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In a mountainous basin, flash-flood-induced soil erosion and its assessment are of major concern to the researchers. Cloudburst-induced extreme rainfall, undulating terrain, and inadequate water and soil conservation practices aggravate the problem of soil erosion. Alaknanda, a major basin of the upper Ganges in India, has experienced several incidents of flash floods. These have resulted in heavy soil loss, water siltation, and pollution in the basin. This study uses the revised universal soil-loss equation (RUSLE) in the GIS framework to assess the soil loss rate in various sub-basins of the Alaknanda. Further, the study suggests sub-basin prioritisation based on high soil erosion rate and past vulnerability that need attention of the decision-makers. RUSLE, an empirical soil erosion model, is easy to comprehend physically, involves minimum resources, and works on readily available inputs. The parameters used in the assessment include R-Rainfall Erosivity, Cover Management-C, Topographic-LS, Conservation Practice-P, and Soil Erodibility-K. The average R, K, LS, C & P factors for the Alaknanda basis are estimated as 437 MJ mm/ha/yr., 0.07 t ha h MJ-1 ha-1 mm-1, 1.4, 0.7, and 0.62, respectively. The mean annual soil erosion rate in the sub-basins varies from 6 to 27.9 t /ha/year with a mean rate of 13.4 t/ha/year and total erosion of 13.7 Mt/year. The results show that out of the twelve sub-basins, two (WS7 and WS5) fall in the high erosional class (18–30 t/ha/year), nine fall in the moderate erosional class (7–18 t /ha /year) and one basin in the low erosional class (1.0–7.0 t /ha/year). It is hoped that the present study will be helpful to the decision-makers while prioritising the actions to be taken for the water and soil conservation purposes. [ABSTRACT FROM AUTHOR]

The Safaga Region (SR) is part of the Red Sea mountain range in Egypt. Catastrophic flash flooding is now an inescapable event, wreaking havoc and causing massive loss of life and property. The majority of the floodwater, however, has been wasted as runoff to the Red Sea, which, if used wisely, could meet a fraction of the water demands for a variety of applications in this area. The current work aims to use GIS techniques to integrate remote sensing data for evaluating, mitigating, and managing flash floods in SR. The data set comprised Tropical Rainfall Measuring Mission (TRMM) thematic rainfall data, 1:50,000 scale topographical map sheets, geological maps, the ASTER Digital Elevation Model (ASTER GDEM), Landsat 7 Enhanced Thematic Mapper" (ETM7+), and Landsat 8 Operational Land Imager. The flash flood risk model of SR is developed using ArcGIS-10.3 geoprocessing tools integrating all the causal factors thematic maps. The final flood risk model for the SR suggests that 57% of the total basins in the SR are at high risk of flooding. Almost 38% of all basins are at moderate flood risk. The remaining 5% of basins are less prone to flooding. Flood-prone zones were identified, suitable dam-building sites were located, and extremely probable areas for water recharge were recognized. On the basis of reliable scientific data, structural and non-structural mitigation strategies that might reduce the damage susceptibility, alleviate the sensitivity of the flash flood, and best utilize its water supply were recommended. [ABSTRACT FROM AUTHOR]

Abstract The impacts of Geo-hazard events are main obstacles to the use of land in numerous arid and semi-arid provinces of the World. Furthermore, the various activities of industrial communities, such as Egypt's 10th Ramadan Industrial Region (10th RIR), are the most dangerous examples of waste's impact on soil, surface water, and groundwater. The current study uses image processing and GIS tools to identify, delineate, monitor, and assess some of the environmental hazards caused by both human and natural activities in the 10th RIR. The findings revealed that there are rapid changes in land cover, which could be attributed to both anthropogenic and natural activities. Furthermore, the results revealed that waterlogging, salt-affected soils, water pollution, and flash floods were the most serious environmental threats to the 10th RIR. The obtained geo-hazard map showed that the 10th RIR has high flash flood hazards zones that are geospatially distributed in the southern parts of the Wadi Gafra basin and the western parts of 10th of Ramadan City. Furthermore, salinized soil zones are viewed as geospatially restricted zone in the eastern portion of 10th of Ramadan City and/or near the oxidation ponds. Additionally, vast areas of highly contaminated groundwater exist beneath industrial, urban, and oxidation pond zones. The current work provides decision-makers with numerous mitigation measures and recommendations required to minimize the impacts of geo-environmental hazards endangering the 10th RIR.

