Measurements of radon flux and soil-gas radon concentration along the Main Central Thrust, Garhwal Himalaya, using SRM and RAD7 detectors

Radon in the Earth’s crust or soil matrix is free to move only if its atoms find their way into pores or capillaries of the matrix. ²²²Rn atoms from solid mineral grains get into air, filling pores through emanation process. Then ²²²Rn enters into the atmosphere from air-filled pores by exhalation process. The estimation of radon flux from soil surface is an important parameter for determining the source term for radon concentration modeling. In the present investigation, radon fluxes and soil-gas radon concentration have been measured along and around the Main Central Thrust (MCT) in Uttarkashi district of Garhwal Himalaya, India, by using Scintillation Radon Monitor (SRM) and RAD7 devices, respectively. The soil radon gas concentration measured by RAD7 with soil probe at the constant depth was found to vary from 12 ± 3 to 2330 ± 48 Bq·m^?3 with geometrical mean value of 302 ± 84 Bq·m^?3. Th significance of this work is its usefulness from radiation protection point of view.     

Temporal and spatial variations in the magnitude of completeness for homogenized moment magnitude catalogue for northeast India

Northeast India region is one of the most seismically active areas in the world. Events data for the period 1897–2010, used in this study has been largely compiled from global ISC, NEIC and GCMT databases. Historical seismicity catalogue of Gupta et al (1986) and some events data from the bulletins of India Meteorological Department are also used. Orthogonal regression relations for conversion of body and surface wave magnitudes to M _w,HRVD based on events data for the period 1978–2006 have been derived. An Orthogonal Standard Regression (OSR) relationship has also been obtained for scaling of intensity estimates to M _w,NEIC using 126 global intensity events with intensity VI or greater during the period 1975–2010.     

Altimeter data assimilation in the tropical Indian Ocean using water property conserving scheme

Altimeter data have been assimilated in an ocean general circulation model using the water property conserving scheme. Two runs of the model have been conducted for the year 2004. In one of the runs, altimeter data have been assimilated sequentially, while in another run, assimilation has been suppressed. Assimilation has been restricted to the tropical Indian Ocean. An assessment of the strength of the scheme has been carried out by comparing the sea surface temperature (SST), simulated in the two runs, with in situ derived as well as remotely sensed observations of the same quantity. It has been found that the assimilation exhibits a significant positive impact on the simulation of SST. The subsurface effect of the assimilation could be judged by comparing the model simulated depth of the 20°C isotherm (hereafter referred to as D20), as a proxy of the thermocline depth, with the same quantity estimated from ARGO observations. In this case also, the impact is noteworthy. Effect on the dynamics has been judged by comparison of simulated surface current with observed current at a moored buoy location, and finally the impact on model sea level forecast in a free run after assimilation has been quantified in a representative example.     

Some Viscous Fluid Cosmological Models in General Relativity

The motivation of this paper is to investigate two viscous fluid cosmological models in General Relativity in which the expansion is only in two directions i.e. one of the Hubble parameters is zero. In the first model, coefficient of shear viscosity is assumed to be constant while in the second model, the coefficient of shear viscosity is proportional to the rate of expansion in the model. Here no additional condition is assumed except for coefficient of shear viscosity. These models are new and different from those models obtained by Bali and Jain (1987, 1988) in which free gravitational field was assumed to be Petrov Type D and non-degenerate for Marder (1958) metric and coefficient of shear viscosity is proportional to the rate of expansion in the model. The various physical and geometrical aspects of the models are also discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

LEOPOLD A. HEINDL,US GEOLOGICAL SURVEY

Abstract

The distributed parameter model ANSWERS was used to predict runoff and soil loss from three agricultural watersheds in the arid zone of India. Model input parameters such as landform, drainage, soil and land use/land cover were derived from Landsat Thematic Mapper false colour composites and limited ground truth. The model predicted hydrographs and sediment graphs within acceptable limits. ANSWERS underpredicted the total soil loss by factors of 2.6 to 3.6. Reasons for these results are discussed.     

