Discharge Estimation with the Use of Unmanned Aerial Vehicles (UAVs) and Hydraulic Methods in Shallow Rivers
Although river discharge is essential hydrologic information, it is often absent, especially for small rivers and remote catchment areas. Practical difficulties frequently impede the installation and operation of gauging stations, while satellite-sensed data have proved to be relatively useful only...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/13/20/2808 |
| _version_ | 1797512938814177280 |
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| author | Sergios Lagogiannis Elias Dimitriou |
| author_facet | Sergios Lagogiannis Elias Dimitriou |
| author_sort | Sergios Lagogiannis |
| collection | DOAJ |
| description | Although river discharge is essential hydrologic information, it is often absent, especially for small rivers and remote catchment areas. Practical difficulties frequently impede the installation and operation of gauging stations, while satellite-sensed data have proved to be relatively useful only for discharge estimation of large-scale rivers. In this study, we propose a new methodology based on UAV-sensed data and photogrammetry techniques combined with empirical hydraulic equations for discharge estimation. In addition, two different riverbed particle size distributions were incorporated, to study the effect of fine sediment inclusion (or exclusion) in the estimation process. Accordingly, 17 study sites were selected and six different approaches were applied in each. Results show that at 75% of sites at least one approach produced an accurate discharge estimation, while in 10 out the 17 sites (58.8%) all six approaches produced accurate estimations. A strong correlation between a threshold value for the hydraulic radius (<i>Rh</i> = 0.3 m) of cross-sections and high estimation errors for sites exceeding it was also observed. The fine sediment inclusion improved only the performance of certain approaches and did not have a consistently positive effect. Overall, the relatively high percentage of sites with satisfactory discharge estimates indicates that using UAV-derived data and simple hydraulic equations can be used for this purpose, with an acceptable level of accuracy. |
| first_indexed | 2024-03-10T06:08:40Z |
| format | Article |
| id | doaj.art-9c72ab6759724d72b8cc2fb839a64da9 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-10T06:08:40Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-9c72ab6759724d72b8cc2fb839a64da92023-11-22T20:21:02ZengMDPI AGWater2073-44412021-10-011320280810.3390/w13202808Discharge Estimation with the Use of Unmanned Aerial Vehicles (UAVs) and Hydraulic Methods in Shallow RiversSergios Lagogiannis0Elias Dimitriou1Department of Water Resources and Environmental Engineering, National Technical University of Athens, 15780 Athens, GreeceHellenic Centre for Marine Research, Institute of Marine Biological Resources and Inland Waters, 19013 Anavyssos, GreeceAlthough river discharge is essential hydrologic information, it is often absent, especially for small rivers and remote catchment areas. Practical difficulties frequently impede the installation and operation of gauging stations, while satellite-sensed data have proved to be relatively useful only for discharge estimation of large-scale rivers. In this study, we propose a new methodology based on UAV-sensed data and photogrammetry techniques combined with empirical hydraulic equations for discharge estimation. In addition, two different riverbed particle size distributions were incorporated, to study the effect of fine sediment inclusion (or exclusion) in the estimation process. Accordingly, 17 study sites were selected and six different approaches were applied in each. Results show that at 75% of sites at least one approach produced an accurate discharge estimation, while in 10 out the 17 sites (58.8%) all six approaches produced accurate estimations. A strong correlation between a threshold value for the hydraulic radius (<i>Rh</i> = 0.3 m) of cross-sections and high estimation errors for sites exceeding it was also observed. The fine sediment inclusion improved only the performance of certain approaches and did not have a consistently positive effect. Overall, the relatively high percentage of sites with satisfactory discharge estimates indicates that using UAV-derived data and simple hydraulic equations can be used for this purpose, with an acceptable level of accuracy.https://www.mdpi.com/2073-4441/13/20/2808unmanned aerial vehiclesremote sensingdischarge estimationshallow riversfine sedimentparticle size distribution |
| spellingShingle | Sergios Lagogiannis Elias Dimitriou Discharge Estimation with the Use of Unmanned Aerial Vehicles (UAVs) and Hydraulic Methods in Shallow Rivers Water unmanned aerial vehicles remote sensing discharge estimation shallow rivers fine sediment particle size distribution |
| title | Discharge Estimation with the Use of Unmanned Aerial Vehicles (UAVs) and Hydraulic Methods in Shallow Rivers |
| title_full | Discharge Estimation with the Use of Unmanned Aerial Vehicles (UAVs) and Hydraulic Methods in Shallow Rivers |
| title_fullStr | Discharge Estimation with the Use of Unmanned Aerial Vehicles (UAVs) and Hydraulic Methods in Shallow Rivers |
| title_full_unstemmed | Discharge Estimation with the Use of Unmanned Aerial Vehicles (UAVs) and Hydraulic Methods in Shallow Rivers |
| title_short | Discharge Estimation with the Use of Unmanned Aerial Vehicles (UAVs) and Hydraulic Methods in Shallow Rivers |
| title_sort | discharge estimation with the use of unmanned aerial vehicles uavs and hydraulic methods in shallow rivers |
| topic | unmanned aerial vehicles remote sensing discharge estimation shallow rivers fine sediment particle size distribution |
| url | https://www.mdpi.com/2073-4441/13/20/2808 |
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