Analysis of seepage from a pond

A semi-analytical solution has been derived for predicting the time of emptying a pond due to seepage. The time for the seeping water to reach the water table since the pond was initially filled has been calculated applying the Green-Ampt infiltration theory. The recharge rate after the wetting front joins the water table has been computed using a non-linear relationship between seepage head and recharge rate proposed by earlier investigators. The maximum rise in the water table beneath the center of the pond consequent to the time-varying recharge is calculated applying kernel coefficients obtained from solution of the linearized Boussinesq equation. It was observed that a pond with 50-m initial diameter at the water surface and 3-m maximum depth of water is dry after 168 days, where the subsoil is sandy clay. If the subsoil happens to be clay, the depth of water in the pond at the end of 9 months, i.e., after completion of the non-monsoon period, is 0.62 m. The maximum mound heights beneath the pond for constant recharge rate and uniform recharging area calculated from the present solution compare well with existing numerical as well as analytical solutions.     

Analysis of Swelling and Shrinkage Behavior of Compacted Clays

The impact of the variation in compaction condition on the swelling and shrinkage behavior of three soils has been examined. Two natural soils, namely red soil and black cotton soil, and one artificially mixed soil sample of commercial bentonite with well-graded sand, were studied. Compaction curve for Standard Proctor conditions were plotted and four compaction conditions were selected. Experimental results showed that clay mineralogy dominates over compaction conditions in influencing the swelling and shrinkage behavior of the tested soils. Monitoring of void ratio (e)−water content (w) relations during shrinkage showed that soil specimens generally shrunk in three distinct linear stages. A small reduction in void ratio occurred on reduction in water content during the first shrinkage stage and was termed as initial shrinkage. In second stage, void ratio decreased rapidly with reduction in water content and was termed as primary shrinkage. In third and final stage, reduction in water content is accompanied by a marginal change in void ratio and it’s called residual shrinkage. Irrespective of initial compaction conditions studied, the transition from primary to residual shrinkage for all the specimens occurred within a narrow range of water content (10–15%).     

Model selection in Bayesian framework to identify the best WorldView-2 based vegetation index in predicting green biomass of salt marshes in the northern Gulf of Mexico

Coastal wetlands are among the most productive ecosystems globally but have experienced dramatic degradation and loss within the past several decades. Vegetation biomass of coastal wetlands is not only the key component of blue carbon storage but also plays an important role in vertical accretion, important for maintaining these habitats under relative sea-level rise. Remote sensing offers a cost-effective approach to study vegetation biomass at a broad spatial scale. We developed statistical models to predict peak aboveground green biomass of Spartina alterniflora and Juncus roemerianus, two dominant species of salt marshes using WorldView-2 satellite imagery at the Grand Bay National Estuarine Research Reserve (NERR) on the Mississippi coast in the northern Gulf of Mexico. The model accounted for nested data structures in the sampled biomass, assimilated uncertainties from data, parameters and model structures, and helped determine the best vegetation index among a variety of commonly-used indices to predict aboveground green biomass. We developed a series of mixed-effects models, which included different combinations of fixed effect(s), random intercept, and random slope(s). The fixed effects were species and one of the 60 vegetation indices derived from a WorldView-2 image obtained on 6 October 2012. The random effect used was site. We implemented the models in a Bayesian framework and selected the best model structure and vegetation index based on minimum posterior predictive loss and deviance information criterion. The results showed that the best vegetation index to predict peak green biomass was the green chlorophyll index derived from the reflectance values of band 8 (near-infrared) and band 3 (green), and its effect on biomass prediction varied among sites. The inclusion of species as a fixed effect improved the model prediction. The study demonstrated the need to account for spatial dependence of data in developing a robust model, and the importance of the second WorldView-2 near-infrared band (860–1040 nm) in predicting aboveground green biomass for the Grand Bay NERR. The analysis using mixed-effects modeling in Bayesian inference which coherently combined field and WorldView-2 data with uncertainties accounted for provides a robust and nondestructive tool for resource managers to monitor the status of coastal wetlands at a high spatial resolution in a timely manner. Through this study, we hope to emphasize the importance of appropriately accounting for nested data structures using mixed-effects models and promote wider application of Bayesian inference to facilitate assimilation of uncertainties in remote sensing applications.     

