Seasonal variation in the deformation rate in NW Himalayan region

We report GPS measurements of continuous observations from the multi-parametric geophysical observatory (MPGO) at Ghuttu, Garhwal Lesser Himalaya. Other than the evidence of secular motion depicting strain accumulation due to locking of the underneath seismically active detachment, measurements at Ghuttu show annual variation of ±4 mm on horizontal component. Such variations are more prominent in the north coordinate and do not directly correlate with the meteorological parameters such as variations in rainfall, water table, and atmospheric pressure measured at the MPGO observatory. These variations are also not the artefact of data processing and network. They correlate with the water load storage in the Ganga plains, with minimum in displacement coinciding with the maximum storage of water in Ganga plains immediately after the monsoon and vice versa. Such variations also appear to cause annual variation in the low-magnitude earthquake frequency in the Himalayan region, being relatively more in the winter period.     

Study of Extended Radio Galaxies at 151.6 MHz using the Mauritius Radio Telescope

The MRT survey will be by far one of the most extensive survey at low frequencies. This survey will provide a moderately deep radio catalog reaching a source density of about 2 × 10⁴ sr^-1over the southern sky with an angular resolution of 4' × 4' and a limiting flux density of 70 mJy (1 σ) at 151 MHz. The availability of zero spacing and short baselines in the MRT array will make it sensitive to the background temperature and to large scale features in the sky. In addition to this feature, the low frequency operation makes a study of continuum emission from large radio sources by MRT to have several interesting and important implications in the study of radio galaxies. This paper discusses the parameter space of radio galaxies which can be explored using the MRT. Images of a few extended radio galaxies are also presented. This revised version was published online in July 2006 with corrections to the Cover Date.     

Identification of coal seam strata from geophysical logs of borehole using Adaptive Neuro-Fuzzy Inference System

Different parameters obtained through well-logging geophysical sensors such as SP, resistivity, gamma–gamma, neutron, natural gamma and acoustic, help in identification of strata and estimation of the physical, electrical and acoustical properties of the subsurface lithology. Strong and conspicuous changes in some of the log parameters associated with any particular stratigraphy formation, are function of its composition, physical properties and help in classification. However some substrata show moderate values in respective log parameters and make difficult to identify or assess the type of strata, if we go by the standard variability ranges of any log parameters and visual inspection. The complexity increases further with more number of sensors involved.An attempt is made to identify the type of stratigraphy from borehole geophysical log data using a combined approach of neural networks and fuzzy logic, known as Adaptive Neuro-Fuzzy Inference System. A model is built based on a few data sets (geophysical logs) of known stratigraphy of in coal areas of Kothagudem, Godavari basin and further the network model is used as test model to infer the lithology of a borehole from their geophysical logs, not used in simulation. The results are very encouraging and the model is able to decipher even thin cola seams and other strata from borehole geophysical logs. The model can be further modified to assess the physical properties of the strata, if the corresponding ground truth is made available for simulation.     

Groundwater arsenic contamination and its health effects in India

During a 28-year field survey in India (1988–2016), groundwater arsenic contamination and its health effects were registered in the states of West Bengal, Jharkhand, Bihar and Uttar Pradesh in the Ganga River flood plain, and the states of Assam and Manipur in the flood plain of Brahamaputra and Imphal rivers. Groundwater of Rajnandgaon village in Chhattisgarh state, which is not in a flood plain, is also arsenic contaminated. More than 170,000 tubewell water samples from the affected states were analyzed and half of the samples had arsenic >10 μg/L (maximum concentration 3,700 μg/L). Chronic exposure to arsenic through drinking water causes various health problems, like dermal, neurological, reproductive and pregnancy effects, cardiovascular effects, diabetes mellitus, diseases of the respiratory and gastrointestinal systems, and cancers, typically involving the skin, lungs, liver, bladder, etc. About 4.5% of the 8,000 children from arsenic-affected villages of affected states were registered with mild to moderate arsenical skin lesions. In the preliminary survey, more than 10,000 patients were registered with different types of arsenic-related signs and symptoms, out of more than 100,000 people screened from affected states. Elevated levels of arsenic were also found in biological samples (urine, hair, nails) of the people living in affected states. The study reveals that the population who had severe arsenical skin lesions may suffer from multiple Bowens/cancers in the long term. Some unusual symptoms, such as burning sensation, skin itching and watering of eyes in the presence of sun light, were also noticed in arsenicosis patients.     

