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Abstract Some areas of Uttarakhand faced heavy rainfall during October 17-19th, 2021. In October, rainfall hit its all-time high. A sudden heavy rainfall occurred due to this, which has affected the daily life of humans. More than 50 casualties were recorded during this study period. The main focus of this study was to monitor the Uttarakhand flood event using satellite observations. The Nainital and Almora districts of the state were mainly affected by this sudden heavy rainfall. On October 18th, Nainital received the maximum rainfall of about 21.51 mm at 11:00 am (UTC). The Nainital district has recorded a cumulative rainfall of more than 300 mm on October 18th, 2021. From the observation, we find out that this heavy rainfall occurred due to a sudden cloud burst at Ramgarh in Nainital district. This sudden extreme rainfall further caused a flash flood in the study area. The rainfall pattern has moved towards Assam after it caused a flash flood in the Nainital district of Uttarakhand, India.

Flash floods and landslides are dangerous natural hazards in hilly areas. They often occur extensively and potentially cause widespread destruction to agriculture, infrastructure, roads, houses, and human beings. This research aimed to analyze the hazard susceptibility on a mountainous roadway using advanced Machine Learning (ML) models. We conducted field surveys to collect data on flash flood and landslide locations in 2017, 2018, and 2019 on a particular roadway in Vietnam, National Highway 6, consisting of 88 flash flood sites and 235 landslide sites. The state-of-art ML models were utilized for the predictive modeling, including AdaBoost-RBF, Bagging-RBF, MultiBoostAB-RBF, and Random Sub-spaceRBF, with Radial Basis Function (RBF) serving as the primary classifier. The AdaBoost-RBF model outperformed all others in predicting landslide and flash flood vulnerability. The resulting map showed that 44.89% or 14,183 ha is in very high susceptibility zones, 15.55% or 4914 ha is in high susceptibility zones, 10.37% or 3.275 ha is in moderate susceptibility zones, 13.69% or 4324 ha is in low susceptibility zones, and 15.50% or 4899 ha is in very low susceptibility zones. A detailed map of the areas where landslides and flash floods are most likely to occur on the roadway might provide local authorities with crucial information for disaster management.

The Masamba area of North Luwu Regency has been hit by a flash flood disaster on July 13, 2020. The flash flood claimed dozens of lives, hundreds of people were injured and thousands of houses were submerged. Based on the analysis of several information, the cause of the flash flood in Masamba was due to high rainfall and landslides that occurred in the upstream area. Land movement vulnerability zoning is needed in this area to provide information in making disaster mitigation policies for post-disaster planning and development. Frequency Ratio and Weight of Evidence methods were applied in this study by using parameters such as: slope, lithology, land cover, rainfall, slope direction, slope convexity, distance from river, distance from fault and soil type. The Weight of Evidence method provides more accurate results with an accuracy rate of 99.83%. Vulnerability zoning of landslides in the Masamba area are grouped into 5 classes; The zone of vulnerability to soil movement is very high, around 6,822.27 ha or about 25.47% of the research area. The high ground movement vulnerability zone is about 4261.84 ha or about 15.91% of the research area.

Study region: Francolí River (Catalonia, Iberian Peninsula). Study focus: The aim is the reconstruction of the October 2019 flash flood, that was documented through extensive field work: rainfall (300 mm in just a few hours), flood marks, times of flood passage and witnesses' snapshots and reports, channel changes, log drift (20,000 trees) and woody debris at bridges, as well as large damage and six fatalities. The methods are: hydrological model built for the rainfall-runoff in the basin and the flood routing in the river, use of hydraulic principles such as flow at waterfalls, flow against obstacles (trees), etc. and finally 1D/2D free surface numerical models. New hydrological insights: The uppermost 100 km2 produced discharges of 700 m3/s (up to 50 m3/s/km2, locally). Three bridges failed, but their cascading failure (when one failure triggers the next one downstream) was not proved. The main channel widened more than 10 times, dragging away soil and vegetation like a bulldozer. The resulting large wood debris that clogged two bridges worsened the inundation. An anomalous flow downstream, probably a surge of around 1090 m3/s, due to the failure of a woody jam at a narrow bridge, took two lives. Water Authority is now warning flood planners that vegetated, torrential basins may cause catastrophic floods in the valley towns, if their narrow bridges are sensitive to woody debris.

This work integrates topographic slope with other geo-environmental flood-causing factors in order to improve the accuracy of flood prediction and susceptibility mapping using logistic regression (LR) model. The work was done for the eastern Jeddah watersheds in Saudi Arabia, where flash floods constitute a danger. A geospatial dataset with 140 historical flood records and twelve geo-environmental flood-causing factors was constructed. A number of significant statistical methods were also applied to provide reliable flood prediction and susceptibility mapping, including Jarque–Bera, Pearson's correlation, multicollinearity, heteroscedasticity, and heterogeneity analyses. The results of the models are validated using the area under curve (AUC) and other seven statistical measures. These statistical measures include accuracy (ACC), sensitivity (SST), specificity (SPF), negative predictive value (NPV), positive predictive value (PPV), root-mean-square error (RMSE), and Cohn's Kappa (K). Results showed that both in training and testing datasets, the LR model with the slope as a moderating variable (LR-SMV) outperformed the classical LR model. For both models (LR and LR-SMV), the adjusted R2 is 88.9 and 89.2%, respectively. The majority of the flood-causing factors in the LR-SMV model had lower Sig. R values than in the LR model. As compared to the LR model, the LR-SMV attained the highest values of PPV (90%), NPV (93%), SST (92%), SPF (90%), ACC (89%), and K (81%), for both training and testing data. Moreover, employing slope as a moderating variable demonstrated its viability and reliability for defining precisely flood-susceptibility zones in order to reduce flood risks. [ABSTRACT FROM AUTHOR]

