Land subsidence in major cities of Central Mexico: Interpreting InSAR-derived land subsidence mapping with hydrogeological data

Castellazzi, Pascal; Arroyo-Domínguez, Norma; Martel, Richard; Calderhead, Angus I.; Normand, Jonathan C.L.; Gárfias, Jaime; Rivera, Alfonso

doi:10.1016/j.jag.2015.12.002

Cited by 124 publications

(93 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The most comprehensive use of InSAR in hydrogeology is its integration in flow model calibration (e.g., Hoffmann et al ; Yan and Burbey ; Siade et al ). More recently, InSAR‐derived ground displacement mapping has been used to (1) estimate storage change within a well‐known lithological context (e.g., Chaussard et al ); (2) improve lithological knowledge and define specific geological structures such as fractures (e.g., Hernandez‐Marin and Burbey ; Xu et al ; Zhang et al ; Castellazzi et al ); (3) predict future land subsidence rates (e.g., Calderhead et al ); and (4) infer changes in hydraulic head after a calibration period relating ground and groundwater levels (Reeves et al ; Chaussard et al ).…”

Section: Detection Of Groundwater Depletionmentioning

confidence: 99%

Assessing Groundwater Depletion and Dynamics Using GRACE and InSAR: Potential and Limitations

Castellazzi¹,

et al. 2016

Self Cite

View full text Add to dashboard Cite

In the last decade, remote sensing of the temporal variation of ground level and gravity has improved our understanding of groundwater dynamics and storage. Mass changes are measured by GRACE (Gravity Recovery and Climate Experiment) satellites, whereas ground deformation is measured by processing synthetic aperture radar satellites data using the InSAR (Interferometry of Synthetic Aperture Radar) techniques. Both methods are complementary and offer different sensitivities to aquifer system processes. GRACE is sensitive to mass changes over large spatial scales (more than 100,000 km 2 ). As such, it fails in providing groundwater storage change estimates at local or regional scales relevant to most aquifer systems, and at which most groundwater management schemes are applied. However, InSAR measures ground displacement due to aquifer response to fluid-pressure changes. InSAR applications to groundwater depletion assessments are limited to aquifer systems susceptible to measurable deformation. Furthermore, the inversion of InSAR-derived displacement maps into volume of depleted groundwater storage (both reversible and largely irreversible) is confounded by vertical and horizontal variability of sediment compressibility. During the last decade, both techniques have shown increasing interest in the scientific community to complement available in situ observations where they are insufficient. In this review, we present the theoretical and conceptual bases of each method, and present idealized scenarios to highlight the potential benefits and challenges of combining these techniques to remotely assess groundwater storage changes and other aspects of the dynamics of aquifer systems.

show abstract

Section: Detection Of Groundwater Depletionmentioning

confidence: 99%

Assessing Groundwater Depletion and Dynamics Using GRACE and InSAR: Potential and Limitations

Castellazzi¹,

et al. 2016

Self Cite

View full text Add to dashboard Cite

show abstract

“…Aside from the above-mentioned TS-InSAR methods, other approaches, e.g., the Temporally Coherent Point InSAR (TCPInSAR) [26], the Quasi-PS (QPS) [27], and the Intermittent SBAS (ISBAS) [28], were proposed for different monitoring situations. These TS-InSAR methods have been widely applied in urban surface subsidence monitoring in Beijing [2,29], Mexico [30], Hanoi [31], Shanghai [32,33], and Jinan [34].…”

Section: Introductionmentioning

confidence: 99%

Wuhan Surface Subsidence Analysis in 2015–2016 Based on Sentinel-1A Data by SBAS-InSAR

et al. 2017

View full text Add to dashboard Cite

Abstract:The Terrain Observation with Progressive Scans (TOPS) acquisition mode of Sentinel-1A provides a wide coverage per acquisition and features a repeat cycle of 12 days, making this acquisition mode attractive for surface subsidence monitoring. A few studies have analyzed wide-coverage surface subsidence of Wuhan based on Sentinel-1A data. In this study, we investigated wide-area surface subsidence characteristics in Wuhan using 15 Sentinel-1A TOPS Synthetic Aperture Radar (SAR) images acquired from 11 April 2015 to 29 April 2016 with the Small Baseline Subset Interferometric SAR (SBAS InSAR) technique. The Sentinel-1A SBAS InSAR results were validated by 110 leveling points at an accuracy of 6 mm/year. Based on the verified SBAS InSAR results, prominent uneven subsidence patterns were identified in Wuhan. Specifically, annual average subsidence rates ranged from −82 mm/year to 18 mm/year in Wuhan, and maximum subsidence rate was detected in Houhu areas. Surface subsidence time series presented nonlinear subsidence with pronounced seasonal variations. Comparative analysis of surface subsidence and influencing factors (i.e., urban construction, precipitation, industrial development, carbonate karstification and water level changes in Yangtze River) indicated a relatively high spatial correlation between locations of subsidence bowl and those of engineering construction and industrial areas. Seasonal variations in subsidence were correlated with water level changes and precipitation. Surface subsidence in Wuhan was mainly attributed to anthropogenic activities, compressibility of soil layer, carbonate karstification, and groundwater overexploitation. Finally, the spatial-temporal characteristics of wide-area surface subsidence and the relationship between surface subsidence and influencing factors in Wuhan were determined.

show abstract

“…In particular, several works have focused on the application of such DInSAR techniques to the detection and monitoring of land subsidence induced by groundwater extraction in many regions of the world. Chaussard et al [28] and Castellazzi et al [29] used DInSAR deformation time-series of ALOS and RADARSAT-2 data, respectively, to study the land subsidence caused by massive groundwater over pumping in the entire central Mexico. Dehghani et al [30] exploited both descending and ascending ENVISAT datasets to measure the magnitude of groundwater related subsidence in the Tehran basin, Iran.…”

Section: Introductionmentioning

confidence: 99%

DInSAR-Based Detection of Land Subsidence and Correlation with Groundwater Depletion in Konya Plain, Turkey

et al. 2017

View full text Add to dashboard Cite

Abstract:In areas where groundwater overexploitation occurs, land subsidence triggered by aquifer compaction is observed, resulting in high socio-economic impacts for the affected communities. In this paper, we focus on the Konya region, one of the leading economic centers in the agricultural and industrial sectors in Turkey. We present a multi-source data approach aimed at investigating the complex and fragile environment of this area which is heavily affected by groundwater drawdown and ground subsidence. In particular, in order to analyze the spatial and temporal pattern of the subsidence process we use the Small BAseline Subset DInSAR technique to process two datasets of ENVISAT SAR images spanning the 2002-2010 period. The produced ground deformation maps and associated time-series allow us to detect a wide land subsidence extending for about 1200 km 2 and measure vertical displacements reaching up to 10 cm in the observed time interval. DInSAR results, complemented with climatic, stratigraphic and piezometric data as well as with land-cover changes information, allow us to give more insights on the impact of climate changes and human activities on groundwater resources depletion and land subsidence.

show abstract

Land subsidence in major cities of Central Mexico: Interpreting InSAR-derived land subsidence mapping with hydrogeological data

Cited by 124 publications

References 28 publications

Assessing Groundwater Depletion and Dynamics Using GRACE and InSAR: Potential and Limitations

Assessing Groundwater Depletion and Dynamics Using GRACE and InSAR: Potential and Limitations

Wuhan Surface Subsidence Analysis in 2015–2016 Based on Sentinel-1A Data by SBAS-InSAR

DInSAR-Based Detection of Land Subsidence and Correlation with Groundwater Depletion in Konya Plain, Turkey

Contact Info

Product

Resources

About