Articles | Volume 30, issue 2
https://doi.org/10.5194/hess-30-459-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-459-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluating the feasibility of scaling the FIER framework for large-scale flood inundation prediction
Kel N. Markert
CORRESPONDING AUTHOR
Google LLC, Mountain View, CA 94043, USA
Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, USA
Hyongki Lee
Department of Civil and Environmental Engineering, University of Houston, Houston, TX 77204, USA
Gustavious P. Williams
Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, USA
E. James Nelson
Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, USA
Daniel P. Ames
Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, USA
Robert E. Griffin
Department of Atmospheric and Earth Science, University of Alabama in Huntsville, Huntsville, AL 35899, USA
Franz J. Meyer
Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA
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Taha Sadeghi Chorsi, Franz J. Meyer, and Timothy H. Dixon
The Cryosphere, 18, 3723–3740, https://doi.org/10.5194/tc-18-3723-2024, https://doi.org/10.5194/tc-18-3723-2024, 2024
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The active layer thaws and freezes seasonally. The annual freeze–thaw cycle of the active layer causes significant surface height changes due to the volume difference between ice and liquid water. We estimate the subsidence rate and active-layer thickness (ALT) for part of northern Alaska for summer 2017 to 2022 using interferometric synthetic aperture radar and lidar. ALT estimates range from ~20 cm to larger than 150 cm in area. Subsidence rate varies between close points (2–18 mm per month).
Sanchit Minocha, Faisal Hossain, Pritam Das, Sarath Suresh, Shahzaib Khan, George Darkwah, Hyongki Lee, Stefano Galelli, Konstantinos Andreadis, and Perry Oddo
Geosci. Model Dev., 17, 3137–3156, https://doi.org/10.5194/gmd-17-3137-2024, https://doi.org/10.5194/gmd-17-3137-2024, 2024
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The Reservoir Assessment Tool (RAT) merges satellite data with hydrological models, enabling robust estimation of reservoir parameters like inflow, outflow, surface area, and storage changes around the world. Version 3.0 of RAT lowers the barrier of entry for new users and achieves scalability and computational efficiency. RAT 3.0 also facilitates open-source development of functions for continuous improvement to mobilize and empower the global water management community.
Ibrahim Nourein Mohammed, Elkin Giovanni Romero Bustamante, John Dennis Bolten, and Everett James Nelson
Hydrol. Earth Syst. Sci., 27, 3621–3642, https://doi.org/10.5194/hess-27-3621-2023, https://doi.org/10.5194/hess-27-3621-2023, 2023
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We present an open-source platform in response to the NASA Open-Source Science Initiative for accessing and presenting quantitative remote-sensing earth observation,and climate data. With our platform scientists, stakeholders and concerned citizens can engage in the exploration, modeling, and understanding of data. We envisioned this platform as lowering the technical barriers and simplifying the process of accessing and leveraging additional modeling frameworks for data.
Sarath Suresh, Faisal Hossain, Sanchit Minocha, Pritam Das, Shahzaib Khan, Hyongki Lee, Konstantinos Andreadis, and Perry Oddo
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-193, https://doi.org/10.5194/hess-2023-193, 2023
Manuscript not accepted for further review
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Using entirely space-based data we explored how well can we predict the fast evolving dynamics of a flooding event in the mountainous region of Kerala during the 2018 disastrous floods. The tool, Reservoir Assessment Tool (RAT) was applied and found to have actionable accuracy in predicting the state of the Kerala reservoirs entirely from space to foster better coordinated management in future for reservoir operations.
Jack Tarricone, Ryan W. Webb, Hans-Peter Marshall, Anne W. Nolin, and Franz J. Meyer
The Cryosphere, 17, 1997–2019, https://doi.org/10.5194/tc-17-1997-2023, https://doi.org/10.5194/tc-17-1997-2023, 2023
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Mountain snowmelt provides water for billions of people across the globe. Despite its importance, we cannot currently measure the amount of water in mountain snowpacks from satellites. In this research, we test the ability of an experimental snow remote sensing technique from an airplane in preparation for the same sensor being launched on a future NASA satellite. We found that the method worked better than expected for estimating important snowpack properties.
Simon Zwieback and Franz J. Meyer
The Cryosphere, 15, 2041–2055, https://doi.org/10.5194/tc-15-2041-2021, https://doi.org/10.5194/tc-15-2041-2021, 2021
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Thawing of ice-rich permafrost leads to subsidence and slumping, which can compromise Arctic infrastructure. However, we lack fine-scale maps of permafrost ground ice, chiefly because it is usually invisible at the surface. We show that subsidence at the end of summer serves as a
fingerprintwith which near-surface permafrost ground ice can be identified. As this can be done with satellite data, this method may help improve ground ice maps and thus sustainably steward the Arctic.
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Short summary
Flooding is a major problem and predicting it accurately over large areas is tough. This study tested a new approach to forecast floods across a large region in the United States. By dividing the area into smaller areas to develop the prediction models and then combining, the method successfully simulated surface water extent for both high and low flow periods. The results were more accurate than existing approaches with similar methods which can improve flood forecasting for larger areas.
Flooding is a major problem and predicting it accurately over large areas is tough. This study...