AbstractThis study addresses a crucial gap in our understanding of flooding in the predominantly agricultural Qaa’Jahran watershed in Yemen, where urbanization, though currently limited in extent, is rapidly expanding. We aim to discern the effects of earth fissures on flood dynamics, particularly focusing on their present significance. It is noteworthy that, in the long run, these fissures are anticipated to accumulate soil and sediment, potentially heightening the risk of future flooding. To achieve this, we developed a comprehensive floodplain delineation model, incorporating field observations and rainfall data from the Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm. Additionally, advanced hydrologic and hydraulic models were integrated to accurately simulate runoff hydrographs and create flood inundation maps. Our findings underscore the considerable influence of earth fissures, effectively mitigating runoff volume, peak discharge, flood depths and inundated areas during storm events. It is imperative to emphasize that specific areas remain persistently vulnerable, with water levels surpassing one meter during historical floods. This reinforces the ongoing risk of flooding in targeted zones and emphasizes the necessity of implementing tailored flood management strategies. In conclusion, this study makes a significant contribution to the field, providing a comprehensive analysis of the intricate factors influencing flooding in the Qaa’Jahran watershed. The integration of flood inundation mapping, advanced hydrologic modelling and meticulous consideration of earth fissures offers a distinctive perspective on flood dynamics in a rapidly evolving and urbanizing environment. Furthermore, it highlights the critical implications for effective flood risk management and urban planning, not only in the Qaa’Jahran watershed but also in similar urbanizing regions worldwide.

The impacts of Geo-hazard events are main obstacles to the use of land in numerous arid and semi-arid provinces of the World. Furthermore, the various activities of industrial communities, such as Egypt's 10th Ramadan Industrial Region (10th RIR), are the most dangerous examples of waste's impact on soil, surface water, and groundwater. The current study uses image processing and GIS tools to identify, delineate, monitor, and assess some of the environmental hazards caused by both human and natural activities in the 10th RIR. The findings revealed that there are rapid changes in land cover, which could be attributed to both anthropogenic and natural activities. Furthermore, the results revealed that waterlogging, salt-affected soils, water pollution, and flash floods were the most serious environmental threats to the 10th RIR. The obtained geo-hazard map showed that the 10th RIR has high flash flood hazards zones that are geospatially distributed in the southern parts of the Wadi Gafra basin and the western parts of 10th of Ramadan City. Furthermore, salinized soil zones are viewed as geospatially restricted zone in the eastern portion of 10th of Ramadan City and/or near the oxidation ponds. Additionally, vast areas of highly contaminated groundwater exist beneath industrial, urban, and oxidation pond zones. The current work provides decision-makers with numerous mitigation measures and recommendations required to minimize the impacts of geo-environmental hazards endangering the 10th RIR. [ABSTRACT FROM AUTHOR]

The aim of this study is to identify and map the zones of different vulnerability to flash floods based on the geospatial analysis of natural conditions in the Porečka River basin (Republic of Serbia). The analysis covers the catchment area of the Porečka River (493.82 km²). Geospatial analysis was conducted using GIS software (QGIS 3.18). The Flash Flood Potential Index (FFPI) was used to determine the terrain's predisposition to flash floods, where the input data for determining the value of the index were the values of the following coefficients: the terrain slope, the type of geological substrate, the way of land use, and the bareness of the terrain. The analysis determined that 50.43% of the total territory of the basin belongs to the class of high and very high susceptibility to flash floods, and when looking at the length of watercourses in the basin, that percentage is 81.94%. The results of this study clearly indicate the advantages of using modern GIS technologies in the land use and risk management. Geospatial analysis is of particular importance in the field of managing regions that stand out as particularly vulnerable to some natural disasters. [ABSTRACT FROM AUTHOR]

This study addresses a crucial gap in our understanding of flooding in the predominantly agricultural Qaa'Jahran watershed in Yemen, where urbanization, though currently limited in extent, is rapidly expanding. We aim to discern the effects of earth fissures on flood dynamics, particularly focusing on their present significance. It is noteworthy that, in the long run, these fissures are anticipated to accumulate soil and sediment, potentially heightening the risk of future flooding. To achieve this, we developed a comprehensive floodplain delineation model, incorporating field observations and rainfall data from the Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm. Additionally, advanced hydrologic and hydraulic models were integrated to accurately simulate runoff hydrographs and create flood inundation maps. Our findings underscore the considerable influence of earth fissures, effectively mitigating runoff volume, peak discharge, flood depths and inundated areas during storm events. It is imperative to emphasize that specific areas remain persistently vulnerable, with water levels surpassing one meter during historical floods. This reinforces the ongoing risk of flooding in targeted zones and emphasizes the necessity of implementing tailored flood management strategies. In conclusion, this study makes a significant contribution to the field, providing a comprehensive analysis of the intricate factors influencing flooding in the Qaa'Jahran watershed. The integration of flood inundation mapping, advanced hydrologic modelling and meticulous consideration of earth fissures offers a distinctive perspective on flood dynamics in a rapidly evolving and urbanizing environment. Furthermore, it highlights the critical implications for effective flood risk management and urban planning, not only in the Qaa'Jahran watershed but also in similar urbanizing regions worldwide. [ABSTRACT FROM AUTHOR]

