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Probabilistic hydro-geomorphological hazard assessment based on UAV-derived high-resolution topographic data: The
Marco La Salandra1, Rodolfo Roseto1, Daniela Mele1
1Department of Earth and Geoenvironmental Sciences, University of Bari, Italy.
Abstract:
The combined use of Unmanned Aerial Vehicles (UAVs) and Structure from Motion (SfM) photogrammetry allows the collection and processing of high-resolution data on demand, which is key for the constant and detailed monitoring of the fluvial environment. In addition, through the ever-increasing development of new techniques of mapping and data processing (i.e., UAVs swarm, BVLOS flight missions, high-performance photogrammetry workflow), it is now possible to detect large areas at high-resolution, providing support for spatiotemporal insights into hydro-geomorphological processes and hazard assessment, in order to ensure an effective management and to prevent catastrophic phenomena (i.e., floods). The main goal of this paper is to use UAV-based high-resolution topographic data to constrain the probabilistic hazard assessment of extended reaches of Basento river (Basilicata, Italy). To demonstrate the influence of geomorphology and riverbed sediment on hazard assessment, a sensitivity analysis was carried out on the resolution of the UAV-derived DEMs; on the riverbed roughness coefficient resulting from photo-sieving analysis and on the morphological change detection over short-time ranges (2019-2021). We found that lower resolution DEMs lead to an increase of flooding probability (in several river cross-sections an increase even higher than 99 % resulted), and that a greater roughness coefficient involves an increase in the probability of flooding (with a maximum increase of about 9 %). Moreover, the multitemporal high-resolution outputs resulting from SfM allowed the identification of morphological changes, in short-times, caused by an anthropic modification of the river bank, which significantly affected the flooding hazard.
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