Assessing the capabilities of the high-density green wavelength LiDAR point cloud and multibeam sonar data to quantify riverbed topography

Riverbed topography in boreal rivers plays a critical role in shaping fluvial and ecological processes. The spatial variation in riverbed elevation and in channel morphology influence for example the flow dynamics, sediment transport and deposition, nutrient cycling, and ecological dynamics providing habitats for variety of aquatic species. Thus, understanding riverbed topography and its change is essential for managing riverine systems and evaluating the impact of climate change and anthropogenic land use. However, quantifying the riverbed topography presents numerous challenges due to the highly dynamic environment (hydraulic conditions, substrate variability and temporal changes) of boreal rivers experiencing extreme events annually (e.g. floods and ice). The advancements in geospatial technologies, such as high-density laser scanning and multibeam sonar mapping, can enable detailed characterization of riverbed characteristics, however there is a lack of understanding the capabilities and limitations of these novel technologies in boreal river conditions. Therefore, the aim of this study is to investigate the capabilities of high density underwater and above water green LiDAR and multibeam sonar data to characterize the riverbed and riverbank topography and to develop methodologies to create seamless high detail digital terrain model (DTM) for the whole river channel. Following main research questions (RQs) were investigated: RQ1: What are the limitations in regards spatial resolution and data comprehensiveness between measurements systems? RQ2: Are the riverbed topography characteristics consistent between measurement systems?

Field surveys were conducted in the Oulankajoki River, located in northeastern Finland during autumn 2024. High-density point cloud data was acquired with the following systems: novel underwater LiDAR (ULi, green wavelength, Fraunhofer IPM) mounted into autonomous surface vehicle (Otter, Maritime Robotics), airborne bathymetric LiDAR (ABS, Fraunhofer IPM) mounted into high payload capacity drone and multibeam sonar (Baywei M4) mounted into Otter. In addition, in-situ control point measurements (VRS-GNSS) as well as water level and flow velocity (ADCP) information were collected to be used as auxiliary information in the analysis. To investigate the set RQs, following two analysis steps were conducted: (1) the point cloud density and coverage was assessed through varying grid size from 10 cm to 2 meter to identify the possible limitations in spatial resolution and coverage of the point clouds (RQ1), (2) the differences of the created DTMs were assessed with varying grid size and the following topographical characteristics were evaluated: elevation and slope variation, shape of river cross-sectional and longitudinal profiles, and bed roughness (small-scale variations of the riverbed surface characterized as the standard deviation of elevation or roughness indices).