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We proposed earthquake forecasting models for Albania, one of the most seismogenic regions in Europe, to give an overview of seismic activity by implementing area source and smoothing approaches. The earthquake catalogue was first declustered to remove foreshocks and aftershocks when they are within the derived distance windows and time windows of mainshocks. Considering catalogue completeness, the events with M≥4.1 during the period of 1960–2006 were implemented for the learning forecast model. The forecasting is implemented into an area source model that includes 20 sub-regions and a smoothing model with a cell size of 0.2 ∘ × 0.2 ∘ to forecast the seismicity in Albania. Both models show high seismic rates along the western coastline and in the southern part of the study area, consistent with previous studies that discussed seismicity in the area and currently active regions. To further validate the forecast performance of the two models, we introduced the Molchan diagram to quantify the correlation between models and observations. The Molchan diagram suggests that the models are significantly better than a random distribution, confirming their forecasting abilities. Our results provide crucial information for subsequent research on seismic activity, such as probabilistic seismic hazard assessment. [ABSTRACT FROM AUTHOR]

We proposed earthquake forecasting models for Albania, one of the most seismogenic regions in Europe, to give an overview of seismic activity by implementing area source and smoothing approaches. The earthquake catalog was firstly declustered to remove foreshocks and aftershocks when they are within the derived distance- and time-windows of mainshocks. Considering catalog completeness, the events with M≥4.0 during the period of 1960–2006 were implemented for the forecast model learning. The forecasting is implemented into an area source model that includes 20 sub-regions and a smoothing model with a cell size of 0.2° x 0.2° to forecast the seismicity in Albania. Both models show high seismic rate along the western coastline and at the southern part of the study area, consistent with previous studies which discussed seismicity in the area and currently active regions. To further validate the forecast performance from the two models, we introduced the Molchan diagram to quantify the correlation between models and observations. The Molchan diagram suggests that both models are significantly better than a random distribution, confirming their forecasting abilities. Our results provide crucial information for subsequent research on the seismic activity, such as probabilistic seismic hazard assessment. [ABSTRACT FROM AUTHOR]

The southernmost portion of the Ryukyu Trench near the island of Taiwan potentially generates tsunamigenic earthquakes with magnitudes from 7.5 to 8.7 through shallow rupture. The fault model for this potential region dips 10° northward with a rupture length of 120 km and a width of 70 km. An earthquake magnitude of Mw 8.15 is estimated by the fault geometry with an average slip of 8.25m as a constraint on the earthquake scenario. Heterogeneous slip distributions over the rupture surface are generated by a stochastic slip model, which represents the decaying slip spectrum according to k-2 in the wave number domain. These synthetic slip distributions are consistent with the abovementioned identical seismic conditions. The results from tsunami simulations illustrate that the propagation of tsunami waves and the peak wave heights largely vary in response to the slip distribution. Changes in the wave phase are possible as the waves propagate, even under the same seismic conditions. The tsunami energy path not only follows the bathymetry but also depends on the slip distribution. The probabilistic distributions of the peak tsunami amplitude calculated by 100 different slip patterns from 30 recording stations reveal that the uncertainty decreases with increasing distance from the tsunami source. The highest wave amplitude for 30 recording points is 7.32m at Hualien for 100 different slips. Compared with the stochastic-slip distributions, the uniform slip distribution will be highly underestimated, especially in the near field. In general, the uniform slip assumption only represents the average phenomenon and will consequently ignore the possibility of tsunami waves. These results indicate that considering the effects of heterogeneous slip distributions is necessary for assessing tsunami hazards to provide additional information about tsunami uncertainties and facilitate a more comprehensive estimation. [ABSTRACT FROM AUTHOR]