Abstract
Water level or water surface elevation (WSE) is an important state variable of rivers, lakes, and wetlands. Hydrodynamic models of rivers and streams simulate WSE and can benefit from spatially distributed WSE observations, to increase model reliability and predictive skill. This has been partially addressed by satellite radar altimetry, but satellite altimetry is unable to deliver useful data for small rivers. To overcome such limitations, we deployed a radar altimetry system on an unmanned aerial vehicle (UAV), to map spatially distributed WSE. We showed that UAV altimetry can provide observations of WSE with a very high spatial resolution (ca. 0.5 m) and accuracy (ca. 3 cm), in a time-saving and cost-effective way. Furthermore, we investigated the value of this dataset for the calibration and validation of hydrodynamic models. Specifically, we introduced spatially distributed roughness parameters in a hydrodynamic model and estimated these parameters, using the observed WSE profiles along the stream as input. A case study was conducted in the Åmose stream, Denmark. The results showed that UAV-borne WSE can identify significant variations of the Manning–Strickler coefficients, along this small and highly vegetated stream and over time. Moreover, the model performed extremely well using distributed roughness coefficients, but it could not reproduce WSE satisfactorily using uniform roughness. We concluded that distributed roughness coefficients should be considered, especially for small vegetated rivers, to improve model performance, both locally and globally. Spatially distributed parameterizations of the effective channel roughness could be constrained with UAV-borne WSE. This study demonstrated for the first time that UAV-borne WSE can help to understand the variations of hydraulic roughness, and can support efficient river management and maintenance.
Highlights
Water level, or water surface elevation (WSE) is the most elementary and important state variable among a number of quantities characterizing surface water systems [1]
We showed that unmanned aerial vehicle (UAV) altimetry can provide observations of WSE with a very high spatial resolution and accuracy, in a time-saving and cost-effective way
The results showed that UAV-borne WSE can identify significant variations of the Manning–Strickler coefficients, along this small and highly vegetated stream and over time
Summary
Water surface elevation (WSE) is the most elementary and important state variable among a number of quantities characterizing surface water systems [1]. In order to achieve this goal, municipalities must monitor and maintain channel conveyance, especially during summer, when small Danish streams are heavily vegetated This approach does not guarantee flood safety for farmland and infrastructure, throughout the entire river/stream reach but only at the control stations. Hydrodynamic models can be used to interpolate spatial and temporal variations in the WSE between gauging stations. Another way is to calibrate roughness parameter using observations, e.g., inundation/WSE The latter results in an effective roughness, which might be different from real physical roughness due to the uncertainties in model structure and bathymetry [12]. The challenge here is to calibrate these distributed roughness parameters To constrain such a high dimensional local model, high spatial resolution datasets, e.g., WSE are, needed [14]. Details of the data processing workflows can be found in Bandini et al [23]
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