Flash floods threaten the lives of people and properties in different regions around the world, especially in arid and semi-arid regions due to infrequent flood events. The current study aims to assess the geomorphological parameters of Wadi Sudr, South Sinai in Egypt to evaluate flash flood risks and provide adequate mitigation methods. This study presents an integrated method that combines geographic information system (GIS) and watershed modeling system (WMS) with HEC-HMS to visualize and assess flood events in the study area. Different morphologic parameters of the watershed were determined, including linear, areal, and relief parameters. GIS was used to analyze the satellite images and determine the characteristics of the valley to get the extension and number of stream orders in the valley, then WMS was used to estimate rainstorms and basin characteristics, as well as estimate the amount of rain that causes flooding. HEC-HMS program was used for hydrological demonstration and precipitation overflow estimation. The morphometric analysis provided a quantitative portrayal of the Wadi Sudr watershed. Wadi Sudr has 4029 streams connected with seventh order of streams spread over an area of 547.45 km2. Based on the results of morphologic and hydraulic parameters of the watershed, two locations of protection dams were suggested. A comparison between the two locations was made to select the best location based on some criteria, including storage capacity, water depth behind the dam, width and shape of the valley, and the area covered by water stored in the reservoir. The comparison between the two locations showed that the first location is more appropriate for dam construction based on the examined criteria. The valley shape in the first location is more regular than in the second. The first location provided higher storage capacity and water depth in front of the dam than the second. The area covered by water and the width of the valley is less than the second. The stability of the dam at the first site could be higher and the cost of construction could cost be less than the second due to these reasons. A comparison was made using the weighted linear combination (WLC) method, which consists of 13 criteria to determine the suitability index (SI) in order to select the best location from the proposed locations. SI proved that the first location is better than the second. The designed dam in the selected site could be cost-efficient to protect the study area from flood risks and harvesting water that can be used in different purposes. This methodology can be applied in different areas for mitigating flash flood risks. [ABSTRACT FROM AUTHOR]

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Abstract Background This paper discusses the hydrological problems assessment of flash floods and the encroachment of wastewater in selected urban areas of Greater Cairo using remote sensing and geographic information system (GIS) techniques. The integration of hydrogeological and geomorphological analyses with the fieldwork of drainage basins (Wadi Degla) hosting these urban areas endeavors to provide the optimum mitigation measures that can be feasibly taken to achieve sustainability of the urban areas and water resources available. Results Landsat 5 and Sentinel-2 satellite images were obtained shortly before and after flash flood events and were downloaded and analyzed to define the active channels, urban interference, storage areas, and the natural depressions response. The quantitative flash flood estimates include total GSMap meteorological data sets, parameters of rainfall depths from remote sensing data, active channel area from satellite images, and storage areas that flooded. In GIS, digital elevation model was used to estimate the hydrographic parameters: flow direction within the catchment, flow accumulation, time zone of the catchment, and estimating of the water volume in the largely inundated depressions. Conclusions Based on the results obtained from the study of available satellite images, it has been shown that there are two significant hydrological problems, including the lack of flash flood mitigation measures for urban areas, as the wastewater depressions and sanitary facilities are dotting in the downstream areas.

