Refine
Document Type
- Article (3)
Language
- English (3)
Has Fulltext
- no (3)
Reviewed
Keywords
Institute
The assessment and mapping of riverine flood hazards and risks is recognized by many countries as an important tool for characterizing floods and developing flood management plans. Often, however, these management plans give attention primarily to open-water floods, with ice-jam floods being mostly an afterthought once these plans have been drafted. In some Nordic regions, ice-jam floods can be more severe than open-water floods, with floodwater levels of ice-jam floods often exceeding levels of open-water floods for the same return periods. Hence, it is imperative that flooding due to river ice processes be considered in flood management plans. This also pertains to European member states who are required to submit renewed flood management plans every six years to the European governance authorities. On 19 and 20 October 2022, a workshop entitled “Assessing and mitigating ice-jam flood hazard and risk” was hosted in Poznań, Poland to explore the necessity of incorporating ice-jam flood hazard and risk assessments in the European Union’s Flood Directive. The presentations given at the workshop provided a good overview of flood risk assessments in Europe and how they may change due to the climate in the future. Perspectives from Norway, Sweden, Finland, Germany, and Poland were presented. Mitigation measures, particularly the artificial breakage of river ice covers and ice-jam flood forecasting, were shared. Advances in ice processes were also presented at the workshop, including state-of-the-art developments in tracking ice-floe velocities using particle tracking velocimetry, characterizing hanging dam ice, designing new ice-control structures, detecting, and monitoring river ice covers using composite imagery from both radar and optical satellite sensors, and calculating ice-jam flood hazards using a stochastic modelling approach.
Combining photogrammetric reconstruction (close-range photogrammetry, CRP) and airborne photogrammetry through the structure from motion method (SFM) with terrestrial three-dimensional (3D) laser scanning (TLS), Maelstrom Cave on Big Island, Hawaii (USA), was mapped in three dimensions. The complementary properties of the two methods generated an overall model that depicted significant features of the cave both spatially and visually. Through various processes, the complex geometric quantities were derived from the model that can be used to answer microbiological and climatological questions. In this report, the procedure for the three-dimensional acquisition of the terrain surface above Maelstrom Cave as well as the interior of the cave with TLS and SFM is described. It is shown how the different data sets were combined and contrasted, including a comparison of geometries from the different survey operations. Finally, the editing processes used to quantify and simplify the cave geometry are presented, as well as the analysis of the ellipses generated accordingly to determine the geometric quantities. Through the analysis of the cave geometry, important geometric properties of the Maelstrom Cave could be quantified and categorized. In this way, an effective tool was developed to directly correlate the structure of the cave system with climatological and microbiological parameters in order to answer the corresponding questions.
Recent flood events (FE) in Germany have shown that the extent and impact of extreme flood events cannot be estimated solely based on numerical models. For analyzing the development of such an event and to develop and implement safety measures more efficiently, additional data must be collected during the event. Within the scope of this research, the possibilities of near real-time recording using an unmanned aerial vehicle (UAV) and data processing with the Structure from Motion (SfM) method were tested in a case study. Different recording parameter combinations were tested in the Laufer
Muehle area on the Aisch river in Germany. The focus of the investigations was the identification of a parameter combination that allows a short recording interval for aerial imagery. Based on these findings, the identification of changes in the study area by comparing multitemporal photography (flood prevention), as well as the recording of flooded areas during a FE should be possible. The accuracy analysis of the different parameter combinations between two point clouds as well as the process of change detection was done by a Multiscale Model to Model Cloud Comparison (M3C2) and
including ground control points. As a result, a parameter combination was identified which led to the desired results in the study area. The processes were transformed into fully automated and scripted workflows. The results serve as a basis for establishing a workflow for near real-time analyses in future studies.