A combined Time Series – Wavelet Model For Prediction of Ground Water Level (Case Study: Firuzabad Plain)

Document Type : Research Paper

Authors

1 MSc of Water resource Engineering Department of Shahid Chamran University of Ahvaz, Iran.

2 Associate Professor, Water Engineering Department, Shahid Chamran University of Ahvaz, Iran

3 Associate Professor, Water Engineering Department, Shahid Chamran University of Ahvaz, Iran.

4 Assistant Professor, Faculty of Mathematics and Computer Sciences, Shahid Chamran University of Ahvaz, Iran.

5 PhD Candidate, Faculty of Water Sciences, Shahid Chamran University of Ahvaz, Iran.

Abstract

Recently, the phenomenon of climate change, drought, the exploitation of the ground water has caused a sharp decline in groundwater levels, which has also led to groundwater related subsidence and desertification. Therefore, reliable prediction of groundwater level for managing these resources is of prime importance. Nowadays wavelet transforms through signal decomposition to time and frequency has created an exceptional method for signal processing, with the help of the transformation of the wavelet that has the ability to split the time series into a multi-dimensional substrate with different scales.
One of the useful characteristics of wavelet transforms is the filtering algorithm, which divids the data into two groups of approximation and details by passing them through the wavelet filter. In this study, monthly groundwater surface, rainfall, and temperature data were used. Using the program code written in MATLAB software, it is necessary to analyze the time series data of all three parameters of temperature, precipitation, and water level. The values ​​of the parameters were selected as inputs and placed in the wavelet function. For analyzing all the parameters, according to various mother-wavelet experiments, and considering the above mentioned point, five mother-wavelets (Haar, Coif, Symlet, Db, Db4) were selected. For this purpose, the program was first implemented for each of the following wavelets with 4 different decomposition levels. After several software runs under specific conditions and scenarios and then comparing them with each other, results were obtained.

Keywords


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Volume 41, Issue 4
January 2019
Pages 1-16
  • Receive Date: 20 October 2015
  • Revise Date: 30 November 2016
  • Accept Date: 03 December 2016
  • Publish Date: 22 December 2018