Mapping Flash Flood Hazards in Arid Regions Using CubeSats

Abstract. Pakistan is prone to natural hazards including floods, in particular, affecting millions of people each year across the country. Patterns from recent years suggest the intensity of flooding are increasing and may continue more aggressively during the coming years because of increased magnitude of the monsoon rains and identified climatic changes in the region. Mapping of flood hazard is essential for planning and mitigation purpose. However, only flood hazard mapping is not sufficient to assess the magnitude of risk to lives and property. Risk mapping is an integral part of pre and post disaster management. Furthermore, the Earth Observation (EO) data could be helpful to update flood risk maps time to time by covering many aspects e.g. population concentration areas, critical infrastructure and commercial areas, to enhance the preparedness planning and mitigation measure against risk of flood. Pakistan has experienced the devastating flood in 2010 due to unexpected heavy rainfall in the monsoon season with enormous losses to property lives and infrastructure in several districts. The Union council Agra, District Charsadda was among the affected most districts by riverine and flash floods. Additionally, growing population in flood plains is another threat to the district. However, to cope with this situation there is immense need to detect risk index to prevent further damages caused by such floods. This study aims to prepare the hazard, vulnerability and risk index for River Kabul and Swat catchment area of union council Agra, Charsadda. the flood risk was identified, and risk index maps were prepared by executing a methodology for assessing risk, based on the physical exposure of the flood hazard, vulnerability of people, and the exposure of critical assets to flood water. Explicitly, spatial flood risk index maps were produced with the help of analytical spatial modeling by considering the areas exposed to flood hazard, morphological characteristics and socio-economic indicators. The produced flood risk maps were verified through visual examination through 3D city flood maps. Results illustrate that the areas of higher flood risk overlapped with the areas of high flood hazard along with high population density and socio-economic exposure to vulnerability.

Using statistical functions and hydro-hydraulic models to develop human vulnerability curves for flash floods: The flash flood of the Taitou catchment (China) in 2016

<p>In the second half of the 20<sup>th</sup> century, hydrological regimes in central Western Europe were largely characterised by large-scale winter floods. This type of event was predominantly triggered by westerly atmospheric fluxes, bringing moist and mild air masses from the Atlantic Ocean to the European continent. Since the late 1990’s, major flooding events seem to have shifted in time and magnitude. Flash flood events, while being a well-known phenomenon in Mediterranean catchments, are increasingly also reported at higher latitudes. Unlike the large-scale winter flood events, flash floods are of very narrow spatial extension and triggered by rather short, but highly intense rainfall events.</p><p>Here, we focus on the specific case of rivers in Luxembourg that have experienced several flash flood events in recent years, while only small to moderate winter flood events have been reported since the late 1990’s. National hydro-meteorological monitoring and flood forecasting systems have been designed for large-scale floods and are not suited for simulating local flash flood events. Therefore, there is a need to increase our understanding of the hydro-meteorological processes underlying flash flood occurrences in our area of interest.</p><p>While increasing air temperature is known to allow a higher air moisture content that can lead to more intense rainfall events and possible flooding, we moreover hypothesize that the recent increase in flash flood occurrences in Luxembourg is reinforced by a change in atmospheric circulation patterns. To test this hypothesis, we analyse the prevailing atmospheric patterns on rainy days during summer and winter months over the period 1954 - 2019, with a particular focus on rainfall events that lead to moderate and extreme floods. In a next step, we intend to extend our findings for Luxembourg in a larger European context. This analysis should allow to better assess the current situation of hydrological extreme events in central Western Europe in order to take precaution measures and prepare for a diversifying hazard.</p>

A national scale flood hazard mapping methodology: The case of Greece – Protection and adaptation policy approaches

FF-BERT: A BERT-based ensemble for automated classification of web-based text on flash flood events

