Electrical resistivity imaging over natural (in situ) geological samples using physical model studies

To understand the characteristic responses of natural geological samples, viz., black granite, green marble, and graphite sheet, and to have “an a priori” knowledge of their physical property through electrical resistivity imaging, the physical model laboratory setup has been established to conduct scale model studies over targets of finite dimensions and resistivities. The present experiment involves IRIS make SYSCAL Pro-96 measuring system using 48 electrodes with 2-cm interelectrode separation in the laboratory model tank. In the present communication, we have presented the 2D cross section images using Wenner, Wenner–Schlumberger, and dipole–dipole array configurations over the resistive (granite, marble) and conductive (graphite) sheets. In the case of resistive target (black granite sheet, green marble), the combined usage of dipole–dipole and Wenner–Schlumberger arrays provided more accurate measures on target parameters, i.e., the combined usage of both the arrays is preferable in searching high-resistive targets beneath the low-resistive ones over burden. The shape of the resistive target (green marble sheet) is inappropriate when the thickness of the target is greater than one half of the minimum array separation. As the thickness of the target increases, the signatures of the target become feeble, and hence, the shape of the resistive target is not properly reflected in the corresponding tomogram. The response over graphite sheet indicates that the true parameters of the target are not reflected in the cross section, and the existence of the low-resistive (high-conductive) target in the host medium (water) deviates the resistivity of the medium. The target parameters from the cross section using dipole–dipole array are somewhat correlated with true parameters in the case of thin targets at shallow depths. In the case of the sequence of layers of gravel–marble gravel–sand gravel simulated in a small model tank in the physical model laboratory, the thickness of the high-resistive marble layer beneath the low-resistive gravel layer is enhanced conspicuously because of the significant resistivity contrast between gravel and marble.     

An approach to sustainable rural water supply in semi-arid Africa with a case study from Namibia

Sustainable-yield estimation in semi-arid conditions is always challenging, especially for fractured rock aquifers. An approach to assess sustainability is discussed using a case study from rural semi-arid Namibia. The fractured-rock aquifers in the study area have complex configuration. Geology maps, hydrocensus data, geophysical surveys, and drilling and hydraulic testing data were used to produce a conceptual model. Aquifer parameters were estimated based on the hydraulic test data and numerical modelling. Due to lack of data, as is often the case in rural Namibia, the simulation results had to be verified against geological and hydrogeological constraints. It is concluded that the aquifer system is sustained by episodic recharge and the long-term gain in storage (about 3,285 m³/a) represents the maximum extractable volume. It is recommended that the continuous monitoring system for groundwater level, river flow and rainfall should be part of a long-term scheme. The magnitude and frequency of the recharge events and extraction should be monitored in order to sustainably manage the resource. Although the illustrated approach is based on limited data, it provides a basis for management of individual groundwater schemes in semi-arid conditions in sub-Saharan Africa.     

Assessment of groundwater vulnerability in Mettur region, Tamilnadu, India using drastic and GIS techniques

A study was carried in Mettur taluk, Salem district of Tamilnadu, India to develop a DRASTIC vulnerability index in GIS environment owing to groundwater pollution with increasing population, industries, and agricultural activities. Seven DRASTIC layers were created from available data (depth to water table, net recharge, aquifer media, soil media, topography, impact of vadose zone, and hydraulic conductivity) and incorporated into DRASTIC model to create a groundwater vulnerability map by overlaying the hydrogeological parameters. The output map indicates southwestern part of the study area with high pollution potential, northern and northwestern parts as moderate pollution potential and northeastern parts as low and no risk of pollution potential. For validating the vulnerability assessment, a total of 46 groundwater samples were collected from different vulnerability zones of the study area for two different seasons (pre- and post-monsoon) and analyzed for major anions and cations. Higher ionic concentrations were noted in wells located near highly industrialized, urbanized, and agricultural active zones. The water types represent Na–Mg–HCO₃ and Na–Cl–HCO₃ type indicating dominance of anthropogenic-related activities. Nitrate and chloride were demarcated as pollution indicators and correlated with DRASTIC vulnerability map. The results show that southwestern, northwestern, and northern parts of the study area recorded with high and moderate vulnerable zones, record higher nitrate values. In contrast to DRASTIC method predicted, low vulnerable zones show higher chloride concentration may be due to agricultural and urban development.     

