Research Article Open Access

PREDICTING GROUNDWATER LEVEL USING FOURIER SERIES INTEGRATED WITH LEAST SQUARE ESTIMATION METHOD

Manoj K. Jha1
  • 1 North Carolina A and T State University, USA
American Journal of Engineering and Applied Sciences
Volume 7 No. 1, 2014, 99-104

DOI: https://doi.org/10.3844/ajeassp.2014.99.104

Submitted On: 4 February 2014 Published On: 26 March 2014

How to Cite: Jha, M. K. (2014). PREDICTING GROUNDWATER LEVEL USING FOURIER SERIES INTEGRATED WITH LEAST SQUARE ESTIMATION METHOD. American Journal of Engineering and Applied Sciences, 7(1), 99-104. https://doi.org/10.3844/ajeassp.2014.99.104

Abstract

Groundwater level data is an important indicator of the availability and distribution of groundwater resources of the region. However, it is difficult to understand the continuous and discrete fluctuations of the groundwater level which is controlled by various factors. This study demonstrated the use of Fourier series integrated with the least square estimation method to predict the groundwater level especially in the case of seasonal-sensitive groundwater fluctuations. It was observed that the designed method was able to model the groundwater-table data, collected at the Hagan Stone Park station in Greensboro, North Carolina, with a fair degree of accuracy with a testing mean square error of 0.0735.

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Keywords

  • Groundwater Level
  • Fourier Series
  • Modeling
  • Greensboro