Estimating Reservoir Sedimentation Rates and Storage Capacity Losses Using High‐Resolution Sentinel‐2 Satellite and Water Level Data

Author:

Yao Fangfang12ORCID,Minear J. Toby1ORCID,Rajagopalan Balaji13ORCID,Wang Chao4ORCID,Yang Kehan56ORCID,Livneh Ben13ORCID

Affiliation:

1. Cooperative Institute for Research in Environmental Sciences (CIRES) University of Colorado Boulder Boulder CO USA

2. Environmental Institute University of Virginia Charlottesville VA USA

3. Department of Civil, Environmental and Architectural Engineering University of Colorado Boulder Boulder CO USA

4. Department of Earth, Marine and Environmental Sciences University of North Carolina at Chapel Hill Chapel Hill NC USA

5. Department of Civil & Environmental Engineering University of Washington Seattle WA USA

6. eScience Institute University of Washington Seattle WA USA

Abstract

AbstractIn nearly all reservoirs, storage capacity is steadily lost due to trapping and accumulation of sediment. Despite critical importance to freshwater supplies, reservoir sedimentation rates are poorly understood due to sparse bathymetry survey data and challenges in modeling sedimentation sequestration. Here, we proposed a novel approach to estimate reservoir sedimentation rates and storage capacity losses using high‐resolution Sentinel‐2 satellites and daily in situ water levels. Validated on eight reservoirs across the central and western United States, the estimated reservoir bathymetry and sedimentation rates have a mean error of 4.08% and 0.05% yr−1, respectively. Estimated storage capacity losses to sediment vary among reservoirs, which overall agrees with the pattern from survey data. We also demonstrated the potential applications of the proposed approach to ungauged reservoirs by combining Sentinel‐2 with sub‐monthly water levels from recent satellite altimeters.

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Geophysics

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