An effective ensemble classification framework using random forests and a correlation based feature selection technique

Accurate classification of heterogeneous land surfaces with homogeneous land cover classes is a challenging task as satellite images are characterized by a large number of features in the spectral and spatial domains. The identifying relevance of a feature or feature set is an important task for designing an effective classification scheme. Here, an ensemble of random forests (RF) classifiers is realized on the basis of relevance of features. Correlation‐based Feature Selection (CFS) was utilized to assess the relevance of a subset of features by studying the individual predictive ability of each feature along with the degree of redundancy between them. Predictability of RF was greatly improved by random selection of the relevant features in each of the splits. An investigation was carried out on different types of images from the Landsat Enhanced Thematic Mapper Plus (Landsat ETM+) and QuickBird sensors. It has been observed that the performance of the RF classifier was significantly improved while using the optimal set of relevant features compared with a few of the most advanced supervised classifiers such as maximum likelihood classifier (MLC), Navie Bayes, multi‐layer perception (MLP), support vector machine (SVM) and bagging.     

Improved earthquake locations in the Koyna-Warna seismic zone

In estimating the likelihood of an earthquake hazard for a seismically active region, information on the geometry of the potential source is important in quantifying the seismic hazard. The damage from an earthquake varies spatially and is governed by the fault geometry and lithology. As earthquake damage is amplified by guided seismic waves along fault zones, it is important to delineate the disposition of the fault zones by precisely determined hypocentral parameters. We used the double difference (DD) algorithm to relocate earthquakes in the Koyna-Warna seismic zone (KWSZ) region, with the P- and S-wave catalog data from relative arrival time pairs constituting the input. A significant improvement in the hypocentral estimates was achieved, with the epicentral errors <30 m and focal depth errors <75 m i.e. errors have been significantly reduced by an order of magnitude from the parameters determined by HYPO71. The earthquake activity defines three different fault segments. The seismogenic volume is shallower in the south by 3 km, with seismicity in the north extending to a depth of 11 km while in the south the deepest seismicity observed is at a depth of 8 km. By resolving the structure of seismicity in greater detail, we address the salient issues related to the seismotectonics of this region.     

A statistical analysis of exploration geochemical data for uranium

This paper describes a statistical analysis of reconnaissance exploration geochemical data for uranium. Three sets of data were analyzed, as they related to: (a) Charlotte-Winston-Salem and (b) Charlotte two-degree NTMS quadrangles of the south-eastern U.S.A. The coefficient of variation for uranium in each of the three sets of data was less than unity and hence no transformation of the original variable was needed. These data were subjected to correlogram analysis. A first-order Markovian model of the type: Y₀ exp (-a |p|) was fit by the least-squares method to serial correlation coefficients of these data using the method proposed by Deming (1948). The model was tested by computing the variance-volume relationship for assumed individual blocks of unit length. The noise in the input (record) was eliminated by the application of an optimum bilateral exponential smoothing technique developed by Agterberg. A comparison of spectral density estimates obtained by a maximum entropy method employing Yule-Walker equations and the Burg algorithm was also made. The prediction error coefficients needed to determine the order of the autoregressive process and hence the spectral densities were determined in both cases for the three sets of data.On leave from National Geophysical Research Institute, Hyderabad-7, India.     

A Godunov-Type Scheme for Atmospheric Flows on Unstructured Grids: Euler and Navier-Stokes Equations

In recent years there has been a growing interest in using Godunov-type methods for atmospheric flow problems. Godunov's unique approach to numerical modeling of fluid flow is characterized by introducing physical reasoning in the development of the numerical scheme (van Leer, 1999). The construction of the scheme itself is based upon the physical phenomenon described by the equation sets. These finite volume discretizations are conservative and have the ability to resolve regions of steep gradients accurately, thus avoiding dispersion errors in the solution. Positivity of scalars (an important factor when considering the transport of microphysical quantities) is also guaranteed by applying the total variation diminishing condition appropriately. This paper describes the implementation of a Godunov-type finite volume scheme based on unstructured adaptive grids for simulating flows on the meso-, micro- and urban-scales. The Harten-Lax-van Leer-Contact (HLLC) approximate Riemann solver used to calculate the Godunov fluxes is described in detail. The higher-order spatial accuracy is achieved via gradient reconstruction techniques after van Leer and the total variation diminishing condition is enforced with the aid of slope-limiters. A multi-stage explicit Runge-Kutta time marching scheme is used for maintaining higher-order accuracy in time. The scheme is conservative and exhibits minimal numerical dispersion and diffusion. The subgrid scale diffusion in the model is parameterized via the Smagorinsky-Lilly turbulence closure. The scheme uses a non-staggered mesh arrangement of variables (all quantities are cell-centered) and requires no explicit filtering for stability. A comparison with exact solutions shows that the scheme can resolve the different types of wave structures admitted by the atmospheric flow equation set. A qualitative evaluation for an idealized test case of convection in a neutral atmosphere is also presented. The scheme was able to simulate the onset of Kelvin-Helmholtz type instability and shows promise in simulating atmospheric flows characterized by sharp gradients without using explicit filtering for numerical stability.     

