Site effects primarily depend on the shear modulus of subsurface layers, and this is generally estimated from the measured shear wave velocity (Vs) an

Quiescent faults may be capable of creating catastrophic earthquakes in locations with moderate and/or low seismic activity, such as Egypt. This study combines structural, remote sensing ($RS$), geophysical, and seismic activity data to examine and analyze the relationship between tectonic structures and seismotectonic activity in Egypt. In a new seismo-lineaments map of Egypt, tectonic lineaments of the Egyptian mainland were delineated and classified. The database contains 8000 lineaments that were divided into distinct geographical zones using statistical analysis and general features. Delineated lineaments were integrated with digitized geological and geophysical surface and subsurface faults and geographic information systems ($GIS$) processing techniques were applied to produce 4249 faults. The spatial distribution of seismic activity was determined to extract 1968 competent faults out of 4249 capable faults (i.e., greater than 10 km and suitably orientated concerning the existing stress field). Maximum expected magnitudes ($M_{max}$) were calculated for distinct seismogenic locations in Egypt, taking into account the nature of the regional rupture. At the national scale, empirical scaling relations between fault lengths and earthquake magnitude were employed for all mapped faults in Egypt. The findings concerning the faults were highly consistent with traditional geological information. The results suggest that our technique for estimating the highest predicted magnitudes produces similar values and might be used to evaluate Egypt’s possible future seismic hazard. The results were compared to seismic databases. The similarity of our results with those reported in the catalogs lends confidence to the proposed scheme.

Seismic hazard analysis provides an estimation of seismic hazard parameters like peak ground acceleration (PGA) or spectral acceleration (SA) for different periods. The extent of ground shaking and the hazard values at a particular region are estimated using ground-motion prediction equations (GMPEs)/attenuation equations. There are several GMPEs applicable for the region to estimate the PGA and SA values. These equations may result in higher or lower PGA and SA values than the region specific reported values, which are based on the parameters involved in the development of GMPEs. In this study, an attempt has been made to identify the best GMPEs for various parts of Peninsular India (PI) by performing an “efficacy test,” which make use of the average log likelihood value (LLH). Various intraplate earthquakes such as Coimbatore earthquake, Satpura earthquake, Anjar earthquake, Koyna earthquake, Bhadrachalam earthquake, Broach earthquake, Shimoga earthquake, Killari earthquake, Jabalpur earthquake, Pala earthquake, Kottayam earthquake, and Bhuj earthquake have been considered for the same. Macroseismic intensity maps of these earthquakes have been digitalized and European Macroseismic Scale (EMS) values at the surface have been synthesized. PGA value determined from each GMPE for known magnitude and hypocentral distances are then converted to EMS values. These calculated EMS values have been used to estimate LLH values which are further used to compute Data Support Index (DSI), rank and weights corresponding to a particular GMPE. Conventionally, LLH values are estimated for the entire distance range and GMPEs are ranked accordingly, but in this study, the LLH is calculated for the distance segments of 0-200 km and 200 km to maximum damaged distance in the region based on Isoseismal maps. If the maximum damaged distance is less than 200 km, a distance segment up to 200 km is adopted. Comparison between the rankings of the GMPEs in segments 0–200 km and 200–maximum damage distance is presented here. Segment-based GMPEs ranking shows different ranks, DSI and weights for each GMPE as compared to ranking considering entire distance. Finally, this study provides a list of GMPEs that perform best for the estimation of ground motion parameters in different parts of PI. This study shows that the GMPEs of HAHO-97, ATK-08, CAM-06, TOR-02, NDMA-10, and PEZA-11 perform better for the estimation of ground motion in most part of PI in the distance segment 0–200 km. The GMPEs of TOR-02, RAIY-07, and RAIY-07 (PI) perform best in the 200-maximum damage distance segment.