scholarly journals A method for producing digital probabilistic seismic landslide hazard maps; an example from the Los Angeles, California, area

1998 ◽  
Author(s):  
Randall W. Jibson ◽  
Edwin L. Harp ◽  
John A. Michael
Author(s):  
Fabio Rollo ◽  
Sebastiano Rampello

AbstractEarthquake-induced slope instability is one of the most important hazards related to ground shaking, causing damages to the environment and, often, casualties. Therefore, it is important to assess the seismic performance of slopes, especially in the near fault regions, evaluating the permanent displacements induced by seismic loading. This paper applies a probabilistic approach to evaluate the seismic performance of slopes using an updated database of ground motions recorded during the earthquakes occurred in Italy. The main advantage of this approach is that of accounting for the aleatory variability of both ground motions and prediction of seismic-induced displacements of slopes. The results are presented in terms of hazard curves, showing the annual rate of exceedance of permanent slope displacement evaluated using ground motion data provided by a standard probabilistic hazard analysis and a series of semi-empirical relationships linking the permanent displacements of slopes to one or more ground motion parameters. The procedure has been implemented on a regional scale to produce seismic landslide hazard maps for the Irpinia district, in Southern Italy, characterised by a severe seismic hazard. Seismic landslide hazard maps represent a useful tool for practitioners and government agencies for a regional planning to identify and monitor zones that are potentially susceptible to earthquake-induced slope instability, thus requiring further detailed, site-specific studies.


2000 ◽  
Vol 58 (3-4) ◽  
pp. 271-289 ◽  
Author(s):  
Randall W Jibson ◽  
Edwin L Harp ◽  
John A Michael

2002 ◽  
Vol 2 (1/2) ◽  
pp. 3-14 ◽  
Author(s):  
F. Ardizzone ◽  
M. Cardinali ◽  
A. Carrara ◽  
F. Guzzetti ◽  
P. Reichenbach

Abstract. Identification and mapping of landslide deposits are an intrinsically difficult and subjective operation that requires a great effort to minimise the inherent uncertainty. For the Staffora Basin, which extends for almost 300 km2 in the northern Apennines, three landslide inventory maps were independently produced by three groups of geomorphologists. In comparing each map with the others, large positional discrepancies arise (in the range of 55–65%). When all three maps are overlain, the locational mismatch of landslide deposit polygons increases to over 80%. To assess the impact of these errors on predictive models of landslide hazard, for the study area discriminant models were built up from the same set of geological-geomorphological factors as predictors, and the occurrence of landslide deposits within each terrain-unit, derived from each inventory map, as dependent variable. The comparison of these models demonstrates that statistical modelling greatly minimises the impact of input data errors which remain, however, a major limitation on the reliability of landslide hazard maps.


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