A proposed new approach for groundwater resources assessment in India

Assessment of groundwater resources in India is guided by National Water Policy (1987, 2002) which states that groundwater resources can be exploited only up to its recharge limit. The methodology for groundwater resources assessment in India is broadly based on Ground Water Resources Estimation Methodology, 1997 and it involves assessment of annual replenishable groundwater resources (recharge), annual groundwater draft (utilization) and the percentage of utilization with respect to recharge (stage of development). The assessment units (blocks/watersheds) are categorized based on stage of groundwater development (utilization) and the long term water level trend. The present methodology though useful in identification and prioritization of areas for groundwater management, falls short of addressing several critical issues like spatial and temporal variation of groundwater availability within the aquifer, accessibility of groundwater resources and quality of groundwater. This paper introduces a new categorisation scheme considering the above issues. The proposed scheme takes into account four criteria, viz. (i) stage of exploitation, (ii) extractability factor, (iii) temporal availability factor and (iv) quality factor. In comparison to the existing method used for categorisation, the proposed approach is more inclusive. The methodology is also equally suitable for both alluvial and hard rock terrain since it takes into consideration the variable characteristics of different types of aquifers and convergence of quantitative and qualitative assessment. The categorisation proposed here involves GIS based integration of different parameters/ themes. This allows better representation of spatial variability. The proposed methodology is demonstrated in this paper taking a case study from a hard rock terrain in central India.     

Evaluation of groundwater resources in wide inundation areas of the Mekong River basin

Severe floods can have disastrous impacts and cause wide ranging destruction in the Mekong River basin. At the same time groundwater resources are significantly influenced and extensively recharged by flood water in inundation areas of the basin. This study determines the variation of groundwater resources caused by flooding over inundated areas located in lower part of the Mekong River basin using numerical modeling and field observations. The inundation calculations have been evaluated using satellite image outputs. Comparing large, medium and small flood events, we conclude that flood control which reduces the area of inundation, results in a reduction of groundwater resources in the area. In 1993, a 19% reduction in inundation areas resulted in a 31% reduction in groundwater storage. In 1998, a 44% reduction in inundation areas led to a 42% reduction in groundwater storage. Thus, while flood control activities are vital to reduce negative flood impacts in the Mekong River basin, they also negatively impact groundwater resources in the area.     

Investigation of general regression neural network architecture for grade estimation of an Indian iron ore deposit

The mineral resource estimation requires accurate prediction of the grade at location from limited borehole information. It plays the dominant role in the decision-making process for investment and development of various mining projects and hence become an important and crucial stage. This paper evaluvates the use of two distinct artificial neural network (ANN)-based models, general regression neural network (GRNN) and multilayer perceptron neural network (MLP NN), to improve the grade estimation from Koira iron ore region in Sundargarh district, Odisha. ANN-based models capture the inherent complex structure of mineral deposits and provide a reliable generalization of the iron grade. The ANN-based approach does not require any preliminary geological study and is free from any statistical assumption on the raw data before its application. The GRNN is a one-pass learning algorithm and does not require any iterative procedure for training less complex structure and requires only one learning parameter for optimization. In this investigation, the spatial coordinates and multiple lithological units were taken as input variables and the iron grade was taken as the output variable. The comparative analysis of these models has been carried out and the results obtained were validated with traditional geostatistical method ordinary kriging (OK). The GRNN model outperforms the other methods, i.e. MLP and OK, with respect to generalization and predictability of the grades at an un-sampled location.     

Estimation of lateral force contribution of boundary elements in steel plate shear wall systems

Steel plate shear walls (SPSWs) are used as lateral force‐resisting systems in new and retrofitted structures in high‐seismic regions. Various international codes recommend the design of SPSWs assuming the entire lateral load to be resisted by the infill plates. Such a design procedure results in significant overstrength leading to uneconomical and inefficient use of materials. This study is focused on the estimation of contribution of boundary elements in resisting the lateral force considering their interaction with the web plates of SPSW systems. Initially, the relative contribution of web plates and boundary frames is computed for a single‐bay single‐story frame with varying rigidity and end connections of boundary elements. Nonlinear static analyses are carried out for the analytical models in OpenSees platform to quantify this contribution. Later, this study is extended to the code‐based designed three‐story, six‐story, and nine‐story SPSWs of varying aspect ratios. Based on the results obtained, a new design procedure is proposed taking the lateral strengths of the boundary frames into account. Nonlinear time‐history analyses are conducted for 40 recorded ground motions representing the design basis earthquake and maximum considered earthquake hazard levels to compare the interstory and residual drift response and yield mechanisms of SPSWs designed as per current practice and the proposed methodology. Finally, an expression has been proposed to predict the lateral force contribution of the infill plate and the boundary frame of SPSWs. Copyright © 2016 John Wiley & Sons, Ltd.     

Seismic strengthening of RC columns using external steel cage

Steel caging technique is commonly used for the seismic strengthening of reinforced concrete (RC) columns of rectangular cross‐section. The steel cage consists of angle sections placed at corners and held together by battens at intervals along the height. In the present study, a rational design method is developed to proportion the steel cage considering its confinement effect on the column concrete. An experimental study was carried out to verify the effectiveness of the proposed design method and detailing of steel cage battens within potential plastic hinge regions. One ordinary RC column and two strengthened columns were investigated experimentally under constant axial compressive load and gradually increasing reversed cyclic lateral displacements. Both strengthened columns showed excellent behavior in terms of flexural strength, lateral stiffness, energy dissipation and ductility due to the external confinement of the column concrete. The proposed model for confinement effect due to steel cage reasonably predicted moment capacities of the strengthened sections, which matched with the observed experimental values. Copyright © 2009 John Wiley & Sons, Ltd.     

Wavelet-ANFIS models for forecasting monsoon flows: Case study for the Gandak River (India)

WANFIS, a conjunction model of discreet wavelet transform (DWT) and adaptive neuro-fuzzy inference system (ANFIS) was developed for forecasting the current-day flow in a river when only available data are historical flows. Discreet wavelet transform decomposed the observed flow time series (OFTS) into wavelet components which captured useful information on three resolution levels. A smoothened flow time series (SFTS) was formed by filtering out the noise wavelet components and recombining the effective wavelet components. WANFIS model is essentially an ANFIS model with SFTS hydrograph as the input, while ANFIS and autoregression (AR) models, developed for comparison purpose, use OFTS hydrograph as input. For performance evaluation, the developed models were utilized for predicting daily monsoon flows for the Gandak River in Bihar state of India. During monsoon (June–October), this river carries large flows making the entire North Bihar unsafe for habitation or cultivation. Based on various performance indices, it was concluded that WANFIS models simulate the monsoon flows in the Gandak more reliably than ANFIS and AR models. The best performing WANFIS model, with four previous days’ flows as input, predicted the current-day Gandak flows with 80.7% accuracy while ANFIS and AR models predicted it with only 71.8 and 51.2% accuracies.     

A class of solutions for anisotropic stars admitting conformal motion

We provide a new class of interior solutions for anisotropic stars admitting conformal motion. The Einstein’s field equations in this construction are solved for specific choices of the density/mass functions. We analyze the behavior of the model parameters like radial and transverse pressures, density and surface tension.