Satellite InSAR survey of structurally-controlled land subsidence due to groundwater exploitation in the Aguascalientes Valley, Mexico

Several major cities in central Mexico suffer from aquifer depletion and land subsidence driven by overexploitation of groundwater resources to address increasing water demands for domestic, industrial and agricultural use. Ground settlement often combines with surface faulting, fracturing and cracking, causing damage to urban infrastructure, including private properties and public buildings, as well as transport infrastructure and utility networks. These impacts are very common and induce significant economic loss, thus representing a key topic of concern for inhabitants, authorities and stakeholders. This work provides an Interferometric Synthetic Aperture Radar (InSAR) 2014-2020 survey based on parallel processing of Sentinel-1 IW big data stacks within ESA&#8217;s Geohazards Exploitation Platform (GEP), using hosted on-demand services based on multi-temporal InSAR methods including Small BAseline Subset (SBAS) and Persistent Scatterers Interferometry (PSI). Surface faulting hazard is constrained based on differential settlement observations and the estimation of angular distortions that are produced on urban structures. The assessment of the E-W deformation field and computation of horizontal strain also allows the identification of hogging (tensile strain or extension) and sagging (compression) zones, where building cracks are more likely to develop at the highest and lowest elevations, respectively. Sentinel-1 observations agree with in-situ observations, static GPS surveying and continuous GNSS monitoring data. The distribution of field surveyed faults and fissures compared with maps of angular distortions and strain also enables the identification of areas with potentially yet-unmapped and incipient ground discontinuities. A methodology to embed such information into the process of surface faulting risk assessment for urban infrastructure is proposed and demonstrated for the Metropolitan Area of Mexico City [1], one of the fastest sinking cities globally (up to 40 cm/year subsidence rates), and the state of Aguascalientes [2], where a structurally-controlled fast subsidence process (over 10 cm/year rates) affects the namesake valley and capital city. The value of this research lies in the demonstration that InSAR data and their derived parameters are not only essential to constrain the deformation processes, but can also serve as a direct input into risk assessment to quantify (at least, as a lower bound) the percentage of properties and population at risk, and monitor how this percentage may change as land subsidence evolves.[1] Cigna F., Tapete D. 2021. Present-day land subsidence rates, surface faulting hazard and risk in Mexico City with 2014&#8211;2020 Sentinel-1 IW InSAR. Remote Sens. Environ. 253, 1-19, doi:10.1016/j.rse.2020.112161[2] Cigna F., Tapete D. 2021. Satellite InSAR survey of structurally-controlled land subsidence due to groundwater exploitation in the Aguascalientes Valley, Mexico. Remote Sens. Environ. 254, 1-23, doi:10.1016/j.rse.2020.112254

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Ongoing research on the pumping-induced land deformation in the Aguascalientes Valley: an analysis of the recent data of vertical deformation, groundwater level variations and local seismicity

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-382-99-2020 ◽

2020 ◽

Vol 382 ◽

pp. 99-102

Author(s):

Martin Hernandez-Marin ◽

Ruben Esquivel-Ramirez ◽

Mario Eduardo Zermeño-De-Leon ◽

Lilia Guerrero-Martinez ◽

Jesus Pacheco-Martinez ◽

...

Keyword(s):

Land Subsidence ◽

Close Association ◽

Active Faults ◽

Vertical Deformation ◽

Ongoing Research ◽

Aquifer System ◽

Groundwater Levels ◽

Critical Information ◽

Aguascalientes Valley ◽

Low Magnitude

Abstract. In the Aguascalientes valley, middle Mexico, the demand of groundwater from the local aquifer system was suddenly increased after the late 1970s. Since then, several related problems have been occurring or become critical such as land subsidence, ground fissuring, and low-magnitude earthquakes. The most recent data of vertical deformation from PSInSAR, groundwater levels, and earthquakes, has provided critical information regarding the relationship amongst all these processes. In particular, that related to land subsidence, earth fissuring and seismicity. Regarding this, more satellite imagery and data from GPS stations are being revised as a possibility of a more generalized vertical deformation derived with low-magnitude seismicity. A particular seismic event recorded on 6 April 2019 has revealed critical information on the close association between vertical displacements occurred in active faults and low-magnitude seismic events.