Flash floods are natural hazards and often occur in small and mountainous river basins with low monitoring. The hydrological and hydrodynamic reconstruction of past rainfall events is useful for understanding the phenomena that led to a flood. This study aims to reconstruct a rainfall event that triggered landslides and floods in 2017 in the Rolante basin (771 km2), southern Brazil, a region with low monitoring. Due to the large magnitude of the flood event, a question was raised whether only the basin response to intense rainfall could have caused that flood. Therefore, different rainfall scenarios were tested with the use of official rain gauges and unofficial rainfall information from local farmers to determine the spatial and temporal distribution of rainfall. The reconstruction of the rainfall event was performed with the use of a hydrologic model (HEC-HMS) to define hydrographs and a hydrodynamic model (Nays2D Flood) to simulate flood propagation, with adjusted methods for the poorly monitored basin. The maximum flood depth and extent were analysed for three rainfall scenarios. The results showed that, with the information provided by the residents, it was possible to determine that extreme and concentrated rainfall occurred in the mountainous area and the basin ordinary response to that rainfall may have caused a flood of that great magnitude. The analysis of past extreme events can contribute to verifying if there are changes in the rainfall patterns and can assist in risk mitigation and disaster management, primarily in ungauged basins. [ABSTRACT FROM AUTHOR]

Flash floods, produced by heavy seasonal rainfall and characterized by high speeds and destructive power, are among the most devastating natural phenomena and are capable of causing great destruction in very little time. In the absence of hydrological data, morphometric characterization can provide important information on preventive measures against flash floods. A priority categorization of hydrographic units in the Cañete River basin was carried out using morphometric analysis together with a weighted sum analysis (WSA) based on a statistical correlation matrix. The delineation of the drainage network was performed based on Digital Elevation Model (DEM) data from the Shuttle Radar Topography Mission (SRTM). The Cañete River basin was subdivided into 11 sub-basins, and 15 morphometric parameters were selected. The priority category (very high, high, and moderate) of each sub-basin was assigned according to the value of the composite factor obtained through WSA. The results of this analysis showed that 26.08% of the total area is under a very high flash flood risk (sub-basins 3, 9, and 11), 38.46% is under a high flash flood risk (sub-basins 5, 7, 8, and 10), and 35.45% is under a moderate flash flood risk. This study concludes that flash floods predominate in sub-basin 3 and that downstream areas present characteristics of river flooding (sub-basins 9 and 11). [ABSTRACT FROM AUTHOR]

Land use and landscape structure play an important role in the functioning of flash floods on the arable plateaus of northern France. Landscape structures have changed considerably over the last decades with an increase in runoff-producing surfaces and an enlargement of the plots. This evolution results in an increase in runoff volumes accompanied by an increasingly easy diffusion of runoff on the slopes. There is therefore potentially an increasingly frequent and important spatial connectivity from the plots to the thalwegs, which can lead to the formation of flash floods. This study proposes to model this diachronic evolution of connectivity in a small agricultural basin of Seine Maritime using a multiagent system (MAS) and to develop synthetic indicators characterising these spatial links in the flow processes. The model outputs show that spatial connectivity has been steadily increasing over the past 70 years due to the enlargement of the parcel grid and the growth of runoff surfaces. For example, for the same 20 mm/h rainfall, the connectivity indicator increases from 40.99% (in 1947) to 78.33% (in 2015). This observation is observed for all levels of rainfall intensity, including the lowest. This modelling, carried out for a 116 ha basin in arable farming, can be transposed to all small agricultural basins. [ABSTRACT FROM AUTHOR]

The frequency and magnitude of flash floods in the olive orchards of southern Spain have increased because of climate change and unsustainable olive-growing techniques. Affected surfaces occupy > 85 % of the rural regions of the Upper Guadalquivir Basin. Dangerous geomorphic processes record the increase of runoff, soil loss and streamflow through time. We report on ripple/dune growth over a plane bed on overland flows, deep incision of ephemeral gullies in olive groves and rock-bed erosion in streams, showing an extraordinary sediment transport capacity of sub-daily pluvial floods. We develop a novel method to design optimal solutions for natural flood management and erosion risk mitigation. We adopt physical-based equations and build a whole-system model that accurately reproduces the named processes. The approach yields the optimal targeted locations of nature-based solutions (NbSs) for active flow-control by choosing the physical-model parameters that minimise the peak discharge and the erosion-prone area, maximising the soil infiltration capacity. The sub-metric spatial resolution used to resolve microtopographic features of terrains/NbS yields a computational mesh with millions of cells, requiring a Graphics Processing Unit (GPU) to run massive numerical simulations. Our study could contribute to developing principles and standards for agricultural-management initiatives using NbSs in Mediterranean olive and vineyard orchards. [ABSTRACT FROM AUTHOR]

When the center of Typhoon Bilis was about 500 km away, an extreme flash-flooding storm hit Lechang City on July 14, 2006, which is located at Nanling Mountains in northern Guangdong Province, China. This study demonstrates that the extreme flash-flooding storm originated from the Dongjiang Reservoir basin in Hunan Province during the accelerated movement of the typhoon, with a life cycle of more than 4 h and travel distances of more than 100 km beyond the reservoir shoreline. Based on high-resolution weather radar data and terrain data, this study employs geographical information system techniques to reveal complex roles of Nanling Mountains in aggravating the extreme precipitation in Lechang by intensifying the storm and changing its propagation direction. Our investigations indicate an extreme storm changed direction two times as it passed Nanling Mountain and stayed over Lechang for a long time. The valley on the northwest of Tiantoushui River basin played a primary role in controlling the convective cells to hit Lechang in an unusual direction under the influence of typhoon. Detailed analysis shows meso-scale and miso-scale terrain, including narrow valley, low mountain and small reservoir, may promote convection as same as high mountain under the influence of typhoon, which are poorly resolved in numerical models. Besides, this research shows the shape of meso-scale mountain also has a significant impact on distribution of severe convection during this extreme storm. More importantly, we found atmospheric inversion over Lechang City before the major storm based on the latest AIRS product. Our findings suggest that the construction of large reservoir in typhoon-prone areas requires comprehensive analysis of the complex interactions between typhoons and terrain in order to avoid the threat of extreme storms to the surrounding areas of the reservoir. [ABSTRACT FROM AUTHOR]

