排序方式： 共有80条查询结果，搜索用时 15 毫秒
71.
Abhishek?Banerjee Prafull?SinghEmail author Kamleshwar?Pratap 《Arabian Journal of Geosciences》2016,9(18):711
Groundwater management is of fundamental importance to meet the rapidly expanding urban, industrial and agricultural water requirements in semi-arid areas. To assess the current rate of groundwater withdrawal and possibility of recharge of potential aquifer in the semi-arid regions is essential for water management. The present study aimed to identify potential area for groundwater recharge structure in the Gwalior area based on land use, rainfall variation, hydrological component and statistical analysis. In this work, a stream survival approach was used for the assessment of water channel by using triangulated network and regression analysis to find out the correlation of individual component with reference to water management. Land use/land cover (LULC) map prepared from multispectral satellite images of the study area and used to validate the hydrological component and the results observed through the regression model shows good correlation. Therefore, immediate and effective water management schemes are required for sustainable water resource development and management in the area. 相似文献
72.
Flow pulsations in two-phase and single-phase near-critical fluids are considered as a possible source of ultra-low-frequency seismo-electromagnetic variations. The conditions for generation and suppression of density wave instability in the crust are analyzed and the surface electromagnetic effect due to streaming potential generation is estimated. The upper limit of amplitude of magnetic field variations due to density wave instability is about 0.1 nT for single-phase supercritical and 1 nT for two-phase flow oscillations in the frequency range \(10^{-4}{-}10^{-2}~\) Hz for the temperature gradients and spatial scales possible during strike slip events. The signal is characterized by a decaying amplitude with typical relaxation time of about several quasi-periods. The possibility of generation of very low-frequency flow pulsations in two-phase fluids via individual bubble evolution and interaction with external acoustic waves is discussed. 相似文献
73.
74.
Abhishek Pandey Khem B. Thapa R. Prasad K. P. Singh 《Journal of the Indian Society of Remote Sensing》2012,40(4):709-715
Estimation of crop variables is necessary for crop type monitoring as well as crop yield forecast. At the present era artificial neural network methodology are widely used to the remote sensing domain for numerous applications like crop yield forecasting and crop type classification. In the present work, two neural network models namely general regression neural network (GRNN) and radial basis function neural network (RBFNN) are used to estimate crop variables: leaf area index (LAI), biomass (BM), plant height (PH) and soil moisture (SM) by using ground based X-band scatterometer data. The both networks are trained and tested with X-band scatterometer data. The performance of the GRNN and RBFNN networks are found that the radial basis approach is more suitable for crop variable estimation in comparison to the GRNN approach. This work presents the applicability of neural network as an estimator and method employed could be useful to estimate the crop variables of other crops. 相似文献
75.
The groundwater inverse problem of estimating heterogeneous groundwater model parameters (hydraulic conductivity in this case) given measurements of aquifer response (such as hydraulic heads) is known to be an ill-posed problem, with multiple parameter values giving similar fits to the aquifer response measurements. This problem is further exacerbated due to the lack of extensive data, typical of most real-world problems. In such cases, it is desirable to incorporate expert knowledge in the estimation process to generate more reasonable estimates. This work presents a novel interactive framework, called the ‘Interactive Multi-Objective Genetic Algorithm’ (IMOGA), to solve the groundwater inverse problem considering different sources of quantitative data as well as qualitative expert knowledge about the site. The IMOGA is unique in that it looks at groundwater model calibration as a multi-objective problem consisting of quantitative objectives – calibration error and regularization – and a ‘qualitative’ objective based on the preference of the geological expert for different spatial characteristics of the conductivity field. All these objectives are then included within a multi-objective genetic algorithm to find multiple solutions that represent the best combination of all quantitative and qualitative objectives. A hypothetical aquifer case-study (based on the test case presented by Freyberg [Freyberg DL. An exercise in ground-water model calibration and prediction. Ground Water 1988;26(3)], for which the ‘true’ parameter values are known, is used as a test case to demonstrate the applicability of this method. It is shown that using automated calibration techniques without using expert interaction leads to parameter values that are not consistent with site-knowledge. Adding expert interaction is shown to not only improve the plausibility of the estimated conductivity fields but also the predictive accuracy of the calibrated model. 相似文献
76.
