3D Subsurface Characterization of Banded Iron Formation Mineralization using Large-Scale Gravity Data: A Case Study in Parts of Bharatpur,Dausa and Karauli Districts of Rajasthan,India

Our study interprets large-scale gravity data to delineate concealed banded iron formation (BIF) iron mineralization in India's Rajasthan province. The study area belongs to the Bharatpur, Dausa, and Karauli districts of Rajasthan. We measured 1462 gravity readings to understand the rock types, depth and geometry of the different rock formations in the proposed study area. We also collected representative lithologies from more than 100 locations in the study area and calculated their density values. The measured gravity datasets are investigated via qualitative (e.g., Bouguer anomaly, first derivative and second derivative) and quantitative (radially averaged power spectrum, 3D Euler deconvolution, and 3D inversion) approach. The qualitative methods suggest a general NE–SW orientation of the BIFs, controlled by the general trend of the study area's structural setting. The lithological contact between the Bhilwara and Vindhyan Supergroups is demarcated by a NE–SW trending steep gravity gradient zone. In this area, representative lithologies yield high densities (about 3.746 gm/cc), and the samples identified as BIF represent exploration targets for iron ore. We have also developed our own in-house 3D gravity inversion code in this study. A model space inversion algorithm is converted into a data space using the identity relationship. It makes inversion algorithm very user-friendly on conventional desktop computers. The outcomes from the 3D inversion suggest that the concealed iron ore thickens to the west. This interpretation is also in good correlation with Euler 3D deconvolution of the gravity data.

     

Correlation of studies of surface-level carbon monoxide concentrations and sodar-observed thermal structures

Measured concentration levels of carbon monoxide present in the atmosphere near the ground surface have been studied in relation to atmospheric stability inferred from acoustic sounder vis-à-vis the density of motor-vehicular traffic responsible for the emission of carbon monoxide gas. It has been seen that concentration levels of carbon monoxide during peak traffic hours depend on the prevailing stability of the atmosphere. The need for continuous monitoring of atmospheric stability at a place using acoustic sounder to assess air quality has been emphasized.     

Temperature dependence of CO2 solubility in high pressure quenched glasses of diopside composition

The temperature dependence of carbon dioxide solubility in glasses of diopside composition, quenched from 20 kbar, has been investigated using a combination of high-temperature mass spectrometry and Raman spectroscopy.CO₂-charged diopside glasses were synthesized in a piston-cylinder apparatus. Because of diffusion of hydrogen through the platinum capsules, significant amounts of H₂O, CH₄ and CO were detected along with CO: in the diopside glasses. All three carbon species show a bimodal release pattern in the mass pyrograms. The CO₂ solubility shows a linear and negative temperature dependence. We do not observe any maxima in the solubility curve as was reported previously (Mysen and virgo, 1980a).None of the additional bands observed in Raman spectra of CO₂-charged diopside glasses compared to those in the spectrum of diopside glass can be assigned to molecular CO₂. These bands are caused by CO^?2₃ ions and indicate that the physical solubility of molecular carbon dioxide is negligible. The bimodal release pattern observed for CO₂ in the mass pyrograms, is consistent with the Raman data which strongly suggests that CO^?2₃ ions are present in at least two distinct sites in the glass.     

Streamflow forecasting in remote areas

Forecasts of runoff volumes are required in order to maximize the utility of water-supply sources. In remote areas where hydrologic and land-use data are sparse, forecast models are needed; such models should be conceptually rational so they can be transferred to remote watersheds where data are sparse. A series of models were calibrated for a large watershed in India. A spatially-distributed seasonally-varying model having a structure similar to the rational method was found to provide precise, unbiased estimates of 10-day streamflow volumes. The model was tested on a watershed that was not used for calibration, with the results indicating a high correlation between the observed and measured streamflow. Thus, the model should provide good estimates of streamflow volumes on other ungaged watersheds.     

