Abstract
In this study, a method was developed for the baseline characterization of river bathymetry and time-varying heights using globally available datasets from the Shuttle Radar Topography Mission (SRTM) elevation data and Landsat visible imagery. Using independent data on river water elevations from satellite altimetry, the SRTM-Landsat approach was verified as to how well it can work for baseline characterization. The technique was demonstrated for Chindwin River locations in Myanmar that were also independently sampled by Sentinel 3A and Jason 3 altimeters. The Modified Normalized Difference Water Index (MNDWI) was used for estimating the water areas and widths using Landsat 8 from 2016 to 2019. A comparison of SRTM-Landsat with Sentinel 3A/Jason 3–based elevation changes resulted in a correlation coefficient up to 0.89 and 0.82 using area-elevation and width-elevation curves, respectively. The presence of river islands during the dry season resulted in a weaker correlation between our proposed SRTM-Landsat technique and altimeter water elevations. This case study over the Chindwin River in Myanmar demonstrated that the use of the SRTM-Landsat combined technique could yield an acceptable baseline for characterization of river bathymetry and time-varying heights at ungauged locations around the world.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article. The Dynamic River Width based Altimeter Height Visualizer website of the SASWE research group (UW) can be accessed at http://depts.washington.edu/saswe/jason3. Landsat-8 data was courtesy of the USGS (https://www.usgs.gov/core-science-systems/nli/landsat). STRM and Jason-3 data was courtesy of NASA/JPL-Caltech (https://www2.jpl.nasa.gov/srtm/ and https://www.jpl.nasa.gov/missions/jason-3, respectively). Sentinel-3A data was courtesy of NOAA (https://coastwatch.noaa.gov/cw/satellite-data-products/ocean-color/near-real-time/olci-sentinel3-global.html).
Acknowledgments
The authors gratefully acknowledge support from the National Aeronautics and Space Administration (NASA) Applied Sciences NNX16AQ54G that allowed the University of Washington to engage and train at the Asian Disaster Preparedness Center (ADPC) as a Surface Water Ocean Topography (SWOT) Satellite Mission Early Adopter. The work was supported by the generous contributions from the University of Washington Global Affairs and The Ivanhoe Foundation.
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Journal of Hydrologic Engineering
Volume 26 • Issue 11 • November 2021
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© 2021 American Society of Civil Engineers.
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Received: Mar 6, 2021
Accepted: Jun 22, 2021
Published online: Sep 8, 2021
Published in print: Nov 1, 2021
Discussion open until: Feb 8, 2022
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