Abstract. Unexpected growth of population and urbanization eventually leads towards disasters, might be natural or manmade for instance climate change, the rise in sea level, pollution, landslides, floods, etc. Subsequently, floods are the worst effects of agricultural revolution and comes up as a potential most natural hazard in the world. It couldn’t be stopped but the adverse impact can be minimized through structural and non-structural measures. Flood hazard mapping have a vital role and is an essential element of land use and pre-disaster planning. Moreover, the Earth Observation (EO) data can help to prepare the updated flood hazard maps by distant viewing. Pakistan have one of the greatest irrigation systems of the world and is the sixth largest populous country. However, having such a huge irrigation system is also a threat to overflow in heavy rains. The monsoon season in 2010, the unexpected heavy rainfall caused a massive flood which ultimately destroyed the agriculture, infrastructure in several districts all over the country. District Charsadda was affected severely by both riverine floods and flash floods in 2010. Furthermore, the floodplains of district is occupied by dense population showing the immense need to assess hazard zones to avoid additional losses. In this case study for the catchment area of River Kabul and River Swat, Charsadda, the flood hazard was identified using participatory approach and weighted overlay method. Results depict that more than 80% of the area was inundated during 2010 devastating flood in the UC Agra.

The rapid growth of impervious areas in urban basins worldwide has increased the number of impermeable surfaces in cities, leading to severe flooding and significant economic losses for civilians. This trend highlights the urgent need for methodologies that assess flood hazards and specifically address the direct impact on pedestrians, which is often overlooked in traditional flood hazard analyses. This study aims to evaluate a methodology for assessing the risk to pedestrians from hydrodynamic forces during urban floods, with a specific focus on Cúcuta, Colombia. The methodology couples research outcomes from other studies on the impact of floodwaters on individuals of different ages and sizes with 1D/2D hydrological modeling. Advanced computational algorithms for image recognition were used to measure water levels at 5‐s intervals on November 6, 2020, using drones for digital elevation model data collection. In Cúcuta, where flood risk is high and drainage infrastructure is limited, the PCSWMM (Computer‐based Urban Stormwater Management Model) was calibrated and validated to simulate extreme flood events. The model incorporated urban infrastructure details and geomorphological parameters of Cúcuta's urban basin. Four return periods (5, 10, 50, 100), with extreme rainfall of 3 h, were used to estimate the variability of the risk map. The output of the model was analyzed, and an integrated and time‐varying comparison of the results was done. Results show that the regions of high‐water depth and high velocity could vary significantly along the duration of the different extreme events. Also, from 5 to 100 years return period, the percentage of area at risk increased from 9.6% to 16.6%. The pedestrian sensitivity appears much higher than the increase in velocities or water depth individually. This study identified medium to high‐risk locations, which are dynamic in time. We can conclude dynamics are spatiotemporal, and the added information layer of pedestrians brings vulnerability information that is also dynamic. Areas of immediate concern in Cúcuta can enhance pedestrian safety during flash flood events. The spatiotemporal variation of patterns requires further studies to map trajectories and sequences that machine learning models could capture.

<strong class="journal-contentHeaderColor">Abstract.</strong> In recent years, flash floods repeatedly occurred in temperate regions of central western Europe. Unlike in Mediterranean catchments, this flooding behaviour is unusual. In the past, and especially in the 1990s, floods were characterized by predictable, slowly rising water levels during winter and driven by westerly atmospheric fluxes (Pfister et al., 2004). The intention of this study is to link the recent occurrence of flash floods in central western Europe to extreme precipitation and specific atmospheric conditions to identify the cause for this apparent shift. Therefore, we hypothesise that an increase in extreme precipitation events has subsequently led to an increase in the occurrence of flash flood events in central western Europe and all that being caused by a change in the occurrence of flash flood favouring atmospheric conditions. To test this hypothesis, we compiled data on flash floods in central western Europe and selected precipitation events above 40 mm h^&minus;1 from radar data (RADOLAN, DWD). Moreover, we identified proxy parameters representative for flash flood favouring atmospheric conditions from the ERA5 reanalysis dataset. High specific humidity in the lower troposphere (q &ge; 0.004 kg kg^&minus;1), sufficient latent instability (CAPE &ge; 100 J kg^&minus;1) and weak deep-layer wind shear (DLS &le; 10 m s^&minus;1) proved to be characteristic for long-lasting intense rainfall that can potentially trigger flash floods. These atmospheric parameters, as well as the flash flood and precipitation events were then analysed using linear models. Thereby we found significant increases in atmospheric moisture contents and increases in atmospheric instability. Parameters representing the motion and organisation of convective systems occurred slightly more often or remained unchanged in the time period from 1981&ndash;2020. Moreover, a trend in the occurrence of flash floods was confirmed. The number of precipitation events, their maximum 5-minute intensities as well as their hourly sums were however characterized by large inter-annual variations and no trends could be identified between 2002&ndash;2020. This study therefore shows that the link from atmospheric conditions via precipitation to flash floods cannot be traced down in an isolated way. The complexity of interactions is likely higher and future analyses should include other potentially relevant factors such as intra-annual precipitation patterns or catchment specific parameters.

