Improving estimates of the b-value in regional catalogs by means of the the b-more-positive method
Abstract
The b-value, which controls the slope of the frequency-magnitude distribution of earthquakes, is a critical parameter in seismic forecasting. However, accurately measuring the true b-value is challenging due to the temporal and spatial variations in the completeness of instrumental seismic catalogs. In this study, we systematically compare traditional methods for estimating the b-value with newer approaches, specifically focusing on the b-more-positive estimator based on positive magnitude difference statistics. We conduct this comparison using both synthetic ETAS catalogs, with artificially introduced incompleteness, and instrumental catalogs from five regions: Japan, Italy, Southern California, Northern California, and New Zealand. Our analysis of synthetic ETAS catalogs demonstrates that traditional estimators systematically underestimate the b-value under incompleteness scenarios, whereas the b-more-positive estimator yields highly accurate results. Consistent patterns are found in instrumental catalogs, suggesting that conventional methods also underestimate the b-value in real datasets, with important implications for seismic forecasting. Moreover, the b-more-positive estimator provides robust evidence of significant differences in the b-value across the considered geographic regions.
Non-technical summaryThe b-value measures the ratio of small to large earthquakes and could provide insights into the stress state of fault zones, making it a key tool in earthquake forecasting. However, accurately estimating the b-value is challenging because small earthquakes are often hidden by larger ones or missed due to detection limitations. In this study, we demonstrate that the novel b-more-positive estimator, which expands upon the innovative approach introduced by the b-positive estimator, provides a more reliable b-value calculation. Unlike traditional methods, which systematically underestimate the b-value, the b-more-positive estimator overcomes the challenges of data incompleteness. This conclusion is supported by extensive simulations using synthetic earthquake catalogs, where the impact of incomplete data was deliberately modeled.
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BibTeX
@article{lippiello2026improving,
title = {{Improving estimates of the b-value in regional catalogs by means of the the b-more-positive method}},
author = {Eugenio Lippiello and Cataldo Godano and Giuseppe Petrillo},
journal = {Seismica},
year = {2026},
month = jul,
doi = {10.26443/seismica.v5i2.1689},
url = {https://hal.science/hal-05773508v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Improving estimates of the b-value in regional catalogs by means of the the b-more-positive method
AU - Eugenio Lippiello
AU - Cataldo Godano
AU - Giuseppe Petrillo
PY - 2026
DA - 2026/07/25
JO - Seismica
DO - 10.26443/seismica.v5i2.1689
UR - https://hal.science/hal-05773508v1
AB - The b-value, which controls the slope of the frequency-magnitude distribution of earthquakes, is a critical parameter in seismic forecasting. However, accurately measuring the true b-value is challenging due to the temporal and spatial variations in the completeness of instrumental seismic catalogs. In this study, we systematically compare traditional methods for estimating the b-value with newer approaches, specifically focusing on the b-more-positive estimator based on positive magnitude difference statistics. We conduct this comparison using both synthetic ETAS catalogs, with artificially introduced incompleteness, and instrumental catalogs from five regions: Japan, Italy, Southern California, Northern California, and New Zealand. Our analysis of synthetic ETAS catalogs demonstrates that traditional estimators systematically underestimate the b-value under incompleteness scenarios, whereas the b-more-positive estimator yields highly accurate results. Consistent patterns are found in instrumental catalogs, suggesting that conventional methods also underestimate the b-value in real datasets, with important implications for seismic forecasting. Moreover, the b-more-positive estimator provides robust evidence of significant differences in the b-value across the considered geographic regions. Non-technical summaryThe b-value measures the ratio of small to large earthquakes and could provide insights into the stress state of fault zones, making it a key tool in earthquake forecasting. However, accurately estimating the b-value is challenging because small earthquakes are often hidden by larger ones or missed due to detection limitations. In this study, we demonstrate that the novel b-more-positive estimator, which expands upon the innovative approach introduced by the b-positive estimator, provides a more reliable b-value calculation. Unlike traditional methods, which systematically underestimate the b-value, the b-more-positive estimator overcomes the challenges of data incompleteness. This conclusion is supported by extensive simulations using synthetic earthquake catalogs, where the impact of incomplete data was deliberately modeled.
SN - 2816-9387
ER -