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Prediction of the area affected by earthquake-induced landsliding based on seismological parameters

  • We present an analytical, seismologically consistent expression for the surface area of the region within which most landslides triggered by an earthquake are located (landslide distribution area). This expression is based on scaling laws relating seismic moment, source depth, and focal mechanism with ground shaking and fault rupture length and assumes a globally constant threshold of acceleration for onset of systematic mass wasting. The seismological assumptions are identical to those recently used to propose a seismologically consistent expression for the total volume and area of landslides triggered by an earthquake. To test the accuracy of the model we gathered geophysical information and estimates of the landslide distribution area for 83 earthquakes. To reduce uncertainties and inconsistencies in the estimation of the landslide distribution area, we propose an objective definition based on the shortest distance from the seismic wave emission line containing 95% of the total landslide area. Without any empirical calibration theWe present an analytical, seismologically consistent expression for the surface area of the region within which most landslides triggered by an earthquake are located (landslide distribution area). This expression is based on scaling laws relating seismic moment, source depth, and focal mechanism with ground shaking and fault rupture length and assumes a globally constant threshold of acceleration for onset of systematic mass wasting. The seismological assumptions are identical to those recently used to propose a seismologically consistent expression for the total volume and area of landslides triggered by an earthquake. To test the accuracy of the model we gathered geophysical information and estimates of the landslide distribution area for 83 earthquakes. To reduce uncertainties and inconsistencies in the estimation of the landslide distribution area, we propose an objective definition based on the shortest distance from the seismic wave emission line containing 95% of the total landslide area. Without any empirical calibration the model explains 56% of the variance in our dataset, and predicts 35 to 49 out of 83 cases within a factor of 2, depending on how we account for uncertainties on the seismic source depth. For most cases with comprehensive landslide inventories we show that our prediction compares well with the smallest region around the fault containing 95% of the total landslide area. Aspects ignored by the model that could explain the residuals include local variations of the threshold of acceleration and processes modulating the surface ground shaking, such as the distribution of seismic energy release on the fault plane, the dynamic stress drop, and rupture directivity. Nevertheless, its simplicity and first-order accuracy suggest that the model can yield plausible and useful estimates of the landslide distribution area in near-real time, with earthquake parameters issued by standard detection routines.zeige mehrzeige weniger

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Verfasserangaben:Odin MarcORCiDGND, Patrick Meunier, Niels HoviusORCiDGND
URN:urn:nbn:de:kobv:517-opus4-418285
DOI:https://doi.org/10.25932/publishup-41828
ISSN:1866-8372
Titel des übergeordneten Werks (Englisch):Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe
Schriftenreihe (Bandnummer):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (557)
Publikationstyp:Postprint
Sprache:Englisch
Datum der Erstveröffentlichung:01.02.2019
Erscheinungsjahr:2017
Veröffentlichende Institution:Universität Potsdam
Datum der Freischaltung:01.02.2019
Freies Schlagwort / Tag:1988 Saguenay; 1994 Northridge; 2008 Wenchuan earthquake; 2010 Haiti earthquake; complex rupture; denali fault; main Himalayan thrust; rupture process; spatial-distribution; strong ground motion
Ausgabe:557
Seitenanzahl:17
Quelle:Natural Hazards and Earth System Sciences 17 (2017) S. 1159–1175 DOI: 10.5194/nhess-17-1159-2017
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät
DDC-Klassifikation:9 Geschichte und Geografie / 91 Geografie, Reisen / 910 Geografie, Reisen
Peer Review:Referiert
Publikationsweg:Open Access
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
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