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Tropical Cyclone Shaheen (TCS), originating in the Arabian Sea on 30 September 2021, followed an east-to-west trajectory and made landfall as a category-1 cyclone in northern Oman on 3 October 2021, causing severe floods and damages before dissipating in the United Arab Emirates. This study aims to analyze the synoptic and dynamical conditions influencing Shaheen's genesis and evolution. Utilizing ERA5 reanalysis data, SEVIRI-EUMETSAT imagery, and Sorbonne University Atmospheric Forecasting System (SUAFS) outputs, it was found that Shaheen manifested as a warm-core cyclone with moderate vertical wind shear within the eyewall. Distinctive features included a trajectory aligned with rising sea surface temperatures and increased specific humidity levels at 700 hPa in the Arabian Sea. As Shaheen approached the Gulf of Oman, a significant increase in rainfall rates occurred, correlated with variations in sea surface temperatures and vertical wind shear. Comparative analysis between SUAFS and ERA5 data revealed a slight northward shift in the SUAFS track and landfall. Advance warnings highlighted heavy rainfall, rough seas, and strong winds. This study provides valuable insights into the meteorological factors contributing to Shaheen's formation and impact. [ABSTRACT FROM AUTHOR]

Ensemble weather forecasting involves the integration of multiple simulations to improve the accuracy of predictions by introducing a probabilistic approach. It is difficult to accurately predict heavy rainfall events that cause flash floods and, thus, ensemble forecasting could be useful to reduce uncertainty in the forecast, thus improving emergency response. In this framework, this study presents the efforts to develop and assess a flash flood forecasting system that combines meteorological, hydrological, and hydraulic modeling, adopting an ensemble approach. The integration of ensemble weather forecasting and, subsequently, ensemble hydrological-hydraulic modeling can improve the accuracy of flash flood predictions, providing useful probabilistic information. The flash flood that occurred on 26 January 2023 in the Evrotas river basin (Greece) is used as a case study. The meteorological model, using 33 different initial and boundary condition datasets, simulated heavy rainfall, the hydrological model, using weather inputs, simulated discharge, and the hydraulic model, using discharge data, estimated water level at a bridge. The results show that the ensemble modeling system results in timely forecasts, while also providing valuable flooding probability information for 1 to 5 days prior, thus facilitating bridge flood warning. The continued refinement of such ensemble multi-model systems will further enhance the effectiveness of flash flood predictions and ultimately save lives and property. [ABSTRACT FROM AUTHOR]

Wildfires are an escalating global threat, jeopardizing ecosystems and human activities. Among the repercussions in the ecosystem services of burnt areas, there are altered hydrological processes, which increase the risks of flash floods. There is limited research addressing this issue in a comprehensive way, considering pre- and post-fire conditions to accurately represent flood events. To address this gap, we present a novel approach combining multiple methods and tools for an accurate representation of post-fire floods. The 2019 post-fire flood in Kineta, Central Greece is used as a study example to present our framework. We simulated the meteorological conditions that caused this flood using the atmospheric model WRF-ARW. The burn extent and severity and the flood extent were assessed through remote sensing techniques. The 2D HEC-RAS hydraulic–hydrodynamic model was then applied to represent the flood event, using the rain-on-grid technique. The findings underscore the influence of wildfires on flooding dynamics, highlighting the need for proactive measures to address the increasing risks. The integrated multidisciplinary approach used offers an improved understanding on post-fire flood responses, and also establishes a robust framework, transferable to other similar cases, contributing thus to enhanced flood protection actions in the face of escalating fire-related disasters. [ABSTRACT FROM AUTHOR]

Flash floods, among the most destructive natural hazards, are commonly studied as to their catastrophic power in terms of fatalities, infrastructure damages and economic losses. A devastating aftermath of flash floods, which has not received much‐deserved attention in the literature, is the sizeable and permanent soil loss due to soil erosion and sediment yields. This study aims at forecasting soil erosion and sediment yields due to the disastrous storm event that occurred in Mandra town (western Attica, Greece) on 15 November 2017. Gridded hydrometeorological forecasts were conducted at 5‐min and 1‐h time steps by means of the chemical hydrological atmospheric ocean wave system (CHAOS). The forecasts of soil erosion and sediment yields were achieved by a high‐resolution geographic information system (GIS) application of the modified universal soil loss equation (MUSLE) on the basis of the forecasted surface runoff hydrographs. The entire event lasted from the afternoon of 14 November until noon of 15 November, but the bulk of the disastrous storm occurred in the morning of 15 November 2017, flooding two torrent basins. As a result of the extreme flash flood, 2195 tons and 1435 tons of sediment were forecasted to be detached from the body of the soil's surface and transported to the stream networks of the Soures and Agia Aikaterini Torrent basins which cross Mandra. Soil erosion maps were constructed for every hour and the spatial and temporal evolution of soil erosion was shown throughout the event. This study provides concrete insights on the erosion‐prone areas of the study basins, which can inform actions against erosion. [ABSTRACT FROM AUTHOR]