Visible flood waves, described as abrupt wave front events (AWF), have been identified on rivers in northern England rising in the Pennines, from both historical and recent gauged data. The focus of this paper is on the characteristics of two gauged AWF events on the Rivers Wear and Tees in 1983 and their comparison to 'normal' floods. The description and analysis is based on contemporaneous photographs and observations and on digital level and flow records. The rapid 15-min rise in these events is compared with the maximum rate of rise in annual maximum peak floods by comparing flood hydrographs. The propagation of the flood wave downstream is illustrated. The 15-min increase in discharge is compared in relation to the peak flow for AWF and normal floods at different gauged locations down the catchments showing striking differences. The character of the AWF response in the vertical or near-vertical wave front and rapid increase in both level and discharge points to the occurrence of kinematic shock waves. [ABSTRACT FROM AUTHOR]

This research aims to map flood inundated areas under changing climate in the Boyo watershed of Southern Ethiopia. A semi-distributed physically based Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) and Hydrologic Engineering Center-River Analysis System (HEC-RAS) were used to simulate the flood events and maps, respectively, for climate scenarios. The bias-corrected data of four climate models were used for the baseline (1976–2005), mid-term (2041–2070) and long-term (2071–2100) cycles under RCP4.5 and RCP8.5 scenarios. The 50- and 100-year return period flood events were generated from the baseline and future period streamflow data. The HEC-RAS model was used to simulate the inundation areas and depths from the flood events. The result exhibited that the average annual rainfall and maximum and minimum temperatures of the catchment will increase in the future with an increase in annual runoff. The severity of annual floods would increase in the future under RCP4.5 and RCP8.5 scenarios. Approximately, 193 ha of the study may be flooded with flood events having a return period of 100 years under the RCP8.5 scenario in the long-term period, which is an extreme case. The result is a benchmark to reduce the flood risk and management of floodplains in this watershed. HIGHLIGHTS The result is a benchmark to reduce the flood risk and management of floodplains in this watershed.; This study will be helpful for cities, farming communities nearby the river bank, local community and government bodies concerned with risk management.;

Chamoli district of Uttarakhand, India, witnessed unprecedented damage to life, property, infrastructure, and landscape due to flash flood triggered on 7th February 2021. During winters, massive debris flow in the Raunthi Gad catchment put a great ambiguity on disaster preparedness. Sustained heavy precipitation for the two days prior to the event and wedge failure structural favorability might have aided the landslide and triggered rock-avalanche. Due to the landslide, the impounding of the river waters resulted in temporary dam creation in the Rishiganga valley, which ultimately led to the breaching. By coupling the data obtained from satellite imagery, characteristic scientific case studies and reports, it can be inferred that the most possible cause is the interplay of extreme meteorological phenomena and particular geological scenarios including the formation of wedge geometry by the intersection of joint and foliation planes in migmatite and tension cracks at crown of slope. Critical reviews over extreme furry of nature and terrain response have also been discussed.

Lack of high-resolution data and inappropriate integration of different data sources make modelling flash flood even more complicated. The IHACRES and AHP models were used to estimate floods for the period 1987 to 2007 for Wadi Al Jizzi arid catchment. The IHACRES model results showed that the average simulated flood was 0.36 m3/s, while that observed for all flood storms was 0.30 m3/s. The average readjusted AHP Simulated Flood for three statically defined clusters: low, moderate, and high rainfall was 3.55, 3.20, and 3.75 m3/s, respectively. The average observed flooding for low, moderate, and high rainfall were 3.23, 1.54, 3.07 m3/s. Pearson correlation between observed and simulated flood showed significant values for IHACRES and AHP with a range of 0.84 and 0.89 respectively. The Nash-Sutcliffe efficiency of the IHACRES model was 0.78, while it shows a good performance for low and high AHP re-adjusted values, which was 0.81 and 0.82. HIGHLIGHTS Identification of extreme hydrologic events for arid areas is developed.; The applied two models were able to represent the actual flood even with limited number of storms.; The AHP performed better than IHACRES in simulating flood events.; For arid areas, hydrologic models require additional readjustment to better simulate flood.; Correlation between the several hydrologic parameters is identified.;

Indonesia is one of the countries in the world that is prone to various types of natural disasters such as Volcanic Eruptions, Earthquakes, Tsunamis, Landslides and Floods. The Geographical condition of the Indonesian territory makes it vulnerable to various kinds of natural disasters (BNPB, 2018). For the development of communication science, Mass Media's role is completed by acceleration of information from Online Media then Social Media. Now, industry too fast to self-involved in publishing information through Social Media. Disaster information must be conveyed by the Mass Media and socialization efforts from the disaster are also needed to community can anticipate further disasters. This research has the significance of how BNPB as a disaster management institution is able to utilize verified Social Media to provide information disclosure. Socialization delivered by Mass Media to Social Media has the same goal, as a tool to convey various disaster efforts that are equipped with data and guidelines. One of the Social Media used as an effort to socialize disaster mitigation is Twitter @BNPB_Indonesia which aims to convey information about disaster mitigation facilities in order to reduce the adverse effects caused by disasters that occur. The purpose of this study is to find out how the disaster mitigation strategy of BNPB through Twitter manages information disclosure. This study uses a Qualitative Approach with the Case Study method on the object of research on the official Twitter account of BNPB, through observation of data on information shared on BNPB's Twitter during the Flash Flood disaster in April 2021, which is studied with Media Consumption Theory. The conclusion of this research is Twitter @BNPB_Indonesia has implemented a flash flood Disaster Mitigation Strategy in Nusa Tenggara Timur Province properly and transparently, reinforced by various data and guidelines in the Buku Saku Hadapi Banjir that published by BNPB in 2019.

