Geology, petrography and geochemistry of rhyolite-hosted uranium mineralization at Mohar, Shivpuri district, Madhya Pradesh

In the westernmost part of the Bundelkhand Granitoid Complex (BGC), a mesa structure represents a unique outlier, surrounded by brecciated granite and filled with Vindhyan sedimentary rocks locally known as the Dhala Formation near Mohar village of Shivpuri district, Madhya Pradesh. Uranium mineralisation located in the area is mostly associated with rhyolite of peralkaline to peraluminous in nature, that has a high average uranium concentration (30 ppm). The mineralization is in or adjacent to caldera and is hydrothermal vein-type. Radioactivity is mainly due to coffinite with limited radioactivity due to U-Ti complex, uranium adsorbed in clay and labile uranium along fracture. Coffinite occurs in association with pyrite and chalcopyrite or chlorite with presence of fluorite. Features such as chloritisation, clay formation and sulfide mineralisation manifest hydrothermal alteration. Chemical analysis indicates the aluminous nature of the rock and their high K₂O/Na₂O (3.81–12.84) ratios are suggestive of predominance of potash feldspar over sodic. The alteration index varies from 49.88–92.40, which, reflects high intensity of hydrothermal alteration. Chlorite-carbonatepyrite index (CCPI), a measure of the intensity of replacement of sodic feldspars and glass by sericite, chlorite, carbonate, and pyrite associated with hydrothermal alteration proximal to the ore bodies varies from 3.84–49.66. On the basis of core study, geochemistry and mineralogy, it is envisaged that epigenetic hydrothermal solutions were responsible for concentration of uranium as coffinite, radioactive carbonaceous matter and adsorbed uranium phases in rhyolite with sulfide confined to weak planes.     

Electrical Resistivity Imaging technique to delineate coal seam barrier thickness and demarcate water filled voids

Exploration and exploitation of coal seams is one of the major resources for the energy sector in any country but at the same time water filled voids/water logged areas in the old workings of these seams are very critical problems for the coal mining industry. In such situations, disasters like inundation, landslides, collapsing of the old seams may occur. In this regard, it is necessary to find out the water saturated/water filled voids and zones in the mining areas. Since no established technique is available to find such zones, an experimental study using Electrical Resistivity Imaging (ERI) has been carried out in one of the coal mining areas near Dhanbad, to find out the feasibility of finding the barrier thickness and the water logged area in underground coal mines. The area under study forms part of Jharia coalfield in Dhanbad district, Jharkhand state. The coal bearing rocks of Barakar Formation of Lower Permian age (Gondwana period) occur in the area under a thin cover (10 m to15 m) of soil and or alluvium. Coal bearing Barakar Formations consist mainly of sandstone of varying grain size, intercalation of shale and sandstone, grey and carbonaceous-shale and coal seams. Since the water saturation reduces the resistivity of a formation to a large extent, water filled voids and old coal workings are expected to have significant resistivity contrast with the surrounding host rock. Hence, ERI technique was applied in such an environment as this technique uses high-density data acquisition both laterally and vertically by using multiple number of electrodes. Along with ERI, mise-à-la-masse (also called charged body) technique was also employed at one of the promising sites to find out the connectivity of water logged areas and also detection of these old workings from the surface measurements was analyzed. The interpreted 2D resistivity sections have clearly indicated the water bearing zone(s) along the profile which was well confirmed with the existing water level in the nearby borewells. On the other hand, this technique did not identify the size of the coal pillar and gallery (air filled voids), which might be due to the small size of the voids (i.e. about 2 m × 2 m) below a depth of 15m and more but have indicated altogether as a high resistive zone ranging from 600–1000 Ohm-m.     

Hydrogeochemical Characterization and Groundwater Quality of Jamshedpur Urban Agglomeration in Precambrian Terrain,Eastern India

This paper reports petrography, geochemistry and Rb-Sr age data on the rare metal bearing Neoarchean fertile (Nb-Ta) granite at Allapatna and elucidates its petrogenesis and role in Nb-Ta-Li-Be mineralization. The Allapatna granite (AG) intrudes the Tonalitic-Trondhjemitic - Granodioritic (TTG) Peninsular Gneiss and analysed SiO₂ (72.3-75.6 wt%), K₂O (4.0-5.7wt%), Na2O (3.0-4.4wt%), CaO (0.7-1wt%), MgO (0.13-0.25wt%) and K₂O/Na₂O (>1) indicating evolved nature. The presence of muscovite, biotite and garnet in the mode, peraluminous nature and high initial ⁸⁷Sr/⁸⁶Sr ratio (0.7284±0.0083) attest to their S-type characteristics. Varying Nb/Ta ratio and high Li with moderate abundance of Cs further indicate affinity to Li-Cs-Ta (LCT) type granite-pegmatite system. TheAG showing whole rock Rb-Sr isochron age of 2803± 68 Ma, is the oldest reported fertile granite in India parental to rare metal pegmatites hosting Nb-Ta, Be, and Li resources. Partial melting of a mixed source consisting of both basement TTG rocks and metapelites has generated such type of granitic magma. Fractionation of such granitic magma possibly has given rise to the rare metal (Ta-Nb-Li-Be) bearing pegmatites intruding the nearby schist belt.     

