Earthquake recurrence probability assessment using integrated multi-fault paleoseismic data: application to the East Kunlun Fault Zone

Reliable earthquake recurrence probability assessment is crucial for seismic hazard mitigation but remains challenging due to sparse paleoseismic data on individual faults. We present an enhanced integrated multi-fault approach that addresses critical limitations in existing methods by incorporating both local and regional paleoseismic data through Monte Carlo simulation. Our method: (1) includes local fault variability data rather than relying solely on non-local sources, (2) restricts analysis to tectonically similar fault zones, and (3) explicitly accounts for epistemic uncertainties in mean recurrence intervals. We applied Brownian Passage Time (BPT) models to seven segments of the East Kunlun Fault Zone in China. Our analysis reveals that mean recurrence intervals are systematically higher than simple arithmetic averages. When dating uncertainties are not considered, coefficients of variation range from 0.48 to 0.60. However, when dating uncertainties are incorporated, coefficients of variation increase substantially to 0.59–0.81. Fifty-year earthquake probabilities vary significantly among segments, with Dongxidatan (0.115), Maqu (0.054), Maqin (0.040), and Tazang (0.026) showing highest probabilities. These results highlight the crucial role of chronological uncertainty in hazard assessment. This methodology provides a robust framework for seismic hazard assessment in data-sparse regions, offering improved reliability for earthquake risk evaluation and disaster preparedness.