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The Darjiling-Sikkim Himalaya (DSH) is located over the Dharan-Gorubathan salient-recess pair and moderate thrust and strike-slip earthquake occur here. The hypocentres cluster not only near the location of the Main Himalayan Thrust (MHT) or the basal decollement of the Himalayan wedge, but also well above and below it. The epicentres cluster over the mapped location of the Lesser Himalayan Duplex (LHD), suggesting that both MHT and LHD are active structures in DSH. The earthquakes below MHT can be related to transverse strike-slip faulting in DSH associated with salient-recess transition on both flanks of the Dharan salient. The 18 September 2011 (Mw 6.9) strike-slip event suggests that the western flank of the Dharan salient is also likely to contain an active transverse strike-slip fault like the Gish Transverse Fault (GTF) on its eastern flank. High-precision Global Positioning System measurements (1997-2006) indicate that a maximum of ~4 mm/year convergence is being accommodated in the Tista Half-Window or LHD west of the surface trace of GTF and DSH is locked south of 27°N both east and west of GTF about 10 km north of the Himalayan mountain front. About 3-4 mm/year sinistral strike-slip is postulated on GTF north of 27?N. Dislocation based forward modelling using two thrust dislocations with oblique slip and a sinistral strike-slip dislocation generated velocities that were closest to the measured back-slip velocity field in DSH. [ABSTRACT FROM AUTHOR]

This study evaluates the impact of multi-GNSS (Global Navigation Satellite System) signals on the estimation of precise position with millimetre accuracy. Compared to standalone satellite systems like the Global Positioning System (GPS), multi-GNSS improves start-up time, performance, satellite visibility, accuracy, spatial geometry and reliability. However, on the flip side it increases the noise, signal interference, hardware complexity of the receiver, intersystem interference and computation complexity which may degrade its performance. Though GNSS is similar at fundamental levels, differences exist in signal structures, reference frames and timing standards. Compatibility and interoperability between the different constellations of the highest order is required to achieve the best results. At present, GPS and Glonass navigation systems are fully functional with global coverage and comparable precision. Glonass satellite constellation, signal structure is slightly different when compared to GPS, whereas major differences exist in the reference frame and epoch time. Combined GPS–Glonass solution significantly improves the accuracy in navigation applications with increased satellite signal observations and spatial distribution of visible satellites. For precise geodetic studies using static post-processing, combined solution may degrade the accuracy, if these differences are not handled carefully. Currently for geodetic studies, only GPS observations are majorly used worldwide. For the first time, daily precise position is estimated for continuous GNSS stations located in India using static postprocessing with standalone GPS, Glonass as well as combined GPS–Glonass to study the impact of multiGNSS signals for geodetic studies. [ABSTRACT FROM AUTHOR]

• Performance of IRI-2016 model is probed through geodetic GPS TEC during 2002–2019. • Large discrepancy is observed in high solar activity phases in both solar cycles. • IRI model fails to manifest the strength of ionization around EIA crest regions. • Differences are observed more during day time hours in all the phases of solar activity. • Winter anomaly is not reflected in IRI outputs during high solar activity years. We evaluate the performance of the latest version of International Reference Ionosphere (IRI-2016) by comparing the estimated Total Electron Content (TEC) with the observed values from four geodetic Global Positioning System (GPS) receivers, latitudinally aligned from the equator to low latitudes (−5° to 20° Geomagnetic) in the Indian longitudes (75–95°) from 2002 to 2019. It is observed that IRI-2016 model underestimates and overestimates the GPS TEC depending on the season, solar activity, and geographic location of observation. On a decadal scale, the monthly mean of IRI TEC and GPS TEC show distinct seasonal variation trends for all years with seasonal asymmetry. The bias and RMSE values are low in the ascending and descending phases of solar cycles 23 and 24 compared to high values with significant fluctuations observed during the peak solar activity phase. For the declining phase of solar cycle 24, IRI TEC underestimates the GPS TEC values at EIA crest regions. On an annual scale, IRI TEC agrees better with GPS TEC during the low solar activity years (2010 and 2019) than the high solar activity years (2002 and 2014). Moreover, IRI model is unable to manifest the winter anomaly characteristics during the high solar activity years. On a diurnal scale, the performance of IRI model is poor with high RMSE during daytime hours and it underestimates the GPS TEC at equatorial and low latitude regions during the high solar activity phases. On a seasonal scale, high bias and RMSE are observed during the spring equinox compared to other seasons under the high solar activity phases. On a spatial scale, the bias and RMSE are high with low yearly coefficient of determination ( R 2) in the EIA crest regions as compared to the equatorial and low latitude regions. High underestimation of IRI model was also observed in November 2011 due to high solar indices. The proportionality relationship between RMSE and solar indices is observed in all the phases of solar activity. Additionally, the mean annual RMSE and R 2 values indicate solar activity predominantly affecting the performance of IRI model. This study suggests that the influence of solar and magnetic indices inputs in the present IRI model could be revisited for reflecting the solar activity effects distinctly in the model outputs. In addition, IRI-2016 model requires further improvements for equatorial, low latitude, and EIA crest regions of the Indian sub-continent, specifically during the high solar activity phases. [ABSTRACT FROM AUTHOR]

The Shuttle Radar Topography Mission (SRTM) Digital Terrain Elevation Data (DTED) are used with the consensus view that it has a minimum vertical accuracy of 16 m absolute error at 90% confidence (Root Mean Square Error (RMSE) of 9.73 m) world-wide. However, vertical accuracy of the data decreases with increase in slope and elevation due to presence of large outliers and voids. Therefore, studies using SRTM data 'as is', especially in regions like the Himalaya, are not statistically meaningful. New data from ~200 high-precision static Global Position System (GPS) Independent Check Points (ICPs) in the Himalaya and Peninsular India indicate that only 1-arc X-Band data are usable 'as is' in the Himalaya as it has height accuracy of 9.18 m (RMSE). In contrast, recently released (2014-2015) 'as-is' 1-arc and widely used 3-arc C-Band data have a height accuracy of RMSE 23.53 m and 47.24 m and need to be corrected before use. Outlier and void filtering improves the height accuracy to RMSE 8 m, 10.14 m, 14.38 m for 1-arc X and C-Band and 3-arc C-Band data respectively. Our study indicates that the C-Band 90 m and 30 m DEMs are well-aligned and without any significant horizontal offset implying that area and length computations using both the datasets have identical values. [ABSTRACT FROM AUTHOR]