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In November 2017, a high‐intensity storm caused a catastrophic flash flood that devastated the city of Mandra, in Greece, and led to the tragic loss of 24 people. The storm caused flooding in the two main tributaries of the basin, creating two very similar hydrological responses with similar flood characteristics that hit two different environments: one within the city and one outside. This work examines the fatal incidents that occurred in relation to the characteristics of the surrounding environment, to investigate the role of the latter in flood mortality. Then, the analysis carried out for the 2017 flood is expanded to a broader database of flood deaths for Greece (1960–2018) for comparison. Results show that certain mortality characteristics differ substantially depending on the setting. Outdoor incidents are more abundant in nonurban environments, in which victims exhibit mostly an active or risk‐taking behaviour against the imminent risk. Urban environments are characterised by a greater diversity of victim activities, higher percentages of indoor deaths, especially for older victims and more passive behaviours. Overall, the study presents evidence on how risk situations develop differently between urban and nonurban settings. Findings are relevant in shaping policy and education programs aiming to mitigate risk. [ABSTRACT FROM AUTHOR]

The spatial and temporal scale of flash flood occurrence provides limited opportunities for measurements and observations using of conventional monitoring networks. These observational difficulties, often accompanied by a lack of instrumental data have turned the focus to event-based, post-disaster studies. Post-flood surveys are particularly useful, as they provide the opportunity to observe aspects of hydrological behaviour of catchments under rare runoff conditions and extreme meteorological forcing, by capitalizing on field evidence.Recently, unmanned aerial vehicles (UAVs) and the Structure for Motion (SfM) technique have been used to enhance field surveys and monitoring related to different aspects of disasters. The simple consumer-grade equipment required, its enhanced observation capabilities and certain conveniences they offer in field surveys indicate a strong potential of these technologies in many aspects of flash floods, especially given the opportunistic nature of their study. This work explores further this potential, aiming to demonstrate the application of UAVs in post-flood peak flow estimation. The research team surveyed two selected cross sections after the catastrophic 2017 flood of Mandra, developing a high resolution (2.7cm) digital surface model (DSM) using UAV imagery and the Structure from Motion technique (SfM). The detailed DSM was used to study channel geometry and flow obstructions, extract cross sections and calculate the cross sectional area and wetted perimeter. Water energy slope was defined with the use of high water marks that were placed on the DSM on the appropriate elevation.Peak discharge in the two ungauged sections were estimated at 170m3/s and 140m3/s (with a range to account for the uncertainty inherent in the dynamic nature of Manning coefficient), using the slope-conveyance method, indicating a unit peak discharge of approximately 9-10m3/s/km2. Following recommendations described in relevant literature on the integration of survey observations by means of hydrological modelling, we applied a spatially distributed hydrologic model to simulate discharge at the surveyed cross-sections (the Kinematic Local Excess Model (KLEM)) and other checks, all of which were in agreement, with the peak flow estimates provided by the UAV-aided survey analysis.The UAV allowed the collection of aerial imagery in a rapid way from an extensive area, despite that a large portion of it was inaccessible due to road closures and safety issues. In addition, detailed DSMs created using aerial imagery and the SfM technique was found to be particularly useful for studying channel geometry, obstructions and other characteristics of flow as well as for measuring cross sectional areas on demand, even at a later time, when the channel had changed due to human intervention (e.g. cleanup using heavy machinery) and water flow. These capabilities fit to the opportunistic context of studying flash flood events in the sense that UAVs can rapidly collect information within the short time frame that it is available. Nevertheless, it has to be noted that combination of ground with aerial observations is preferable. [ABSTRACT FROM AUTHOR]

Flash floods cause some of the most severe natural disasters in Europe and around the world. They induce devastating damages on property and infrastructure and cause numerous casualties on a yearly basis. The diversity and discontinuity of flash flood impacts, which are controlled mostly by surface properties, leads to major difficulties in obtaining a holistic appraisal and a realistic overview of flash flood effects and makes predicting future impacts a significant challenge. Previous studies have identified the need for a better understanding and prediction of flash flood impacts and a more systematic recording of their severity and have tried to tackle the problem by categorizing effects in various severity levels organized by different general criteria. The present study proposes a method that provides a coherent overview of flash flood effects through classification of their type, severity and mapping of their spatial extent. To this end, flood effects are grouped into 4 categories depending on the affected elements, namely: (i) Impacts on built environment (including any human-built structure, property or infrastructure), (ii) Impacts on mobile objects (including all types of vehicles, household and other man-made mobile objects), (iii) Impacts on the natural environment (including vegetation and agriculture, pollution phenomena, geomorphic effects) and (iv) Impacts on the human population (entrapments, injuries, fatalities).Each of the four above categories is classified in a system of 10 severity classes that are defined by objective class boundaries and are ordered by increasing importance of damages. The system's application is illustrated in the present work in two major, well-described flash flood events. The first one is the 2014 flash flood in Athens, Greece that caused extensive and very diverse damages in an urban environment, and the second one is the catastrophic flash flood of Mandra, Greece, in 2017, that killed 24 people and devastated a small town.The categorization and classification of flood effects in both cases resulted in the development of high spatial resolution impact-severity maps that revealed interesting damage patterns and highlighted high damage-severity areas. The proposed approach fits the event-based, opportunistic nature of flash flood studies that focus on post-flood surveys using post-event hydrometeorological, societal and impact-related observations. The method enhances the appraisal of flash flood damages, simplifies the complexity of flood effects and indirectly facilitates the prediction of future flash flood impacts in space. In addition, it shows potential for application in larger flood event datasets that could at a later time allow correlations between hydrometeorological characteristics and impact severity. [ABSTRACT FROM AUTHOR]