In recent years, flash floods repeatedly occurred in temperate regions of central western Europe. Unlike in Mediterranean catchments, this flooding behaviour is unusual. In the past, and especially in the 1990s, floods were characterized by predictable, slowly rising water levels during winter and driven by westerly atmospheric fluxes (Pfister et al., 2004). The intention of this study is to link the recent occurrence of flash floods in central western Europe to extreme precipitation and specific atmospheric conditions to identify the cause for this apparent shift. Therefore, we hypothesise that an increase in extreme precipitation events has subsequently led to an increase in the occurrence of flash flood events in central western Europe and all that being caused by a change in the occurrence of flash flood favouring atmospheric conditions. To test this hypothesis, we compiled data on flash floods in central western Europe and selected precipitation events above 40 mm h−1 from radar data (RADOLAN, DWD). Moreover, we identified proxy parameters representative for flash flood favouring atmospheric conditions from the ERA5 reanalysis dataset. High specific humidity in the lower troposphere (q ≥ 0.004 kg kg−1), sufficient latent instability (CAPE ≥ 100 J kg−1) and weak deep-layer wind shear (DLS ≤ 10 m s−1) proved to be characteristic for long-lasting intense rainfall that can potentially trigger flash floods. These atmospheric parameters, as well as the flash flood and precipitation events were then analysed using linear models. Thereby we found significant increases in atmospheric moisture contents and increases in atmospheric instability. Parameters representing the motion and organisation of convective systems occurred slightly more often or remained unchanged in the time period from 1981–2020. Moreover, a trend in the occurrence of flash floods was confirmed. The number of precipitation events, their maximum 5-minute intensities as well as their hourly sums were however characterized by large inter-annual variations and no trends could be identified between 2002–2020. This study therefore shows that the link from atmospheric conditions via precipitation to flash floods cannot be traced down in an isolated way. The complexity of interactions is likely higher and future analyses should include other potentially relevant factors such as intra-annual precipitation patterns or catchment specific parameters.

In recent years, flash floods repeatedly occurred in temperate regions of central western Europe. Unlike in Mediterranean catchments, this flooding behaviour is unusual. In the past, and especially in the 1990s, floods were characterized by predictable, slowly rising water levels during winter and driven by westerly atmospheric fluxes (Pfister et al., 2004). The intention of this study is to link the recent occurrence of flash floods in central western Europe to extreme precipitation and specific atmospheric conditions to identify the cause for this apparent shift. Therefore, we hypothesise that an increase in extreme precipitation events has subsequently led to an increase in the occurrence of flash flood events in central western Europe and all that being caused by a change in the occurrence of flash flood favouring atmospheric conditions. To test this hypothesis, we compiled data on flash floods in central western Europe and selected precipitation events above 40 mm h−1 from radar data (RADOLAN, DWD). Moreover, we identified proxy parameters representative for flash flood favouring atmospheric conditions from the ERA5 reanalysis dataset. High specific humidity in the lower troposphere (q ≥ 0.004 kg kg−1), sufficient latent instability (CAPE ≥ 100 J kg−1) and weak deep-layer wind shear (DLS ≤ 10 m s−1) proved to be characteristic for long-lasting intense rainfall that can potentially trigger flash floods. These atmospheric parameters, as well as the flash flood and precipitation events were then analysed using linear models. Thereby we found significant increases in atmospheric moisture contents and increases in atmospheric instability. Parameters representing the motion and organisation of convective systems occurred slightly more often or remained unchanged in the time period from 1981–2020. Moreover, a trend in the occurrence of flash floods was confirmed. The number of precipitation events, their maximum 5-minute intensities as well as their hourly sums were however characterized by large inter-annual variations and no trends could be identified between 2002–2020. This study therefore shows that the link from atmospheric conditions via precipitation to flash floods cannot be traced down in an isolated way. The complexity of interactions is likely higher and future analyses should include other potentially relevant factors such as intra-annual precipitation patterns or catchment specific parameters.

