The present study is carried out to understand the factors controlling halogens present in biotites, role of halogens in metallogeny in context to the magmatic evolution of Tusham Ring Complex (TRC), NW Indian Shield. The investigated rocks are identified with hypersolvus, high-K calc-alkaline, peraluminous, ferroan-enriched and typical A-type granitoids affinity. They are enriched in SiO$_{2}$, Na$_{2}$O + K$_{2}$O, REEs (except Eu), LILE + HFSE, elevated in Fe/Mg, Ga/Al, Th/U, A/CNK ratio and depleted in CaO, MgO, Sr, Cr, Ni, P, Ti, V and Eu abundances. The sequential accumulation of incompatible trace elements (LILE, HFSE, REEs and others) in studied rocks overlaps almost entirely the range of rare metal granitoids and high heat-producing granitoids. The elemental geochemistry in conjunction with high abundances of F (0.80–7.11 wt%) and Cl (0.44–1.56 wt%) in biotite mineral collectively attribute to hydrothermal fluid activity and the subsequent mineralization around TRC region. Our new results suggest that the acidic magmatism that occurred in the TRC is considered as a part of the plume-related Neoproterozoic Malani Igneous Suite (MIS) anorogenic magmatism.

$\bf{Highlights}$

$\bullet$ The bulk geochemistry data and the high concentration of fluorine (0.80–7.11 wt%) and chlorine (0.44–1.56 wt %) in biotite mineral indicate halogen enriched magmatic source.

$\bullet$ The halogen enriched magma is an important key to understand the magmatic evolution and metallogeny of Tusham Ring Complex.

$\bullet$ The high concentration of rare metal, rare earth metals and radioactive elements suggests that the investigated granitoids are rare metal granitoids with high heat producing capacity.

$\bullet$ The acid volcano-plutonic rocks of Tusham Ring Complex are important barcodes to reconstruct the Neoproterozoic Rodinia supercontinent and related tecto-magmatic activities occurred in NW Indian shield.

The major objective of any national weather forecasting services is to provide weather forecast and warnings and other meteorological related information to the public and government for the safety of life and property and economic activities. The heavy rainfall causes huge loss to the public in form of flood and landslide in varying severity mainly during monsoon season (June–September). Hence its accurate prediction is essential and the accuracy of prediction needs to be verified quantitatively to evaluate its strength and weakness. The National Weather Forecasting Centre (NWFC) of India Meteorological Department (IMD) issues heavy rainfall (HR) warnings for the safety of life and property of the public. In this study, verification of operational heavy rainfall (HR) warning issued by NWFC of IMD for 36 sub-divisions of India is carried out. The verification scores presented in the study are for 24 hrs (D1), 48 hrs (D2) and 72 hrs (D3) lead period average warning skills during 2014–2018 and year-wise trend of the HR warnings for the period 2002–2018. In general, it is observed that there are significant improvements in skill scores in recent years. The improvement in D3 is at higher rate as compared to D1 scores. The improvement in the recent years is mainly due to improvement in model resolution and data assimilation in the Numerical Prediction (NWP) Models runs by Ministry of Earth Sciences (MoES), Government of India and their interpretation and utilization by the forecasters for objective consensus forecast using an objective decision support system and synoptic value addition.

$\bf{Highlights}$

$\bullet$ There is significant improvement in heavy rainfall warning skill of India Meteorological Department during monsoon season in recent two years (2017 and 2018) as compared to 2002–2016.

$\bullet$ The skill scores namely, Probability of Detection (PoD), Critical Success Index (CSI) and Heidke Skill Score (HSI) has improved by 48%, 46% and 33%, respectively, as compared to mean of scores between 2002–2016 for Day 1 (D1) warning.

$\bullet$ In Day 3 (D3) warning, there is an improvement by 69%, 54% and 54% in PoD, CSI and HSS respectively during 2017–2018 as compared to mean of 2013–2015. The improvement in D3 warning is at higher rate as compared to D1 warning.

$\bullet$ In general, the skill scores are higher over the regions with higher frequency of heavy rainfall and lower over less prone regions of heavy rainfall.

$\bullet$ These improvements in the forecast warning skill may be attributed to availability and use of latest forecasting models with high resolution and better data assimilation. Apart from the above, the structured monitoring of the monsoon circulations parameters, interpretation of NWP models guidance through Forecast Demonstration Project (FDP), objective consensus through decision support system and subjective consensus amongst the forecasters through video conference contributed significantly improved HR warning in recent years.

