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Singh S.K.,National Institute of Hydrology
Journal of Irrigation and Drainage Engineering | Year: 2012

The suitability of the widely used existing solution for calculating groundwater mound due to artificial recharge from rectangular areas is examined for its applicability to unconfined aquifers, and this solution has been found applicable only to confined aquifers. The solution applicable for confined aquifers is derived and shown equivalent to the existing solutions. A computationally simple function is proposed for accurately approximating the integral appearing in this or existing solutions. A procedure involving analytical approximation is outlined for using this solution for unconfined aquifers. A method to calculate groundwater mound height in unconfined aquifers due to arbitrarily varying temporal recharge (percolation) is also proposed. It is hoped that the proposed methods would be of help to field engineers and practitioners. © 2012 American Society of Civil Engineers. Source


Nayak P.C.,National Institute of Hydrology
Journal of Hydrologic Engineering | Year: 2010

This paper presents a popular fuzzy rule-based model for river flow forecasting for an Indian basin. To set up the fuzzy rules, a cluster estimation method is adopted to determine the number of rules and the membership functions of variables involved in the premises of the rules. The most appropriate set of input variables was determined by trial and error procedure to test the coherence of the different input variables in forecasting flood. It is observed that the last time steps of measured runoff are dominating the forecast. The developed model is used to forecast up to 12 h in advance. The values of three performance evaluation criteria namely, the coefficient of efficiency, the root-mean-square error and the coefficient of correlation, were found to be very good and consistent for flows forecasted 1 h in advance by the model. The performance is decreasing as the forecast horizon is increasing and a reasonable forecast is obtained up to 9 h ahead. A set of fuzzy rules is extracted and used for understanding of the behavior of the developed model. It is observed that the developed model follows the trend of the input membership grade in antecedent part of the fuzzy model. © 2010 ASCE. Source


Singh S.K.,National Institute of Hydrology
Journal of Irrigation and Drainage Engineering | Year: 2010

Two sets of unimodal diagnostic curves, one set assumes no aquitard storage and the other set assumes aquitard storage, are developed for identifying the parameter of leaky aquifers from early drawdowns, which yields accurate estimates of the parameters and lessens the subjectivity due to personal errors. The proposed diagnostic curve method is simple, easy to apply, and is based on matching of the diagnostically plotted observed drawdowns to an appropriate diagnostic curve. The new method is simple, easy to apply, does not require either the initial guess for the parameter values or repetitive evaluation of the leaky aquifer well function, and outperforms the conventional curve-matching, optimization, extended Kalman filter, and artificial neural network methods. The proposed set of diagnostic curves has a good diagnostic property and is able to easily identify nonideal conditions. The new method suggests a shorter duration pumping test, which would save time, money, and water. It is hoped that the proposed method would be useful to the field engineers and practitioners. © 2010 ASCE. Source


Singh S.K.,National Institute of Hydrology
Journal of Irrigation and Drainage Engineering | Year: 2010

Simple method and explicit equations are proposed for estimating the parameters of leaky aquifers from drawdown at an observation well, which avoid the curve matching or initial estimate of the parameter. The proposed method is computationally simple and the calculations can be performed even on a handheld calculator. The application of the methods is illustrated, using published data sets. The new method yields quick and accurate estimates of the leaky-aquifer parameters, if observed drawdowns do not contain large errors. The proposed method can also analyze the early drawdowns for accurate characteristics/parameters of a confined aquifer, if the conductance of the aquitard is assigned a zero value. It is hoped that the proposed method would be of help to field engineers and practitioners. © 2010 ASCE. Source


Budu K.,National Institute of Hydrology
Journal of Hydrologic Engineering | Year: 2014

The present study demonstrates the capability of two preprocessing techniques such as wavelets and moving average (MA) methods in combination with feed-forward neural networks-namely, back propagation (BP) and radial basis (RB) and multiple linear regression (MLR) models-in the prediction of the daily inflow values of the Malaprabha reservoir in Belgaum, India. Daily data on 11 years of rainfall, inflow, and streamflow at an upstream gauging station have been used. The observed inputs are decomposed into subseries using discrete wavelet transform with different mother wavelet functions, and then the appropriate subseries is used as input to the neural networks for forecasting reservoir inflow. Model parameters are calibrated using 7 years of data, and the remaining data are used for model validation. More statistical indices have been used to determine the optimal models. Optimum architectures of the wavelet neural network (WNN) models are selected according to the obtained evaluation criteria in terms of the Nash-Sutcliffe efficiency coefficient, root mean squared error, and correlation coefficient. The result of this study has been compared by developing two standard neural network models and a multiple linear regression (MLR) model and MA. The results of this study indicate that the WNN model performs better compared to artificial neural network (ANN) and MLR models in forecasting the inflow hydrograph effectively. The study only used reservoir inflow data from one area, and further studies using data from various areas may be required to strengthen these conclusions. © 2014 American Society of Civil Engineers. Source

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