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Widespread extent of irrecoverable aquifer depletion revealed by country-wide analysis of land surface subsidence hazard in Iran, 2014–2022, using two component Sentinel-1 InSAR time series
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  • Jessica A. Payne,
  • Andrew Robert Watson,
  • Yasser Maghsoudi,
  • Susanna K Ebmeier,
  • Richard Rigby,
  • Milan Lazecky,
  • Mark Thomas,
  • John Ross Elliott
Jessica A. Payne
COMET, University of Leeds

Corresponding Author:[email protected]

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Andrew Robert Watson
SatSense
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Yasser Maghsoudi
School of Earth and Environmental Sciences, University of Exeter
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Susanna K Ebmeier
University of Leeds
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Richard Rigby
University of Leeds
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Milan Lazecky
University of Leeds
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Mark Thomas
University of Leeds
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John Ross Elliott
University of Leeds
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Abstract

Ongoing depletion of Iran’s groundwater, driven by human extraction, has contributed to 108 incidences of basin-scale land-surface subsidence covering 29,600 km² (>10 mm/yr, 1.8 %) of the country, 75 % of which correlates with agriculture. We find Karaj city, neighbouring Iran’s capital Tehran, is exposed to the steepest surface velocity gradients (angular distortion, β) caused by differential subsidence rates, with 23,000 people exposed to ‘high’ subsidence induced hazard. We further use these velocity gradients to aid identification of structural and geological controls on surface velocities of seven of Iran’s most populated cities, identifying potentially unmapped tectonic faults. We demonstrate that most of Iran’s subsidence is permanent (inelastic), with the spatial pattern of the proportion of inelastic deformation potentially depending on geology. During a recent, severe regional drought (2020–2023) we demonstrate the control of precipitation on the elastic, recoverable subsidence deformation magnitude with the elastic to inelastic deformation ratio falling from 41–44 % pre-drought to 31–36 % post-drought. We use automatically processed short baseline networks of Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) data, 2014–2022, to generate and estimate these ground displacements through time. We correct for atmospheric noise using weather model data and perform time series analysis in the satellite line-of-sight direction, serving this data through an open-access online portal. For each subsidence region, we decompose line-of-sight velocities into 100 m resolution vertical and horizontal (east-west) surface velocity fields. We use temporal Independent Component Analysis to constrain automatically and manually the inelastic and elastic components of subsidence, respectively.
30 Sep 2024Submitted to ESS Open Archive
30 Sep 2024Published in ESS Open Archive