The role of floods in sediment transport and river morphology has been proven. In this study, the effect of different parameters on the transfer of sediment bed load under flash flood has been investigated. The input flood hydrograph of the symmetric triangular type with the base time of 90 sec and peak flow rate 30 and 45 lit/s were considered. Sediment particles of quartz type with a moderate diameter of 1.2 and 3 mm and two bed slopes of 0.006 and 0.014 were tested. In this study, changes in water surface profile, rate of bed load in steady and unsteady conditions, and unsteadiness parameter relative to total work done of flow and sediment rate were investigated. By using dimensional analysis, the parameters affecting sediment transport were determined and evaluated in experiments. The results showed that the unsteadiness parameter in unsteady flow had a significant effect on sediment transport. On the other hand, the work done by the flow has a greater impact on sediment transport than the unsteadiness number. In this regard, the effect of channel slope on sediment transport should be considered. The role of channel slope in the transfer of bed load is very important so that by doubling the bed slope, the total amount of sediment transferred to the downstream increases almost 5 times. Also, with increasing the sediment flow rate, the unsteadiness parameter increases and it plays an effective role in the whole work. In general, in high-value hydrographs, the amount of transfer sediment increases and there is a large relationship between the amount of transfer sediment and the total flow work. Reducing the time of the rising arm of the hydrograph shows the effect of increasing the flow rate, which is effective in these waterways, so that with the faster the flood peak time, the more sediment is transferred and the probability of damage and destruction increases.

The Bahorok River basin has a high flash-flood hazard index. This is shown by loss of lives and damage of homes due to floods in recent years, however, no research examined community preparedness on the hazard of flash-flood. This research aimed to assess the effect of disaster experience and flood-risk perception on disaster preparedness of the people of Bukit Lawang Plantation Village. A cross-sectional survey design was used to determine the relationship between disaster experience, risk perception and preparedness as the independent and dependent variables, respectively. The results showed that disaster experience and risk perception positively and significantly affect the community preparedness. Disaster risk reduction programs in the region only focus on emergency response, rehabilitation, and reconstruction. Furthermore, increasing public awareness and preparedness has not been prioritized in reducing flood risk. This is an essential aspect for consideration because mountainous areas are often marginalized and lack access to disaster risk reduction programs.

Abstract The internet of things is a disruptive technology that has been applied as a solution to problems in many fields of monitoring environmental variables. It is supported by technologies such as wireless sensor networks, which offer many protocols and hardware platforms in the market today. Protocols such as 6LoWPAN are novel, so this work focuses on determining whether its implementation on TelosB mote is feasible; these would be placed on an experimental deployment for a particular scenario of flash floods in a sector known as “La Brigada”, in the city of Barranquilla. This proposal has not been evaluated in Colombia for this type of application, and no similar work has been done for this type of scenario. For the evaluation of 6LoWPAN, a deployment with two end nodes and a sink node has been designed, due to the monitoring section under study; 5-min tests are proposed where through round trip time traffic PINGv6 packets are generated back and forth (Echo) between a sink node and two end nodes. The results are based on the evaluation of metrics such as delay and ping packet request/response rate. The performance of these metrics is subject to test scenarios that vary according to distance, packet size, and channel scan time. Two routing options, static or dynamic, are also proposed for this application case. The tests performed yielded results in terms of better performance in the test scenarios for packets with an average size of 120 B and channel monitoring times of 1024 ms. Likewise, the use of the TelosB platform was validated as a viable and innovative option for a monitoring scenario to flash floods in short stretches of the city of Barranquilla—Colombia. This study is important because it can provide information on the use of the TelosB platform as a valid solution for similar application scenarios; furthermore, the tests performed can be replicated in similar studies to evaluate congestion, power consumption, routing, topologies, and other metrics. This study is providing a road map for the research community to follow the simulation scenario to apply the test to their own studies. This work also provides the guidelines for similar researchers to monitor the flood in their own regions and then compare their results with this study.

The territory of the Uttarakhand Himalaya is highly susceptible to meteorological and geophysical hazards. Earthquakes, cloudburst-triggered landslides, debris flows, and flash floods are very common, frequent, intensive, and devastating. Snow avalanches/glacier outbursts are rare, however, they are very dangerous. This article examines the Rishi and Dhauli Ganga tragedy that occurred due to glacier outbursts on February 7, 2021 in the source area of Rishi Ganga, i.e., ‘the Nanda Devi glacier’ in Chamoli district, Uttarakhand. It describes the major drivers, which triggered debris flows/flash floods in the Rishi and Dhauli Ganga valleys, and illustrates its consequences. The calamity has led to the loss of approximately Rs. 20,000 million and the death of about 205 people. Land degradation, loss of soils and forests, and formation of landslide scars in the affected areas were other consequences. This study suggests several policy measures to reduce the casualties related to natural hazard processes.

