Comparison of TOPEX/POSEIDON Altimeter Derived Wind Speed and Wave Parameters with Ocean Buoy Data in the North Indian Ocean

Results of comparison exercises carried out between the state-of-the-art TOPEX/POSEIDON altimeter-derived ocean surface wind speed and ocean wave parameters (significant wave height and wave period) and those measured by a set of ocean data buoys in the North Indian Ocean are presented in this article. Altimeter-derived significant wave height values exhibited rms deviation as small as - 0.3 m, and surface wind speed of - 1.6 m/s. These results are found consistent with those found for the Pacific Ocean. For estimation of ocean wave period, the spectral moments-based semiempirical approach, earlier applied on GEOSAT data, was extended to TOPEX/POSEIDON. For this purpose, distributions of first four years of TOPEX/POSEIDON altimeter data and climatology over the North Indian Ocean were analyzed and a new set of coefficients generated for estimation of wave period. It is shown that wave periods thus estimated from TOPEX/POSEIDON data (for the subsequent two years), when compared with independent data set of ocean data buoys deployed in the North Indian Ocean, exhibit improved accuracy (rms ~ - 1.4 nos) over those determined earlier with GEOSAT data.     

Tilted Bianchi Type I Models with Heat Conduction Filled with Disordered Radiations of Perfect Fluid in General Relativity

In this paper, we have investigated some tilted Bianchi Type I models with heat conduction filled with disordered radiation of perfect fluid. To get a determinate solution, we have assumed a condition A =(BC) ⁿ between metric potentials. Alternatively we have discussed the case A=(BC) ^1/3 for which tilted nature of the model is preserved. The various and geometrical features with singularities in the models are also discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Inhomogeneous viscous fluid cosmological model with electromagnetic field in general relativity

The object of this paper is to investigate the behaviour of electromagnetic field in inhomogeneous cosmological models obtained for viscous fluid distributions. The various particular cases when both the electromagnetic and viscosity are absent, are also discussed.     

Landslide susceptibility assessment of the region affected by the 25 April 2015 Gorkha earthquake of Nepal

Nepal was hit by a 7.8 magnitude earthquake on 25^th April, 2015. The main shock and many large aftershocks generated a large number of coseismic landslips in central Nepal. We have developed a landslide susceptibility map of the affected region based on the coseismic landslides collected from remotely sensed data and fieldwork, using bivariate statistical model with different landslide causative factors. From the investigation, it is observed that most of the coseismic landslides are independent of previous landslides. Out of 3,716 mapped landslides, we used 80% of them to develop a susceptibility map and the remaining 20% were taken for validating the model. A total of 11 different landslide-influencing parameters were considered. These include slope gradient, slope aspect, plan curvature, elevation, relative relief, Peak Ground Acceleration (PGA), distance from epicenters of the mainshock and major aftershocks, lithology, distance of the landslide from the fault, fold, and drainage line. The success rate of 87.66% and the prediction rate of 86.87% indicate that the model is in good agreement between the developed susceptibility map and the existing landslides data. PGA, lithology, slope angle and elevation have played a major role in triggering the coseismic mass movements. This susceptibility map can be used for relocating the people in the affected regions as well as for future land development.     

Bianchi Type I Anisotropic Magnetized Cosmological Model in General Relativity

Bianchi Type I magnetized Cosmological model for perfect fluid distribution is investigated. The magnetic field is due to an electric current produced along x-axis. The distribution consists of an electrically neutral perfect fluid with an infinite electrical conductivity. To get a determinate solution, a supplementary conditionA = BC between metric potentials is used. The behaviour of the model in presence and absence of magnetic field is also discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Digital soil mapping in a Himalayan watershed using remote sensing and terrain parameters employing artificial neural network model

Digital soil mapping relies on field observations, laboratory measurements and remote sensing data, integrated with quantitative methods to map spatial patterns of soil properties. The study was undertaken in a hilly watershed in the Indian Himalayan region of Mandi district, Himachal Pradesh for mapping soil nutrients by employing artificial neural network (ANN), a potent data mining technique. Soil samples collected from the surface layer (0–15 cm) of 75 locations in the watershed, through grid sampling approach during the fallow period of November 2015, were preprocessed and analysed for various soil nutrients like soil organic carbon (SOC), nitrogen (N) and phosphorus (P). Spectral indices like Colouration Index, Brightness Index, Hue Index and Redness Index derived from Landsat 8 satellite data and terrain parameters such as Terrain Wetness Index, Stream Power Index and slope using CartoDEM (30 m) were used. Spectral and terrain indices sensitive to different nutrients were identified using correlation analysis and thereafter used for predictive modelling of nutrients using ANN technique by employing feed-forward neural network with backpropagation network architecture and Levenberg–Marquardt training algorithm. The prediction of SOC was obtained with an R² of 0.83 and mean squared error (MSE) of 0.05, whereas for available nitrogen, it was achieved with an R² value of 0.62 and MSE of 0.0006. The prediction accuracy for phosphorus was low, since the phosphorus content in the area was far below the normal P values of typical Indian soils and thus the R² value observed was only 0.511. The attempts to develop prediction models for available potassium (K) and clay (%) failed to give satisfactory results. The developed models were validated using independent data sets and used for mapping the spatial distribution of SOC and N in the watershed.     

Lidar observation of aerosol stratification in the lower troposphere over Pune during pre-monsoon season of 2006

Lidar observations of aerosol vertical distributions in the lower troposphere along with observations of horizontal and vertical winds from collocated UHF radar (Wind Profiler) over a tropical Indian station, Pune during the pre-monsoon season (March–May) of 2006 as part of an ISRO-GBP national campaign (ICARB) have been examined. Lidar vertical profiles showed high aerosol concentrations in the surface layers and a subsequent gradual decrease with height. Results showed the presence of an elevated stratified aerosol layer around 2000–3500m height which persisted throughout the months of March and April. Observed strong vertical gradients in both horizontal and vertical winds in the lower troposphere seem to be a possible cause for the formation of elevated aerosol layers. Further, high daytime temperatures accompanied by dry conditions at the surface help to enhance the aerosol loading in the lower layers over this location.