Quantifying the Impact of Declustering Techniques on Completeness Magnitude Estimation

Seismicity analysis and earthquake hazard assessment require catalogs of independent events and accurate estimates of completeness. The magnitude of completeness (Mc) defines the threshold below which earthquakes are likely to be missed; declustering, used to remove dependent events, can substantially alter Mc by reshaping the lower tail of the frequency–magnitude distribution. Because such changes propagate to the Gutenberg– Richter b-value, method choices may bias downstream analyses. Using a regional instru-mental catalog from southern Italy, we try to quantify how widely used declustering approaches affect catalog-based estimates of Mc. We apply three declustering families: fixed window (Gardner and Knopoff original formulation, including Gruenthal and Uhrhammer windows), linked window (Reasenberg, three parameter configurations), and nearest neighbor. Then we estimate Mc with five catalog-based methods: maximum curvature, goodness-of-fit test, median-based analysis of segment slope, entire magnitude range, and magnitude of completeness by b-value stability. Comparing across declustered and observed catalogs, we evaluate how declustering event removal modifies the fre-quency–magnitude distribution and in turn the sensitivity of catalog-based Mc methods to these modifications. Resampling is used to assess precision and stability, the results remain essentially unchanged even with small bootstrap sizes, indicating the need but large numbers of resamples are unnecessary. Overall, the analysis highlights that declus-tering choice and completeness estimation are critical decisions and should be reported jointly when deriving the b-value for seismic hazard applications.