Combining UAS LiDAR, Sonar, and Radar Altimetry for River Hydraulic Characterization
Accurate river hydraulic characterization is fundamental to assess flood risk, parametrize flood forecasting models, and develop river maintenance workflows. River hydraulic roughness and riverbed/floodplain geometry are the main factors controlling inundation extent and water levels. However, gaugi...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/9/1/31 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832588664474959872 |
|---|---|
| author | Monica Coppo Frias Alexander Rietz Vesterhauge Daniel Haugård Olesen Filippo Bandini Henrik Grosen Sune Yde Nielsen Peter Bauer-Gottwein |
| author_facet | Monica Coppo Frias Alexander Rietz Vesterhauge Daniel Haugård Olesen Filippo Bandini Henrik Grosen Sune Yde Nielsen Peter Bauer-Gottwein |
| author_sort | Monica Coppo Frias |
| collection | DOAJ |
| description | Accurate river hydraulic characterization is fundamental to assess flood risk, parametrize flood forecasting models, and develop river maintenance workflows. River hydraulic roughness and riverbed/floodplain geometry are the main factors controlling inundation extent and water levels. However, gauging stations providing hydrometric observations are declining worldwide, and they provide point measurements only. To describe hydraulic processes, spatially distributed data are required. In situ surveys are costly and time-consuming, and they are sometimes limited by local accessibility conditions. Satellite earth observation (EO) techniques can be used to measure spatially distributed hydrometric variables, reducing the time and cost of traditional surveys. Satellite EO provides high temporal and spatial frequency, but it can only measure large rivers (wider than ca. 50 m) and only provides water surface elevation (WSE), water surface slope (WSS), and surface water width data. UAS hydrometry can provide WSE, WSS, water surface velocity and riverbed geometry at a high spatial resolution, making it suitable for rivers of all sizes. The use of UAS hydrometry can enhance river management, with cost-effective surveys offering large coverage and high-resolution data, which are fundamental in flood risk assessment, especially in areas that difficult to access. In this study, we proposed a combination of UAS hydrometry techniques to fully characterize the hydraulic parameters of a river. The land elevation adjacent to the river channel was measured with LiDAR, the riverbed elevation was measured with a sonar payload, and the WSE was measured with a UAS radar altimetry payload. The survey provided 57 river cross-sections with riverbed elevation, and 8 km of WSE and land elevation and took around 2 days of survey work in the field. Simulated WSE values were compared to radar altimetry observations to fit hydraulic roughness, which cannot be directly observed. The riverbed elevation cross-sections have an average error of 32 cm relative to RTK GNSS ground-truth measurements. This error was a consequence of the dense vegetation on land that prevents the LiDAR signal from reaching the ground and underwater vegetation, which has an impact on the quality of the sonar measurements and could be mitigated by performing surveys during winter, when submerged vegetation is less prevalent. Despite the error of the riverbed elevation cross-sections, the hydraulic model gave good estimates of the WSE, with an RMSE below 3 cm. The estimated roughness is also in good agreement with the values measured at a gauging station, with a Gauckler–Manning–Strickler coefficient of M = 16–17 m<sup>1/3</sup>/s. Hydraulic modeling results demonstrate that both bathymetry and roughness measurements are necessary to obtain a unique and robust hydraulic characterization of the river. |
| format | Article |
| id | doaj-art-f20aa651b4304604a34e3b5a5fd9d4e7 |
| institution | Kabale University |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-f20aa651b4304604a34e3b5a5fd9d4e72025-01-24T13:29:43ZengMDPI AGDrones2504-446X2025-01-01913110.3390/drones9010031Combining UAS LiDAR, Sonar, and Radar Altimetry for River Hydraulic CharacterizationMonica Coppo Frias0Alexander Rietz Vesterhauge1Daniel Haugård Olesen2Filippo Bandini3Henrik Grosen4Sune Yde Nielsen5Peter Bauer-Gottwein6Department of Environmental and Resource Engineering, Technical University of Denmark, 2800 Kongens Lyngby, DenmarkNational Space Institute, DTU Space, Technical University of Denmark, 2800 Kongens Lyngby, DenmarkNational Space Institute, DTU Space, Technical University of Denmark, 2800 Kongens Lyngby, DenmarkDepartment of Environmental and Resource Engineering, Technical University of Denmark, 2800 Kongens Lyngby, DenmarkDrone Systems Aps, CVR: 36734914, 8200 Arhus, DenmarkDrone Systems Aps, CVR: 36734914, 8200 Arhus, DenmarkDepartment of