Secondary geochemical dispersion in the Precambrian auriferous Hutti-Maski schist belt, Raichur district, Karnataka, India. Part I: anomalies of As, Sb, Hg and Bi in soil and groundwater

The nature of secondary geochemical dispersion of As, Sb, Hg and Bi in soil and ground water of the semi-arid, tropical, Archaean, auriferous, Hutti-Maski greenstone belt has been investigated for identification of appropriate geochemical techniques for Au exploration in similar terrains.Results indicate that the <180 μm size-fraction of C-horizon soil is an appropriate sampling medium for delineating pedogeochemical anomalies of As, Sb, Hg and Bi related to gold mineralisation. These pedogeochemical anomalies along with anomalous values of alkalinity, chloride, sulphate, As and Sb in groundwater are controlled significantly by primary mineralisation located along shear zones in the greenstone belt. Arsenic anomalies in soil are broad, whereas, those of Sb and Bi are restricted to narrow zones directly over mineralised areas. In contrast, Hg anomalies around known mineralised areas are irregular and do not clearly demarcate the mineralised areas. The study indicates that anomalies of As, Sb and Hg in soil are principally hydromorphic, whereas those of Bi are clastic.The study recommends use of groundwater sampling at 2–3 km spacing with routine analysis of chloride, sulphate and alkalinity along with As and Sb in the first phase. This may be followed up with sampling of C-horizon of soils on a 1 km square grid for As-anomalies. Arsenic-anomalous areas may be sampled for As, Sb, Hg and Bi on a 500 m square grid for detailed exploration.     

Integration of Sparse Geologic Information in Gold Targeting Using Logistic Regression Analysis in the Hutti–Maski Schist Belt,Raichur, Karnataka,India—A Case Study

Logistic regression has been used in the study to integrate indicator patterns for estimation of the probability of occurrence of gold deposits in a part of the auriferous Archaean Hutti–Maski schist belt. Data used consist of categorical and continuous variables obtained from a coded lineament map and geochemical anomaly maps of the pathfinder elements of gold in soil and groundwater. Main effects and interactions of the variables studied were used in formulating the logistic regression model. Regression models using lineament-proximity data, combined with soil and groundwater geochemical anomalies were tested on parts of the schist belt with data not used in estimation of model parameters. Predicted probabilities greater than 0.9 identified known deposit locations in the area.     

Limitations of real-time models for forecasting river flooding from monsoon rainfall

Very intense rainfall during the southwest and northeast monsoons causes severe river flooding in India. Some traditional techniques used for real-time forecasting of flooding involve the relationship between effective rainfall and direct surface runoff, which simplifies the complex interactions between rainfall and runoff processes. There are, however, serious problems in deducing these variables in real time, so it is highly desirable to have a real-time flood forecasting model that would directly relate the observed discharge hydrograph to the observed rainfall. The storage routing model described by Baba and Hoshi (1997), Tanaka et al. (1997), and Baba et al. (2000), and a simplified version of this model, have been used to compute observed river discharge directly from observed hourly rainfall. This method has been used to study rainfall–runoff data of the Ajay River Basin in eastern India. Five intense rainfall events of this basin were studied. Our results showed that the Nash–Sutcliffe efficiency of discharge prediction for these five events was 98.6%, 94.3%, 86.9%, 85.6%, and 67%. The hindcast for the first two events is regarded as completely satisfactory whereas for the next two events it is deemed reasonable and for the fifth it is unsatisfactory. It seems the models will yield accurate hindcast if the rainfall is uniform over the drainage basin. When the rainfall is not uniform the performance of the model is unsatisfactory. In future this problem can, in principle, be corrected by using a weighted amount if rainfall is based upon multiple rain-gauge observations over the drainage basin. This would provide some measure of the dispersion in the rainfall. The model also seems unable to simulate flooding events with multiple peaks.     

Effect of Lime Stabilized Soil Cushion on Strength Behaviour of Expansive Soil

An experimental investigation was undertaken to study the effects of lime-stabilized soil-cushion on the strength behavior of expansive soil. In the present investigation, a series of laboratory tests (Unconfined compression tests and CBR tests) were conducted on both expansive soil alone and expansive soil cushioned with lime-stabilized non-expansive cohesive soil. Lime contents of 2, 4, 6, 8 and 10% by dry weight of cohesive non-swelling soil was used in the stabilized soil cushion. Both expansive soil and lime stabilized soil cushion were compacted to Standard Proctor’s optimum condition with thickness ratio 2:1. Tests on cushioned expansive soils were conducted at different curing and soaking periods i.e., 7, 14, 28 and 56 days. The test results revealed that maximum increase in strength was achieved after 14 days of curing or soaking period with 8% of lime content.     

