Despite being relatively rare, Mediterranean tropical-like cyclones, also known as Medicanes, induce significant impacts on coastal Mediterranean areas. Under climate change, it is possible that these effects will increase in frequency and severity. Currently, there is only a broad understanding of the types and mechanisms of these impacts. This work studied Medicane Ianos (September 2020) and its effects on the Ionian Islands, in Greece, by developing a database of distinct impact elements based on field surveys and public records. Through this archive, the study explored the range of Ianos’ impacts to develop a systematic categorization. Results showed different types of effects induced on the natural and the built environment that can be grouped into 3 categories and 39 sub-categories in inland and coastal areas, indicating an extensive diversity of impacts, ranging from flooding and geomorphic effects to damages in various facilities, vehicles and infrastructure. The systematic description of the typology of Medicanes’ effects presented in this study is a contribution to a better understanding of their consequences as means to improve our ability to prepare for, respond to, and recover from them, a necessary stepping stone in improving the overall preparedness of both the general public and relevant authorities.

The spatial and temporal scale of flash flood occurrence provides limited opportunities for observations and measurements using conventional monitoring networks, turning the focus to event-based, post-disaster studies. Post-flood surveys exploit field evidence to make indirect discharge estimations, aiming to improve our understanding of hydrological response dynamics under extreme meteorological forcing. However, discharge estimations are associated with demanding fieldwork aiming to record in small timeframes delicate data and data prone-to-be-lost and achieve the desired accuracy in measurements to minimize various uncertainties of the process. In this work, we explore the potential of unmanned aerial systems (UAS) technology, in combination with the Structure for Motion (SfM) and optical granulometry techniques in peak discharge estimations. We compare the results of the UAS-aided discharge estimations to estimates derived from differential Global Navigation Satellite System (d-GNSS) surveys and hydrologic modelling. The application in the catchment of the Soures torrent in Greece, after a catastrophic flood, shows that the UAS-aided method determined peak discharge with accuracy, providing very similar values compared to the ones estimated by the established traditional approach. The technique proved to be particularly effective, providing flexibility in terms of resources and timing, although there are certain limitations to its applicability, related mostly to the optical granulometry as well as the condition of the channel. The application highlighted important advantages and certain weaknesses of these emerging tools in indirect discharge estimations, which we discuss in detail.

Flash floods have been the cause of some of the most devastating events worldwide. The wide diversity of the effects, as well as the variety in the severity of the impacts, lead to major obstacles in obtaining a realistic understanding of the damages caused by a flood event, thus hampering at the same time our ability to predict future impacts. In assessing flood impacts and their severity, most existing methods use a qualitative characterization (e.g., major, catastrophic, etc.) or view the impacts from a single viewpoint or discipline (e.g., economic losses). In this study, we apply the Flash Flood Impact Severity Scale (FFISS) to assess, map, and classify the impacts of two flash floods from the Lilas River in Greece in 2009 and 2020. This application aims to discuss the different severity levels in terms of how one flood can affect the impacts of the next event. The methodology encompasses comprehensive field research, including the collection of ground-based and aerial observations utilizing UAV technology to document the impacts. These observations are subsequently georeferenced, followed by application of the Flash Flood Impact Severity Scale (FFISS) and generation of detailed maps to assess and evaluate the severity of the impacts associated with the two flood events. The results show that despite the higher water stage of the second flood, the impacts in previously hit areas indicate lower severity values, attributed to the gradual adaptation of the community and its infrastructure, as well as significant local widening of the river channel. On the contrary, high severity remains an issue in newly flooded areas during the second event. Overall, the application of the FFISS can show the spatial patterns of severity impacts, providing insights into the nature of floods locally but also indicating a potential reduction in the overall risk in the post-flood period.

Flash floods have been responsible for some of the most catastrophic events globally. The extensive range of effects and the varying severity of impacts present significant challenges in accurately understanding the damage caused by a flood event, thereby hindering our capacity to predict future consequences. When evaluating flood impacts and their severity, most existing approaches rely on qualitative descriptions (e.g., major, catastrophic, etc.) or examine the impacts from a single perspective or discipline, such as economic losses. In this study, the Flash Flood Impact Severity Scale (FFISS) is employed to evaluate, map, and categorize the impacts of two flash floods that occurred in the Lilas River in Greece in 2009 and 2020. The goal of this application is to analyze the varying severity levels and how one flood event can influence the impacts of a subsequent event. The methodology involved extensive fieldwork, including the collection of ground-based and aerial observations using UAV technology to document the impacts. These observations were subsequently georeferenced, followed by applying the Flash Flood Impact Severity Scale (FFISS) and creating detailed maps to assess and evaluate the severity of impacts associated with the two flood events. The results indicate that, despite the higher water levels during the second flood, areas previously affected show lower severity values. This reduction is attributed to the community’s gradual adaptation, improvements in infrastructure, and significant local widening of the river channel. Conversely, newly flooded areas during the second event exhibit high severity levels. Overall, applying the FFISS reveals spatial patterns of impact severity, offering insights into the local nature of floods while suggesting a potential reduction in overall risk during the post-flood period.