From late May to early June 2022, 130 people died in catastrophic landslides and flash flood events triggered by exceptionally heavy rains in the states of Pernambuco, Alagoas, and Paraíba, along the coast of Northeast Brazil. Total rainfall in the city of Recife on May 25–30 was 551 mm, 140 mm higher than the average of the month of May. Rain was heaviest on May 25 and 28, with 100–200 mm and 151–250 mm, respectively. This coincided with easterly wave disturbances. May 28 saw the most rain, due to a significant cold front. Fourteen municipalities in the metropolitan region of Recife declared a state of emergency. According to the Civil Defense of Pernambuco state, the rain impacted 130,000 people there. Most of the heavy precipitation fell over areas with medium to very high geological vulnerability to landslides and extreme hydrological events. The loss of life and substantial economic impacts in Recife caused by the heavy precipitation of May 2022 and the disasters induced by it show that this city, like many others around the world, has limited capacity to cope with climate extremes. Urbanization has increased population density occupying hills and slopes of the city, contributing to the problem. To reduce the impact of such disasters, residents must be made aware of the risks of climate-related events, and they must be encouraged to heed alerts warning of natural disasters issued by state and federal institutions. Efficient monitoring of risk is also needed. Risk management will be viable only when everyone participates, which requires education and cultural change.

Urban sewage sludge (USS) is increasingly being used as an alternative organic amendment in agriculture. Because USS originates mostly from human excreta, partially metabolized pharmaceuticals have also been considered in risk assessment studies after reuse. In this regard, we investigated the cumulative effect of five annual USS applications on the spread of antibiotic-resistant bacteria (ARB) and their subsequent resistance to toxic metals in two unvegetated soils. Eventually, USS contained bacterial strains resistant to all addressed antibiotics with indices of resistance varying between 0.25 for gentamicin to 38% for ampicillin and azithromycin. Sludge-amended soils showed also the emergence of resistome for all tested antibiotics compared to non-treated controls. In this regard, the increase of sludge dose generally correlated with ARB counts, while soil texture had no influence. On the other hand, the multi-antibiotic resistance (MAR) of 52 isolates selected from USS and different soil treatments was investigated for 10 most prescribed antibiotics. Nine isolates showed significant MAR index (≥ 0.3) and co-resistance to Cd, As and Be as well. However, events including an extreme flash flood and the termination of USS applications significantly disrupted ARB communities in all soil treatments. In any case, this study highlighted the risks of ARB spread in sludge-amended soils and a greater concern with the recent exacerbation of antibiotic overuse following COVID-19 outbreak. [ABSTRACT FROM AUTHOR]

Rainfall is a spatiotemporally variated process and one of the key elements to accurately capture both catchment runoff response and floodplain extents. Flash floods are the result of intense rainfall, typically associated to highly variable rain in both space and time, such as convective storms. In this work, the extent within-storm variability affects runoff and flooding is explored. The Kan catchment (Tehran, Iran) is used as base topography for the simulations. The allochthonous nature of floods in the catchment and how they interact with the effects of storm variability are further investigated. For this, 300 synthetic rainfall signals with different hyetograph variabilities are generated and imposed on a 1D/2D hydrodynamic model. Additionally, a set of simulations with different levels of spatial variability are performed. The results suggest that temporal and spatial variability affect the runoff response in different degrees. Peak discharge and hydrograph shapes, as well as flooded areas, are affected. The effect of storm temporal variability is shown to be significantly higher than storm spatial variability and storm properties such as return period, duration, and volume. Further on the influence of storm spatiotemporal variability on stream discharge and flood response is seen to be strongly dependent on the location within the drainage network at which it is assessed. [ABSTRACT FROM AUTHOR]

According to the United Nations (UN), an additional 1.35 billion people will live in cities by 2030. Well-planned measures are essential for reducing the risk of flash floods. Flash floods typically inflict more damage in densely populated areas. The province of Hail encompasses 120,000 square kilometers, or approximately 6% of the total land area of the Kingdom of Saudi Arabia. Due to its innate physiographic and geologic character, Hail city is susceptible to a wide variety of geo-environmental risks such as sand drifts, flash floods, and rock falls. The aim of this work is to evaluate the rate of urban sprawl in the Hail region using remote sensing data and to identify urban areas that would be affected by simulated worst-case flash floods. From 1984 to 2022, the global urbanization rate increased from 467 to 713% in the Hail region. This is a very high rate of expansion, which means that the number of urban areas exposed to the highest level of flood risk is rising every year. With Gridded Surface Subsurface Hydrologic Analysis (GSSHA), a wide range of hydrologic scenarios can be simulated. The data sources for the soil type, infiltration, and initial moisture were utilized to create the coverage and index maps. To generate virtual floods, we ran the GSSHA model within the Watershed Modeling System (WMS) program to create the hazard map for flash flooding. This model provides a suitable method based on open access data and remote data that can help planners in developing countries to create the risk analysis for flash flooding. [ABSTRACT FROM AUTHOR]

With the spatial–temporal variability of rainstorms becoming more diversified, it is urgent to summarize how the spatial–temporal variability of rainstorm affects the flash flood discharge process and to explore its internal mechanism. This work proposes a research framework based on the rainstorm spatial–temporal structure design method and the quantitative analysis of flash flood discharge process modeling. This framework generates rainstorm data with different spatial–temporal variability through the rainstorm spatial–temporal structure design method, and further simulates discharge process under different rainstorm scenarios through the hydrodynamic model. Based on the analysis of simulated results, the error correction coefficient is generated to improve the accuracy of simulation. In this study, the Baogaisi watershed was used for simulation. The results show that when the rainstorm center is at the upstream watershed, the peak discharge increases, and the flood peak time is advanced because of the transformation of gravitational potential energy into kinetic energy. When the rainstorm center is fixed at a position, the total flood volume and the peak discharge are about 2 ~ 10 times that of uniform spatial distributed scenario, the flood peak time can be advanced to 55 min. In the mobile rainstorm, the peak discharge and the total flood volume are significantly reduced and the flood peak time is lagged, the flood peak discharge can be reduced by up to 30% of the uniform spatial distributed scenario. Strengthening the understanding of the impact can help to improve the accuracy of discharge process simulation. [ABSTRACT FROM AUTHOR]

