Quantification and assessment methods for large wood (LW) in fluvial systems

Abstract

Wood in rivers acts as a natural and ecological important element as it moderates stream power, regulates sediment transport and provides habitat for fish and other living organisms. Besides the beneficial effects of wood in rivers, an abundance of organic material, which is often introduced to waterways by changing climatic conditions and modern land-use practices, may impact stream ecology and flood mitigation adversely. The often sudden occurrence of large wood (LW) during floods regularly affects stream systems, infrastructure and communities all over the world. Due to a lack of applicable remote sensing methodologies in LW research, to date little is known about transport dynamics of wood in rivers. In order to expand the current understanding of flow-sediment-wood interaction processes, especially at higher flow rates, LW interactions with the environment need to be studied. This research project aims to apply state-of-the-art technologies for quantifying and assessing LW interactions. Nine-degree of freedom (9-DoF) smart sensors are implanted into scaled wooden dowels, resulting in ‘SmartWood’, being able to capture complex movement processes of wood in a hydraulic laboratory environment. Each of the smart sensors comprises an internal processor for time-synchronisation of accelerometer, gyroscope and magnetometer data, and stores the data on an on-board memory card. A measuring frequency of 100 Hz was found to accurately measure transport, impact and accumulation processes. Structure form Motion (SfM) photogrammetry is used for the generation of three-dimensional (3D) LW accumulation models, as well as for the detection of changes in channel morphology due to LW obstructed flow conditions. The technique uses two-dimensional (2D) images, with large image overlap, for the generation of 3D point cloud models, which are edited and meshed, following a new workflow-pipeline for LW specific applications. The use of those innovative methodologies allow for novel insights into LW transport and deposition dynamics alongside effective and accurate volumetric quantification opportunities. An improved knowledge of wood movement processes is essential to better predict impacts on channel morphology, river-crossing infrastructure and environment. Gained results will contribute in a more reliable risk assessment for LW-prone stream systems, inform river and forestry managers, and may help in the development of improved management strategies under consideration of LW conveyance and filtering of critical key-logs.