More frequent high-intensity, short-duration rainfall events increase the risk of flash floods on steeply sloped watersheds. Where measured data are unavailable, numerical models emerge as valuable tools for predicting flash floods. Recent applications of various hydrological and hydrodynamic models to predict overland flow have highlighted the need for improved representations of the complex flow processes that are inherent in flash floods. This study aimed to identify an optimal modeling approach for characterizing leaf litter losses during flash floods. At a gauged watershed in the Hidegvíz Valley in Hungary, a physical-based model was calibrated using two distinct rainfall–runoff events. Two modeling methodologies were implemented, integrating canopy interception and leaf litter storage, to understand their contributions during flash flood events. The results from the model’s calibration demonstrated this approach’s effectiveness in determining the impact of leaf litter on steep-sloped watersheds. Soil parameters can estimate the behavior of leaf litter during flash flood events. In this study, hydraulic conductivity and initial water content emerged as critical factors for effective parametrization. The findings underscore the potential of a hydrodynamic model to explore the relationship between leaf litter and flash flood events, providing a framework for future studies in watershed management and risk-mitigation strategies.

Extreme rainfall events can trigger flash floods that pose serious risks to communities, infrastructure, and critical services, particularly in arid and rapidly urbanizing environments. In the Kingdom of Saudi Arabia, short hydrological response times, strong spatial variability of precipitation, complex topography, and limited observational data significantly challenge flood early warning capabilities, which affect emergency management at the national scale. Addressing these challenges requires integrated and scalable hydro-meteorological forecasting systems capable of operating across large spatial domains while resolving convective weather events and associated localized flood impacts in urban/suburban areas.This study presents a nationwide, operational flash flood early warning system developed for the Kingdom of Saudi Arabia. The system is designed to provide consistent coverage across the country while capturing fine-scale weather, hydrological and hydrodynamic processes relevant to flash flooding in arid environments. It operates over 137 hydrological domains, representing more than 6,000 outlets, delivering 2D flood simulations at a spatial resolution of 30 m nationwide, with enhanced resolution of up to 2.5 m in selected urban areas.The forecasting framework is structured as an end-to-end modeling chain that links atmospheric forcing, hydrological response, hydraulic flood propagation, and infrastructure impacts. High-resolution numerical weather predictions generated by the Weather Research and Forecasting (WRF) model are combined with real-time radar and rain gauge observations to produce hourly ensemble weather and precipitation forecasts and hindcasts. These meteorological inputs drive a distributed hydrological model (CREST), which simulates runoff generation across arid catchments using spatially explicit information on topography, land cover, soil properties, and drainage networks. A reservoir management module is fully integrated within the modeling chain, allowing the system to account for reservoir storage dynamics, controlled releases, and spillway operations, and to assess the influence of dam infrastructure on downstream flood evolution.Hydrological outputs are used as boundary conditions to a two-dimensional hydrodynamic model, which simulates floodplain dynamics, water depths, and inundation extents.All model components are coupled within a WebGIS-based operational platform that displays deterministic and ensemble weather and hydrologic forecasts, probabilistic flood warnings, and real-time nowcasting products. Flood hazard information is delivered through interactive maps, warning levels, and time series, to support decision- making by civil protection authorities and emergency managers at national and local scales.The functionality and operational performance of the system are demonstrated through its application on a recent extreme rainfall and flash flood events that affected the entire region of Saudi Arabia in the period of December 9-16, 2025. The system successfully captured the timing, spatial extent, and severity of flooding across multiple domains, providing useful lead times and high-resolution inundation maps. This case study highlights the robustness, scalability, and operational value of the framework, demonstrating its potential to enhance flood preparedness through early warning, and risk management across the Kingdom of Saudi Arabia under increasing hydro- meteorological extremes.

