Estimation of annual groundwater changes from InSAR‐derived land subsidence. (23rd May 2022)

• Record Type: Journal Article
• Authors: Ali, Muhammad Zeeshan; Chu, Hone‐Jay; Tatas, ; Burbey, Thomas J.
• Is Part Of: Water and environment journal. Volume 36:Number 4(2022)
• Page Start: 622
• Page End: 632
• Publication Date: 2022-05-23
• Subjects: annual groundwater drawdown -- InSAR deformation -- spatial regression; Sewage -- Periodicals; Water-supply -- Periodicals; Environmental management -- Periodicals; Water-supply engineering -- Periodicals; Pollution -- Periodicals; 628.1
• DOI: 10.1111/wej.12802
• Languages: English
• ISSNs: 1747-6585

Abstract

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.