Unmanned Aircraft Systems (UAS) can be used to enhance monitoring of a wide range of environmental parameters, including acquiring data on various types of hydro-geomorphic phenomena.Their capabilities to provide on demand images and videos of high resolution, are particularly useful in the case of flash flood phenomena, which occur in spatial and temporal scales that do not favor traditional monitoring processes.In this work, flow velocity is estimated using aerial imaging acquired by means of an Unmanned Aircraft Vehicle (UAV) as well as ground observations during the catastrophic flash flood event of November 2017 in Mandra, Greece.In these imaging detailed tracing of various floating objects and particles such as light trash, debris etc. was carried out using multiple high-resolution video frames with specific time marks. Water velocity estimations were also cross-examined using flood mark-derived velocity hydraulic heads extracted by ground observations after the flood.The analysis was applied at a variety of locations across the study area, leading to a map of velocities for parts of the floodplain. Velocity values varied significantly depending on location, reaching up to 10m/s.The UAS proved to be very useful for the collection of important information for an extended area during the flood since a large portion of it was inaccessible due to road closures and safety issues. Nevertheless, the approach comes with certain limitations, including flight regulations, safety precautions and that rainfall is at a level that allows the deployment of a UAV during a flash flood.The findings show that the integration of aerial with ground observations in post-flood analysis contributes the completeness and accuracy of datasets regarding specific flash flood parameters and in the future could become a useful source of information, especially in data-poor regions.

Geomorphological transformations represent one of the most significant outcomes of high-magnitude flood events, as intense hydraulic forces have the capacity to rapidly reshape river channels, redistribute sediments, and modify the connectivity and functionality of adjacent floodplains. Understanding these processes is crucial for both hazard assessment and sustainable river management. In this context, the present study employs a multi-temporal approach using Unmanned Aerial Systems (UAS) combined with Structure-from-Motion (SfM) photogrammetry to detect, visualize and quantify geomorphological changes induced by flooding along selected sections of the Lilas River, located on Evia Island in Central Greece. These particular river reaches were strongly affected by the extreme flash flood that occurred in August 2020, an event that caused significant geomorphic disruption.High-resolution aerial surveys were carried out both before the flood event, and shortly thereafter, in June 2018 and in September 2020 respectively. These surveys enabled the generation of highly detailed Digital Surface Models (DSMs) and orthomosaics, with a ground sampling resolution of approximately 2.5 cm. By performing differential analyses of the DSMs, the study was able to capture detailed patterns of erosion and deposition along the river corridor. The results indicate a pronounced spatial variability, with areas of intense erosion exhibiting local vertical lowering exceeding 7 meters, while zones of sediment accumulation showed depositional aggradation of up to approximately 5 meters after corrections for vegetation cover. Such extreme geomorphic changes highlight the uneven distribution of flood-induced forces along the river channel.One of the most striking findings of the study is the substantial channel widening that occurred in response to the flood. At specific locations, cross-sectional widths expanded by factors ranging from three to nine, primarily as a result of lateral bank erosion. These findings underscore the complex interactions between natural geomorphic processes, extreme hydrological forcing, and anthropogenic landscape modifications, demonstrating that flood impacts cannot be understood without considering the coupled effects of these factors.Overall, the study illustrates the capability of repeatable UAS–SfM workflows to provide high-resolution, quantitative evidence of flood-driven geomorphic change. Such data are invaluable for supporting post-event assessments, informing river restoration planning, and guiding the design of infrastructure adaptation strategies. Moreover, the results contribute to broader efforts in flood risk management, particularly in Mediterranean catchments that are highly susceptible to extreme weather events. By integrating detailed topographic measurements with hydrological and ecological considerations, the methodology presented here represents a powerful tool for anticipating and mitigating the consequences of future floods.