Investigation of correlation of the variations in land subsidence (detected by continuous GPS measurements) and methodological data in the surrounding areas of Lake Urmia

Moghtased-Azar, Khosro; Mirzaei, Ali; Nankali, H.; Tavakoli, Farokh

doi:10.5194/npg-19-675-2012

Cited by 10 publications

(4 citation statements)

References 29 publications

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“…Signal decomposition algorithms, such as principal component analysis (PCA), the Fourier transform (FT), have been used to separate temporal component from geodetic time series [11,[45][46][47]. Rudolf et al [48] used PCA to extract the dominant temporal behavior from InSAR time series, while Chaussard et al [49] performed PCA to extract the spatiotemporal variability of deformation and to investigate the seasonal deformation and water level changes.…”

Section: Wavelet Transform For Time-series Analysismentioning

confidence: 99%

Regional Land Subsidence Analysis in Eastern Beijing Plain by InSAR Time Series and Wavelet Transforms

et al. 2018

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Land subsidence is the disaster phenomenon of environmental geology with regionally surface altitude lowering caused by the natural or man-made factors. Beijing, the capital city of China, has suffered from land subsidence since the 1950s, and extreme groundwater extraction has led to subsidence rates of more than 100 mm/year. In this study, we employ two SAR datasets acquired by Envisat and TerraSAR-X satellites to investigate the surface deformation in Beijing Plain from 2003 to 2013 based on the multi-temporal InSAR technique. Furthermore, we also use observation wells to provide in situ hydraulic head levels to perform the evolution of land subsidence and spatial-temporal changes of groundwater level. Then, we analyze the accumulated displacement and hydraulic head level time series using continuous wavelet transform to separate periodic signal components. Finally, cross wavelet transform (XWT) and wavelet transform coherence (WTC) are implemented to analyze the relationship between the accumulated displacement and hydraulic head level time series. The results show that the subsidence centers in the northern Beijing Plain is spatially consistent with the groundwater drop funnels. According to the analysis of well based results located in different areas, the long-term groundwater exploitation in the northern subsidence area has led to the continuous decline of the water level, resulting in the inelastic and permanent compaction, while for the monitoring wells located outside the subsidence area, the subsidence time series show obvious elastic deformation characteristics (seasonal characteristics) as the groundwater level changes. Moreover, according to the wavelet transformation, the land subsidence time series at monitoring well site lags several months behind the groundwater level change.

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Section: Wavelet Transform For Time-series Analysismentioning

confidence: 99%

Regional Land Subsidence Analysis in Eastern Beijing Plain by InSAR Time Series and Wavelet Transforms

et al. 2018

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“…Lack of proper water recharging of wells and irregular water withdrawal are two main factors of aquifer system compaction in Iran (Dehghani et al 2009;Motagh et al 2008). Although, seasonal aquifer recharge in NW Iran is higher than the rest of Central Iran, the NW has undergone subsidence due to excessive ground water extraction over the last decades (Sedighi et al 2010 andMoghtased-Azar et al 2012). There are probably hundreds of illegal deep wells used mainly for agricultural purposes in the region.…”

Section: Ground Water and Watershed Transformmentioning

confidence: 99%

Characterization of land subsidence in Tabriz basin (NW Iran) using InSAR and watershed analyses

Karimzadeh

2015

Acta Geod Geophys

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Iran as a semi-arid and arid country has a serious water challenge in the recent decades. While water demand is increasing, as a consequence, land subsidence due to excessive water extraction is happening in major basins of the country. Recently the land subsidence has been proposed as an environmental problem in the country and thus important projects on this matter have been conducted. For example several basins in the country have been studied using SAR data and their result had a great deal on water management section. This paper studies the large-scale immature land subsidence in the Tabriz basin (NW Iran) using the permanent scatterer synthetic aperture radar interferometry technique with the small baseline InSAR approach and watershed analysis. InSAR time series analysis of 17 Envisat advanced SAR images between 2003 and 2010 reveals three oval-shaped regions of subsidence. The recognized water wells in the study area are categorized into two groups (sub-basin 1 and 2) based on watershed analysis in the TB and are compared with InSAR results. InSAR time series from Kriging interpolation method are also compared with GPS time series of permanent TABZ station which suggests that the land subsidence only is growing in the basin far away from the Tabriz city.

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“…Coefficients c and d describe the annual periodic motion, while e and f describe semi-annual motion. The next term corrects for any numbers (n j ) of offsets with magnitudes g i and epochs T g j [40]. The error term is a linear combination of a sequence of uncorrelated unit-variance random variables α(t i ) and a coloured noise sequence…”

Section: Maximum Likelihood Estimation Methods (Mle)mentioning

confidence: 99%

High-order Ionospheric Effects on GPS Coordinate Time Series

Jiang¹,

Deng²,

Li³

2015

Satellite Positioning - Methods, Models and Applications

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Investigation of correlation of the variations in land subsidence (detected by continuous GPS measurements) and methodological data in the surrounding areas of Lake Urmia

Cited by 10 publications

References 29 publications

Regional Land Subsidence Analysis in Eastern Beijing Plain by InSAR Time Series and Wavelet Transforms

Regional Land Subsidence Analysis in Eastern Beijing Plain by InSAR Time Series and Wavelet Transforms

Characterization of land subsidence in Tabriz basin (NW Iran) using InSAR and watershed analyses

High-order Ionospheric Effects on GPS Coordinate Time Series

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