Spatiotemporal characteristics and geophysical drivers of the fractal dimension and b-value in North China seismicity

Abstract

The North China Craton Destruction Zone, one of continental China’s most seismically active regions, exhibits complex spatiotemporal seismicity patterns due to its intricate geology. Using the North China Block earthquake catalog (1970–2025), we applied a stochastic declustering method based on the spatiotemporal Epidemic-Type Aftershock Sequence (ETAS) model to process the data. We then calculated the spatial fractal dimension and the b -value of seismicity using the correlation dimension and the maximum likelihood method, respectively. These analyses were conducted to explore their relationships with regional tectonic setting, stress state, and geophysical field characteristics. Declustering increased the spatial fractal dimension of background seismicity from 1.20 to 1.45, effectively reducing spatial clustering without significantly altering the statistical characteristics of the b-value. The fractal dimension is heterogeneous, with high values concentrated in tectonically fragmented zones like the Fen-Wei seismic belt and the central-northern North China Plain, while low values correspond to stable areas such as the Ordos Block. The fractal dimension exhibited systematic temporal changes, characterized by a decreasing before the mainshock and a recovery afterward. This pattern potentially reflects a transition from strain localization, akin to rupture nucleation, to post-seismic stress readjustment, suggesting it may reflect pre-seismic processes. The spatial relationship between fractal dimension and the b -value is complex, showing negative correlation in extreme value zones and positive correlation in moderate value zones. Different parameter combinations ( b -value and fractal dimension) can indicate distinct seismic hazard states. Quantitative analysis reveals the strongest positive correlation between fractal dimension and maximum shear strain rate, and a negative correlation with terrestrial heat flow, confirming that seismic spatial complexity is primarily driven by tectonic forces and modulated by deep thermal state. This study provides refined fractal-based criteria for characterizing seismicity and informing medium- to long-term seismic hazard assessment in the region.