Flash Flood Guidance (FFG) is a rainfall threshold which initiates flooding in streams. It merely provides a binary output (yes or no) which has large uncertainties in forecasting. In this paper, we propose a new method by combining FFG with the Frequentist method to present the probability of flash flood occurrence based on historical rainfall events. We first calculated deviation from the log transform rainfall data leading to flash floods. Kernel Density Estimation (KDE) was used to describe the deviation. Normal Distribution Function (NDF) was chosen to fit the KDE output and to calculate probabilities of flooding as per the Frequentist FFG. In order to aid decision making, three probability thresholds (10, 20 and 60%) were used for defining four flood risk classes, namely very low, low, significant and high, and were colour coded respectively as green, yellow, orange and red. The proposed Frequentist FFG method was then applied to the Posina River basin in Italy. Comparison of forecasts from the conventional FFG (with probability 0 or 1) and Frequentist FFG for 94 6-hourly rainfall events, including 23 flood events, shows that the Frequentist FFG presented a probability of flooding varying from 0 to 100% and the corresponding risk class can be used to reduce false alarms while still reducing the disaster risk. The application of the developed approach to the Posina basin shows that decision making regarding flash forecasting is easier with the presented approach compared to the traditional FFG approach. [ABSTRACT FROM AUTHOR]

This study aims to map flood susceptibility in the Qaa'Jahran watersheds located in Dhamar, Yemen, using geoprocessing and computational techniques. Historical flood data and SAR imagery were used to monitor and create a flood inventory map. The artificial neutral network (ANN) was trained using a novel algorithm called GWO_LM, which is a hybridization between the Levenberg-Marquardt algorithm (LM) and Grey Wolf Optimizer (GWO) meta-heuristic algorithm and compared the results with state of art machine learning algorithms. The GWO_LM_ANN model exhibited excellent performance in the evaluation, achieving a precision of 97.92%, sensitivity of 100%, specificity of 100%, F1 score of 98.95%, accuracy of 98.75% and AUC of 98.48. This indicates that using GWO_LM for training ANN enhanced the searching process for the optimal weights, resulting in outperforming other state-of-the-art models. The findings hold significant implications for disaster preparedness and response in the Qaa'Jahran watersheds, enabling targeted and efficient non-structural solutions to mitigate the detrimental effects of flash floods in particularly sensitive locations. The use of the previously unexplored GWO_LM model represents a notable advancement in flood susceptibility assessment, surpassing traditional methods and offering novel insights to the existing literature. [ABSTRACT FROM AUTHOR]

Flash floods are the most hazardous types of floods, specifically in urban areas, since they impose huge financial damages and tremendous life loss. A flood risk map is required to identify the most vulnerable areas of a city for better management of this phenomenon. This research aims at achieving the risk and vulnerability maps of the city of Sanandaj, Kurdistan Province, Iran, using the geographical information system and fuzzy analytic hierarchy process through the assessment of several conditioning factors. The parameters slope, elevation, profile curvature, drainage density, land use, and distance from waterways were applied to prepare a hazard of flood map of Sanandaj city. Also, effective information layers, including slope, elevation, permeability index, distance from hospitals, distance from fire stations, distance from trails, distance from refueling centers, distance from roads, and distance from historical monuments, were considered for designing a flood vulnerability map. By multiplying the hazard of flood occurrence map and the flood vulnerability map, the flood risk map is obtained. The designed flash flood risk map demonstrated that about 30% of the city's areas were classified as the most prone to flash floods. The results indicate that the flash flood is a serious concern in the city of Sanandaj, which should be considered by the city's officials and authorities. The designed flood risk map can be used as an appropriate management tool for reducing or avoiding flood risks. [ABSTRACT FROM AUTHOR]

The Sinai Peninsula in Egypt is highly vulnerable to flash flooding due to its huge variation in relief and erratic rainfall. However, assessing flood risk in the Sinai is a difficult challenge due to the almost complete lack of accurate flood observations and relevant drainage basin characteristics. Therefore, this study evaluates the flood hazard in the Sinai Peninsula through multi-criteria analysis of morphometric characteristics of the drainage patterns, which can be easily inferred from readily available remote sensing data and geographical analysis tools. From a digital elevation model with a spatial resolution of 30 m, 112 catchments are identified, each characterized by twenty morphometric parameters, grouped into three categories: geometry, drainage network and relief. The importance of the morphometric parameters on flooding is assessed with the analytical hierarchy process. Normalized weights for each parameter and category, obtained from pairwise comparison matrices, allow to derive a flood sensitivity index and create a map showing different degrees of flash flood hazard. The results show that basins characterized as highly sensitive to flooding generally have high values for all three morphometric parameter categories: geometry, flow network and relief. About 17% of the Sinai appears to be very highly sensitive to flooding, 39% highly sensitive and 34% moderately sensitive. The very highly flood-prone basins are all located in the southern Sinai mountain ranges, while the highly flood-prone basins are mainly found along the outer edges of the southern Sinai mountain ranges and in some sub-basins of wadi El-Aris. Comparison with case studies reported in other publications and the media shows a strong agreement, indicating that the proposed methodology is reliable and accurate. Based on the obtained flash flood sensitivity map, management plans are proposed to reduce the risk of flash flooding and to protect major cities and roads by installing side channels and culverts to collect and drain the excess water from areas most affected prone to flooding. [ABSTRACT FROM AUTHOR]

