scholarly journals Characterization of Irreversible Land Subsidence in the Yazd-Ardakan Plain, Iran from 2003-2020 InSAR Time Series

2021 ◽  
Author(s):  
Sayyed Mohammad Javad Mirzadeh ◽  
Shuanggen Jin ◽  
Esmaeel Parizi ◽  
Estelle Chaussard ◽  
Roland Burgmann ◽  
...  
Keyword(s):  
Time Series ◽  
Land Subsidence

Characterization of Irreversible Land Subsidence in the Yazd‐Ardakan Plain, Iran from 2003‐2020 InSAR Time Series

2021 ◽  
Author(s):  
Sayyed Mohammad Javad Mirzadeh ◽  
Shuanggen Jin ◽  
Esmaeel Parizi ◽  
Estelle Chaussard ◽  
Roland Bürgmann ◽  
...  
Keyword(s):  
Time Series ◽  
Land Subsidence

Optimal design of an hydrogeophysical monitoring system of compacting volcanic aquifers (Tenerife Island)

2021 ◽  
Author(s):  
Pablo J. Gonzalez ◽  
Maria Charco ◽  
Antonio Eff-Darwich ◽  
Anthony Lamur ◽  
Rayco Marrero ◽  
...  
Keyword(s):  
Time Series ◽  
Network Design ◽  
Water Table ◽  
Land Subsidence ◽  
Penalty Function ◽  
Surface Deformation ◽  
Low Rank ◽  
Tenerife Island ◽  
Compaction Processes

<p>Groundwater in volcanic islands is usually the main source of freshwater, and it is essential for sustainable development. In Tenerife Island, groundwater extraction occurs by drilling horizontal water tunnels, called water galleries, as well as numerous coastal wells. Since around 1900, but especially since the 1960s, hundreds of water tunnels have been drilled for agriculture and freshwater supply. This has resulted in a sustained extraction of groundwater larger than the natural recharge, leading to a general water table decline, locally up to 200 m of down drop. Since 2000, satellite radar interferometry (InSAR) applied to measure surface deformation has located several subsidence bowls (e.g., Fernandez et al., 2009). The localized surface deformation patterns have been correlated with water table changes and hence aquifer compaction. However, no further investigations have been carried out to confirm which characteristics (chemical composition, texture, porous network, alterations, etc.) of the volcanic materials can control compaction process, and to which extent porous volcanic units, the most abundant material in Tenerife, can compact to explain the observed surface deformation. This lack of knowledge might affect the effectiveness of water management policies.</p><p>To investigate the compaction processes affecting the volcanic aquifer, we propose to set up a passive hydrogeophysical monitoring network composed of geodetic and seismological instruments. However, considering logistic constrains it is desirable to have as low as possible number of observation sites, whist maximizing the detection and characterization of the aquifer dynamics. Here, we explore different network configurations to maximize the spatial and temporal characterization of the compaction processes using machine learning methods (low-rank matrix techniques). We pose the network design as an optimization process with the aim to parsimoniously have as fewer as possible ground station sites, and have a low error on reconstructing spatiotemporal land subsidence observations. Land subsidence rates were estimated using Sentinel-1 radar interferometric observations from October 2014 to December 2020. This method allows for an optimal network configuration, with respect to the dual penalty function, which facilitate the decision making. Nevertheless, this type of network design should be regarded as proposals because some station site conditions are a priori unknown. Although, one could modify the penalty function to optimize the network considering additional types of information, e.g., geological materials, groundwater table time series, etc.</p><p>Fernandez, J., et al. (2009), Gravity-driven deformation of Tenerife measured by InSAR time series analysis, Geophys. Res. Lett., 36, L04306, doi:10.1029/2008GL036920.</p>

The Comparison of Land Subsidence between East and West Side of Bangkok, Thailand

