Geostatistical Modelling and Vertical Effect Analysis of a Ferruginous East Coast Bauxite Deposit,India

Geology of Ore Deposits - Exploration and mining success of a bauxite deposit rely greatly on an adequate modelling of spatial characteristics of constituent geo-variables through an understanding...     

Fractal study of seismicity in order to characterize the various tectonic blocks of North-east Himalaya,India

North-eastern Himalaya is said to be one of the world most complex geological set-up with different kinds of seismotectonic systems. Region has experienced two of the world’s strongest earthquakes, such as Shillong earthquake of 1897 known as Assam earthquake and subsequent 1950 earthquake in Arunachal Pradesh, both of with magnitude of 8.7, and also several other strong earthquakes. Various techniques have been applied to understand the past strong earthquake mechanism as well as hazard estimation carried out for future earthquake. Fractal correlation dimension (D _c) is being used in this study with the seismicity for the period 1961 to recent for understanding the pattern of seismic hazard. The entire area has been divided into four major tectonic blocks, and each block event was divided into consecutive fifty events window for seeing spatiotemporal patterns. After comparing the patterns, we have identified that Block of Eastern Himalaya near Main Central Thrust, Main Boundary Thrust, north of Kopili lineament and Block of Shillong plateau near Dauki fault are having relatively intense clustering of events in recent times, which may be identified as the zones of most potential to have a strong event.     

Landslide susceptibility assessment using Information Value Method in parts of the Darjeeling Himalayas

Landslide susceptibility is the likelihood of a landslide occurrence in an area predicted on the basis of local terrain conditions. Since last few years, researchers have attempted to analyse the probability of landslide occurrences and introduced different methods of landslide susceptibility assessment. The objective of this paper is to assess the landslide susceptibility in parts of the Darjeeling Himalayas using a relatively simple bivariate statistical technique. Seven factor layers with 24 categories, responsible for landslide occurrences in this area, are prepared from Cartosat and Resourcesat — 1 LISS-IV MX data. Each category was given a weight using the Information Value Method. Weighted sum of these values were used to prepare a landslide susceptibility map. The result shows that 8% area was predicted for high, 32% for moderate and remaining 60% for low landslide susceptibility zones. The high value (0.89) of the area under the receiver operating characteristic curve showed the high accuracy of the prediction model.     

Rock slope stability assessment using finite element based modelling – examples from the Indian Himalayas

Numerical modelling of rock slides is a versatile approach to understand the failure mechanism and the dynamics of rock slopes. Finite element slope stability analysis of three rock slopes in Garhwal Himalaya, India has been carried out using a two dimensional plane strain approach. Two different modelling techniques have been attempted for this study. Firstly, the slope is represented as a continuum in which the effect of discontinuities is considered by reducing the properties and strength of intact rock to those of rock mass. The equivalent Mohr-Coulomb shear strength parameters of generalised Hoek-Brown (GHB) criterion and modified Mohr-Coulomb (MMC) criterion has been used for this continuum approach. Secondly, a combined continuum-interface numerical method has been attempted in which the discontinuities are represented as interface elements in between the rock walls. Two different joint shear strength models such as Barton-Bandis and Patton’s model are used for the interface elements. Shear strength reduction (SSR) analysis has been carried out using a finite element formulation provided in the PHASE². For blocky or very blocky rock mass structure combined continuum-interface model is found to be the most suitable one, as this model is capable of simulating the actual field scenario.     

Geochemical alterations in surface waters of Govind Ballabh Pant Sagar,Northern Coalfield,India

Major ions showed high concentrations, ionic strength and chemical activity in the surface waters of Govind Ballabh Pant Sagar reservoir. Various geochemical ratios showed the dominance of silicate over carbonate weathering and major ions such as Na⁺ + K⁺ account for about 52 % of the cation budget. The high Na⁺ and K⁺ showed sedimentation of rock/coal particles consisting of highly weathered silicate minerals contributed by the discharge of mine water, fly ash mixing during transportation, etc. Further, Ca²⁺ + Mg²⁺/Na⁺ + K⁺ ratio was <1 (0.92) indicating the occurrence of silicate weathering in the reservoir catchment. The comparative assessment showed that the proportion of Ca²⁺ + Mg²⁺/Na⁺ + K⁺ tends to be lower along the coal mining belts compared to non-coal mining regions in the world. The Ca²⁺/SO₄ ^2? ratio <1 revealed not only H₂CO₃ but H₂SO₄ also acting as a source of protons for rock weathering. The cause underlying these differences can be related directly to geological substrate and anthropogenic activities.     

Earthquake damage identification: a case study using soft classification approach

The October 8, 2005, Kashmir earthquake (M _w 7.6) affected the rough mountainous regions of India and Pakistan with poor accessibility, and thus, no proper comprehensive ground survey was possible. However, due to the ability of remote sensing technology to acquire spectral measurements of damaged areas at various spatial and temporal scales, extraction of damaged areas can be carried out quickly and with great reliability. The fuzzy-based classifiers [Possibilistic c-Means (PCM), noise cluster (NC), and NC with entropy (NCE)] were applied to identify 2005 Kashmir earthquake, induced landslides, as well as built-up damage (BD) areas, as soft computing approaches using supervised classification. Results indicate that for the identification of landslides and BD areas, NCE classifier generated the best outputs, while for the identification of built-up undamaged areas, NC classifier generated the best output. Further, it was found that the proposed Class Based Sensor Independent (CBSI) technique can improve spectral information of specific class for better identification.     

Bootstrap aggregating approach to short-term load forecasting using meteorological parameters for demand side management in the North-Eastern Region of India

Theoretical and Applied Climatology - Electricity is an essential commodity that must be generated in response to demand. Hydroelectric power plants, fossil fuels, nuclear energy, and wind energy...