Wavelet and Gaussian Approaches for Estimation of Groundwater Variations Using GRACE Data.
作者： Farzam Fatolazadeh , Behzad Voosoghi , Mehdi Raoofian Naeeni
DOI: 10.1111/GWAT.12325
关键词: Environmental science 、 Groundwater 、 Remote sensing 、 Water storage 、 Gaussian 、 Wavelet 、 Data assimilation 、 Water resources 、 Snow 、 Water content
摘要: In this study, a scheme is presented to estimate groundwater storage variations in Iran. The are estimated using 11 years of Gravity Recovery and Climate Experiments (GRACE) observations from period 2003 April 2014 combination with the outputs Global Land Data Assimilation Systems (GLDAS) model including soil moisture, snow water equivalent, total canopy storage. To do so, sums GLDAS subtracted terrestrial determined by GRACE observations. Because stripping errors data, two methodologies based on wavelet analysis Gaussian filtering applied refine data. It shown that approach could better localize desired signal increase signal-to-noise ratio thus results more accurate estimation variations. validate our procedure ground variations, they compared measurements pisometric wells data near Urmia Lake which shows favorable agreements results.
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