A common source of uncertainty in flood inundation forecasting is the hydrograph used. Given the role of sea‐air‐hydro‐land chain processes on the water cycle, flood hydrographs in coastal areas can be indirectly affected by sea state. This study investigates sea‐state effects on precipitation, discharge, and flood inundation forecasting implementing atmospheric, ocean wave, hydrological, and hydraulic‐hydrodynamic coupled models. The Chemical Hydrological Atmospheric Ocean wave System (CHAOS) was used for coupled hydro‐meteorological‐wave simulations 'accounting' or 'not accounting' the impact of sea state on precipitation and, subsequently, on flood hydrograph. CHAOS includes the WRF‐Hydro hydrological model and the WRF‐ARW meteorological model two‐way coupled with the WAM wave model through the OASIS3‐MCT coupler. Subsequently, the 2D HEC‐RAS hydraulic‐hydrodynamic model was forced by the flood hydrographs and map the inundated areas. A flash flood event occurred on 15 November 2017 in Mandra, Attica, Greece, causing 24 fatalities, and damages was selected as case study. The calibration of models was performed exploiting historical flood records and previous studies. Human interventions such as hydraulic works and the urban areas were included in the hydraulic modelling geometry domain. The representation of the resistance caused by buildings was based on Unmanned Aerial System (UAS) data while the local elevation rise method was used in the urban‐flood simulation. The flood extent results were assessed using the Critical Success Index (CSI), and CSI penalize. Integrating sea‐state affected the forecast of precipitation and discharge peaks, causing up to +24% and from −8% to +36% differences, respectively, improving inundation forecast by 4.5% and flooding additional approximately 70 building blocks. The precipitation forcing time step was also highlighted as significant factor in such a small‐scale flash flood. The integrated multidisciplinary methodological approach could be adopted in operational forecasting for civil protection applications facilitating the protection of socio‐economic activities and human lives during similar future events. [ABSTRACT FROM AUTHOR]

Severe hydrometeorological hazards such as floods, droughts, and thunderstorms are expected to increase in the future due to climate change. Due to the significant impacts of these phenomena, it is essential to develop new and advanced early warning systems for advance preparation of the population and local authorities (civil protection, government agencies, etc.). Therefore, reliable forecasts of extreme events, with high spatial and temporal resolution and a very short time horizon are needed, due to the very fast development and localized nature of these events. In very short time-periods (up to 6 h), small-scale phenomena can be described accurately by adopting a "nowcasting" approach, providing reliable short-term forecasts and warnings. To this end, a novel nowcasting system was developed and presented in this study, combining a data assimilation system (LAPS), a large amount of observed data, including XPOL radar precipitation measurements, the Chemical Hydrological Atmospheric Ocean wave System (CHAOS), and the WRF-Hydro model. The system was evaluated on the catastrophic flash flood event that occurred in the sub-urban area of Mandra in Western Attica, Greece, on 15 November 2017. The event was one of the most catastrophic flash floods with human fatalities (24 people died) and extensive infrastructure damage. The update of the simulations with assimilated radar data improved the initial precipitation description and led to an improved simulation of the evolution of the phenomenon. Statistical evaluation and comparison with flood data from the FloodHub showed that the nowcasting system could have provided reliable early warning of the flood event 1, 2, and even to 3 h in advance, giving vital time to the local authorities to mobilize and even prevent fatalities and injuries to the local population. [ABSTRACT FROM AUTHOR]

Nowadays, as extreme weather increasingly threatens human health and economy, early warning system approaches are critical for timely preparedness and response. Towards the implementation of a multi-model forecasting system for flood hazards, this study presents a coupled application of three (3) models: The WRF-ARW weather model, the WRF-Hydro hydrological model, and the HEC-RAS 2D hydraulic model. A flash flood event that occurred on 9 October 2006 in Volos city, Greece, is used as a case study to assess the accuracy of the integrated modelling approach to simulate the flood hydrograph and flood extent in Xerias ungauged catchment. The hydrometeorological simulation results indicated a severe persistent storm over Pelion mountain at the northeast of Volos, as the main factor of the major flash flood and extensive impacts. Historical flood records retrieved by several conventional and non-conventional sources are used to validate the flooded area. Compared to the collected data and prior studies, the generated inundation map of Xerias river is found to realistically capture highly impacted areas which experienced infrastructure damage and human rescues from inundated roads and buildings. Results from our analyses show that the proposed physically-based modelling approach can give reliable inputs into flood risk management. [ABSTRACT FROM AUTHOR]