Wavelet and Gaussian Approaches for Estimation of Groundwater Variations Using GRACE Data. Issue 1 (11th May 2015)

• Record Type: Journal Article
• Authors: Fatolazadeh, Farzam; Voosoghi, Behzad; Naeeni, Mehdi Raoofian
• Is Part Of: Ground water. Volume 54:Issue 1(2016:Jan./Feb.)
• Page Start: 74
• Page End: 81
• Publication Date: 2015-05-11
• Subjects: Groundwater -- Periodicals; Wells -- Periodicals; Eau souterraine -- Périodiques; Puits -- Périodiques; Grondwater; Eau souterraine; Puits; Electronic journals; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 551.49
• DOI: 10.1111/gwat.12325
• Languages: English
• ISSNs: 0017-467X

Abstract

Abstract: In this study, a scheme is presented to estimate groundwater storage variations in Iran. The variations are estimated using 11 years of Gravity Recovery and Climate Experiments (GRACE) observations from period of 2003 to April 2014 in combination with the outputs of Global Land Data Assimilation Systems (GLDAS) model including soil moisture, snow water equivalent, and total canopy water storage. To do so, the sums of GLDAS outputs are subtracted from terrestrial water storage variations determined by GRACE observations. Because of stripping errors in the GRACE data, two methodologies based on wavelet analysis and Gaussian filtering are applied to refine the GRACE data. It is shown that the wavelet approach could better localize the desired signal and increase the signal‐to‐noise ratio and thus results in more accurate estimation of groundwater storage variations. To validate the results of our procedure in estimation of ground water storage variations, they are compared with the measurements of pisometric wells data near the Urmia Lake which shows favorable agreements with our results.