Seasonal dynamics of zooplankton in Lake Huetzalin, Xochimilco (Mexico City, Mexico)

We quantified the seasonal changes in the zooplankton abundances collected from the Huetzalin Lake (Mexico City, Mexico) for two years (February 2003–January 2004 and then March 2005–February 2006). Selected physicochemical variables (Secchi depth, temperature, pH, conductivity, dissolved oxygen, phosphorus, nitrogen, carbon and chlorophyll a concentration) were also measured at the time of zooplankton collection. The data on zooplankton abundances and the physicochemical variables were subjected to multiple correlation analysis and we also derived Shannon–Wiener species diversity index. Secchi depth ranged from 9 to 65 cm. Generally the lake was alkaline (pH 7–12). The conductivity ranged from 500–1000 mS cm⁻¹, while the mean water temperature was 20.5 °C. Dissolved oxygen levels were generally >3 mg L⁻¹ and were higher in the winter than warmer months. Nitrates (90–95 μg L⁻¹) and phosphates (.2–.5 mg L⁻¹) indicated that the water was eutrophic. Chlorophyll a levels ranged from 143 to 696 μg L⁻¹ during the study period. The zooplankton community was dominated by rotifers (46 species), followed by cladocerans (9 species) and there were only two copepod species. The dominant rotifer species were Brachionus angularis, Brachionus calyciflorus, Brachionus havanaensis, Brachionus quadridentatus, Lecane bulla and Polyarthra vulgaris. Rare rotifer species in Lake Huetzalin were Lecane ohioensis, Dicranophorus forcipatus, Lecane pyriformis, Lindia torulosa, Pleurotrocha petromyzon and Brachionus durgae. Highest densities (occasional peaks of 400 ind L⁻¹) of B. quadridentatus occurred between April and December, while B. havanaensis reached peak densities, during June to October. B. calyciflorus reached densities higher than 1240 ind L⁻¹ during May–September. Cladoceran and copepod densities in Lake Huetzalin were much lower than that of the rotifers. This study confirmed the earlier findings that Xochimilco system of canals is dominated by rotifers and the crustacean zooplankton have much lower abundances possibly due to predation from fish.     

The Cadmium Zinc Telluride Imager on AstroSat

The Cadmium Zinc Telluride Imager (CZTI) is a high energy, wide-field imaging instrument on AstroSat. CZTI’s namesake Cadmium Zinc Telluride detectors cover an energy range from 20 keV to \(>200\) keV, with 11% energy resolution at 60 keV. The coded aperture mask attains an angular resolution of 17\(^\prime \) over a 4.6\(^\circ \) \(\times \) 4.6\(^\circ \)  (FWHM) field-of-view. CZTI functions as an open detector above 100 keV, continuously sensitive to GRBs and other transients in about 30% of the sky. The pixellated detectors are sensitive to polarization above \(\sim \)100 keV, with exciting possibilities for polarization studies of transients and bright persistent sources. In this paper, we provide details of the complete CZTI instrument, detectors, coded aperture mask, mechanical and electronic configuration, as well as data and products.     

Differentiation of oil seed crops by remote sensing based on their spectral reflectance pattern

The feasibility of differentiating four oil-seed crops viz., mustard, toria, yellow sarson and sunflower, based on their spectral reflectance in the visible and near infra red region was studied in a field experiment, The spectral vegetative index profiles, generated during the growth period of different oil seed crops indicated two vegetative growth peaks and a depression between the two peaks, due to the conspicuous yellow colour of flowers, which masked the green leaves. The magnitude of such depression in the spectral vegetation indices viz., ‘Greenness’ and ‘Perpendicular Vegetation Index’ (PVI), were of higher magnitude in yellow sarson. The flowering period parameters viz., flowering time, duration and intensity, deduced from the spectral vegetation indices were found to be beneficial in differentiating different oil-seed crops by remote sensing. A plot of ‘Brightness’ vs. ‘Greenness’ values determined during the growth of the crops formed typical clusters. The cluster representing toria crop was significantly different from the other crops, thereby making toria identifiable from others by remote sensing.