Newmark displacement data for low to moderate magnitude events in the Betic Cordillera.

Land-use decisions in relation to seismic-induced landslide hazard are usually made through the preparation of hazard maps. The rigid-block method is probably the most used for this purpose. Under this method, Newmark displacement is computed for each slope unit and this displacement is used as a guide for establishing categories of hazard. At present, most relations used for computing Newmark displacement are established from moderate-to-high magnitude earthquakes (Mw ≥ 6.5). This data article provides Newmark displacements computed from accelerograms recorded in the Betic Cordillera for low-to-moderate magnitude earthquakes (Mw = 3.5-6.3). Records come from the Spanish Strong Ground Motion database (Instituto Geográfico Nacional). Newmark displacements were computed focusing on yield accelerations frequently recorded in such scenarios (0.02, 0.03, 0.04, 0.05, 0.06, 0.08 and 0.10), although higher accelerations were also considered (0.125, 0.15, 0.20, 0.25 and 0.30 g's). These data are useful for the study of the hazard in seismic scenarios of low-to-moderate magnitude, very frequent in practice. These data have been used in the study by Delgado et al. [1].

Unbiased logic-tree data for earthquake-induced landslide hazard maps for low-to-moderate magnitude events.

Land-use planning in regard of earthquake-triggered landslides is usually implemented by means of the production of hazard maps. The well-known Newmark rigid block methodology is the most frequent used approach for this purpose. In this method, slope stability is evaluated by the estimation of the Newmark displacement, which is used to set different categories of hazard. This methodology presents limitations due to the difficulty of incorporating the variability of the used variables. For that reason, the logic-tree approach has been used in order to incorporate the epistemic uncertainties and compute probabilistic seismic-landslide hazard maps. However, the used weights in the logic-tree are usually set for each branch based on an expert judgement or subjective criteria. This article provide data obtained from the use of logic-tree methodology; this dataset is useful for deriving the unbiased weights to use in such methodology and in moderate-to-low magnitude scenarios. The data presented here are related to the article entitled "Obtaining suitable logic-tree weights for probabilistic earthquake-induced landslide hazard analyses" (Rodríguez-Peces et al., 2020) [1].