Fluoride (F$^{-}$ ) pollution in groundwater of the Older Alluvial Plain (OAP) of Delhi has been reported as a major problem. About 34% of the groundwater samples collected for this study had F$^{-}$ level beyond the permissible limit; with F$^{-}$ concentration in the range of 0.14–3.15 mg/L (average 1.20 mg/L). In this context, this article for the first time attempts on the genesis of major ions chemistry and F$^{-}$ pollution in groundwater of OAP Delhi by going beyond the statistical analysis to sediment geochemistry, chemical weathering processes and understanding of the processes using stable environmental isotopes ($^{2}$H and $^{18}$O). The XRD of the OAP sediments revealed the dominance of fluor-biotite, albite, calcite, quartz, and chlorite. Whereas, the separated clay revealed the dominance of chlorite, kaolinite, and illite minerals. The saturation index (SI) values indicated that the groundwater chemistry is in the process of further F$^{-}$ enrichment by way of sediment groundwater interaction. With the given mineralogy of the sediments, the dominance of major ions like Na$^{+}$), K$^{+}$, Mg$^{2+}$, Ca$^{2+}$, Cl$^{-}$ and F$^{-}$ has been attributed to chemical weathering of biotites, phlogopites, albite, and calcite during sediment–water interaction. While the dominance of SO$_{4}$ $^{2-}$ has been attributed to anthropogenic sources and confirmed by its association with heavier stable isotopes of hydrogen ($\delta^{2}$H: −50.44 to −40.02 per thousand) and oxygen ($\delta^{18}$O: −7.19 to −5.62 per thousand) indicating evaporative enrichment during isotopic fractionation.

In the recent past, there were extensive floods in the Western Himalayan region (WHR) due to continuous long spells of heavy rainfall for 3–4 days that caused a huge loss in life and property over the region. WHR is a data sparse region, with limited meteorological stations having a continuous long spell of daily precipitation data. In the present study, spatial and temporal variability of seasonal as well as annual precipitation, precipitation days and maximum accumulated daily, 2 days, 3 days, 4 days and 5 days precipitation over WHR is considered by using daily precipitation data of 18 meteorological stations of the region. Out of 18 meteorological stations, five stations have continuous data from 1901 to 1980 and remaining 13 stations data is considered for their common period from 1981 to 2014. Accordingly, the analysis is carried out in two parts, first for 1901–1980 (for 5 stations) and second for 1981–2014 (for all the 18 stations). The analysis suggests high variability in the spatial and temporal distribution of seasonal as well as maximum accumulated daily to 5 days precipitation over WHR. In general, increasing trends in maximum accumulated precipitation in lower altitude stations and decreasing trends in higher altitude stations are observed in monsoon season and vice-versa in the winter season during the period 1981–2014. The increase in maximum accumulated daily to 5 days precipitation is up to 9.7 mm per decade during 1901–1980 and is up to 45.5 mm per decade during 1981–2014 in monsoon season in lower altitude stations. Thus, the increase in maximum accumulated precipitation during monsoon season becomes manifold during 1981–2014 as compared to the period 1901–1980.

Identification of thin interbedded non-coal bands and coal seams with varying carbon contents within a coal seam is of paramount interest in coal exploration due to its banded nature. The manual interpretation and conventional modelling based on Fourier/Walsh transform techniques fail to derive such information accurately from geophysical well log data due to its non-stationary nature. The present study proposes a combined principal component analysis (PCA) and continuous wavelet transform (CWT) algorithm for automatic lithological modelling of geophysical well log data. In the first step of well log lithology modelling, a median filter is applied on well log data to preserve the thinner beds and other valuable geological signatures of coal seams. In the second step, the filtered log data is subjected to PCA, and the variance level of PC scores is determined to study the physical relationship of input parameters. The third step is to apply CWT on the selected PC scores and determine lithological discontinuities from the modulus maxima lines drawn on the wavelet scalogram. For filling the lithology skeleton with the proper interpretation, a database is also created by correlating the selected PC score values with input parameters. We have applied the proposed algorithm to gamma ray, density, and resistivity logs of two boreholes located in the Bisrampur and Jharia coalfields of eastern India. The results of the proposed PCA-CWT based modelling match well with core data and manual interpretations of the boreholes. At a few depth ranges, the proposed algorithm also reveals some additional lithological discontinuities that were not mapped in the core data. The study further conveys that PCA-CWT-based lithological modelling of geophysical logs is helpful to pace up the exploration work in coal blocks with poor core recovery.