Wavelet based identification of dominant scales for self-affine road roughness in context of riding comfort in vehicles

We present a simulation based study of multiscale roughness of road surfaces and its effect on riding comfort in vehicles, given the fact that characterization of the measured roughness is important to ensure smooth ride. Self-affine fractals are used to simulate typically measured roughness data. Multiscale characteristics of such surfaces are obtained through varied level of spatial resolutions. The hierarchical nature of the multiscale fractal roughness and their role in affecting the riding comfort is investigated herein. Wavelet transform technique is exploited for multiscale decomposition. Roughness is synthesized from cumulation of scales in a multiscale fashion. Single degree of freedom car model is used for characterizing riding comfort parameters in terms of dynamic response of vehicle suspension system subjected to jerks exerted by rough profiles. The dominant scales of roughness governing the comfort parameters are identified through parametric study. It is shown that not all the scales are equally important in deciding the comfort parameters; rather, these parameters remain nearly intact with the inclusion of only a few initial scales. This facilitates multiscale visualization of roughness data and allows representing the profiles in a precise form by excluding the spurious higher scales. Apparently, it gives an economic estimate of the required resolution in the physical measurement for specific purpose.     

Identification of groundwater prospective zones by using remote sensing and geoelectrical methods in and around saidnagar area,dakor block,jalaun district,uttar pradesh

The study area around Saidnagar falls in Bundelkhand granitic terrain forming buried pediplain (granite derived material). The occurrence and movement of groundwater is restricted to the unconsolidated material, weathered and fractured rock. For the selection of tube-well sites, geoelectrical resistivity investigations have been carried out at the sites which are found suitable based on remote sensing and hydrogeological studies. Twenty six Vertical Electrical Soundings (VES) have been carried out by using Schlumberger electrode configuration, which have brought out 3 and 4 layered sub-surface sections. The resistivity of water-bearing weathered/fractured rocks varies from 10 to 20 ohm m, with thickness ranging from 3.4 to 75.0 m. The depth to the basement is found ranging between 6.8 and 93.0 m The integrated studies have revealed that the northern part of the study area forms groundwater prospective zone, consisting of unconsolidated water-bearing weathered material, In the southern part of the study area, weathered layer is either thin or absent and the groundwater movement and storage is restricted to the weathered/fractured zone only. This zone extends down to a depth of 3.4 to 75.0 m and may yield sufficient amount of water since it gets recharged by direct infiltration due to precipitation and percolation through Nalas.     

Orbits of a Charged Particle in a Skew Uniform Magnetic Field on Kerr Back Ground Geometry

In this paper we discuss the particle trajectories in a uniform magnetic field superimposed on Kerr geometry. The rotation axis of the Kerr black hole makes an angle with the asymptotic magnetic field. We find that the particle is trapped for suitable initial conditions.     

Microflares as possible sources for coronal heating

We present a preliminary study of 27 microflares observed by Solar X-ray Spectrometer (SOXS) mission during July 2003 to August 2006. We found that all 27 microflares show the Fe-line feature peaking around 6.7 keV, which is an indicator of the presence of coronal plasma temperature ≥ 9 MK. On the other hand, the spectra of microflares show hybrid model of thermal and non-thermal emission, which further supports them as possible sources of coronal heating. Our results based on the analysis show that the energy relapsed by the microflares is good enough for heating of the active corona. We discuss our results in the light of the hybrid model of microflares production.     

A composite stellar model of geostrophic flows I

This paper has been presented the geometric study and solutions of the electromagnetogeostrophic flows, and spatially the geometry of magnetic and current lines are discussed.