In recent years a growing understanding has emerged regarding the need to expand the modeling paradigm to include conceptual model uncertainty for groundwater models. Conceptual model uncertainty is typically addressed by formulating alternative model conceptualizations and assessing their relative likelihoods using statistical model averaging approaches. Several model averaging techniques and likelihood measures have been proposed in the recent literature for this purpose with two broad categories—Monte Carlo-based techniques such as Generalized Likelihood Uncertainty Estimation or GLUE (Beven and Binley 1992) and criterion-based techniques that use metrics such as the Bayesian and Kashyap Information Criteria (e.g., the Maximum Likelihood Bayesian Model Averaging or MLBMA approach proposed by Neuman 2003) and Akaike Information Criterion-based model averaging (AICMA) (Poeter and Anderson 2005). These different techniques can often lead to significantly different relative model weights and ranks because of differences in the underlying statistical assumptions about the nature of model uncertainty. This paper provides a comparative assessment of the four model averaging techniques (GLUE, MLBMA with KIC, MLBMA with BIC, and AIC-based model averaging) mentioned above for the purpose of quantifying the impacts of model uncertainty on groundwater model predictions. Pros and cons of each model averaging technique are examined from a practitioner's perspective using two groundwater modeling case studies. Recommendations are provided regarding the use of these techniques in groundwater modeling practice. 相似文献
77.
Abhishek Singh Douglas D. Walker Barbara S. Minsker Albert J. Valocchi 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(6):881-898
The interactive multi-objective genetic algorithm (IMOGA) combines traditional optimization with an interactive framework that considers the subjective knowledge of hydro-geological experts in addition to quantitative calibration measures such as calibration errors and regularization to solve the groundwater inverse problem. The IMOGA is inherently a deterministic framework and identifies multiple large-scale parameter fields (typically head and transmissivity data are used to identify transmissivity fields). These large-scale parameter fields represent the optimal trade-offs between the different criteria (quantitative and qualitative) used in the IMOGA. This paper further extends the IMOGA to incorporate uncertainty both in the large-scale trends as well as the small-scale variability (which can not be resolved using the field data) in the parameter fields. The different parameter fields identified by the IMOGA represent the uncertainty in large-scale trends, and this uncertainty is modeled using a Bayesian approach where calibration error, regularization, and the expert’s subjective preference are combined to compute a likelihood metric for each parameter field. Small-scale (stochastic) variability is modeled using a geostatistical approach and added onto the large-scale trends identified by the IMOGA. This approach is applied to the Waste Isolation Pilot Plant (WIPP) case-study. Results, with and without expert interaction, are analyzed and the impact that expert judgment has on predictive uncertainty at the WIPP site is discussed. It is shown that for this case, expert interaction leads to more conservative solutions as the expert compensates for some of the lack of data and modeling approximations introduced in the formulation of the problem. 相似文献
78.
79.
Abhishek Kumar Chaurasia H. K. Pandey H. C. Nainwal Jitendra Singh S. K. Tiwari 《Journal of the Geological Society of India》2017,89(6):689-696
The rock mass rating (RMR) and slope mass rating (SMR) has been carried out to classify the slope in terms of slope instability. To understand the RMR and SMR various geostructural, geomorphologic and hydrological parameters of the slopes were measured and analyzed. 32 rock slopes/rock cum debris slopes were identified in the study area. The present RMR and SMR study is an outcome of extensive field study along a stretch of about 10 km on road leading from Srinagar to Pauriarea along Alaknanda valley. The technique followed incorporates the relation between discontinuities and slope along with rock mass rating (RMR) and slope mass rating (SMR). The analysis of the 32 studied slopes shows that in the Gangadarshan area out of six rock slope facets, two falls in class II (stable) and four in class IV (unstable). It is significant to note that the slope facets coming under class IV are comprised of active landslide portions. While the slopes under class II show minor failure or old landslide debris. 相似文献
80.
Considerable damages during an earthquake (EQ) are the consequence of in situ soil losing its shear strength which is popularly known as liquefaction. A number of methodologies are available to quantify the safety of a site against liquefaction occurrence. Widely accepted recent methodologies follow iterative process making it cumbersome for the field engineer. In the present work, empirical correlations are proposed in accordance with widely accepted methodology, analysing the effect of various parameters such as overburden pressure, fines content (FC), factor of safety (FOS) etc. These proposed correlations are easy to use for the designers and the field engineers to determine the liquefaction potential of a site. Considering data from 207 global sites, proposed correlations are validated by comparing with standard methodology. Three different graphical validations are presented supporting that the results based on the proposed correlations are closely matching with the standard methodology. In case a site is found susceptible to liquefaction, so far no correlations are available to determine the shear strength required to be achieved after ground improvement which will ensure no liquefaction during future EQ. Proposed correlations in this work can also be used easily to determine improved shear strength required for a known FOS, FC and EQ magnitude (M) from ground improvement. Two flowcharts explaining the use of proposed correlations to determine FOS of a site and improvement shear strength required for a liquefied site from ground improvement respectively are developed in this work. Based on the second flowchart, determination of shear strength required from ground improvement are done for 45 random sites out of 207 liquefied sites during worldwide EQ in this work. 相似文献