Current study reports the present-day inter-seismic deformation of Kopili fault zone of north-east India and slip rate estimate of Kopili fault using five epochs of global positioning system (GPS) data collected from seven campaigns and five permanent sites. The rate of baseline length change of the GPS sites across the Kopili fault indicates »2.0 mm/yr EÀW convergence across the fault. The fault parallel GPS site velocities clearly indicate dextral slip of the Kopili fault. The fault normal velocities show convergence across the Kopili fault, suggesting it to be a transpressional fault. The fault parallel velocities are inverted for fault slip and locking depth using an elastic dislocation model. The first-order, best-fit elastic dislocation model suggest average right lateral slip of 2.62 § 0.79 mm/yr and a shallow locking depth (3 § 2 km) of the Kopili Fault. The slip of the Kopili fault is contributing to seismic moment accumulation (»70.74 £ 10 15 Nm/yr), sufficient to drive possible future earthquakes (Mw 5.17).

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Accurate geodetic crustal deformation estimates with realistic uncertainties are essential to constrain geophysical models. A selection of appropriate noise model in geodetic data processing based on the characteristics of the geodetic time series being studied is the key to achieving realistic uncertainties. In this study, we report noise characteristics of a 12-yr long global positioning system (GPS) geodetic time series (2002-2013) obtained from 22 continuous mode GPS stations situated in northeast India, Nepal and Bhutan Himalayas which are one of the most complex tectonic regimes influenced by the largest hydrological loading and impacted with a load of the largest inland glaciers. A comparison of the maximum log likelihood estimates of three different noise models-(i) white plus power law (WPL), (ii) white plus flicker law (WFL) and (iii) white plus random walk noise-adopted to process the GPS time series reveals that among the three models, ∼74% of the time series can be better described either by WPL or WFL model. The results further showed that the horizontals in Nepal Himalayas and verticals in northeast India are highly correlated with time. The impact analysis of noise models on velocity estimation shows that the conventional way of assuming time uncorrelated noise models (white noise) for constraining the crustal deformation of this region severely underestimates rate uncertainty up to 14 times. Such simplistic assumption, being adopted in many geodetic crustal deformation studies, will completely mislead the geophysical interpretations and has the potential danger of identifying any inter/intra-plate tectonic quiescence as active tectonic deformation. Furthermore, the analysis on the effect of the time span of observations on velocity uncertainties suggests 3 yr of continuous observations as a minimum requirement to estimate the horizontal velocities with realistic uncertainties for constraining the tectonics of this region.

The area of NorthEast India and Nepal Himalaya undergoes seasonal deformations due to the variation of surface mass loads induced mainly by annual monsoon precipitation. The present study focuses on comparing seasonal horizontal deformations of the Earth's surface obtained over the area of NorthEast India and Nepal Himalaya using Global Positioning System (GPS) and the corresponding ones obtained from Gravity Recovery and Climate Experiment (GRACE) satellite mission data. Seasonal deformations of the Earth's surface in horizontal components were determined using daily observations from 36 GPS stations located in NorthEast India and Nepal Himalaya and Release-05 GRACE-based Global Geopotential Models (GGMs). The consistency between these seasonal horizontal deformations was investigated using three statistical metrics, namely: the correlation, Weighted Root Mean Square (WRMS) reduction and Nash-Sutcliffe model Efficiency (NSE). The results obtained indicate that at nearly 89% of GPS stations investigated, positive correlation can be determined between seasonal deformations of the Earth's surface in the north component obtained from GPS and the corresponding ones from GRACE data. The percentage of WRMS reductions computed from seasonal horizontal deformations of the Earth's surface obtained using GPS and GRACE data reach ~ 18% and 0.71% in north and east components, respectively. Moreover, we obtain the median value of NSE almost 0.28 for north and − 0.01 for east components. The study finds that seasonal horizontal deformations in the area investigated are controlled by local tectonics, and realizes the need of a realistic Earth model comprising local crustal inhomogeneities and tectonic features for better constraining the surface deformations in this region.

<p>The GNSS (Global Navigation Satellite Systems) position time series contains various geophysical signals which can be grouped into tectonic and non-tectonic signals. The tectonic signals include the signals of crustal deformation, volcanic deformation, transient signals of the earthquake and even landslide. On the other hand, the non-tectonic signal contains contributions of various surface mass loadings induced by temporal mass variations within the Earth’s system. The effects of the tidal components of these temporal mass variations are generally get removed during routine GNSS data processing. However, the effects of non-tidal mass loading are typically removed in the post GNSS data processing stage. Therefore, a raw GNSS position time series provides an opportunity to study the sensitivity of a GNSS station towards various non-tidal mass loadings. The understanding of the effect of non-tidal mass loadings in coastal GNSS stations is very important as these coastal GNSS stations are generally used to constrain vertical land motions of Tide gauge stations.</p><p>The objective of this study is to investigate the effects of various non-tidal mass loadings, such as non-tidal ocean loading, non-tidal atmospheric loading, hydrological loading and sea level loading, in a few coastal GNSS permanent stations. The vertical GNSS position time series of these stations are obtained from the Nevada Geodetic Laboratory (NGL) and analysed using the seasonal decomposition method. The seasonal components of the GNSS position time series resulting from this analysis are assessed through surface deformations due to various surface mass loading effects provided by the German Research Centre for Geosciences (GFZ). Furthermore, the resulted seasonal components of the GNSS position time series are also compared with the corresponding ones obtained from Gravity Recovery and Climate Experiment/GRACE Follow-On (GRACE/GRACE-FO) satellite missions data. The results of these assessments and comparisons are analysed and discussed from the perspective of surface deformations induced by non-tidal mass loadings at coastal GNSS stations.</p>