Analyses and settlement study of a group of two,three and four partially stiffened floating granular piles

ABSTRACT

Use of granular pile as a ground improvement technique in case of soft soils is one of the reliable and economic options. Analysis of a partially stiffened group of granular floating piles has been numerically assessed and presented here. Partial stiffening simply means that instead of using conventional material for making the granular pile (GP) in its full length, top region is replaced partially by some suitable material, having better mechanical properties, i.e. higher deformation modulus. Various normalised parameters like settlement influence factor for top of GP, settlement interaction factor, settlement reduction factor, percentage load shared by the base and shear stress distribution along the length of the granular pile are evaluated. The settlement influence factor for top of GP is found to decrease with the increase in the values of the stiffening parameters. The interfacial shear stresses get redistributed along the length of the granular pile.     

Forecasting quantitative rainfall over India using multi-model ensemble technique

A new approach to ensemble forecasting of rainfall over India based on daily outputs of four operational numerical weather prediction (NWP) models in the medium-range timescale (up to 5 days) is proposed in this study. Four global models, namely ECMWF, JMA, GFS and UKMO available on real-time basis at India Meteorological Department, New Delhi, are used simultaneously with adequate weights to obtain a multi-model ensemble (MME) technique. In this technique, weights for each NWP model at each grid point are assigned on the basis of unbiased mean absolute error between the bias-corrected forecast and observed rainfall time series of 366 daily data of 3 consecutive southwest monsoon periods (JJAS) of 2008, 2009 and 2010. Apart from MME, a simple ensemble mean (ENSM) forecast is also generated and experimented. The prediction skill of MME is examined against observed and corresponding outputs of each constituent model during monsoon 2011. The inter-comparison reveals that MME is able to provide more realistic forecast of rainfall over Indian monsoon region by taking the strength of each constituent model. It has been further found that the weighted MME technique has higher skill in predicting daily rainfall compared to ENSM and individual member models. RMSE is found to be lowest in MME forecasts both in magnitude and area coverage. This indicates that fluctuations of day-to-day errors are relatively less in the MME forecast. The inter-comparison of domain-averaged skill scores for different rainfall thresholds further clearly demonstrates that the MME algorithm improves slightly above the ENSM and member models.     

Improving Ocean State by Assimilating SARAL/AltiKa Derived Sea Level and Other Satellite-Derived Data in MITGCM

Assimilation of satellite-derived surface datasets has been explored in the study. Three types of surface data, namely sea level anomaly, sea surface temperature and sea surface salinity, have been used in various data assimilation experiments. The emphasis has been on the extra benefit arising out of the additional sea level assimilation and hence there are two parallel runs, in one of which sea level assimilation has been withheld. The model used is a state-of-the art ocean general circulation model (OGCM) and the assimilation method is the widely used singular evolutive extended Kalman filter (SEEK). Evaluation of the assimilation skill has been carried out by comparing the simulated depth of the 20°C isotherm with the same quantity measured by buoys and Argo floats. Simulated subsurface temperature and salinity profiles have also been compared with the same profiles measured by Argo floats. Finally, surface currents in the assimilation runs have been compared with currents measured by several off-equatorial buoys. Addition of sea level has been found to substantially improve the quality of simulation. An important feature that has been effectively simulated by the addition of sea level in the assimilation scheme is the near-surface temperature inversion (2-3°C) in the northern Bay of Bengal.     

Role of 3d-dispersive Alfven waves in coronal heating

Coronal heating is one of the unresolved puzzles in solar physics from decades. In the present paper we have investigated the dynamics of vortices to apprehend coronal heating problem. A three dimensional (3d) model has been developed to study propagation of dispersive Alfvén waves (DAWs) in presence of ion acoustic waves which results in excitation of DAW and evolution of vortices. Taking ponderomotive nonlinearity into account, development of these vortices has been studied. There are observations of such vortices in the chromosphere, transition region and also in the lower solar corona. These structures may play an important role in transferring energy from lower solar atmosphere to corona and result in coronal heating. Nonlinear interaction of these waves is studied in view of recent simulation work and observations of giant magnetic tornadoes in solar corona and lower atmosphere of sun by solar dynamical observatory (SDO).