Rainfall flood hazard at nuclear power plants in India

Flood hazard evaluation is an important input for Nuclear Power Plants external events safety studies. In the present study, flood hazard at various nuclear sites in India due to rainfall has been evaluated. Hazard estimation is a statistical procedure by which rainfall intensity versus occurrence frequency is estimated from historical records of rainfall data and extrapolated with asymptotic extreme value distribution. Rainfall data needed for flood hazard assessment are daily annual maximum rainfall (24?h data). The observed data points have been fitted using Gumbel, power law and exponential distribution, and return period has been estimated. To study the stationarity of rainfall data, a moving window estimate of the parameters has been performed. The rainfall pattern is stationary in both coastal and inland regions over the period of observation. The coastal regions show intense rainfall and higher variability than inland regions. Based on the plant layout, catchment area and drainage capacity, the prototype fast breeder reactor (PFBR) site is unlikely to be flooded.     

Assessment of flexural analysis applied to the Sumatra-Java subduction zone

Indian Ocean subduction zone is one of the most active plate margins of the globe as evident from its vast record of great magnitude earthquake and tsunami events. We use Bouguer admittance (Morlet isostatic response function) in Sumatra-Java subduction zones comprising both the subduction and over-riding plates to determine the lithospheric mechanical strength variations. We determine effective elastic thickness (T _e ) for five oceanic windows (size 990 × 990 km²) by analyzing the admittance using Bouguer gravity and bathymetry data. The results show bimodal T _e values < 20 km for Sumatra and 20−40 km for Java. The lower bimodal values obtained for Sumatra appears to correlate well with the zones of historical seismicity. This is in sharp contrast with Java subduction zone, which shows higher T _e values (20–40 km) and apparently associated with low magnitude earthquakes. We suggest a strong and wide interseismic coupling for Sumatra between the subducting and over-riding plates, and deeper mantle contributing to low strength, shallow focus — high magnitude seismicity and vice versa for Java, leading to their seismogenic zonation.     

Identification of aquifer-recharge zones and sources in an urban development area (Delhi, India), by correlating isotopic tracers with hydrological features

Recharge zones and sources in an urban setup (NCT of Delhi, India) were identified using environmental isotopes (²H, ³H, ¹⁸O); they were then correlated with hydrogeological conditions. The isotopic results showed that groundwater is being recharged by surface water during the dry season, while recharge associated with local precipitation becomes prominent during the monsoon. The effect of source-water evaporation and altitude on the isotopic characteristics of groundwater was clearly noted. A gradual increase in groundwater age, i.e. decrease in tritium content, while moving away from the river/canals/drains, suggests a degree of mixing of old-aged groundwater with relatively young recharging water. Further, to substantiate the findings of isotopic investigations, surface recharge conditions were differentiated into potential pervious (recharge prone) and impervious (recharge resistant) surfaces through mapping of potential recharge areas based on soil type and water-table depth, to depict a three-dimensional illustration of hydrogeologically mediated recharge zones of the area. The hydrogeological evidence thus obtained about the spatial distribution of permeable zones, slope and boundary conditions, aptly substantiates the isotopic findings. The study seeks its impact by correlation of the isotopic findings with the regional groundwater flow regime which has been altered by the urban development.     

Machine learning techniques applied to prediction of residual strength of clay

Stability with first time or reactivated landslides depends upon the residual shear strength of soil. This paper describes prediction of the residual strength of soil based on index properties using two machine learning techniques. Different Artificial Neural Network (ANN) models and Support Vector Machine (SVM) techniques have been used. SVM aims at minimizing a bound on the generalization error of a model rather than at minimizing the error on the training data only. The ANN models along with their generalizations capabilities are presented here for comparisons. This study also highlights the capability of SVM model over ANN models for the prediction of the residual strength of soil. Based on different statistical parameters, the SVM model is found to be better than the developed ANN models. A model equation has been developed for prediction of the residual strength based on the SVM for practicing geotechnical engineers. Sensitivity analyses have been also performed to investigate the effects of different index properties on the residual strength of soil.