Spatial validation of submerged fluvial topographic models by mesohabitat units

Mapping the streambed morphology is crucial for understanding fluvial forms and processes, for advancing both our knowledge and best management practice of riverine systems. It is often done by wading streams but recently topobathymetric Light Detection and Ranging (LiDAR) and imagery captured from airborne platforms are becoming promising and effective surveying methodologies. The recent use of remotely piloted aerial systems (RPAS) combined with structure-from-motion (SfM) photogrammetric processing provides a novel, high-resolution approach to modelling fluvial morphology. Nevertheless, a complicating factor of such data acquisition in fluvial settings is linked to water bodies, whose presence introduces errors and distortions because of light reflection and refraction at the air-water interface. Although proof-of-concept research has shown it is possible to reduce the effects of refraction in certain settings (e.g., clear waters, unbroken surfaces), corresponding validation methods remain limited to point-based assessments of error, these being typically limited to accessible parts of the channel. Here, we provide the first high-resolution, spatially continuous validation of a stream reach bathymetry surveyed with SfM and corrected with an advanced refraction method. This method required only the camera co-ordinates and is available as open source, coded in C++. We used RPAS imagery from a regulated reach of the Palancia River, Spain, where a diversion structure fully dewatered the reach and let us obtain the entire streambed topography, which we used as spatially continuous control topography to compare the bathymetry surveyed from imagery during normal flow conditions. We compared this method with the small angle refraction correction (SARC), which has less data requirements, and analysed the error distribution across habitat types (i.e. pools and riffles). These results showed that our approach had smaller errors than SARC in both habitat types, especially in the riffle. By analysing the relationship between error and channel roughness obtained from our dry-bed model, we found that the greatest errors arise in the peripheral zones of the water surface and in its areas where streambed roughness generates more turbulence. Quantitative validation confirmed the reliability of our method as a relatively low-cost tool for the modelling and management of geomorphology and habitat within small - to medium-sized streams.

Automated summary

Mapping streambed morphology is crucial for understanding river forms and processes, and recent advancements in using topobathymetric LiDAR and imagery from airborne platforms have provided a promising and effective surveying methodology. The use of RPAS combined with SfM photogrammetric processing offers a high-resolution approach to modeling fluvial morphology, with the possibility of correcting errors caused by water bodies in the data acquisition process. Results from this study showed that the novel refraction correction method presented smaller errors in modeling streambed morphology compared to traditional methods, especially in riffle habitats.