Advancing water resource assessment with InSAR data and subsidence models
Second International Meeting for Applied Geoscience & Energy(2022)
Abstract
PreviousNext You have accessSecond International Meeting for Applied Geoscience & EnergyAdvancing water resource assessment with InSAR data and subsidence modelsAuthors: Ryan SmithRyan SmithMissouri University of Science and TechnologySearch for more papers by this authorhttps://doi.org/10.1190/image2022-3752562.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractOver the past three decades, Interferometric Synthetic Aperture Radar (InSAR) has grown from a tool for monitoring earthquakes and other massive signature deformation events to tracking the subtle, slow deformation processes associated with changes in groundwater storage. Improvements in time-series processing and noise reduction, as well as improved models of deformation, have enabled this advancement. InSAR has proven to be a valuable tool for characterizing elastic deformation in regions experiencing little long-term storage loss, as well as inelastic deformation in over-stressed aquifers.Keywords: InSAR, groundwater, subsidencePermalink: https://doi.org/10.1190/image2022-3752562.1FiguresReferencesRelatedDetails Second International Meeting for Applied Geoscience & EnergyISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2022 Pages: 3694 publication data© 2022 Published in electronic format with permission by the Society of Exploration Geophysicists and the American Association of Petroleum GeologistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 15 Aug 2022 CITATION INFORMATION Ryan Smith, (2022), "Advancing water resource assessment with InSAR data and subsidence models," SEG Technical Program Expanded Abstracts : 3033-3035. https://doi.org/10.1190/image2022-3752562.1 Plain-Language Summary KeywordsInSARgroundwatersubsidencePDF DownloadLoading ...
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water resource assessment,insar data,subsidence models
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