Sensitivity Analysis on the Impact of Input Parameters on Seismic Hazard Results: A Case Study of Central America

We present a sensitivity analysis on the impact of input parameters and methods used on the results of a probabilistic seismic hazard assessment (PSHA). The accurate estimation of the parameters in recurrence models (declustering and fitting methods), along with the selection of scaling relationships for determining maximum magnitude and the selection of ground motion models (GMMs), enhance control over epistemic uncertainties when constructing the logic tree, minimizing final calculation errors and producing credible results for the study region. This study focuses on Central America, utilizing recent data from seismic, geological, and geophysical studies to improve uncertainty analyses through classic statistical methods. The results demonstrate that proper fitting of the recurrence model can stabilize acceleration variations regardless of the declustering method or b-value fitting method used. Regarding scaling relationships, their low impact on the final results is noted, provided the models are tailored to the tectonic regime under study. Finally, it is shown that the GMM contributes the most variability to seismic hazard results; therefore, their selection should be conditioned on calibration with observed data through residual analysis where region-specific models are not available.