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Deepak Kumar Anshuman Singh Rishi Kumar Jha Sunil Kumar Sahoo Vivekanand Jha 《Environmental Earth Sciences》2018,77(19):702
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. 相似文献
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Rishi Kumar Tiwari 《中国天文和天体物理学报》2010,10(4)
Einstein's field equations with variable gravitational and cosmological constants are considered in the presence of perfect fluid for the Bianchi type-Ⅰ universe by assuming that the cosmological term is proportional to R-m(R is a scale factor and m is a constant).A variety of solutions are presented.The physical significance of the respective cosmological models are also discussed. 相似文献
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Summary. A differential-difference equation governing the distribution of radiogenic heat in the crust has been obtained. The solution of this equation gives the exponential model of the heat production distribution with the logarithmic decrement as determined in Singh & Negi. 相似文献
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Summary In the paper we have transformed the steady and unsteady conductive heat transfer differential equation in spherical coordinates into a system of first order differential equations and processed them by method of propagator matrices to extrapolate the known surface heat flux and temperature to any desired depth. The elements of propagator matrices have been summarised for various piecewise continuous conductivity and rate of heat generation functions to approximate inhomogeneities in the earth. In the analysis the rate of heat generation is either assumed to depend linearly upon temperature or correspond to first order irreversible chemical reactions. 相似文献
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Summary An analysis is made to ascertain the effect of conductivity variation with temperature on the temperatures within the crust. It shows that this effect is very small and can safely be neglected. 相似文献
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Flow records, rising‐stage sediment samplers, and a sand suspension model are used to examine suspended sediment concentrations during major floods caused by tropical cyclones TC Joni and TC Kina in the Rewa River, Fiji. The highest concentrations of total suspended solids were measured during the early stages of TC Kina. The suspension model predicts higher sand concentrations for TC Kina compared with TC Joni because of the larger slope and higher shear stresses during Kina. Extremely high wash load concentrations early in TC Kina are at least partly due to remobilization of fine sediment deposited during the earlier TC Joni flood. Samples from the TC Kina had volumetric concentrations larger than 5%, indicating hyperconcentrated streamflows. Mass‐density shear stresses in the hyperconcentrated flows are up 1·6 times larger than clear‐water shear stresses, but they occur early during low stages of the flood and probably do not result in severe bed erosion. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
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Trullenque Ghislain Parashar Rishi Delcourt Clément Collet Lucille Villard Pauline Potel Sébastien 《Hydrogeology Journal》2017,25(3):813-827
Results of a series of deformation experiments conducted on gabbro samples and numerical models for computation of flow are presented. Rocks were subjected to triaxial tests (σ1 > σ2 = σ3) under σ3 = 150 MPa confining pressure at room temperature, to generate fracture network patterns. These patterns were either produced by keeping a constant confining pressure and loading the sample up to failure (conventional test: CT), or by building up a high differential stress and suddenly releasing the confining pressure (confining pressure release test: CPR). The networks are similar in overall density but differ primarily in the orientation of smaller fractures. In the case of CT tests, a conjugate fracture set is observed with one dominant fracture zone running at about 20° from σ1. CPR tests do not show such a conjugate pattern and the mean fracture orientation is at around 35° from σ1. Discrete fracture network (DFN) methodology was used to determine the distribution of flow and hydraulic head for both fracture sets under simple boundary conditions and uniform transmissivity values. The fracture network generated by CT and CPR tests exhibit different patterns of flow field and hydraulic head configurations, but convey approximately the same amount of flow at all scales for which DFN models were simulated. The numerical modelling results help to develop understanding of qualitative differences in flow distribution that may arise in rocks of the same mineralogical composition and mechanical properties, but under the influence of different stress conditions, albeit at similar overall stress magnitude.
相似文献9.
Forecasting monthly precipitation using sequential modelling 总被引：1，自引：1，他引：0
In the hydrological cycle, rainfall is a major component and plays a vital role in planning and managing water resources. In this study, new generation deep learning models, recurrent neural network (RNN) and long short-term memory (LSTM), were applied for forecasting monthly rainfall, using long sequential raw data for time series analysis. “All-India” monthly average precipitation data for the period 1871–2016 were taken to build the models and they were tested on different homogeneous regions of India to check their robustness. From the results, it is evident that both the trained models (RNN and LSTM) performed well for different homogeneous regions of India based on the raw data. The study shows that a deep learning network can be applied successfully for time series analysis in the field of hydrology and allied fields to mitigate the risks of climatic extremes. 相似文献
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Cubic law with aperture-length correlation: implications for network scale fluid flow 总被引：2，自引：2，他引：0
Christian Klimczak Richard A. Schultz Rishi Parashar Donald M. Reeves 《Hydrogeology Journal》2010,18(4):851-862
Previous studies have computed and modeled fluid flow through fractured rock with the parallel plate approach where the volumetric flow per unit width normal to the direction of flow is proportional to the cubed aperture between the plates, referred to as the traditional cubic law. When combined with the square root relationship of displacement to length scaling of opening-mode fractures, total flow rates through natural opening-mode fractures are found to be proportional to apertures to the fifth power. This new relationship was explored by examining a suite of flow simulations through fracture networks using the discrete fracture network model (DFN). Flow was modeled through fracture networks with the same spatial distribution of fractures for both correlated and uncorrelated fracture length-to-aperture relationships. Results indicate that flow rates are significantly higher for correlated DFNs. Furthermore, the length-to-aperture relations lead to power-law distributions of network hydraulic conductivity which greatly influence equivalent permeability tensor values. These results confirm the importance of the correlated square root relationship of displacement to length scaling for total flow through natural opening-mode fractures and, hence, emphasize the role of these correlations for flow modeling. 相似文献