Multi-temporal InSAR evidence of ground subsidence induced by groundwater withdrawal: the Montellano aquifer (SW Spain)

Ruíz-Constán, Ana; Ruiz-Armenteros, Antonio M.; Lamas‐Fernández, Francisco; Martos-Rosillo, Sergio; Delgado, Jorge; Bekaert, David; Sousa, Joaquim J.; Gil, A. J.; Cuenca, Miguel Caro; Hanssen, Ramon F.; Galindo-Zaldı́var, Jesús; Galdeano, Carlos Sanz de

doi:10.1007/s12665-015-5051-x

Cited by 17 publications

(6 citation statements)

References 38 publications

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“…The use of multi‐temporal SAR interferometry has made a breakthrough in the spatial and temporal monitoring of surface vertical displacements (natural or anthropogenic) over wide areas, at a higher resolution and with a lower cost than other conventional techniques (Amelung et al , ; Tomás et al , ). This methodology has been applied to diverse geological contexts usually interconnected with human activity or human settlements such as: seismicity (Funning et al , ; Peyret et al , ; Bell et al , ); overexploitation of aquifers (Tomás et al , ; Boni et al ., ; Ruiz‐Constán et al , ); oil extraction (Zhang et al , ); delta dynamics (Mazzotti et al ., ; Higgins et al , ); or urbanization (Stramondo et al , ) among others.…”

Section: Introductionmentioning

confidence: 99%

Factors determining subsidence in urbanized floodplains: evidence from MT‐InSAR in Seville (southern Spain)

Ruíz-Constán

Ruiz-Armenteros

Galindo-Zaldı́var

et al. 2017

Earth Surf Processes Landf

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Major rivers have traditionally been linked with important human settlements throughout history. The growth of cities over recent river deposits makes necessary the use of multidisciplinary approaches to characterize the evolution of drainage networks in urbanized areas. Since under‐consolidated fluvial sediments are especially sensitive to compaction, their spatial distribution, thickness, and mechanical behavior must be studied. Here, we report on subsidence in the city of Seville (Southern Spain) between 2003 and 2010, through the analysis of the results obtained with the Multi‐Temporal InSAR (MT‐InSAR) technique. In addition, the temporal evolution of the subsidence is correlated with the rainfall, the river water column and the piezometric level. Finally, we characterize the geotechnical parameters of the fluvial sediments and calculate the theoretical settlement in the most representative sectors. Deformation maps clearly indicate that the spatial extent of subsidence is controlled by the distribution of under‐consolidated fine‐grained fluvial sediments at heights comprised in the range of river level variation. This is clearly evident at the western margin of the river and the surroundings of its tributaries, and differs from rainfall results as consequence of the anthropic regulation of the river. On the other hand, this influence is not detected at the eastern margin due to the shallow presence of coarse‐grain consolidated sediments of different terrace levels. The derived results prove valuable for implementing urban planning strategies, and the InSAR technique can therefore be considered as a complementary tool to help unravel the subsidence tendency of cities located over under‐consolidated fluvial deposits. Copyright © 2017 John Wiley & Sons, Ltd.

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Section: Introductionmentioning

confidence: 99%

Factors determining subsidence in urbanized floodplains: evidence from MT‐InSAR in Seville (southern Spain)

Ruíz-Constán

Ruiz-Armenteros

Galindo-Zaldı́var

et al. 2017

Earth Surf Processes Landf

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“…Mathematical morphology processing of edge features of INSAR images can effectively extract the edge features of agricultural waters. On this basis, the correlation between the pollution of agricultural waters and the ground spectrum is studied so as to effectively monitor and schedule the pollution disaster of agricultural waters [20]. The following methods are used to verify it.…”

Section: Monitoring and Scheduling Of Pollution Disaster In Agricultumentioning

confidence: 99%

Monitoring and scheduling of pollution disaster in agricultural waters based on INSAR

