The magnitude of mass movements, which may be expressed by their dimension in terms of area or volume, is an important component of intensity together with velocity. In the case of slow-moving deep-seated landslides, the expected magnitude is the prevalent parameter for defining intensity when assessed as a spatially distributed variable in a given area. In particular, the frequency–volume statistics of past landslides may be used to understand and predict the magnitude of new landslides and reactivations. In this paper we study the spatial properties of volume frequency distributions in the Arno river basin (Central Italy, about 9100 km2). The overall landslide inventory taken into account (around 27,500 events) shows a power-law scaling of volumes for values greater than a cutoff value of about 2 × 104 m3. We explore the variability of the power-law exponent in the geographic space by setting up local subsets of the inventory based on neighbourhoods with radii between 5 and 50 km. We found that the power-law exponent α varies according to geographic position and that the exponent itself can be treated as a random space variable with autocorrelation properties both at local and regional scale. We use this finding to devise a simple method to map the magnitude frequency distribution in space and to create maps of exceeding probability of landslide volume for risk analysis. We also study the causes of spatial variation of α by analysing the dependence of power-law properties on geological and geomorphological factors, and we find that structural settings and valley density exert a strong influence on mass movement dimensions.
Spatial patterns of landslide dimension: A tool for magnitude mapping
Catani F.
Writing – Original Draft Preparation
;
2016
Abstract
The magnitude of mass movements, which may be expressed by their dimension in terms of area or volume, is an important component of intensity together with velocity. In the case of slow-moving deep-seated landslides, the expected magnitude is the prevalent parameter for defining intensity when assessed as a spatially distributed variable in a given area. In particular, the frequency–volume statistics of past landslides may be used to understand and predict the magnitude of new landslides and reactivations. In this paper we study the spatial properties of volume frequency distributions in the Arno river basin (Central Italy, about 9100 km2). The overall landslide inventory taken into account (around 27,500 events) shows a power-law scaling of volumes for values greater than a cutoff value of about 2 × 104 m3. We explore the variability of the power-law exponent in the geographic space by setting up local subsets of the inventory based on neighbourhoods with radii between 5 and 50 km. We found that the power-law exponent α varies according to geographic position and that the exponent itself can be treated as a random space variable with autocorrelation properties both at local and regional scale. We use this finding to devise a simple method to map the magnitude frequency distribution in space and to create maps of exceeding probability of landslide volume for risk analysis. We also study the causes of spatial variation of α by analysing the dependence of power-law properties on geological and geomorphological factors, and we find that structural settings and valley density exert a strong influence on mass movement dimensions.File | Dimensione | Formato | |
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