EGU21-16000, updated on 29 Oct 2021
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Improving global land subsidence analysis

Pablo Ezquerro1,4, Gerardo Herrera-García1,2,3, Roberto Tomás2,5, Marta Béjar-Pizarro1, Juan López-Vinielles1,6, Mauro Rossi7, Rosa M. Mateos1,3, Dora Carreón-Freyre2,8, John Lambert2,9, Pietro Teatini2,10, Enrique Cabral-Cano2,11, Gilles Erkens2,12,13, Devin Galloway2,14, Wei-Chia Hung2,15, Najeebullah Kakar2,16, Michelle Sneed2,17, Luigi Tosi2,18, Hanmei Wang2,19, and Shujun Ye2,20
Pablo Ezquerro et al.
  • 1Geohazards INSAR Laboratory and Modelling group, Instituto Geológico y Minero de España, Madrid, Spain.
  • 2Land Subsidence International Initiative (LASII), UNESCO, Paris, France.
  • 3Geological Surveys of Europe, Brussels, Belgium.
  • 4Escuela Técnica Superior de Ingenieros de Caminos, Canales y Puertos, Universidad Politécnica de Madrid, Madrid, Spain.
  • 5Departamento de Ingeniería Civil, Universidad de Alicante, Alicante, Spain.
  • 6HEMAV SL, Castelldefels, Barcelona, Spain.
  • 7Istituto di Ricerca per la Protezione Idrogeologica, Perugia, Italy.
  • 8Centro de Geociencias, Universidad Nacional Autónoma de México, Queretaro, Mexico.
  • 9Deltares, Delft, The Netherlands.
  • 10Department of Civil, Environmental and Architectural Engineering, University of Padova, Padova, Italy.
  • 11Departamento de Geomagnetismo y Exploración, Instituto de Geofísica, Universidad Nacional Autónoma de México, Mexico City, Mexico.
  • 12Deltares, Utrecht, The Netherlands.
  • 13Utrecht University, Utrecht, The Netherlands.
  • 14U.S.Geological Survey, Solsberry, IN, USA.
  • 15Department of Civil Engineering, National Chiao Tung University, Hsinchu, Taiwan.
  • 16Department of Geology, University of Balochistan, Quetta, Pakistan.
  • 17U.S.Geological Survey, Sacramento, CA, USA.
  • 18Institute of Geosciences and Earth Resources - National Research Council, Padova, Italy.
  • 19Shanghai Institute of Geological Survey, Shanghai, China.
  • 20Department of Hydrosciences, School of Earth Sciences and Engineering, Nanjing University, Nanjing, China

Land subsidence associated with groundwater withdrawal is often an underestimated geological hazard that may produce important damage to buildings and infrastructure, change flood risk in some areas, and cause loss of groundwater storage capacity. In the current framework of global climate change, the increasing agricultural and urban use of groundwater resources is a growing problem, especially in arid and semiarid areas. Because monitoring subsidence in these areas is important for management, but early detection is difficult due to slow displacement rates, we developed global groundwater induced land subsidence probability maps.  Global land subsidence probability was calculated by applying statistical methods to a set of susceptible geographical, environmental and geological properties based on known, documented subsidence affected areas. Highest values of subsidence probability are concentrated over flat areas composed of unconsolidated sediments, and in agricultural or urban areas subject to prolonged dry periods. Including water scarcity and groundwater use data resulted in an estimation of a proxy land subsidence hazard. Calculated probability does not imply that all the high value areas are currently incurring land subsidence, but it can alert policymakers and groundwater managers to areas that have potential exposure to subsidence hazards and warrant monitoring. The complete results of this work are published in Science Policy Forum section under the title “Mapping the global threat of land subsidence” DOI: 10.1126/science.abb8549

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