmental conditions.

Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

“…The erosion estimates produced with the LSU-derived C factor map range from 0.0 to 16 t ha −1 a −1 with a mean erosion of 1.18 t ha −1 a −1 . High erosion rates are concentrated on the south exposed slopes where grassland cover is scarce due to pasturing and at landslides (Meusburger and Alewell, 2009). The highest values occur at spots of bare soil located along rivers, roads and landslides (Fig.…”

Soil erosion by snow gliding – a first quantification attempt in a subalpine area in Switzerland

“…We used the result from a QuickBird land cover classification with a resolution of 2.4 m (subsequently resampled to 5 m) as land cover input (Meusburger et al, 2010a). Combining this land cover map with a land use map (Meusburger and Alewell, 2009), it was possible to derive the parameter forest stand. A uniform static friction coefficient (µ s ) was assigned to each of the four investigated land cover types.…”

“…Mabit et al, 1999;Benmansour et al, 2013;Meusburger et al, 2013) and by soil erosion models (Nearing et al, 1989;Merritt et al, 2003). Since the end of the 1970s empirical soil erosion models such as the Universal Soil Loss Equation (USLE; Smith, 1965, 1978) and its refined versions, the Revised USLE (RUSLE; Renard et al, 1997) and the Modified USLE (MUSLE;Smith et al, 1984), have been used worldwide to evaluate soil erosion magnitude under various conditions (Kinnell, 2010).…”

Geophysical imaging of shallow subsurface topography and its implication for shallow landslide susceptibility in the Urseren Valley, Switzerland

“…Key static parameters of landslide susceptibility are slope angle, soil composition, soil saturation level and bedrock orientation (Meusburger and Alewell, 2009;Schoeck, 2010). Each of these parameters can be constrained with different methodologies, but until now high-resolution geophysical methods have played a minor role in investigating shallow landslides.…”