Empirical earthquake source scaling relations for maximum magnitudes estimations in Central America

Central America is a seismically active region where six tectonic plates (North America, Caribbean, Cocos, Nazca, Panama, and South America) interact in a subduction zone with transform faults and two triple points. This complex tectonic setting makes the maximum magnitude - M (sub max) - estimation a challenging task, with the crustal fault earthquakes being the most damaging in the seismic history of Central America. The empirical source scaling relations (ESSR) allow the M (sub max) of faults to be determined from rupture parameters. In this study, we use a dataset of well-characterized earthquakes in the region, comprising 64 events from 1972 to 2021 with magnitudes between M (sub w) 4.1 and 7.7. The dataset incorporates records of rupture parameters (length, width, area, slip, and magnitude) and information on the faults and aftershocks associated. This database is an important product in itself, and through its use we determine which global relations fit best to our data via a residual analysis. Moreover, based on the best-quality records, we develop scaling relations for Central America (CA-ESSR) for rupture length, width, and area. These new relations were tested and compared with recent earthquakes, and logic trees are proposed to combine the CA-ESSR and the best-fit global relations. Therefore, we estimate the M (sub max) for 30 faults using the logic tree for rupture length, considering a total rupture of the fault and multifault scenarios. Our results suggest that in Central America rupture areas larger than other regions are required to generate the same magnitudes. We associate this with the shear modulus (mu ), which seems to be lower ( approximately 30% less) than the global mean values for crustal rocks. Furthermore, considering multifault ruptures, we found several fault systems with potential M (sub max) > or = M (sub w) 7.0. These findings contribute to a better understanding of regional seismotectonics and to the efficient characterization of fault rupture models for seismic hazards.