2020 ◽  
Vol 17 (3) ◽  
pp. 1
Author(s):  
Angkana Pumpuang ◽  
Anuphao Aobpaet
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Time Series Data ◽  
Series Data ◽  
Industrial Estates ◽  
Vertical Displacements ◽  
Land Deformation ◽  
Extensive Farming ◽  
Chao Phraya River ◽  
Set Up

The land deformation in line of sight (LOS) direction can be measured using time series InSAR. InSAR can successfully measure land subsidence based on LOS in many big cities, including the eastern and western regions of Bangkok which is separated by Chao Phraya River. There are differences in prosperity between both sides due to human activities, land use, and land cover. This study focuses on the land subsidence difference between the western and eastern regions of Bangkok and the most possible cause affecting the land subsidence rates. The Radarsat-2 single look complex (SLC) was used to set up the time series data for long term monitoring. To generate interferograms, StaMPS for Time Series InSAR processing was applied by using the PSI algorithm in DORIS software. It was found that the subsidence was more to the eastern regions of Bangkok where the vertical displacements were +0.461 millimetres and -0.919 millimetres on the western and the eastern side respectively. The districts of Nong Chok, Lat Krabang, and Khlong Samwa have the most extensive farming area in eastern Bangkok. Besides, there were also three major industrial estates located in eastern Bangkok like Lat Krabang, Anya Thani and Bang Chan Industrial Estate. By the assumption of water demand, there were forty-eight wells and three wells found in the eastern and western part respectively. The number of groundwater wells shows that eastern Bangkok has the demand for water over the west, and the pumping of groundwater is a significant factor that causes land subsidence in the area.Keywords: Subsidence, InSAR, Radarsat-2, Bangkok

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

2012 ◽  
Vol 19 (6) ◽  
pp. 675-683 ◽  
Author(s):  
K. Moghtased-Azar ◽  
A. Mirzaei ◽  
H. R. Nankali ◽  
F. Tavakoli
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Salt Lake ◽  
Linear Trend ◽  
Groundwater Resources ◽  
Time Interval ◽  
Gps Measurements ◽  
Lake Urmia ◽  
North West ◽  
Continuous Gps

Abstract. Lake Urmia, a salt lake in the north-west of Iran, plays a valuable role in the environment, wildlife and economy of Iran and the region, but now faces great challenges for survival. The Lake is in immediate and great danger and is rapidly going to become barren desert. As a result, the increasing demands upon groundwater resources due to expanding metropolitan and agricultural areas are a serious challenge in the surrounding regions of Lake Urmia. The continuous GPS measurements around the lake illustrate significant subsidence rate between 2005 and 2009. The objective of this study was to detect and specify the non-linear correlation of land subsidence and temperature activities in the region from 2005 to 2009. For this purpose, the cross wavelet transform (XWT) was carried out between the two types of time series, namely vertical components of GPS measurements and daily temperature time series. The significant common patterns are illustrated in the high period bands from 180–218 days band (~6–7 months) from September 2007 to February 2009. Consequently, the satellite altimetry data confirmed that the maximum rate of linear trend of water variation in the lake from 2005 to 2009, is associated with time interval from September 2007 to February 2009. This event was detected by XWT as a critical interval to be holding the strong correlation between the land subsidence phenomena and surface temperature. Eventually the analysis can be used for modeling and prediction purposes and probably stave off the damage from subsidence phenomena.

Characterization of Epileptic EEG Time Series (I): Gabor Transform and Nonlinear Dynamics Methods

1997 ◽  
pp. 179-226 ◽  
Author(s):  
Susana Blanco ◽  
Silvia Kochen ◽  
Rodrigo Quian Quiroga ◽  
Luis Riquelme ◽  
Osvaldo A. Rosso ◽  
...  
Keyword(s):  
Nonlinear Dynamics ◽  
Time Series ◽  
Gabor Transform

Characterization of Time Series Data

2017 ◽  
pp. 211-230
Author(s):  
W. Kulp Christopher ◽  
J. Niskala Brandon
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Series Data
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