Characterization of Earthquake Dynamics in Northeastern India Regions: A Modern Nonlinear Forecasting Approach

The Northeastern India (NEI) region, is seismotectonically one of the most active regions of the world. Earlier studies of NEI earthquake data have provided contrasting evidence for the presence of randomness and low-dimensional ‘‘strange attractor.’’ Here, in the present study, we assess the dimensionality of an earthquake-generating mechanism by nonlinear predictability analyses on phase portrait constructed by monthly frequency earthquake time series which was obtained from the NOAA catalogue. The result of nonlinear forecasting analyses suggests that the earthquake processes in the NEI region evolve on a non-random high-dimensional chaotic system. Such a complex high-dimensional earthquake behavior is indicative of heterogeneous geological structures in which weak fault zones and/or individual fault interactions might have strength fluctuations due to pore pressure variation. Further, K2 entropy analysis was performed to isolate the non-random component from the data. The analysis reveals a quasi-coherent time structure, (K2 0.08/month) which corresponds to a seasonal time scale of about 12 months. We argue that stochastic resonance created by seasonality bias may have combined with noise to affect the pore pressure variation leading to subsequent earthquake triggering. It is interesting to note that most earthquakes and swarm activities occurred during or after the monsoon season. Geological and geophysical evidence also reconciles with the above view. Evidence for high-dimensional chaos associated with ‘‘seasonal’’ bias in the NEI region may provide useful constraints for testing models and criteria to assess earthquake hazards on a more rigorous and quantitative basis.