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Abstract

The b-value, obtained from the Gutenberg-Richter distribution, is a critical parameter for probabilistic seismic hazard assessment. It describes the relative ratio of small to large earthquakes in a scale-free population. However, in earthquake sequences, this parameter experiences variations not accounted for in conventional seismic hazard models. Therefore, understanding the nature and impact of these variations is crucial, particularly in regions with high seismicity or prone to aftershock sequences that can last several days, weeks, or even months. Different techniques and methods are commonly employed to estimate the b-value, but they could introduce uncertainties or biases in the calculation. The amount of data used to estimate this parameter is critical in its estimation. Despite this, the behavior of the b-value during aftershock sequences and its influence on seismicity rates are not yet fully understood. In this study, we evaluate how various factors in an aftershock sequence can influence the estimation of the b-value by analyzing real and synthetic data from different contexts and characteristics. We aim to enhance the accuracy of probabilistic seismic hazard assessments and advance our knowledge of earthquake physics. The findings of this study have significant implications for improving the understanding of earthquake processes and hazard assessments. Accurate estimates of the b-value are essential for forecasting earthquake activity and assessing potential risks in seismically active regions.