Estimation of annual groundwater changes from InSAR-derived land subsidence

Muhammad Zeeshan Ali, Hone Jay Chu*, Tatas, Thomas J. Burbey

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Understanding the extent and quantity of groundwater drawdown is critical for developing a mitigation strategy for water management. This study illustrates that the data-driven model can be used for the spatial estimation of groundwater drawdown using interferometric synthetic aperture radar (InSAR)-based deformation data. Here, InSAR derived from Sentinel-1 imagery is used to estimate surface deformations in the Choshui river alluvial fan, Taiwan, between 2016 and 2018. Spatial regression (SR) is applied to estimate the annual groundwater drawdown with a calculated R-square of 0.96, which is shown to be superior to a nonspatial model. This study demonstrates the potential of the satellite-based groundwater drawdown map prediction using InSAR-derived land deformation. In predication, the SR model can reliably catch the patterns of annual predicted drawdown without requiring detailed groundwater observations.

Original languageEnglish
Pages (from-to)622-632
Number of pages11
JournalWater and Environment Journal
Volume36
Issue number4
DOIs
Publication statusPublished - Nov 2022

Keywords

  • InSAR deformation
  • annual groundwater drawdown
  • spatial regression

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