Ashutosh Chamoli

Wavelet and rescaled range approach for the Hurst coefficient for short and long time series

The calculation of Hurst coefficient (H) by different techniques is sensitive to the length of the profile and noise. Synthetic fractional Brownian motions with different values of H have been generated and the effectiveness of the techniques has been tested on these time series. H values are calculated by wavelet transform (WT), power spectrum (PS), roughness length (RL), semi-variogram (SV), and rescaled range (R/S) methods. On the basis of the error estimates two methods: R/S analysis and WT are suggested for calculation of H for short/long datasets. Further, WT method is applied to geophysical data of the Bay of Bengal. The gravity, magnetic and bathymetry data indicate the self-affine nature with H=0.8, 0.8 and 0.9, respectively.

Multifractality in seismic sequences of NW Himalaya

Multifractal behaviour of interevent time sequences is investigated for the earthquake events in the NW Himalaya, which is one of the most seismically active zones of India and experienced moderate to large damaging earthquakes in the past. In the present study, the multifractal detrended fluctuation analysis (MF-DFA) is used to understand the multifractal behaviour of the earthquake data. For this purpose, a complete and homogeneous earthquake catalogue of the period 1965–2013 with a magnitude of completeness Mw 4.3 is used. The analysis revealed the presence of multifractal behaviour and sharp changes near the occurrence of three earthquakes of magnitude (Mw) greater than 6.6 including the October 2005, Muzaffarabad–Kashmir earthquake. The multifractal spectrum and related parameters are explored to understand the time dynamics and clustering of the events.

Implications of transient deformation in the northern Basin and Range, western United States

Transient deformation events observed in Global Positioning System (GPS) data from the Basin and Range extensional province may illuminate qualitatively similar transient events observed in subduction zones and other tectonic environments. We model GPS time series at 22 sites using a combination of hyperbolic tangent function analysis and elastic load deformation estimated from climatological data. We identify two transient events, ~2000.4 and ~2004.4, with roughly similar timing and displacement to those described previously by other researchers. The first few years of GPS observations, adopted as a reference state in earlier studies, are found to be anomalous. Our results differ from previous studies in two respects. First, a significant component of northward transient motion occurs during both events, despite a reversal of sign in east component motion. Second, sites move coherently in the eastern as well as the western Basin and Range. Surface mass loading, the largest source of transient stress forcing in the region, exhibits no evidence of a simple relationship to the deformation transients. Prior studies inferred slip on a single megadetachment at the Moho, but that hypothesis assumes negligible ductile deformation of the lower crust and a dry olivine rheology for the uppermost mantle. Recent measurements of crustal quartz abundance and effective elastic thickness suggest both assumptions are unlikely. Basin and Range transients can be reconciled with the frictional slip mechanism widely accepted for subduction zone transients provided that slip is occurring on discontiguous detachment surfaces at midcrustal depths.

Investigating the Tsunamigenic Potential of Earthquakes from Analysis of the Informational and Multifractal Properties of Seismograms

Revealing the tsunamigenic potential of an earthquake is very challenging in regards to minimizing the casualties a tsunami can provoke. Thus, development of methodologies that can reliably furnish a early warnings of a tsunami is crucial. In order to accomplish this aim it is important to preliminarily identify the characteristics of seismograms that can be used to distinguish tsunamigenic (TS) earthquakes from non-tsunamigenic (NTS) earthquakes. In this paper P-wave time dynamic of 17 seismograms of TS earthquakes and 26 NTS seismograms are analysed by means of two advanced statistical tools: the Fisher–Shannon method and the multifractal detrended fluctuation analysis (MFDFA). Both methods are well suited to disclosing the inner time properties of complex signals, as seismograms appear to be. Using these two methods jointly, we defined a classifier, the performance of which was tested by means of the receiver-operating characteristic curve that plots true positive rate versus false positive rate. This classifier shows a discrimination power that can be considered acceptable in comparison with the devastating effects caused by a non-alarmed tsunami. Our findings indicate that proper choice of the classifier’s threshold allows correctly identification of approximately 69 % of the NTS seismograms and approximately 76 % of the TS seismograms. The presented results presented may be helpful in addressing the complex problem of early tsunami warning.