Environmental and Resource Engineering, Technical University of Denmark, 2800 Kongens Lyngby, DenmarkAccurate river hydraulic characterization is fundamental to assess flood risk, parametrize flood forecasting models, and develop river maintenance workflows. River hydraulic roughness and riverbed/floodplain geometry are the main factors controlling inundation extent and water levels. However, gauging stations providing hydrometric observations are declining worldwide, and they provide point measurements only. To describe hydraulic processes, spatially distributed data are required. In situ surveys are costly and time-consuming, and they are sometimes limited by local accessibility conditions. Satellite earth observation (EO) techniques can be used to measure spatially distributed hydrometric variables, reducing the time and cost of traditional surveys. Satellite EO provides high temporal and spatial frequency, but it can only measure large rivers (wider than ca. 50 m) and only provides water surface elevation (WSE), water surface slope (WSS), and surface water width data. UAS hydrometry can provide WSE, WSS, water surface velocity and riverbed geometry at a high spatial resolution, making it suitable for rivers of all sizes. The use of UAS hydrometry can enhance river management, with cost-effective surveys offering large coverage and high-resolution data, which are fundamental in flood risk assessment, especially in areas that difficult to access. In this study, we proposed a combination of UAS hydrometry techniques to fully characterize the hydraulic parameters of a river. The land elevation adjacent to the river channel was measured with LiDAR, the riverbed elevation was measured with a sonar payload, and the WSE was measured with a UAS radar altimetry payload. The survey provided 57 river cross-sections with riverbed elevation, and 8 km of WSE and land elevation and took around 2 days of survey work in the field. Simulated WSE values were compared to radar altimetry observations to fit hydraulic roughness, which cannot be directly observed. The riverbed elevation cross-sections have an average error of 32 cm relative to RTK GNSS ground-truth measurements. This error was a consequence of the dense vegetation on land that prevents the LiDAR signal from reaching the ground and underwater vegetation, which has an impact on the quality of the sonar measurements and could be mitigated by performing surveys during winter, when submerged vegetation is less prevalent. Despite the error of the riverbed elevation cross-sections, the hydraulic model gave good estimates of the WSE, with an RMSE below 3 cm. The estimated roughness is also in good agreement with the values measured at a gauging station, with a Gauckler–Manning–Strickler coefficient of M = 16–17 m<sup>1/3</sup>/s. Hydraulic modeling results demonstrate that both bathymetry and roughness measurements are necessary to obtain a unique and robust hydraulic characterization of the river.https://www.mdpi.com/2504-446X/9/1/31UAS hydrometryhydraulic modelingWSEbathymetryriver cross-sections |
| spellingShingle | Monica Coppo Frias Alexander Rietz Vesterhauge Daniel Haugård Olesen Filippo Bandini Henrik Grosen Sune Yde Nielsen Peter Bauer-Gottwein Combining UAS LiDAR, Sonar, and Radar Altimetry for River Hydraulic Characterization Drones UAS hydrometry hydraulic modeling WSE bathymetry river cross-sections |
| title | Combining UAS LiDAR, Sonar, and Radar Altimetry for River Hydraulic Characterization |
| title_full | Combining UAS LiDAR, Sonar, and Radar Altimetry for River Hydraulic Characterization |
| title_fullStr | Combining UAS LiDAR, Sonar, and Radar Altimetry for River Hydraulic Characterization |
| title_full_unstemmed | Combining UAS LiDAR, Sonar, and Radar Altimetry for River Hydraulic Characterization |
| title_short | Combining UAS LiDAR, Sonar, and Radar Altimetry for River Hydraulic Characterization |
| title_sort | combining uas lidar sonar and radar altimetry for river hydraulic characterization |
| topic | UAS hydrometry hydraulic modeling WSE bathymetry river cross-sections |
| url | https://www.mdpi.com/2504-446X/9/1/31 |
| work_keys_str_mv | AT monicacoppofrias combininguaslidarsonarandradaraltimetryforriverhydrauliccharacterization AT alexanderrietzvesterhauge combininguaslidarsonarandradaraltimetryforriverhydrauliccharacterization AT danielhaugardolesen combininguaslidarsonarandradaraltimetryforriverhydrauliccharacterization AT filippobandini combininguaslidarsonarandradaraltimetryforriverhydrauliccharacterization AT henrikgrosen combininguaslidarsonarandradaraltimetryforriverhydrauliccharacterization AT suneydenielsen combininguaslidarsonarandradaraltimetryforriverhydrauliccharacterization AT peterbauergottwein combininguaslidarsonarandradaraltimetryforriverhydrauliccharacterization |