Egypt is one Arab country that is vulnerable to flash floods caused by heavy and intensive rainfall. Different locations in Egypt are vulnerable to the hazards of flash floods, especially in Upper Egypt. Throughout history, Egypt witnessed a series of events of flash floods that lead to mortality, damages, and economic losses. The intensity and frequency of flash floods in Egypt vary from year to year according to a number of hydrological and climatological variables. Although several previous flash floods studies have been conducted in Egypt, studies on the governorate of Asyut are still limited. This study integrates the physical and social parameters in order to assess the vulnerability to flash floods. The objectives of this study are to shed light on flash floods in the study area, develop a vulnerability model to determine the regions vulnerable to the impacts of flash floods, and propose a flash flood alert system in the governorate of Asyut in Egypt to mitigate the impacts of flash floods and to avoid the loss of life and property. The AHP (analytical hierarchy process) is used for assigning the optimal criterion weight of the considered vulnerability parameters based on the responses of eight expert respondents to an online Google forms questionnaire. The highest weighted flash floods causative parameters are population density (27.4%), precipitation (22.1%), total population (16.4%), and elevation (10.2%), respectively. The results reveal that Asyut is one of the Egyptian governorates prone to flash floods' impacts, especially in Dayrut, Al-Qusiyah, and Abnub, urban districts. The findings of this study are expected to be useful to policymakers and responsible authorities for better disaster risk management and for dealing with the flash floods events in the future. [ABSTRACT FROM AUTHOR]

Predicting the occurrence and spatial patterns of rainfall induced flash floods is still a challenge. Instant genesis and typically smaller areal coverage of the flash floods are the major impediments to their forecasting. Analysis of the morphometric parameters provides useful insight on hydrological response of the drainage basins to high intensity rainfall events. This information is valuable for understanding the flash flood potential of the drainage basins and for evading the destructions caused by the hazard. Here, we use eighteen morphometric parameters that influence the runoff volume, flow velocity, and inundation depth scenario of a flash flood. The analysis has been carried out for simulating the relative flash flood susceptibility of thirteen watersheds (B1 to B13) of variable sizes in southeastern Bangladesh. The morphometric parameters were derived from Digital Elevation Model (DEM) using Geographic Information System (GIS). The evaluated basin parameters include: area (A), perimeter (P), length (Lb), stream order (Su), stream number (Nu), stream length (Lu), stream frequency (Fs), drainage density (Dd), texture ratio (Rt), bifurcation ratio (Rb), basin relief (Hr), relief ratio (Rr), ruggedness number (Rn), time of concentration (Tc), infiltration number (If), and form factor (F). Two relative flash flood susceptibility scenarios were generated: (i) general watershed level, and (ii) more precise pixel level status. The watershed level comparison reveals that B4 and B6 watersheds constituting 72.61% of the total area are 'very high' susceptible, whereas the susceptibility of the other watersheds has been found as 'high' [B5 (6.95%)], 'moderate' [B8 and B13 (8.63%)], 'low' [B2, B10, B11 (4.64%)], and 'very low' [B1, B3, B7, B9, and B12 (7.18%)]. The derived watershed susceptibility map was subsequently integrated with two spatial analysis algorithms i.e., topographic wetness index (TWI) and topographic position index (TPI) through overlay analysis. The integration helped to understand the combined role of the general watershed morphometry and the in situ topography for determining the flash flood susceptibility of each spot (30 m × 30 m) within all the selected watersheds. The quantitative analysis and characterization of the watersheds from the perspective of flash flood hazard in this investigation is expected to be useful for implementing the site-specific mitigation measures and alleviating the effects of the hydrological hazard in the study area. [ABSTRACT FROM AUTHOR]

In the work described here, flash flood prediction mapping for the Wadi El-Laqeita in the Central Eastern Desert of Egypt was established, using machine learning approaches involving two algorithms—extreme gradient boosting (XGBoost) and k-nearest neighbor (KNN). Flash flood driving factors, including elevation, slope, curvature, slope-aspect, lithological rock units, distance from streams, stream density, and topographic wetness index (TWI) were selected. Based on the machine learning models, the XGBoost and KNN algorithms were quite similar, in terms of variables importance, with distance from the stream network, slope angle, elevation, and stream density identified as the key driving factors, in order of importance. It is often difficult to allocate model parameter settings; therefore, hyper-parameter setting optimization was applied to improve model prediction performance. The models were trained using 70% flooding location and 70% non-flooding data, with the remaining 30% flooding and 30% non-flooding location data used for model and simulation result validation. The applied models exhibited accuracies of 90.2% and 80.7% for XGBoost and KNN, respectively, showing that the XGBoost algorithm performed better than KNN in this situation. Therefore, XGBoost was used in a powerful approach to flash flood prediction mapping, with the obtained predictions providing important guidance for decision-makers with respect to future study site development. [ABSTRACT FROM AUTHOR]

