Water vapour is highly variable over tropical region and sensitive to weather condition, monsoon onset, green house effect, and pollution level in Ganga River. In the present study, variability in water vapour derived from Global Positioning System (GPS) over Varanasi (25$^{\circ}$20$^{\prime}$N, 82$^{\circ}$59$^{\prime}$E) during the period 2007–2010 has been studied. The GPS-derived water vapour (WV) has been compared with those retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) and ECMWF. The GPS-WV data concurrent to MODIS and ECMWF timing has been correlated to perform further analysis. To study the accuracy of water vapour retrieved from the MODIS and ECMWF, root mean square error (RMSE), absolute error (AE), correlation and standard deviation in it are computed with respect to GPS-derived water vapour. Analysis shows an annual correlation $R^{2}$ = 86%, RMSE = 9.5 mm and AE (MODIS–GPS) = 7.0 mm in MODIS retrieval and annual correlation R$^{2}$ = 86%, RMSE = 6.1 mm and AE (ECMWF–GPS) = 2.4 mm in ECMWF reanalysis retrieval. Correlation of ECMWF and MODIS datasets with the GPS datasets are found to vary significantly with seasons. The correlation is high during monsoon season and low during spring season. Water vapour is found to be an indicator for the onset of monsoon.

$\bf{Highlights}$

$\bullet$ Accuracy of water vapor (WV) retrieved from the MODIS and ECMWF with respect to GPS WV.

$\bullet$ High Annual correlation of $R^{2}$ = 0.86 between both MODIS–GPS and ECMWF–GPS.

$\bullet$ The correlation is high during monsoon season and low during spring season.

$\bullet$ The performance of ECMWF is found to be better than that of MODIS.

Magnetotelluric (MT) data has been collected along 32 stations along E–W profile in northern part and eight LMT (long period MT) stations in north-central part of Saurashtra region. Dimensionality analysis is carried out prior to MT modelling for obtaining the subsurface dimension as well as the direction of the underlying substructures. To estimate the subsurface dimensionality from MT data, different techniques Swift skew, Bhar’s skew, normalized weights, phase tensor (PT) analysis and Wall’s rotational invariant approach have been applied. These results suggest 1D structure for lower periods (0.01–1 s) and 3D structure for higher periods (1–10000 s) along two different profiles indicating that the study area is highly heterogeneous. Regional strike has been estimated through phase tensor (PT) and Groom–Bailey (GB) techniques suggests N40$^{\circ}$ E regional strike direction that correlates well with the Delhi–Aravalli tectonic trend. 2D modelling of MT/LMT data sets brings out different resistivity and conductivity blocks. Basaltic magmatic intrusion and its recrystallization have resulted in resistivity blocks with conductivity anomalies (trapped fluids) in between them. It has been reflected as 3D structures at higher periods. Different sedimentary basins at shallow depth are observed as 1D structure in dimensionality analysis.

$\bf{Highlights}$

$\bullet$ Magnetotelluric (MT)/long period Magnetotelluric (LMT) survey is carried out in northern part of Saurashtra. Different dimensionality techniques were used to assess the structural dimensionality of the electrical conductivity of the earth and were compared.

$\bullet$ Analysis of MT sites by using various methods indicates the electrical conductivity structure is less complex at the shallowest depths with mixed 1D and 2D cases that are affected by galvanic distortion. Both MT/LMT denote complex 3D nature from middle and lower depths.2D inversion of MT/LMT data brings out large-scale heterogeneities in the crust. This is attributed to different resistive and conductive blocks present at mid-crustal depths and extending up to lower crustal depths and correlates with dimensionality analysis.

The perturbation produced in the atmosphere/ionosphere associated with earthquake precursors during seismic activity of two major earthquakes which occurred on (1) 24 June 2019 in Indonesia (M = 7.3) and (2) on 19 August 2018 at Ndoi, Fiji (M = 8.2), are studied. Based on statistical analysis of total electron content (TEC) data, the presence of ionospheric perturbations 5 days before and after the main shock are found, which depends on the distance as well as direction of observation point from the epicentre. In general, ionospheric perturbations after the EQ at all the stations are found larger than that before the EQ. Probable mechanisms behind these perturbations associated with EQ are also being discussed. The ionospheric perturbations are observed at stations which are at larger distances from the epicentre, but not observed over other stations in different directions which are comparatively closer to the epicentre. These results suggest that seismic induced ionospheric anomaly is not isotropic in nature. Ozone data from three satellites: AIRS, OMI, and TOMS-like and MERRA-2 model are also analyzed 5 days before the EQ day and compared to the monthly average level. A strong link between anomalous variation in ionospheric TEC and atmospheric ozone data prior to both the EQs is noticed.

Both audio-magnetotelluric and magnetotelluric data were acquired across Aravalli and Tural hot springs (in Konkan region of Deccan volcanic province). The objective is to bring out the geoelectrical crustal structure beneath these geothermal zones. Two-dimensional inversion of data brings out different conductivity anomalies (i) shallow conductivity anomaly related to upward propagation of meteoric water through faults/fracture zones, (ii) major fracture/fault zones extending up to midcrustal depths through which Deccan volcanism may have erupted and (iii) the presence of mid-crustal conductivity anomalies are related to trapped carbonate Cuids that are linked to thermal effects of Deccan volcanism.