The applicability of time-integrated unit stream power for estimating bridge pier scour using noncontact methods in a gravel-bed river
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Abstract
In near-field remote sensing, noncontact methods (radars) that measure stage and surface water velocity have the potential to supplement traditional bridge scour monitoring tools because they are safer to access and are less likely to be damaged compared with in-stream sensors. The objective of this study was to evaluate the use of radars for monitoring the hydraulic conditions that contribute to bridge–pier scour in gravel-bed channels. Measurements collected with a radar were also leveraged along with minimal field measurements to evaluate whether time-integrated stream power per unit area (Ω) was correlated with observed scour depth at a scour-critical bridge in Colorado. The results of this study showed that (1) there was close agreement between radar-based and U.S. Geological Survey streamgage-based measurements of stage and discharge, indicating that radars may be viable tools for monitoring flow conditions that lead to bridge pier scour; (2) Ω and pier scour depth were correlated, indicating that radar-derived Ω measurements may be used to estimate scour depth in real time and predict scour depth based on the measured trajectory of Ω. The approach presented in this study is intended to supplement, rather than replace, existing high-fidelity scour monitoring techniques and provide data quickly in information-poor areas.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | The applicability of time-integrated unit stream power for estimating bridge pier scour using noncontact methods in a gravel-bed river |
| Series title | Remote Sensing |
| DOI | 10.3390/rs14091978 |
| Volume | 14 |
| Issue | 9 |
| Year Published | 2022 |
| Language | English |
| Publisher | MDPI |
| Contributing office(s) | Arizona Water Science Center, Colorado Water Science Center |
| Description | 1978, 31 p. |
| Country | United States |
| State | Colorado |
| Other Geospatial | Gunnison River |
| Google Analytic Metrics | Metrics page |