Testing Utility of ICESat-2 and SWOT Altimetry in Monitoring Monthly Groundwater Levels of Dune Field Water Table Lakes

Groundwater levels are usually mapped as water table contours produced from point data, that is, hydraulic heads measured in modest numbers of observation wells distributed across a given region. The typically sparse distributions of wells, especially in remote areas, severely limit the number of observations that can be made and may lead to ambiguous groundwater-level estimates at unsampled locations. Satellite altimetry provides reliable estimates of hydraulic heads wherever surface water and groundwater intersect, regardless of how remote the location is. Therefore, we tested the use of Ice, Cloud, and Land Elevation Satellite 2 (ICESat-2) and Surface Water and Ocean Topography (SWOT) measurements of water levels in interdune water table lakes to characterize groundwater levels in the Nebraska Sandhills (central USA), the largest dune field in the Western Hemisphere. Our satellite altimetry estimates of groundwater levels in the Nebraska Sandhills closely approximate the measurements made in nearby observation wells. ICESat-2 showed a root-mean squared error (RMSE) of 0.68 m with ± 0.45 m standard deviation (SD). SWOT estimated an RMSE of 0.75 m with ± 0.76 m SD. Monthly groundwater levels were estimated using kriging with an external drift and generalized additive models, with RMSEs ranging from 1.9 m to 3.3 m and with unbiased errors (mean error of −0.003 m to 0.153 m). We conclude that satellite altimetry has potential for the remote measurements of groundwater levels under certain geographic conditions, especially where groundwater-dominated lakes are prevalent.

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Publication Details

Journal
Water
Published
2026-07-01
DOI
https://doi.org/10.3390/w18131601
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Testing Utility of ICESat-2 and SWOT Altimetry in Monitoring Monthly Groundwater Levels of Dune Field Water Table Lakes

Aaron R. Mittelstet, Nawaraj Shrestha, Troy E. Gilmore, R. Matthew Joeckel
Water
Flood Risk Assessment and Management
article

Testing Utility of ICESat-2 and SWOT Altimetry in Monitoring Monthly Groundwater Levels of Dune Field Water Table Lakes

Aaron R. Mittelstet, Nawaraj Shrestha, Troy E. Gilmore, R. Matthew Joeckel
article en

Abstract

Groundwater levels are usually mapped as water table contours produced from point data, that is, hydraulic heads measured in modest numbers of observation wells distributed across a given region. The typically sparse distributions of wells, especially in remote areas, severely limit the number of observations that can be made and may lead to ambiguous groundwater-level estimates at unsampled locations. Satellite altimetry provides reliable estimates of hydraulic heads wherever surface water and groundwater intersect, regardless of how remote the location is. Therefore, we tested the use of Ice, Cloud, and Land Elevation Satellite 2 (ICESat-2) and Surface Water and Ocean Topography (SWOT) measurements of water levels in interdune water table lakes to characterize groundwater levels in the Nebraska Sandhills (central USA), the largest dune field in the Western Hemisphere. Our satellite altimetry estimates of groundwater levels in the Nebraska Sandhills closely approximate the measurements made in nearby observation wells. ICESat-2 showed a root-mean squared error (RMSE) of 0.68 m with ± 0.45 m standard deviation (SD). SWOT estimated an RMSE of 0.75 m with ± 0.76 m SD. Monthly groundwater levels were estimated using kriging with an external drift and generalized additive models, with RMSEs ranging from 1.9 m to 3.3 m and with unbiased errors (mean error of −0.003 m to 0.153 m). We conclude that satellite altimetry has potential for the remote measurements of groundwater levels under certain geographic conditions, especially where groundwater-dominated lakes are prevalent.

WaterVol. 18(13)
University of Nebraska–Lincoln (US)
U.S. Geological Survey
Life below water
Openalex Percentile: Top 8%
Flood Risk Assessment and Management
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