Liu¹,

Zhang²,

Li³

et al. 2019

Desalination and Water Treatment

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Objective: To improve the quality of monitoring image in agricultural waters by effective methods, to obtain information of the pollution disaster in agricultural waters in time, to provide the necessary data for the disaster management and decision making of agricultural waters, and to promote the development of agricultural economy in this region. Methods: by using the monitoring and scheduling method for pollution disaster in agricultural waters based on INSAR, comprehensive and accurate monitoring of pollution disaster in agricultural waters can be conducted. SRTM3 DEM is used to eliminate baseline error in INSAR interferogram. According to different scattering characteristics of different ground objects in the INSAR image, the gray value is different, and a two-dimensional gray histogram is built to preprocess the INSAR image so as to avoid the false alarm in the detection of the edge of the agricultural waters. Through the monitoring method of ground wave spectrum, the two directions reflection ratio factor of waterbody is measured, and the correlation between the pollution of agricultural waters and the ground spectrum is studied, and the monitoring and scheduling of the pollution disaster in the agricultural waters are effectively carried out. Results: there is a significant correlation between the pollution in agricultural waters and the satellite reflectance spectrum on the ground, with a correlation coefficient of about 0.8. The false area which is not connected with the agricultural waters of the preprocessed INSAR image is almost completely removed by using the proposed method. The boundary of the extracted water area is well matched with the boundary of the actual image. The false alarm rate and the leakage rate for processing the agricultural waters image under different scenes are all very low, and the accuracy of the INSAR image extraction and calculation efficiency are better and with good robustness. The proposed method can reduce the strong scattering point and the speckle noise of the building, and effectively restrain the edge of the buildings, such as the buildings around the agricultural waters. The information of disaster change in agricultural waters obtained by the proposed method is relatively accurate. Conclusion: the proposed method can extract the image of agricultural waters and obtain the information of the pollution disaster in agricultural waters in real time and accurately, so as to realize the effective monitoring and scheduling of the pollution disaster in the agricultural waters.

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“…Therefore, surface subsidence monitoring is particularly important. Traditional subsidence monitoring is mainly based on leveling and GNSS measurement [6,7], and these technologies are mainly based on the target of monitoring points and lack certain timeliness in the observation process [8,9]. For the monitoring of large-scale subsidence in some Chinese cities, the aforementioned technologies have the disadvantages of low spatial resolution, long period, and high cost [10,11].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Inversion and Mechanism Analysis of Surface Subsidence in Shanghai Area Based on Time-Series InSAR

Zhou

Ren

et al. 2021

Applied Sciences

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Abnormal surface subsidence has become a widespread geological problem being faced by cities. As a first-tier city in the world, there are problems such as unclear analysis of subsidence mechanism. Therefore, the monitoring of the Shanghai surface is particularly important. In this paper, the Sentinel-1A satellite SAR image data of 36 scenes covering Shanghai area from January 2018 to March 2020 were processed on the basis of time-series interferometry synthetic aperture radar technique. The subsidence rate field and accumulated surface subsidence in Shanghai area during the study period were obtained, and the spatial–temporal distribution characteristics of subsidence in the study area were discussed and analyzed from many different aspects. Moreover, the correlation between regional subsidence and geological structure, precipitation, urbanization, and other influencing factors were analyzed and established. Results show that the non-uniform subsidence in Shanghai area is clear, and those of the districts of eastern Songjiang, southern Jinshan, and Fengxian are more serious with a maximum subsidence rate of -26.2 mm/yr. After analyzing the causes of subsidence, the special foundation of soft soil in Shanghai area is determined as the main reason for the subsidence, and the uneven subsidence is mainly caused by the over-exploitation of groundwater, human activities, and the subsidence of soil layer. Through comparative analysis, factors, such as rainfall, groundwater, and urbanization process, have high correlation with surface subsidence.

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Multi-temporal InSAR evidence of ground subsidence induced by groundwater withdrawal: the Montellano aquifer (SW Spain)

Cited by 17 publications

References 38 publications

Factors determining subsidence in urbanized floodplains: evidence from MT‐InSAR in Seville (southern Spain)

Factors determining subsidence in urbanized floodplains: evidence from MT‐InSAR in Seville (southern Spain)

Monitoring and scheduling of pollution disaster in agricultural waters based on INSAR

Spatiotemporal Inversion and Mechanism Analysis of Surface Subsidence in Shanghai Area Based on Time-Series InSAR

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