NISCAIR Online Periodicals Repository

Research Journals >
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP) >
BVAAP Vol.20 [2012] >
BVAAP Vol.20(1) [June 2012] >

Title: Hybrid subtractive clustering technique for estimation of ground water table
Authors: Mehta, Rama
Kumar, Vipin
Garvit, Kumar
Saini, Naresh
Issue Date: Jun-2012
Publisher: NISCAIR-CSIR, India
Abstract: Groundwater scarcity and groundwater table decline at alarming rate create many problems for managers and planners. This problem will be worsening in future as demand for water would rise tremendously due to steady rise in human population. Optimal-exploitation of groundwater ‘in all the areas that are getting fast depleted’ is required to estimate the groundwater table. Keeping this in view, different models have been developed for an Indian catchment located in North – East region of India. Groundwater studies have not been conducted much by researchers for the problematic area of Budaun district where the water table is continuously declining at a faster rate. The present study is taken up to study the groundwater availability in the district. Models have been developed for prediction of water table behaviour and a proper groundwater recharge plan for the problematic areas can be suggested. Over the last decade, soft computing techniques like Fuzzy logic and Artificial Neural Networks (ANN) are increasingly used in hydrological studies. Furthermore, their computational speed in simulating and forecasting is very welcomed in real time operations. It is robust and flexible in managing real world complex systems involving uncertainty and imprecise data. Fuzzy Logic Controller (FLC) provides a means of converting a linguistic control strategy based on operators’ knowledge into an automatic control strategy. An important feature of fuzzy set theory is the symmetry between the objective function and constraints. During this study, a Neuro-Fuzzy approach such as ANFIS (Adaptive Neuro Fuzzy Inference System) subtractive cluster method (SCM) and ANN techniques have been used for monsoon (M) and non-monsoon (NM) periods in order to estimate the ground water tables. Input data of the network are composed by past measurements of nearby inflow and rainfall, and the quantity of water which has been pumped out from ground during that specific period. Input data are fuzzified with different degrees of membership. The models are developed and applied for Budaun district in Uttar Pradesh to get the optimum output during monsoon and non-monsoon period. Models developed by SCM technique give better results than ANN technique.
Page(s): 70-76
CC License:  CC Attribution-Noncommercial-No Derivative Works 2.5 India
ISSN: 0975-2412 (Online); 0771-7706 (Print)
Source:BVAAP Vol.20(1) [June 2012]

Files in This Item:

File Description SizeFormat
BVAAP 20(1) 70-76.pdf156.12 kBAdobe PDFView/Open
 Current Page Visits: 71 
Recommend this item


Online Submission of Articles |  NISCAIR Website |  National Knowledge Resources Consortium |  Contact us |  Feedback

Disclaimer: NISCAIR assumes no responsibility for the statements and opinions advanced by contributors. The editorial staff in its work of examining papers received for publication is helped, in an honorary capacity, by many distinguished engineers and scientists.

CC License Except where otherwise noted, the Articles on this site are licensed under Creative Commons License: CC Attribution-Noncommercial-No Derivative Works 2.5 India

Copyright © 2015 The Council of Scientific and Industrial Research, New Delhi. All rights reserved.

Powered by DSpace Copyright © 2002-2007 MIT and Hewlett-Packard | Compliant to OAI-PMH V 2.0

Home Page Total Visits: 162638 since 01-Sep-2015  Last updated on 21-Jun-2016Webmaster: