Periodic Reporting for period 1 - SmartWood_3D (Applying state of the art smart sensor technology and Structure from Motion (SfM) photogrammetry for quantification of large wood (LW) movement processes and accumulation assessment in fluvial systems)
Reporting period: 2020-09-01 to 2022-08-31
As a consequence of changing climatic conditions and land-use, large amounts of wood are introduced into streams more frequently. Large wood (LW) represent an important element in rivers, as it provides food and shelter for living organisms and regulates sediment budgets. During floods, the benefits of wood in rivers can quickly turn into challenges, when large amounts of wood are recruited from hillslopes, banks and bars; often affecting fluvial ecosystems, instream structures and human populations. An abundance of mobile wood in rivers increases the probability of collisions (impacts) with instream structures, but also the risk of LW accumulations at critical cross-sections (e.g. bridges, weirs, gorges). Depending on the porosity and packing of such LW accumulations, hydraulic flow conditions are significantly altered. Changing flow conditions may then affect channel morphology, which could increase the risk of flooding (damming effects), or structural failure (erosion, bridge scour).
To date, little knowledge is available about LW dynamics (e.g. roll, rotation, impact forces) and accumulation characteristics (e.g. volume, porosity, structural alignment). However, such knowledge is urgently needed to reduce the risk and damage potential of LW during catastrophic events, and help in the design of more resilient instream structures and well-functioning LW retention racks. This Marie Skłodowska-Curie Action (MSCA), titled “SmartWood_3D”, closes the gap in data availability by employing (1) innovative smart sensors, installed into prototype logs “SmartWood” for quantifying LW dynamics during transport, and (2) an image-based 3D-surveying method “Structure from Motion (SfM) photogrammetry” for the assessment of LW accumulation characteristics via 3D models (digital twin models). The gained data and results allow for novel insights into LW movement behavior, help in the prediction of actual impact forces and significantly advance the assessment of prototype LW accumulations, which will be of relevance for river managers and engineers to maintain the functionality of instream structures and safety for local communities.
The overall objectives of the MSCA are: (1) to introduce state-of-the-art technologies into LW research, in order to advance applicable methodologies and to provide an efficient workflow-pipeline, (2) to generate digital twin models of prototype LW accumulations, allowing for its most accurate assessment, (3) to quantify mobilisation, transport and depositional processes of LW, (4) to determine impact forces from collisions of LW with instream structures and channel boundaries, and (5) to merge the gained results for a more comprehensive understanding of complex flow-sediment-wood interaction processes in rivers.
To date, little knowledge is available about LW dynamics (e.g. roll, rotation, impact forces) and accumulation characteristics (e.g. volume, porosity, structural alignment). However, such knowledge is urgently needed to reduce the risk and damage potential of LW during catastrophic events, and help in the design of more resilient instream structures and well-functioning LW retention racks. This Marie Skłodowska-Curie Action (MSCA), titled “SmartWood_3D”, closes the gap in data availability by employing (1) innovative smart sensors, installed into prototype logs “SmartWood” for quantifying LW dynamics during transport, and (2) an image-based 3D-surveying method “Structure from Motion (SfM) photogrammetry” for the assessment of LW accumulation characteristics via 3D models (digital twin models). The gained data and results allow for novel insights into LW movement behavior, help in the prediction of actual impact forces and significantly advance the assessment of prototype LW accumulations, which will be of relevance for river managers and engineers to maintain the functionality of instream structures and safety for local communities.
The overall objectives of the MSCA are: (1) to introduce state-of-the-art technologies into LW research, in order to advance applicable methodologies and to provide an efficient workflow-pipeline, (2) to generate digital twin models of prototype LW accumulations, allowing for its most accurate assessment, (3) to quantify mobilisation, transport and depositional processes of LW, (4) to determine impact forces from collisions of LW with instream structures and channel boundaries, and (5) to merge the gained results for a more comprehensive understanding of complex flow-sediment-wood interaction processes in rivers.
To address the objectives of the SmartWood_3D action, the workload has been split into two work packages (WPs). WP1 considers close-range aerial SfM photogrammetry for addressing objectives (1), (2) and (5), while WP2 considers innovative smart-sensors to address objectives (1), (3), (4) and (5). During this action, the fellow secured an additional funding of CHF 61’700, required for the development and application of innovative smart sensors. Due to the flood situation in the summer of 2021, a significant amount of novel data could be collected for both WPs. Field experiments for both WPs were conducted throughout a range of alpine catchments in Switzerland. WP1 required digital mapping of intact LW accumulations in the field, bevor being removed and analysed for their net wood volume (solid cubic meter volume, Fig.1). The gained data of WP1 grant new insights into LW accumulations, while accurate measurements of accumulation volume and porosity are of significant importance for assessing the effects of LW accumulations on flow hydraulics and channel morphology. WP2 employed innovative smart sensors with external GPS modules, installed into prototype wood logs “SmartWood”, for quantification of LW movement dynamics in the field. The SmartWood-logs were fed into flooded rivers (HQ1, Fig.2) and measured complex movement processes on their journey downstream. For the very first time, highly accurate data about LW dynamics were generated, allowing the study of complex movement processes (roll, rotation) but also the measurement of impact forces. From the sensor and GPS data, LW orientation as well as transport routes have been reconstructed, which are required for the design and functioning of LW retention structures as well as for the calibration and verification of numerical modes. The fellow is leading this MSCA and has submitted national as well as international journal articles and presented results at several occasions in Switzerland, but also at international conferences (EGU 2021 in Austria, AGU 2021 in the USA, IAHR 2022 in Spain). The collected data at field-scale are far exceeding the proposed expectations, and allow to securely complete the list of deliverables. Objectives (1) to (4) have been fully met, while (5) is currently in development.
This MSCA has pushed forward the frontiers in LW research in numerous ways. The introduced methods, based on state-of-the-art technologies and detailed analyses in the field, have shed new light onto LW research at field-scale. Challenges with the application of sensitive sensing equipment in rough stream environments, but also logistical issues with the required heavy equipment for removal and analyses of prototype LW accumulations have been overcome. The feedback and support received from the general public and decision makers, who truly appreciate the efforts and findings of this MSCA, has been tremendous. The prediction of log velocity, orientation, and impacts forces but also accumulation volume and porosity will improve LW management in future and fostering the competitiveness of European excellence in river sciences. Findings and raised hypotheses of this MSCA provide great potential for future studies (e.g. investigating the effects of structural alignment on flow hydraulics). In-stream infrastructures may be maintained and designed with respect to the gained knowledge from this MSCA. Considering LW transport processes and routes, potentially harmful LW can be filtered and removed at a suitable stream section (e.g. design of LW retention racks). The introduced SfM appraoch and generation of digital twin models will be of help to better predict flow hydraulics in the presence of LW accumulations. Both, LW related backwater effects as well as scour and aggradation processes will be better understood and controlled for. Furthermore, the gained data from the SmartWood_3D action are needed for the calibration and verification of numerical models. Currently there are many more manuscripts in development, utilising data acquired in the course of this fellowship, and thus continuing to publish impactful results and findings in the upcoming years.
The dissemination and exploitation of results is fully in progress. The Fellow and host institution (VAW) have agreed to continue working closely together in the near future, in order to fully realize the maximum dissemination and exploitation of results from this action. The fellow will propose together with the VAW for an ‘Ambizione Grant by the Swiss Nation Science Foundation’, enabling the fellow to become an even more independent researcher, while following up and further disseminate results of the SmartWood_3D action.
The dissemination and exploitation of results is fully in progress. The Fellow and host institution (VAW) have agreed to continue working closely together in the near future, in order to fully realize the maximum dissemination and exploitation of results from this action. The fellow will propose together with the VAW for an ‘Ambizione Grant by the Swiss Nation Science Foundation’, enabling the fellow to become an even more independent researcher, while following up and further disseminate results of the SmartWood_3D action.