Swamp forests are now at the edge of extinction in the Haor (Haor ecosystem is a type of wetland comprised of swamp forest located in the lowlands of the north-eastern part of Bangladesh which is characterized by a bowl or saucer shaped shallow depression) region of Bangladesh. To reverse such a trend, there is an urgent need to start a reforestation program. However, the silvics of individual species and dynamics of swamp forest stands are only marginally understood. Hence, the purpose of this study was to provide detailed information on swamp vegetation water tolerance range and to identify suitable habitat range for species that are dominant in the reforestation program. It was found that high water-tolerant species can tolerate waterlogging conditions for an average of 13 weeks, followed by 07 weeks by medium water-tolerant species and 02 weeks by low water-tolerant species. In the case of species water depth tolerance, the high water-tolerant group can tolerate an average of 4ft water followed by 2.5 ft water by medium and 1ft by low water tolerant group. Hijol (Barringtonia acutangula), Koroch (Pongamia pinnata), Pitali (Trewia nudiflora) and Borun (Crataeva magna) were the dominant species used for existing small scale reforestation programs. There are no significant differences in resistance against water flow among Hijol, Koroch, Pitali and Borun regardless of vegetation density and water depth. For future large-scale plantations, the machine learning model shows that more than 50% of Haor area is suitable for plantations by these four species. The information generated through this study can be beneficial to planners and managers to aid in developing plantation plans and the design of habitat restoration and enhancement efforts. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) models have become a well-established tool for channel flow, as well as rain-induced overland flow simulations. In channel flow simulations, slopes are usually less than a few percent and water depths are over several meters, while overland flow simulations show steep slopes and flow of a few centimeters. Despite these discrepancies, modelers transfer roughness coefficients, validated for channel flow, to overland flow. One purpose of this study is to verify whether roughness values from the literature are also valid for overland flow simulations. Laboratory experiments with different degrees of bed roughness, various discharges and a range of experimental flume slopes were carried out. For a given discharge, water depth was measured, and bed roughness was derived. Experimental results reveal that roughness shows no clear dependence on slope but is strongly dependent on water depth for vegetated surfaces. To verify the influence of different roughness approaches, they were implemented in a 2D model. A comparison of different simulation results indicates differences in the hydrograph. Here, consideration of water depth-related roughness coefficients leads to retention and translation effects. With the results of this study, modelers may enhance the precision of the hydraulic component in overland flow simulations. [ABSTRACT FROM AUTHOR]

The assessment of flash flood hazards in the coastal zone of Ras Ghareb City (RGC), Red Sea, Egypt, was accomplished through the use of GIS tools and the spatial multi-criteria approach. The presented work aims to assess, integrate, and generate potential flash flood hazard maps. The analytic hierarchy process was utilized to calculate weights of hazard and vulnerability of flash flood controlling factors and their parameters such as topographical, geological, and hydrological factors. In addition, the risk degree of each specific basin and its sub-basins is estimated by combining standardized parameter values. Despite its location in an arid region, the basin may receive a large amount of rainwater, which can cause flash floods at the basin's outlet. Recently, flash flooding took place in the coastal region of RGC in October 2016 and September 2020, resulting in the loss of many human lives and catastrophic effects on local infrastructure and surrounding environments. According to reports from Hurghada, Red Sea Governorate, the RGC experienced exceptional flooding that exceeded 120 million cubic meters as a result of 51 mm of rainfall. Based on the remote sensing satellite data such as Aster Digital Elevation Model (GDEM) and the GIS tools, the basin and sub-basin drainage patterns were delineated and compared with reference topographical map sheets of a scale of 1: 50,000. The sub-basins have been isolated and morphometrically studied to determine vulnerability to flash flooding. In addition, the flash flood threat model was developed using geoprocessing tools provided by ArcGIS software to incorporate all contributing factors spatially. The flash flood risk in the Ras Ghareb (RG) basins and their sub-basins has been identified and classified into three classes (high, medium, and low hazard degree). High and moderate flood-risk basins require comprehensive studies to introduce measures to protect certain areas from flood danger. Finally, the GIS and the spatial multi-criteria analyses were effective ways to carry out a flash flood management system in order to support the decision-makers by recommendations to conserve and mitigate the possible flash flood hazards in the study areas. [ABSTRACT FROM AUTHOR]

Earthquakes–induced landslides generally provide abundant loose materials at hillslopes, possibly triggering morphological reshaping processes at river channels and riverbeds during the large flash flood hydrograph and bringing huge risk downstream. Therefore, in a Wenchuan earthquake-affected catchment, the collected hydro-meteorological data and high-precision small Unmanned Aerial Vehicle (sUAV) data were used to quantitatively analyze channel evolution by a large flash flood event on 25 and 26 June 2018. It was found that the stable riverbed structure formed by the armour layer appeared in the tenth year after the Wenchuan earthquake. In a confined channel, the layer can protect the channel and resist the drastic change after the flash flood event with only a small bed elevation from 0.2 m to 2 m. Without the protection of the armour, the change could reach 6 m in the unconfined channel. Meanwhile, more materials with a deposition volume of about 7450 m3 from tributaries were generally taken to the main channel, and more intense erosion with a volume of 105 m3 mostly occurred downstream of tributaries. It was noted that, in the cross-section, the increased channel width could lead to a significant change with the large volume of 35 m3. Additionally, a conceptual diagram of the generalized channel response to large flash floods was provided during multi-stage periods after the Wenchuan earthquake. It determined the rebalance processes of channel evolution in the tenth year after the earthquake. This study will contribute to understanding the post-earthquake long-term channel evolutions and could provide decision-makers of assessing the mitigation strategies for higher-magnitude flood disasters triggered by channel change in earthquake-affected watersheds. [ABSTRACT FROM AUTHOR]

