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June 1, 2026Geophysical Research Letters0 citationsOpen Access

The Potential for Leveraging SWOT‐Mapped Uneven Water Surface Elevations to Enhance ICESat‐2–Derived Lake Levels

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CHC. HuangHGHuilin Gao

Key Points

  • The aim is to improve the accuracy of water surface elevation measurements from ICESat-2 using SWOT-derived data.
  • Utilized SWOT mission two-dimensional water surface elevation difference maps to enhance ICESat-2 data.
  • Analyzed data over Lake Erie and Lake Powell to establish agreement with in situ measurements.
  • Investigated water surface elevations across 81,133 lakes globally to identify bias hotspots.
  • SWOT-derived WSE maps showed strong agreement with in situ data over Lake Erie (R²=0.79).
  • For Lake Powell, the R² value improved from 0.62 to 0.89 after applying the SWOT method.
  • SWOT data accounted for 44% of the uncertainty in median WSE fluctuations in global lakes.

Abstract

Abstract Satellite altimetry is advantageous for measuring water surface elevations (WSE) globally. However, biases of time series can be caused by uneven water surfaces, as nadir pointing measurements are often collected at different locations across a lake. This study demonstrates how two‐dimensional WSE difference maps derived from the SWOT mission can enhance ICESat‐2 WSE time series. First, the SWOT‐derived WSE difference maps showed strong agreement with in situ data over Lake Erie ( R 2 = 0.79). For Lake Powell, this method improves the R 2 of the ICESat‐2 time series from 0.62 to 0.89. Furthermore, spatial variability in water surface, as estimated using SWOT data, accounts for 44% and 16% of the uncertainty in median WSE fluctuations in global lakes and reservoirs, respectively. By analyzing 81,133 lakes worldwide, this study identifies hotspots of bias and offers an advantage for integrating multi‐satellite altimetry data, facilitating more accurate and long‐term hydrological monitoring across diverse global landscapes.

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Cite This Study

Huang et al. (2026) studied this question.

synapsesocial.com/papers/6a1d224302fbce913063803ahttps://doi.org/10.1029/2025gl119771
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