Liquefaction Identification Using IRS-1D Temporal Indices Data

One of the major after effect of Bhuj Earthquake which occurred on January 26, 2001 was wide spread appearance of liquefaction of soil in the Rann of Kachchh and the coastal areas of Kandla port covering an area of more than tens of thousands of kilometers. Remote sensing data products allow us to explore the land surface parameters at different spatial scales. In this work, an attempt has been made to identify the liquefied soil area using conventional indices from IRS-1D temporal images. The same has been investigated and compared with Class Based Sensor Independent (CBSI) spectral indices, while applying fuzzy based noise classification as soft computing approach using supervised classification. Seven spectral indices have been investigated to identify liquefied soil areas using temporal multi-spectral images. The result shows that the temporal variations can be accounted by using appropriate remote sensing based spectral indices. It is found that CBSI based TNDVI using temporal data yields the best results for identification of liquefied soil areas, while CBSI based SR gives best results for water body identification.     

Exploring the diverse potentials of <Emphasis Type="Italic">Planococcus</Emphasis> sp. TRC1 for the deconstruction of recalcitrant kraft lignin

Kraft lignin (KL) is the chief contaminant which is responsible for dark coloration, toxicity and high chemical oxygen demand (COD) of paper pulp mill effluent. The present study investigated the diverse potentials of Planococcus sp. TRC1 in the biodegradation of KL. Preliminary evaluation indicated that the strain was able to grow on broad spectrum of lignin-derived compounds, decolorize lignin-mimicking dyes and catabolize substrates of ligninolytic enzymes. Response surface methodology (RSM) was executed to perform the optimization of different process parameters. The results displayed that Planococcus sp. TRC1 could completely utilize 100 mg L^?1 of KL and 78% of 200 mg L^?1 of KL as sole source of carbon with concurrent reduction in COD and color. The biokinetic details of KL biodegradation showed that the values of \(\mu^{*}\), µ _max, \(q^{*}\) and q _max were 0.018 h^?1, 0.01 h^?1, 0.023 g g^?1 h^?1 and 0.05 g g^?1 h^?1, respectively. UV–visible spectrophotometry, SEM and FTIR indicated the significant alterations in the surface morphology, functional groups and chromophores during the course of biodegradation. XRD revealed the emergence of peak signifying the formation of low molecular weight intermediates after bacterial treatment. Considering the environmental impact, bacterial-treated KL illustrated less phytotoxicity using Vigna radiata seed bioassay. These results suggested that Planococcus sp. TRC1 could be a promising strain for the degradation of KL in an ecofriendly way.     

Knowledge-Driven and Data-Driven Fuzzy Models for Predictive Mineral Potential Mapping

In this paper, we describe new fuzzy models for predictive mineral potential mapping: (1) a knowledge-driven fuzzy model that uses a logistic membership function for deriving fuzzy membership values of input evidential maps and (2) a data-driven model, which uses a piecewise linear function based on quantified spatial associations between a set of evidential evidence features and a set of known mineral deposits for deriving fuzzy membership values of input evidential maps. We also describe a graphical defuzzification procedure for the interpretation of output fuzzy favorability maps. The models are demonstrated for mapping base metal deposit potential in an area in the south-central part of the Aravalli metallogenic province in the state of Rajasthan, western India. The data-driven and knowledge-driven models described in this paper predict potentially mineralized zones, which occupy less than 10% of the study area and contain at least 83% of the model and validation base metal deposits. A cross-validation of the favorability map derived from using one of the models with the favorability map derived from using the other model indicates a remarkable similarity in their results. Both models therefore are useful for predicting favorable zones to guide further exploration work.     

Spherical variable-energy blast wave in self-gravitating gas

Modified similarity method has been used to study the propagation of spherical-variable energy blast waves through a self-gravitating gas. For an energy inputE =E ₀t^4/3, whereE is the energy released up to timet andE ₀ is a functional constant, the similarity solutions correct up to third approximation have been obtained. It is found that the effects of self-gravitational forces are of third order. An increase in the parameterA ² (characterising the gravitational field) increases the shock velocity.     

Hydrogeochemistry of the Koyna River basin,India

Hydrogeochemistry of the Koyna River basin, famous for the Koyna earthquake (magnitude 7) of 1967, has been studied. Basalt is the primary aquifer; laterites, alluvium, and talus deposits form aquifers of secondary importance. Groundwater generally occurs under water table conditions in shallow aquifers. Deeper aquifers are associated only with basalts. One hundred and 87 water samples were collected from various sources, such as dugwells, borewells, springs, and surface water, including 40 samples for analysis of iron. Only major constituents were analyzed. Analyses show that the concentrations of Ca²⁺ exceed that of Mg²⁺ in almost all water samples; the concentrations of Na⁺ are generally next to Ca²⁺ and are always higher than that of K⁺; and CO₃ ^2– and SO₄ ^2– are very low and are often negligible. Groundwater in borewells tapping deeper aquifers has higher mineralization compared to that in dugwells representing shallow aquifers. Majority of the water samples are dominated by alkaline earths (Ca²⁺, Mg²⁺) and weak acids (HCO₃ ⁻, CO₃ ^2–). Groundwater from shallow aquifers is generally calcium-bicarbonate type (53%) and calcium-magnesium-bicarbonate type (27%). In case of deeper aquifer, it is mostly calcium-magnesium-bicarbonate type (29%), sodium-bicarbonate type (24%), calcium-bicarbonate type (19%), calcium-magnesium-sodium-bicarbonate type (19%) and sodium-calcium-bicarbonate type (9%). Groundwater water is generally fit for drinking and irrigation purposes, except in the lower reaches of the Koyna River basin, which is affected by near water logging conditions.     

Enabling affordable omnidirectional subsurface extended image volumes via probing

Image gathers as a function of subsurface offset are an important tool for the inference of rock properties and velocity analysis in areas of complex geology. Traditionally, these gathers are thought of as multidimensional correlations of the source and receiver wavefields. The bottleneck in computing these gathers lies in the fact that one needs to store, compute, and correlate these wavefields for all shots in order to obtain the desired image gathers. Therefore, the image gathers are typically only computed for a limited number of subsurface points and for a limited range of subsurface offsets, which may cause problems in complex geological areas with large geologic dips. We overcome increasing computational and storage costs of extended image volumes by introducing a formulation that avoids explicit storage and removes the customary and expensive loop over shots found in conventional extended imaging. As a result, we end up with a matrix–vector formulation from which different image gathers can be formed and with which amplitude‐versus‐angle and wave‐equation migration velocity analysis can be performed without requiring prior information on the geologic dips. Aside from demonstrating the formation of two‐way extended image gathers for different purposes and at greatly reduced costs, we also present a new approach to conduct automatic wave‐equation‐based migration‐velocity analysis. Instead of focusing in particular offset directions and preselected subsets of subsurface points, our method focuses every subsurface point for all subsurface offset directions using a randomized probing technique. As a consequence, we obtain good velocity models at low cost for complex models without the need to provide information on the geologic dips.