Land Use/Cover Change Detection of Tiruchirapalli City, India, Using Integrated Remote Sensing and GIS Tools

The rapid growth of urban population in India is a cause of concern among country??s urban and town planners for efficient urban planning. The drastic growth of urban areas has resulted in sharp land use and land cover changes. In recent years, the significance of spatial data technologies, especially the application of remotely sensed data and geographical information systems (GIS) has been widely used. The present study investigates the urban growth of Tiruchirapalli city, Tamilnadu using IRS satellite data for the years 1989, 1992, 1995, 1998, 2001, 2004, 2007, and 2010. The eight satellite images are enhanced using convolution spatial enhancement method with Kernel (7?×?7) edge enhance function. Supervised classification method is used to classify the urban land use and land cover. The GIS is used to prepare the different layers belonging to various land uses identified from remotely sensed data. The analysis of the results show the drastic increase of built up area and reduced green cover within the city boundary limit.     

An Ar–Ar laser-probe study of pseudotachylites in charnockite gneisses from the Cauvery Shear Zone system, South India

The age of pseudotachylite formation in the crustal-scale Cauvery Shear Zone system of the Precambrian Southern Granulite Terrain (South India) has been analyzed by laser-probe ⁴⁰Ar–³⁹Ar dating. Laser spot analyses from a pseudotachylite from the Salem–Attur shear zone have yielded ages ranging from 1214 to 904 Ma. Some evidence for the presence of excess Ar is indicated by the scatter of ages from this locality. The host gneiss preserves Palaeoproterozoic Rb–Sr whole rock–biotite ages (2350 ± 11 to 2241 ± 11 Ma). A mylonite in the Koorg shear, ca. 200 km to the north, yielded an age of 895 ± 17 Ma the consistency of the age distribution from spot analyses precludes the presence of significant excess Ar. Despite published evidence for the growth of high-grade minerals within some components of the Cauvery Shear Zone during the Pan-African event (700–550 Ma), the pseudotachylites in this study provide no evidence for Pan-African formation. Instead they document the first evidence for Mesoproterozoic tectonism in the Cauvery Shear Zone system, thus prompting a review of the correlation between the Cauvery Shear Zone system and the large-scale shear zones located elsewhere in eastern Gondwana.     

Large are variability in climate-based soil moisture estimates and implications for remote sensing

Although the basic physical relationships between various remotely sensed signatures and soil are sound, the representativeness of pixel-averaged wetness used to interpret the remotely sensed data is often suspect and at times even doubtful. To study the affect of local variation in soil moisture on the large-area average, mean areal precipitation, temperature and modelled soil moisture in 1/4° grid cells were analyzed for a 700 km by 400 km region in the US Southern Great Plains. Variability in five years of mean daily grid cell data was investigated for 150 km² study sites, approximately corresponding in size to a satellite microwave pixel. The number of wetted grid cells and the magnitude of precipitation in grid cells within a site were highly variable. The variability of each of these factors is critical, and will not only influence mean site wetness, but also how the area will be seen from space. Analysis indicated that similar mean site precipitation values may result from numerous widely differing combinations of precipitation magnitude and watted gric cell population. Consequently, mean site moisture is also highly variable in the distribution and magnitude of the individual cell moisture values. Extreme values in several grid cells may severely bias the quadrant mean, while influencing a remote measurement much less. Although large-scale surface wetness may eventually be reliably inferred from satellite measurements, a degree of uncertainty will always exist, especially in semi-arid areas. One may be required to associate mean soil moisture with an expected distribution of wetness within a pixel.     

Groundwater arsenic contamination in Manipur,one of the seven North-Eastern Hill states of India: a future danger

Manipur State, with a population of 2.29 million, is one of the seven North-Eastern Hill states in India, and is severely affected by groundwater arsenic contamination. Manipur has nine districts out of which four are in Manipur Valley where 59% of the people live on 10% of the land. These four districts are all arsenic contaminated. We analysed water samples from 628 tubewells for arsenic out of an expected total 2,014 tubewells in the Manipur Valley. Analyzed samples, 63.3%, contained >10 μg/l of arsenic, 23.2% between 10 and 50 μg/l, and 40% >50 μg/l. The percentages of contaminated wells above 10 and 50 μg/l are higher than in other arsenic affected states and countries of the Ganga–Meghna–Brahmaputra (GMB) Plain. Unlike on the GMB plains, in Manipur there is no systematic relation between arsenic concentration and the depth of tubewells. The source of arsenic in GMB Plain is sediments derived from the Himalaya and surrounding mountains. North-Eastern Hill states were formed at late phase of Himalaya orogeny, and so it will be found in the future that groundwater arsenic contamination in the valleys of other North-Eastern Hill states. Arsenic contaminated aquifers in Manipur Valley are mainly located within the Newer Alluvium. In Manipur, the high rainfall and abundant surface water resources can be exploited to avoid repeating the mass arsenic poisoning that has occurred on the GMB plains.