@article{RaultRobertMarcetal.2019,
  author    = {Rault, Claire and Robert, Alexandra and Marc, Odin and Hovius, Niels and Meunier, Patrick},
  title     = {Seismic and geologic controls on spatial clustering of landslides in three large earthquakes},
  series = {Earth surface dynamics},
  volume    = {7},
  journal   = {Earth surface dynamics},
  number    = {3},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {2196-6311},
  doi       = {10.5194/esurf-7-829-2019},
  pages     = {829 -- 839},
  year      = {2019},
  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.},
  language  = {en}
}
@misc{MarcMeunierHovius2017,
  author    = {Marc, Odin and Meunier, Patrick and Hovius, Niels},
  title     = {Prediction of the area affected by earthquake-induced landsliding based on seismological parameters},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {557},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-41828},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-418285},
  pages     = {17},
  year      = {2017},
  abstract  = {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 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.},
  language  = {en}
}
@article{MarcMeunierHovius2017,
  author    = {Marc, Odin and Meunier, Patrick and Hovius, Niels},
  title     = {Prediction of the area affected by earthquake-induced landsliding based on seismological parameters},
  series = {Natural hazards and earth system sciences},
  volume    = {17},
  journal   = {Natural hazards and earth system sciences},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1561-8633},
  doi       = {10.5194/nhess-17-1159-2017},
  pages     = {1159 -- 1175},
  year      = {2017},
  abstract  = {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 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.},
  language  = {en}
}
@article{MarcHoviusMeunieretal.2015,
  author    = {Marc, Odin and Hovius, Niels and Meunier, Patrick and Uchida, Taro and Hayashi, Shin-Ichiro},
  title     = {Transient changes of landslide rates after earthquakes},
  series = {Geology},
  volume    = {43},
  journal   = {Geology},
  number    = {10},
  publisher = {American Institute of Physics},
  address   = {Boulder},
  issn      = {0091-7613},
  doi       = {10.1130/G36961.1},
  pages     = {883 -- 886},
  year      = {2015},
  abstract  = {Earthquakes impart an impressive force on epicentral landscapes, with immediate catastrophic hillslope response. However, their legacy on geomorphic process rates remains poorly constrained. We have determined the evolution of landslide rates in the epicentral areas of four intermediate to large earthquakes (M-w, 6.6-7.6). In each area, landsliding correlates with the cumulative precipitation during a given interval. Normalizing for this meteorological forcing, landslide rates have been found to peak after an earthquake and decay to background values in 1-4 yr, with the decay time scale probably proportional to the earthquake magnitude. The transient pulse of landsliding is not related to external forcing such as rainfall or aftershocks, and we tentatively attribute it to the reduction and subsequent recovery of ground strength. Observed geomorphic trends are not linked with groundwater level changes or root system damage, both of which could affect substrate strength. We propose that they are caused by reversible damage of rock mass and/or loosening of regolith. Qualitative accounts of ground cracking due to strong ground motion abound, and our observations are circumstantial evidence of its potential importance in setting landscape sensitivity to meteorological forcing after large earthquakes.},
  language  = {en}
}
@article{MarcHoviusMeunieretal.2016,
  author    = {Marc, Odin and Hovius, Niels and Meunier, Patrick and Gorum, Tolga and Uchida, Taro},
  title     = {A seismologically consistent expression for the total area and volume of earthquake-triggered landsliding},
  series = {Journal of geophysical research : Earth surface},
  volume    = {121},
  journal   = {Journal of geophysical research : Earth surface},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {2169-9003},
  doi       = {10.1002/2015JF003732},
  pages     = {640 -- 663},
  year      = {2016},
  abstract  = {We present a new, seismologically consistent expression for the total area and volume of populations of earthquake-triggered landslides. This model builds on a set of scaling relationships between key parameters, such as landslide spatial density, seismic ground acceleration, fault length, earthquake source depth, and seismic moment. To assess the model we have assembled and normalized a catalog of landslide inventories for 40 shallow, continental earthquakes. Low landscape steepness causes systematic overprediction of the total area and volume of landslides. When this effect is accounted for, the model predicts the total landslide volume of 63\% of 40 cases to within a factor 2 of the volume estimated from observations (R-2 = 0.76). The prediction of total landslide area is also sensitive to the landscape steepness, but less so than the total volume, and it appears to be sensitive to controls on the landslide size-frequency distribution, and possibly the shaking duration. Some outliers are likely associated with exceptionally strong rock mass in the epicentral area, while others may be related to seismic source complexities ignored by the model. However, the close match between prediction and estimate for about two thirds of cases in our database suggests that rock mass strength is similar in many cases and that our simple seismic model is often adequate, despite the variety of lithologies and tectonic settings covered. This makes our expression suitable for integration into landscape evolution models and application to the anticipation or rapid assessment of secondary hazards associated with earthquakes.},
  language  = {en}
}