Land subsidence in central Mexico detected by ALOS InSAR time-series

Estelle Chaussard, Shimon Wdowinski, Enrique Cabral-Cano, Falk Amelung

Research output: Contribution to journalArticle

176 Scopus citations

Abstract

Massive groundwater extraction is common throughout Mexico and is well known to result in land subsidence. However, most land subsidence surveys focus on one single city, mainly Mexico City, and thus fail to reveal the regional extent of the problem. Here we use 2007-2011 Interferometric Synthetic Aperture Radar (InSAR) time-series analysis of ALOS data to resolve land subsidence in the entire central Mexico region. We identify land subsidence in 21 areas, including 17 cities. Linear vertical rates over 30. cm/yr are observed in Mexico City, while in the other locations rates of 5-10. cm/yr are detected. We define 3 main categories of subsidence using the averaged velocity maps in conjunction with previously published structural, surface geology, and land use mapping: (1) rapid, large-scale subsidence, (2) rapid, local-scale subsidence, and (3) slow, patchy subsidence. The correlation between subsidence and land use confirms that groundwater extraction mainly for agricultural and urban activities is the main cause of land subsidence. We observe that the boundaries of the subsiding areas are typically characterized by high velocity gradients often coinciding with pre-existing faults, motion on these faults being driven by water extraction rather than by tectonic activity. Regional surveys of this type are necessary to understand the spatial and temporal evolution of land subsidence, to constrain the distribution and connectivity of water-bearing units, and ultimately to reach better hazard mitigation plans.

Original languageEnglish (US)
Pages (from-to)94-106
Number of pages13
JournalRemote Sensing of Environment
Volume140
DOIs
StatePublished - Jan 2014

Keywords

  • Faults
  • Groundwater
  • InSAR
  • Land subsidence
  • Mexico
  • SBAS time-series
  • Tectonics

ASJC Scopus subject areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences

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