Background: This paper discusses the hydrological problems assessment of flash floods and the encroachment of wastewater in selected urban areas of Greater Cairo using remote sensing and geographic information system (GIS) techniques. The integration of hydrogeological and geomorphological analyses with the fieldwork of drainage basins (Wadi Degla) hosting these urban areas endeavors to provide the optimum mitigation measures that can be feasibly taken to achieve sustainability of the urban areas and water resources available. Results: Landsat 5 and Sentinel-2 satellite images were obtained shortly before and after flash flood events and were downloaded and analyzed to define the active channels, urban interference, storage areas, and the natural depressions response. The quantitative flash flood estimates include total GSMap meteorological data sets, parameters of rainfall depths from remote sensing data, active channel area from satellite images, and storage areas that flooded. In GIS, digital elevation model was used to estimate the hydrographic parameters: flow direction within the catchment, flow accumulation, time zone of the catchment, and estimating of the water volume in the largely inundated depressions. Conclusions: Based on the results obtained from the study of available satellite images, it has been shown that there are two significant hydrological problems, including the lack of flash flood mitigation measures for urban areas, as the wastewater depressions and sanitary facilities are dotting in the downstream areas. [ABSTRACT FROM AUTHOR]

The UN Office for Disaster Risk Reduction listed 10 reasons businesses should reduce their disaster exposure, including risk factoring, which cannot be achieved without historical data about hazards, their locations, magnitudes, and frequencies. Substantial hazard data are reported by newspapers, which could add value to disaster management decision making. In this study, a text-mining program extracted keywords related to floods' geographic location, date, and damages from newspaper analyses of flash floods in Fujairah, UAE, from 2000–2018. The paper describes extracting such information as well as geocoding and validating flood-prone areas generated through geographic information system (GIS) modeling. The generation of flood-prone areas was based on elevation, slope, land use, soil, and geology coupled with topographic wetness index, topographic position index, and curve number. Analytical Hierarchy Process (AHP) produced relative weight for each factor, and GIS map algebra generated flood-prone areas. AHP inclusion helped minimize weight subjectivity among various experts. Of all areas, 85% are considered medium and low flood-prone zones, mainly mountainous areas. However, the 15% that are high/very high are dominated by urban areas in low coastal plains, predisposing them to flash floods. Eighty-four percent of flood events reported by newspapers were in areas rated as high/very high flood-prone zones. In the absence of flood records, newspapers reports can be used as a reference. Policymakers should assess whether flood-prone area models offer accurate analyses. These findings are useful for organizations related to disaster management, urban planning, insurance, archiving, and documentation. [ABSTRACT FROM AUTHOR]

Egypt suffers from freshwater crisis, and the shortage is predicted to become severe by 2025. Egypt is exposed to flash floods, especially in Sinai governorate, causing rapid rises of water in a short amount of time and can trigger other catastrophic hazards associated with damage, danger to human life, properties and environment. Flash floods may be considered a source of water that can be explored to meet the water shortage problem. In this study, a composite flash floods vulnerability index based on an integrated hydro-climatic and physical vulnerability component was created. The composite index was based on eight parameters including rainfall distribution, elevation and slope, flow direction, streams, geomorphological features, soil type and land cover. The composite index was ranked into three categories: high, moderate and low. The index can help identify the weak and strong points to support the decision-making process concerned with water management as an essential prerequisite for Egypt sustainable development. The results revealed that the urban, vegetation cover, loamy sand, sand dunes, the low elevation and the flat areas are the most affected by the flash floods in EL-Arish City in Sinai governorate. 42% of Wadi El-Arish had low vulnerability, 45% moderate vulnerability and 13% high vulnerability. [ABSTRACT FROM AUTHOR]

Floods are considered one of the most severe natural disasters worldwide. They impact vast areas, particularly in arid/semi-arid regions, causing serious damages with thousands of human casualties and billions of Euros in economic losses. This study contributes to a comprehensive evaluation of flash flooding occurrences, impacts, and possible mitigation. In this study, The Dahab region in southern Egypt's Sinai Peninsula was selected for flash flooding vulnerability assessment. Although located in an arid region, it suffers from frequent and severe flash floods. Here, a straightforward workflow was applied to simulate the impact of flash flooding and assess the vulnerability of the Dahab area via consideration of a maximum storm event as a worst- case scenario. Originally, morphometric analysis was performed to determine the most hazardous sub-basins susceptible to flash flooding. The highest recorded storm event in the region was selected to calculate the maximum volume of surface runoff for the model simulation. Then, the hydrologic model and River Analysis System (HEC-RAS) software were used to calculate the inundation level across the entire city of Dahab. Despite some data limitations, this study shows clearly that the Dahab area would have problems incurring from flash flooding if no mitigation measures were to be considered. Results indicate that the area of Dahab is greatly vulnerable to flash flooding with approximately 72% of the total infrastructure being negatively impacted in the worst-case scenario. The adopted approach used in this study can be applied efficiently in similar regions in the Sinai Peninsula or elsewhere. [ABSTRACT FROM AUTHOR]