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Land subsidence caused by groundwater exploitation in Suzhou City, China

Hydrogeology Journal ◽

10.1007/s10040-002-0225-5 ◽

2003 ◽

Vol 11 (2) ◽

pp. 275-287 ◽

Cited By ~ 70

Author(s):

Chongxi Chen ◽

Shunping Pei ◽

Jiu Jiao

Keyword(s):

Land Subsidence ◽

Groundwater Exploitation ◽

Suzhou City

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Study on compaction mechanism of overconsolidated soil and critical groundwater level in Cangzhou

E3S Web of Conferences ◽

10.1051/e3sconf/20197902010 ◽

2019 ◽

Vol 79 ◽

pp. 02010

Author(s):

Yunlong Wang ◽

Ye Chen ◽

Haipeng Guo ◽

Xisheng Zang

Keyword(s):

Stress Analysis ◽

Water Level ◽

Water Resource ◽

Land Subsidence ◽

Groundwater Level ◽

Groundwater Exploitation ◽

Groundwater Levels ◽

Good Consistency ◽

Long Time ◽

Groundwater Overexploitation

Cangzhou area is facing increasingly serious land subsidence problem caused by groundwater overexploitation during a long time. In order to make effectively use of water resource and to limit the development of subsidence, it is necessary to establish the warning critical water level, that is, the subsidence rate will increase significantly as the water level depths exceeds the critical groundwater levels. In this paper, the 3rd aquifer group, the main groundwater exploitation layer, has been taken as a research object. The critical water level is calculated by stress analysis, and then determined by the correlation between the monitoring data of groundwater levels and subsidence. The calculated results indicate good consistency.

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Multi-Scale and Multi-Dimensional Time Series InSAR Characterizing of Surface Deformation over Shandong Peninsula, China

Applied Sciences ◽

10.3390/app10072294 ◽

2020 ◽

Vol 10 (7) ◽

pp. 2294 ◽

Cited By ~ 2

Author(s):

Mimi Peng ◽

Chaoying Zhao ◽

Qin Zhang ◽

Zhong Lu ◽

Lin Bai ◽

...

Keyword(s):

Time Series ◽

Land Subsidence ◽

Surface Deformation ◽

Land Reclamation ◽

Yellow River ◽

Ground Deformation ◽

Shandong Peninsula ◽

Groundwater Exploitation ◽

Multi Scale ◽

The Yrd

Shandong peninsula, the largest peninsula of China, is prone to severe land subsidence hazards along the coastline. In this paper, we provide, for the first time, multi-scale and multi-dimensional time series deformation measurements of the entire Shandong peninsula with advanced time series Interferometric Synthetic Aperture Radar (InSAR) techniques. We derive the spatiotemporal evolutions of the land subsidence by integrating multi-track Sentinel-1A/B and RADARSAT-2 satellite images. InSAR measurements are cross validated by the independent deformation rate results generated from different SAR tracks, reaching a precision of less than 1.3 cm/a. Two-dimensional time series over the Yellow River Delta (YRD) from 2017 to 2019 are revealed by integrating time series InSAR measurements from both descending and ascending tracks. Land subsidence zones are mainly concentrated on the YRD. In total, twelve typical localized subsidence zones are identified in the cities of Dongying (up to 290 mm/a; brine and groundwater exploitation for industrial usage), Weifang (up to 170 mm/a; brine exploitation for industrial usage), Qingdao (up to 70 mm/a; aquaculture and land reclamation), Yantai (up to 50 mm/a; land reclamation) and Rizhao (up to 60 mm/a; land reclamation). The causal factors of localized ground deformation are discussed, encompassing groundwater and brine exploitation, aquaculture and land reclamation. Multi-scale surveys of spatiotemporal deformation evolution and mechanism analysis are critical to make decisions on underground fluid exploitation and land reclamation.

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Monitoring Land Subsidence in Wuhan City (China) using the SBAS-InSAR Method with Radarsat-2 Imagery Data

Sensors ◽

10.3390/s19030743 ◽

2019 ◽

Vol 19 (3) ◽

pp. 743 ◽

Cited By ~ 14

Author(s):

Yang Zhang ◽

Yaolin Liu ◽

Manqi Jin ◽

Ying Jing ◽

Yi Liu ◽

...

Keyword(s):

Land Subsidence ◽

Human Activities ◽

Hydrological Modeling ◽

Central China ◽

Natural Conditions ◽

Wuhan City ◽

Groundwater Exploitation ◽

Urban Construction ◽

Wide Range ◽

Sbas Insar

Wuhan city is the biggest city in central China and has suffered subsidence problems in recent years because of its rapid urban construction. However, longtime and wide range monitoring of land subsidence is lacking. The causes of subsidence also require further study, such as natural conditions and human activities. We use small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) method and high-resolution RADARSAT-2 images acquired between 2015 and 2018 to derive subsidence. The SBAS-InSAR results are validated by 56 leveling benchmarks where two readings of elevation were recorded. Two natural factors (carbonate rock and soft soils) and three human factors (groundwater exploitation, subway excavation and urban construction) are investigated for their relationships with land subsidence. Results show that four major areas of subsidence are detected and the subsidence rate varies from −51.56 to 27.80 millimeters per year (mm/yr) with an average of −0.03 mm/yr. More than 83.81% of persistent scattered (PS) points obtain a standard deviation of less than −6 mm/yr, and the difference between SBAS-InSAR method and leveling data is less than 5 mm/yr. Thus, we conclude that SBAS-InSAR method with Radarsat-2 data is reliable for longtime monitoring of land subsidence covering a large area in Wuhan city. In addition, land subsidence is caused by a combination of natural conditions and human activities. Natural conditions provide a basis for subsidence and make subsidence possible. Human activities are driving factors and make subsidence happen. Moreover, subsidence information could be used in disaster prevention, urban planning, and hydrological modeling.

