Evaluating the Potential to Quantify Salmon Habitat via UAS‐Based Particle Image Velocimetry
Abstract Continuous, high‐resolution data for characterizing freshwater habitat conditions can support successful management of endangered salmonids. Uncrewed aircraft systems (UAS) make acquiring such fine‐scale data along river channels more feasible, but workflows for quantifying reach‐scale salm...
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| Format: | Article |
| Language: | English |
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Wiley
2025-03-01
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| Series: | Water Resources Research |
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| Online Access: | https://doi.org/10.1029/2024WR038045 |
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| author | Lee R. Harrison Carl J. Legleiter Brandon T. Overstreet James S. White |
| author_facet | Lee R. Harrison Carl J. Legleiter Brandon T. Overstreet James S. White |
| author_sort | Lee R. Harrison |
| collection | DOAJ |
| description | Abstract Continuous, high‐resolution data for characterizing freshwater habitat conditions can support successful management of endangered salmonids. Uncrewed aircraft systems (UAS) make acquiring such fine‐scale data along river channels more feasible, but workflows for quantifying reach‐scale salmon habitats are lacking. We evaluated the potential for UAS‐based mapping of hydraulic habitats using spectrally based depth retrieval and particle image velocimetry (PIV) by comparing these methods to a more well‐established flow modeling approach. Our results indicated that estimates of water depth, depth‐averaged velocity, and flow direction derived via remote sensing and modeling techniques were comparable and in good agreement with field measurements. Predictions of spring‐run Chinook salmon (Oncorhynchus tshawytscha) juvenile rearing habitat produced from PIV and model output were similar, with small errors relative to direct field observations. Estimates of hydraulic heterogeneity based on kinetic energy gradients in the flow field were generally consistent between PIV and flow modeling, but errors relative to field measurements were larger. PIV results were sensitive to the velocity index (α) used to convert surface velocities to depth‐averaged velocities. Sun glint precluded PIV analysis along the margins of some images and a large degree of overlap between frames was thus required to obtain continuous coverage of the reach. Similarly, shadows cast by riparian vegetation caused gaps in spectrally based bathymetric maps. Despite these limitations, our results suggest that for sites with sufficient water surface texture, UAS‐based PIV can provide detailed hydraulic habitat information at the reach scale, with accuracies comparable to traditional field methods and multidimensional flow modeling. |
| format | Article |
| id | doaj-art-4b9c41234eb249cfbbdab059cf22058c |
| institution | OA Journals |
| issn | 0043-1397 1944-7973 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Wiley |
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| series | Water Resources Research |
| spelling | doaj-art-4b9c41234eb249cfbbdab059cf22058c2025-08-20T02:09:27ZengWileyWater Resources Research0043-13971944-79732025-03-01613n/an/a10.1029/2024WR038045Evaluating the Potential to Quantify Salmon Habitat via UAS‐Based Particle Image VelocimetryLee R. Harrison0Carl J. Legleiter1Brandon T. Overstreet2James S. White3Southwest Fisheries Science Center National Oceanic and Atmospheric Administration Santa Cruz CA USAObserving Systems Division U.S. Geological Survey Golden CO USAOregon Water Science Center U.S. Geological Survey Portland OR USAOregon Water Science Center U.S. Geological Survey Portland OR USAAbstract Continuous, high‐resolution data for characterizing freshwater habitat conditions can support successful management of endangered salmonids. Uncrewed aircraft systems (UAS) make acquiring such fine‐scale data along river channels more feasible, but workflows for quantifying reach‐scale salmon habitats are lacking. We evaluated the potential for UAS‐based mapping of hydraulic habitats using spectrally based depth retrieval and particle image velocimetry (PIV) by comparing these methods to a more well‐established flow modeling approach. Our results indicated that estimates of water depth, depth‐averaged velocity, and flow direction derived via remote sensing and modeling techniques were comparable and in good agreement with field measurements. Predictions of spring‐run Chinook salmon (Oncorhynchus tshawytscha) juvenile rearing habitat produced from PIV and model output were similar, with small errors relative to direct field observations. Estimates of hydraulic heterogeneity based on kinetic energy gradients in the flow field were generally consistent between PIV and flow modeling, but errors relative to field measurements were larger. PIV results were sensitive to the velocity index (α) used to convert surface velocities to depth‐averaged velocities. Sun glint precluded PIV analysis along the margins of some images and a large degree of overlap between frames was thus required to obtain continuous coverage of the reach. Similarly, shadows cast by riparian vegetation caused gaps in spectrally based bathymetric maps. Despite these limitations, our results suggest that for sites with sufficient water surface texture, UAS‐based PIV can provide detailed hydraulic habitat information at the reach scale, with accuracies comparable to traditional field methods and multidimensional flow modeling.https://doi.org/10.1029/2024WR038045uncrewed aircraft system (UAS)particle image velocimetry (PIV)bathymetryremote sensinghydrodynamic modelingsalmon habitat |
| spellingShingle | Lee R. Harrison Carl J. Legleiter Brandon T. Overstreet James S. White Evaluating the Potential to Quantify Salmon Habitat via UAS‐Based Particle Image Velocimetry Water Resources Research uncrewed aircraft system (UAS) particle image velocimetry (PIV) bathymetry remote sensing hydrodynamic modeling salmon habitat |
| title | Evaluating the Potential to Quantify Salmon Habitat via UAS‐Based Particle Image Velocimetry |
| title_full | Evaluating the Potential to Quantify Salmon Habitat via UAS‐Based Particle Image Velocimetry |
| title_fullStr | Evaluating the Potential to Quantify Salmon Habitat via UAS‐Based Particle Image Velocimetry |
| title_full_unstemmed | Evaluating the Potential to Quantify Salmon Habitat via UAS‐Based Particle Image Velocimetry |
| title_short | Evaluating the Potential to Quantify Salmon Habitat via UAS‐Based Particle Image Velocimetry |
| title_sort | evaluating the potential to quantify salmon habitat via uas based particle image velocimetry |
| topic | uncrewed aircraft system (UAS) particle image velocimetry (PIV) bathymetry remote sensing hydrodynamic modeling salmon habitat |
| url | https://doi.org/10.1029/2024WR038045 |
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