Re-Analysis of QPO in 3C 273 Light Curve

We have developed analysis tools to search for quasi periodic oscillations in light curves from active galactic nuclei, using the following time series techniques: Wavelets, periodogram, Lomb–Scargle periodogram, structure function and multi-harmonic analysis of variance. The analysis tools incorporate different noise models with significant levels for all the techniques that is an improvement over the previous work. By looking for consistently high significance, we make the detection of periodicities more robust. We apply this tool to a previously reported QPO (Espaillat et al. 2008) in the X-ray light curve of 3C 273 with a periodicity of ~3300 s and find that the significance is only 74% in the wavelet and fails to show up above 95% significance in the periodogram and multi-harmonic analysis of variance.     

Emissions from grassland burning in Kaziranga National Park,India – analysis from IRS-P6 AWiFS satellite remote sensing datasets

Biomass burning from vegetation fires is an important source of greenhouse gas emissions. In this study, we quantify biomass burning emissions from grasslands from the highly sensitive Kaziranga National Park, Assam, Northeast India. Most of the fires in the park are ‘controlled burning fires’ set by the park officials for management purposes. We evaluated the short-term impacts of fires and the resulting air pollution through integrating biomass burnt information from satellite remote sensing datasets. IRS-P6 Advanced Wide Field Sensor (AWiFS) data during March and April corresponding to dry season were evaluated to delineate the burnt areas. These burnt area estimates were then integrated with biomass data and emission factors for quantifying the greenhouse gas emissions. Results suggested that of the total study area of 37,822 ha, nearly 3163.282 ha has been burnt during March, 2005. Within one month, the burnt area increased to 7443.92 ha by April, i.e., from 8.36% to 19.68%. In total, biomass burning from the grasslands contributed to 29.65 Tg CO₂, 1.19 Tg CO, 0.071 Tg NOx, 0.042 Tg CH₄, 0.0625 Tg total non-methane hydrocarbons, 0.152 Tg of particulate matter, and 0.062 Tg of organic carbon and 0.008 Tg of black carbon during April. The importance of ‘fire’ as a management tool for maintaining the wildlife habitat has been highlighted in addition to some of the adverse affects of air pollution resulting from such management practices. The results from this study will be useful to forest officials as well as policy makers to undertake some sustainable forest management practices to maintain an ideal habitat for Kaziranga's wildlife.     

Using remote sensing technologies to enhance resource conservation and agricultural productivity in underutilized lands of South Asia

Satisfying the food demands of an ever-increasing population, preserving the natural resource base, and improving livelihoods are major challenges for South Asia. A large area of land in the Middle and Lower Gangetic Plains of South Asia remains either uncultivated or underused following the rice harvest in the kharif (wet) season. The area includes “rice-fallow,” estimated at 6.7 million ha, flood-prone riversides (“diara lands,” 2.4 million ha), waterlogged areas (4.9 million ha), and salt-affected soils (2.3 million ha). Bringing these lands under production could substantially improve the food supply and enhance livelihoods in the region. This paper describes a methodological case study that targeted resource-conserving technologies in underused lands of the Ballia District of eastern Uttar Pradesh (India) using multispectral remote-sensing images. Classification of temporal satellite data IRS-P6 in combination with Spot VGT 2 permitted the identification of all major categories of underused land during the post-rainy rabi/winter season, with an average accuracy of 89%. Based on three-year averages of field demonstrations, farmers gained an additional income of $63 ha⁻¹ by introducing raised beds in salt-affected soils; $140 and $800 ha⁻¹ by introducing deepwater rice varieties (monsoon) and boro rice (winter) in waterlogged areas; and $581 ha⁻¹ by introducing zero-till lentil (winter) in rain-fed fallow lowland. Timely wheat planting through zero-tillage implies an additional income of $147 ha⁻¹ and could increase wheat production by 35,000-65,000 tons in the district. The methodologies and technologies suggested in the study are applicable to more than 15 million ha of underutilized lands of the Indo-Gangetic Plains of South Asia. If the technologies are precisely applied, they can result in more than 3000 million US $ of additional income every year to these poverty prone areas.