A seismologically consistent expression for the total area and volume of earthquake‐triggered landsliding

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.

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

“…Below this threshold, landsliding is rare or minor, and therefore a reasonable estimation of the size and shape of the landslide distribution area could be found by intersecting the region where the peak ground acceleration exceeds a c and the region with sufficiently steep topography for landsliding to occur. Marc et al (2016b) have successfully modelled the total volume and area of the population of landslides due to a given earthquake, using seismological scaling laws to constrain the magnitude and extent of ground shaking. They assumed that a c is a threshold acceleration for damage above which an effective reduction of strength occurred within the hillslope materials, increasing the likelihood of failure of slopes steeper than the angle of internal friction and thus stable due to a significant cohesion.…”

“…The mean depth of emission is assumed to be the mean asperity depth because asperities emit most of the high-frequency waves (Ruiz et al, 2011;Avouac et al, 2015) and seem to explain best the observed patterns and amounts of landsliding (Meunier et al, 2013b;Marc et al, 2016b). Note that waves with frequencies of 0.5 to 10 Hz are often the most important for landslide triggering because they have wavelengths ranging from the landslide size to the hillslope size (Marc et al, 2016b).…”

“…A simpler approach is to predict first-order variables such as the total volume and area of landsliding caused by an earthquake based on simple seismological considerations (e.g. Marc et al, 2016b). If the input parameters for such a model can be quantified in minutes to hours after an earthquake, then this could yield a quick insight into the scale of the affected area and the total amount of landsliding within.…”

“…However, the definition of the relationship between A d and seismic moment and of the influence of other seismological and geomorphic parameters has a slender theoretical basis. Recently, expressions for the total area and volume of landslides triggered by an earthquake have been derived based on seismological scaling laws and simple topographic characterizations (Marc et al, 2016b). …”

Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes

“…Within 48 h of the 25 April mainshock, initial estimates of the likely geographical distribution of landslides were based upon the outputs of the USGS ShakeMap and a limited number of reports from the ground (e.g., via social media). Although this provided a first-order approximation of potential landslide locations, coseismic landsliding is determined by the interactions between topography, ground shaking, and local site geology (Meunier et al, 2008;Parker et al, 2015;Marc et al, 2016). Empirical landslide susceptibility models (Gallen et al, 2016;Parker et al, 2017;Robinson et al, 2017) provided probabilistic estimates of the likelihood of a landslide at any point in space within the affected area.…”