Arid regions are prone to unprecedented extreme rainfall events that often result in severe flash floods. Using near-real-time precipitation data in hydrological modelling can aid in flood preparedness. This study analyzed rainfall data obtained from Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG V. 06) since 2001 to highlight recent trends of extreme rainfall indices for three selected watersheds in the UAE. Additionally, to validate the trends, the present study incorporated CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) into the analysis. Furthermore, for the first time, this study assessed the performance of the three products of IMERG in modelling flash flood events in the selected watersheds of UAE. A physical-based, fully distributed model was used to simulate the heaviest storm event. Also, a sensitivity analysis of the model’s output to variations in the input parameters was conducted using the one-factor-at-a-time method. The result of the trend analysis indicated that IMERG and CHIRPS show similar trends in both datasets, indicating agreement and reliability in their observations. However, there are a few instances where IMERG and CHIRPS show slight discrepancies in the nature of the trend. In general, the trend analysis results indicated an increasing trend of total precipitation (mm) and consecutive wet days, which suggests a rise in the risk of flash floods. The simulation of the flash flood event showed that the IMERG final product outperformed the other two products, closely matching the model output of the gauge rainfall data with mean absolute error (MAE) of 1.5, 2.37, and 0.5 for Wadi Ham, Wadi Taween, and Wadi Maidaq, respectively. The model’s performance was positively correlated with the size of the watershed. The sensitivity analysis results demonstrated that the model’s output was most sensitive to infiltration parameters. The study’s outcomes provide a good opportunity to improve near-real-time impact evaluation of flash flood events in the watersheds of the UAE.

This research aimed at assessing flood hazard areas and flood literacy of the elderly population in Bangkok, Thailand and analyzing their flood preparedness through SWOT analysis. Expert interviews and a community survey were conducted. Using the analytic hierarchy process (AHP) and GIS technique, the results indicated that land-use, drainage density, and annual maximum rainfall were the most heavily weighted factors in flood hazard mapping in Bangkok. About half (50.32%) of Bangkok’s total area was defined as high flood hazard area. A total of 736 questionnaires were distributed in flood-prone areas and in the areas with the highest percentage of elderly population. The results of both SWOT and survey analysis found that many senior citizens have low digital and media literacy and limited experience in using information technology for flood preparedness. Lack of integration of disaster risk reduction and aging population policy, ineffective warning system, and lack of access to disaster preparedness training were the key barriers in reducing vulnerability to flood hazard. The survey revealed that the majority of elderly respondents (75%) have neither used online applications for their flood hazard management both before and during flood disaster nor shared/communicated information via online platforms. Some respondents (13%) used Facebook and Line applications to obtain information before a flood event. Very few of the elderly respondents (&lt;2%) accessed the national/provincial web-based platform to find out flood-related information. Almost all respondents, especially who are living in high-risk flood zones, had never participated in the community training of flood preparedness and management. Therefore, effective strategies in enhancing social engagement of the elderly and their literacy skills in flood risk preparedness and management are urgently needed.

Earth Observation from space has allowed characterizing, detecting, and managing natural hazards in spatiotemporal scale. Flash flood is the most frequent natural disaster that causes destruction to human lives, the economy, and infrastructure. Thus, developing a flash flood hazard zone (FFHZ) map is significant for comprehensive flash flood risk assessment and management to minimize its harmful effects, particularly in residential areas, because of climate change. Therefore, in this article, ten parameters derived from satellite images, including lithology, slope, topographic wetness index (TWI), Stream Power Index (SPI), Stream Transport Index (STI), Terrain Roughness Index (TRI), drainage density (Dd), distance to river, radar intensity map, and rainfall distribution map, were fused to predict the flood-vulnerable areas through GIS-based overlay analysis after normalization and assigning weight by applying Analytical Hierarchy Analysis (AHP). The findings allowed for the identification of the most vulnerable areas and provided an explanation for the flood's effects on New Qena City (NQC). The output FFHZs of the Wadi Qena Basin (WQB) were divided into six hazard zones, i.e., extreme hazard (6.86%), very strong (15.04%), strong (18.74%), moderate (22.58%), low (22.80%), and very low (13.98%) susceptibility. Furthermore, approximately 35% of the under-construction NQC is subject to the extreme to very serious hazards, as opposed to the extension area to NQC east of the Qena-Safaga Road. Interferometry Synthetic Aperture Radar (InSAR) change detection coherence (CCD) and spatiotemporal analysis of Landsat and Sentinel-2 data revealed steady changes in vegetation and infrastructure from 1984 to present. Based on GIS analyses about 10, and 14% of the NQC can be inundated if the flood extends 500, and 1000 m around the flood canal, respectively. Thus, several strategies were advised to safeguard the development projects, particularly the residential sections of the under construction NQC, including erecting four dams with a total capacity of 300 million m3, reinforce the dam at Wadi Shahadein, constructing concrete chevron bunds along the flood zone, and extending the depths of the flooding canal.