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Land Subsidence Prediction Induced by Multiple Factors Using Machine Learning Method

Remote Sensing ◽

10.3390/rs12244044 ◽

2020 ◽

Vol 12 (24) ◽

pp. 4044

Author(s):

Liyuan Shi ◽

Huili Gong ◽

Beibei Chen ◽

Chaofan Zhou

Keyword(s):

Machine Learning ◽

Linear Regression ◽

Influencing Factors ◽

Land Subsidence ◽

Quaternary Deposit ◽

Groundwater Exploitation ◽

Level Change ◽

Multiple Factors ◽

Beijing Plain ◽

The Relationship

In the Beijing Plain, land subsidence is one of the most prominent geological problems, which is affected by multiple factors. Groundwater exploitation, thickness of the Quaternary deposit and urban development and construction are important factors affecting the formation and development of land subsidence. Here we choose groundwater level change, thickness of the Quaternary deposit and index-based built-up index (IBI) as influencing factors, and we use the influence factors to predict the subsidence amount in the Beijing Plain. The Sentinel-1 radar images and the persistent scatters interferometry (PSI) were adopted to obtain the information of land subsidence. By using Google Earth Engine platform and Landsat8 optical images, IBI was extracted. Groundwater level change and thickness of the Quaternary deposit were obtained from hydrogeological data. Machine learning algorithms Linear Regression and Principal Component Analysis (PCA) were used to investigate the relationship between land subsidence and influencing factors. Based on the results obtained by Linear Regression and PCA, a suitable machine learning algorithm was selected to predict the subsidence amount in the Beijing Plain in 2018 through influencing factors. In this study, we found that the maximum subsidence rate in the Beijing Plain had reached 115.96 mm/y from 2016 to 2018. The land subsidence was serious in eastern Chaoyang and northwestern Tongzhou. In addition, the area where thickness of the Quaternary deposit reached 150–200 m was prone to more serious land subsidence in the Beijing Plain. In groundwater exploitation, the second confined aquifer had the greatest impact on land subsidence. Through Linear Regression and PCA, we found that the relationship between land subsidence and influencing factors was nonlinear. XGBoost was feasible to predict subsidence amount. The prediction accuracy of XGBoost on the subsidence amount reached 0.9431, and the mean square error was controlled at 15.97. By using XGBoost to predict the subsidence amount, our research provides a new idea for land subsidence prediction.

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Understanding Land Subsidence Along the Coastal Areas of Guangdong, China, by Analyzing Multi-Track MTInSAR Data

Remote Sensing ◽

10.3390/rs12020299 ◽

2020 ◽

Vol 12 (2) ◽

pp. 299 ◽

Cited By ~ 1

Author(s):

Yanan Du ◽

Guangcai Feng ◽

Lin Liu ◽

Haiqiang Fu ◽

Xing Peng ◽

...

Keyword(s):

Land Subsidence ◽

Coastal Areas ◽

Alos Palsar ◽

Groundwater Exploitation ◽

Average Deformation ◽

Deformation Velocity ◽

Multi Temporal ◽

Small Baseline Subset ◽

Small Baseline ◽

The Stability

Coastal areas are usually densely populated, economically developed, ecologically dense, and subject to a phenomenon that is becoming increasingly serious, land subsidence. Land subsidence can accelerate the increase in relative sea level, lead to a series of potential hazards, and threaten the stability of the ecological environment and human lives. In this paper, we adopted two commonly used multi-temporal interferometric synthetic aperture radar (MTInSAR) techniques, Small baseline subset (SBAS) and Temporarily coherent point (TCP) InSAR, to monitor the land subsidence along the entire coastline of Guangdong Province. The long-wavelength L-band ALOS/PALSAR-1 dataset collected from 2007 to 2011 is used to generate the average deformation velocity and deformation time series. Linear subsidence rates over 150 mm/yr are observed in the Chaoshan Plain. The spatiotemporal characteristics are analyzed and then compared with land use and geology to infer potential causes of the land subsidence. The results show that (1) subsidence with notable rates (>20 mm/yr) mainly occurs in areas of aquaculture, followed by urban, agricultural, and forest areas, with percentages of 40.8%, 37.1%, 21.5%, and 0.6%, respectively; (2) subsidence is mainly concentrated in the compressible Holocene deposits, and clearly associated with the thickness of the deposits; and (3) groundwater exploitation for aquaculture and agricultural use outside city areas is probably the main cause of subsidence along these coastal areas.

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