Computing the 3D in-situ stress field from shut-in pressure data using statistical regression

The paper describes a multivariable statistical regression technique for computing the 3D stress tensor applied to the shut-in pressure data obtained on fractures during in-situ stress measurement by hydraulic fracturing in a short borehole. This method computes the mean value of components of the 3D stress tensor and their confidence intervals at a desired confidence level. This has been applied to the data of shut-in pressure from Narwapahar mine, India and Kamaishi mine, Japan. The computed in-situ stress tensor is corroborated with that obtained by other methods.     

Utilization of ochre as an adsorbent to remove Pb(II) and Cu(II) from contaminated aqueous media

The ability of ochre to remove Pb(II) and Cu(II) from aqueous media has been studied by batch sorption studies varying the contact time, initial metal concentration, initial solution pH and temperature to understand the adsorption behaviour of these metals through adsorption kinetics and isotherms. The pH of the solution and the temperature controlled the adsorption of metal ions by ochre and rapid uptake occurred in the first 30 min of reaction. The kinetics of adsorption followed a pseudo-second-order rate equation (R ² > 0.99) and the isotherms are well described by the Freundlich model. Adsorption of metals onto ochre is endothermic in nature. Between the two metals, Pb(II) showed more preference towards the exchangeable sites on ochre than Cu(II). This study indicates that ochre is a very effective adsorbent in removing Pb(II) and Cu(II) from the aqueous environment with an adsorptive capacity of 0.996 and 0.628 mg g^?1 and removal efficiency of 99.68 and 62.80 %, respectively.     

Using spatial statistics to identify the uranium hotspot in groundwater in the mid-eastern Gangetic plain,India

The occurrence of uranium in groundwater is of particular interest due to its toxicological and radiological properties. It has been considered as a relevant contaminant for drinking water even at a low concentration. Uranium is a ubiquitously occurring radionuclide in the environment. Four hundred and fifty-six (456) groundwater samples from different locations of five districts of South Bihar (SB) were collected and concentrations of uranium (U) were analyzed using a light-emitting diode (LED) fluorimetric technique. Uranium concentrations in groundwater samples varied from 0.1 µg l^?1 to 238.2 µg l^?1 with an average value of 12.3 µg l^?1 in five districts of Bihar in the mid-eastern Gangetic plain. This study used hot spot spatial statistics to identify the distribution of elevated uranium concentration in groundwater. The hypothesis whether spatial distribution of high value and low value of U is more likely spatially clustered due to random process near a uranium hotspot in groundwater was tested based on z score and Getis-Ord Gi* statistics. The method implemented in this study, can be utilized in the field of risk assessment and decision making to locate potential areas of contamination.     

Bearing capacity of strip foundations reinforced with geogrid sheets by using upper bound finite‐element limit analysis

By using the upper bound finite‐elements limit analysis, with an inclusion of single and two horizontal layers of reinforcements, the ultimate bearing capacity has been computed for a rigid strip footing placed over (i) fully granular, (ii) cohesive‐frictional, and (iii) fully cohesive soils. It is assumed that (i) the reinforcements are structurally strong so that no axial tension failure can occur, (ii) the reinforcement sheets have negligible resistance to bending, and (iii) the shear failure can take place between the reinforcement and soil mass. It is expected that the different approximations on which the analysis has been based would generally remain applicable for reinforcements in the form of geogrid sheets. A method has been proposed to incorporate the effect of the reinforcement in the analysis. The efficiency factors, η_c and η_γ, to be multiplied with N_c and N_γ , for finding the bearing capacity of reinforced foundations, have been established. The results have been obtained (i) for different values of ? in case of fully granular and cohesive‐frictional soils, and (ii) for different rates at which the cohesion increases with depth for a fully cohesive soil. The optimum positions of the reinforcements' layers have also been determined. The effect of the reinforcements' length on the results has also been analyzed. As compared to cohesive soils, the granular soils, especially with higher values of ?, cause a much greater increase in the bearing capacity. The results compare reasonably well with the available theoretical and experimental data from literature. Copyright © 2013 John Wiley & Sons, Ltd.