landslide clustering
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2019 ◽  
Vol 7 (3) ◽  
pp. 829-839 ◽  
Author(s):  
Claire Rault ◽  
Alexandra Robert ◽  
Odin Marc ◽  
Niels Hovius ◽  
Patrick Meunier

Abstract. The large, shallow earthquakes at Northridge, California (1994), Chi-Chi, Taiwan (1999), and Wenchuan, China (2008), each triggered thousands of landslides. We have determined the position of these landslides along hillslopes, normalizing for statistical bias. The landslide patterns have a co-seismic signature, with clustering at ridge crests and slope toes. A cross-check against rainfall-induced landslide inventories seems to confirm that crest clustering is specific to seismic triggering as observed in previous studies. In our three study areas, the seismic ground motion parameters and lithologic and topographic features used do not seem to exert a primary control on the observed patterns of landslide clustering. However, we show that at the scale of the epicentral area, crest and toe clustering occur in areas with specific geological features. Toe clustering of seismically induced landslides tends to occur along regional major faults. Crest clustering is concentrated at sites where the lithology along hillslopes is approximately uniform, or made of alternating soft and hard strata, and without strong overprint of geological structures. Although earthquake-induced landslides locate higher on hillslopes in a statistically significant way, geological features strongly modulate the landslide position along the hillslopes. As a result the observation of landslide clustering on topographic ridges cannot be used as a definite indicator of the topographic amplification of ground shaking.



2019 ◽  
Vol 19 (7) ◽  
pp. 1433-1444
Author(s):  
Susanne A. Benz ◽  
Philipp Blum

Abstract. An increasing awareness of the cost of landslides on the global economy and of the associated loss of human life has led to the development of various global landslide databases. However, these databases typically report landslide events instead of individual landslides, i.e., a group of landslides with a common trigger and reported by media, citizens and/or government officials as a single unit. The latter results in significant cataloging and reporting biases. To counteract these biases, this study aims to identify clusters of landslide events that were triggered by the same rainfall event. An algorithm is developed that finds a series of landslide events that (a) is continuous with no more than 2 d between individual events and where (b) precipitation at the location of an individual event correlates with precipitation of at least one other event. The developed algorithm is applied to the Global Landslide Catalog (GLC) maintained by NASA. The results show that more than 40 % of all landslide events are connected to at least one other event and that 14 % of all studied landslide events are actually part of a landslide cluster consisting of at least 10 events and up to 108 events in 1 d. Duration of the detected clusters also varies greatly from 1 to 24 d. Our study intends to enhance our understanding of landslide clustering and thus will assist in the development of improved, internationally streamlined mitigation strategies for rainfall-related landslide clusters.



2018 ◽  
Author(s):  
Claire Rault ◽  
Alexandra Robert ◽  
Odin Marc ◽  
Niels Hovius ◽  
Patrick Meunier

Abstract. The large, shallow earthquakes at Northridge, California (1994), Chi-Chi, Taiwan (1999) and Wenchuan, China (2008) each triggered thousands of landslides. We have determined the position of these landslides along hillslopes, normalizing for statistical bias. The landslide patterns have a co-seismic signature, with clustering at ridge crests and slope toes. A cross check against rainfall-induced landslide inventories confirms that crest-clustering is specific to seismic-triggering. In our three study areas, seismic ground motion parameters, and lithologic and topographic features have limited bearing on the observed patterns of landslide clustering. However, we show that at the scale of the epicentral area, crest- and toe-clustering occur in areas with specific geological features. Toe-clustering of seismically-induced landslides tends to occur along major faults. Crest-clustering is concentrated at sites where the lithology along hillslopes is approximately uniform, or made of alternating soft and hard strata, and without strong overprint of geological structures. Although earthquake-induced landslides locate higher on hillslopes in a statistically significant way, geological features strongly modulate the landslide position along the hillslopes. As a result the observation of landslide clustering on topographic ridges cannot be used directly as an indicator of seismic parameters such as ground shaking.



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