Hydrometeorological disasters are showing an increasing trend in Indonesia. Flash floods are part of a hydrometeorological disaster that has a significant livelihood impact. Flash Flood is triggered by the intensity of extreme rain, several actions of mitigation can be taken by early warning systems, hazard and risk mapping, community preparedness, and climate change adaptation. So, how does future land use have an impact, and how much loss will result from the flash flood disaster in Batu City? The hydrometeorological disaster that occurred in Indonesia was the Batu Flash Flood. The Flash Flood occurred on November 4, 2021. The flash flood has a lot of impact on many locations, including the Bumiaji District and Junrejo District. Based on the disaster history recorded, the flash flood in Batu has only happened once, but the impact was quite big because there are many houses in the midstream of Bulukerto. Based on the losses caused, this can be the basis for efforts to control the spatial pattern of Batu City in the future. The methodology used in this study is risk assessment. While the risk study related to delta (Δ) the study of flash floods risk in spatiotemporal prevention uses the 2030 spatial plan for delta prediction (Δ), which can later predict the consequences of climate change and meteorological disasters from flash floods in Batu. The results of this study are the delta (Δ) of flash flood risk and the damage assessment of the flash flood that occurred in Batu. [ABSTRACT FROM AUTHOR]

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Roads are the most critical means of connectivity in Himalayan villages. However, the terrain is inherently fragile with varied geological, geomorphological, ecological, and climate regimes, that result in frequent slope failure and disruption in connectivity. The risk is further to be increased by extreme events-generated hazards, which are expected to rise in frequency and magnitude with ongoing climate change. Critical scientific intervention, however, can improve the sustainability of road networks. The present study attempts to analyse and quantify the impacts of a major road widening project initiated in 2018 in the upper Ganga catchment, Uttarakhand Himalaya which has destabilised valley slopes along the widened segments. Also, a large quantity of excavated sediments is dumped down slopes, which is posing a threat to aquatic biodiversity. The estimates are based on Google Earth imagery of a few representative road segments recently widened in the upper Ganga catchment, which indicate a substantial increase in the landslide and unstable slope area following the road widening. The increase in unstable slope area is attributed to improper road widening approaches and poor slope management in seismically active Himalayan terrain. Further, the mean velocity plots of Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) indicate that the segments undergoing road widening are coherent with areas of significant earth surface change. A broad correlation between the road width and sediment yield indicates that even a slight increase in road width can result in a large-scale mass removal from the toe of the hillslope, inflicting cascading impact on hillslopes. The study recommends a more flexible road construction approach based on the environmental and geological aspects of the terrain for sustainable road networks. Further, the impact of climate change is looming over the Himalayas, and the relation between climate change and its potential effects on the stability of slopes remains an open issue. [ABSTRACT FROM AUTHOR]

Damage to rural buildings in mountainous regions caused by flash floods accounts for a significant proportion of economic losses from disasters. The unreinforced masonry (URM) wall is the most vulnerable structural element of rural buildings exposed to flash floods. The failure of a URM wall indicates damage to rural buildings in flash floods. Based on the yield line theory of out-of-plane damage of URM walls and the virtual work method, brittle failure criteria for URM walls under the impact of flash floods were established. According to the field investigation data of the 26 June 2020 flash flood event in Damawu Gully and the corresponding simulation results of FLO-2D, the disaster-causing process was analysed, and the failure criteria were validated. Three building parameters were identified to influence the flood-resistance of URM walls, including the mortar grade, the span-to-height ratio of the wall, and the number of floors of the rural building. The results showed that the cause of the 26 June disaster was the diversion of a 50-year flash flood into the residential community on the alluvial fan. The affected buildings were constructed with hollow blocks and lacked flood-resistance reinforcement. The critical failure depth of a URM wall restrained at the top by ring beams (RBs) under hydrostatic load conditions is 1.17 to 1.20 times greater than that of a URM wall without RBs, and the difference is even more pronounced when lower-strength mortar is used. The flood-resistance of a URM wall constructed with Mb 7.5 mortar and restrained by RBs is almost as strong as that of a URM wall constructed with Mb 20 mortar and without RBs. The span-to-height ratio of a URM wall should not be greater than 1.875 in this case. However, the flood-resistance of a URM wall with RB restraint is almost independent of the span-to-height ratio. The brittle fracture energy of masonry mortar is more crucial to the flood-resistance of 4-edge restrained URM walls if L/Z > 1.875. The flood-resistance of the URM wall of the first storey increases linearly with the number of floors. Single-storey rural buildings should be given priority to the use of high-grade masonry mortar and high-density blocks to improve flood-resistance. The failure criteria and the influence laws of building parameters on the flood-resistance of URM walls can provide references for flash flood mitigation and flood-resistance reinforcement of rural buildings in mountainous regions of Southwest China. [ABSTRACT FROM AUTHOR]

Subsurface stormflow is a dominant runoff mechanism in steep humid mountainous areas. An insite measurement of subsurface stormflow suggests that the bedrock surface plays an important role in the runoff generation and routing process, which was rarely adopted in hydrological modelling studies. To improve the runoff simulation performance, the bedrock surface topographic index is introduced, and a modified TOPMODEL based on the bedrock surface topographic index is developed to simulate the runoff. The modified TOPMODEL is applied to the Huangbengliu (HBL), a steep watershed in Gongga Mountain, and proved to be more appropriate for the HBL watershed, especially for peak simulation. The Nash-Sutcliffe model efficiency (NSE) is improved from 0.24 to 0.58 in the calibration period and from 0.40 to 0.62 in the verification period. The result of this study can advance the understanding of the mechanism of flash floods and contribute flood control and disaster prevention in the HBL watershed and similar areas. [ABSTRACT FROM AUTHOR]