Multivariate singular spectrum analysis of seismicity in the space–time-depth-magnitude domain: insight from eastern Nepal and the southern Tibetan Himalaya

The aim of the current study is to apply multivariate singular spectrum analysis (M-SSA) techniques and investigate both shallow and intermediate-depth earthquake characteristics in eastern Nepal and the southern Tibetan Himalaya. Space–time-depth-magnitude (STDM) domain time-series were computed for a time window of 776 events, using a complete catalog (2005–2020) provided by the European-Mediterranean Seismological Center. Several criteria and tests, such as the quantile–quantile plot, Hankel matrix, and principal and reconstruction components analysis of STDM time-series were introduced to characterize the causality and predictability of seismic changes. It was evident from the quantile–quantile plot those events (Mw) do not approximate a linear trend but present a nonlinear trend, which is possibly due to the unusual seismically generated strain that cannot be accurately unstable compared to large earthquakes. Principal component analysis of the Hankel matrix strongly influences the ability of M-SSA to extract the measured and noise errors of an STDM time-series. Based on a reconstruction component analysis, the separability of the varying correlation coefficient between measured and predicted STDM time-series was evaluated and reconstructed in three groups: trend, oscillating, and noise group components. In conclusion, supporting the current research, it can be claimed that the results serve as a baseline study of seismicity using the M-SSA approach; by taking the example of eastern Nepal and the southern Tibetan Himalaya, users will be able to utilize M-SSA at the global level.