This study aims to assess the impact of the 2010–2011 flash floods on the crop production of Sanghar—an eastern district of Sindh. The population of almost two million is mainly dependent on agriculture. Cotton, sugarcane, and wheat are the main cash crops of the district. In 2010–2011 Sanghar was hit by flash floods after heavy rainfall. These floods adversely affected the crops standing at that time. However, on the other hand, they increased the fertility of agricultural lands. Satellite images, precipitation data, and geographical information system (GIS) tools were used to quantify floods’ effects by mapping pre- and post-flood vegetation cover. Supervised classification was applied on Landsat images from 2009 to 2013 to extract vegetation area. The temporal analysis unveils a significant increase in the vegetation cover in the post-flood years. Furthermore, the comparison between pre-and post-flood crop production data collected from the Pakistan Bureau of Statistics also validated the study results by revealing an increase in crop production.

This paper aims to quantify the hydrological parameters for the flash flood event of 17th January 2010 in Sinai using multiple sets of remote sensing data and field work for the nongaged catchments (approximately 2100 sq km) of the wadis affecting Ras Sudr area, which is heavily occupied by numerous oil fields and related activities. The affected areas were visited, and several cross sections of the main active channels were surveyed to estimate the peak discharge rates. The Tropical Rainfall Monitoring Mission (TRMM) data have been used to estimate rainfall parameters for the catchments due to the absence of in situ data. The digital elevation model (DEM) of the Shuttle Radar Topography Mission (SRTM) was used to extract the hydrographic data following standard procedures and techniques of the Geographic Information Systems (GIS). Both of the surveyed and extracted parameters for the active channels were integrated into GIS to estimate the runoff parameters using the open-channel flow equation of Manning’s. The simulated hydrographs show that the total discharge exceeded 5.7 million cubic meters and the peak discharge rate was 70 cubic meters per second. The mitigation of extreme flash flood is possible by altering the natural flow dispersion over the alluvial fan, and conveying the resulting flows into one adjusted channel.

The assessment of hydrometeorological hazards in the mountainous area of Southwestern Sinai area (SWSA) necessitates reliable and accurate information about natural hazards, especially flash floods. Flash floods are the main dangerous hazards that threaten lives and any sustainable development planning in and around the rugged topography areas. The SWSA receives occasional heavy rainstorms every two or four years, triggering destructive floods that runoff towards the Gulf of Suez. The present study aims to extract, evaluate, integrate and map the potential flash flood hazards by applying remote sensing, GIS tools and by statistically analyzing the geomorphometric parameters. Moreover, assessing the flash flood hazard risk ranks was carried for the three main basins (W. Baba, W. Sidri, and W. Nukhul). The drainage networks and basins were extracted from DEM then, delineated into seventy-two sub-basins and then the morphometric parameters of these sub-basins were estimated. The analysis of the various morphometric parameters of the three main basins shows that they have different effects on flash flood hazards. Depending on the statistical analysis of the commutative weights of the important geomorphometric parameters and GIS functions; the studied basins were categorized into three risk ranks; namely: high, moderate and low flash flood risk. The integration of the different controlling parameters revealed that the zones of high flash flood hazard risk are characterized by the low probability of groundwater recharge which should be put into consideration to help the decision makers avoid risks which are considered to be one of the most dangerous obstacles to the sustainable development of the study area. [ABSTRACT FROM AUTHOR]

Abstract: The hydrology of Wadi Al Saaf was investigated to estimate the quantitative parameters of flash flood and its interaction with the landuse using multitude of remote sensing data, digital elevation models (DEM), field work and topographic survey. The waste water is being conveyed into the lower part of this catchment through a transient drain “Al Saaf Drain” and the newly constructed treatment plant for “Al Saaf City”. The flash flood of May 2014 was completely trapped into the oxidation pools of the treatment plant and its surrounding low areas in the wadi floor. The active channels and accumulated water bodies of this flash flood were traced from the satellite images acquired shortly after the event. The DEM was analyzed into geographic information system (GIS) to estimate the distributed unit hydrograph given the application of Manning's for the open channel flow equation. The surveyed cross-sectional areas of the active channels and their equivalent hydraulic radii gave a mean peak discharge of 110 m 3 per second. The estimated net discharge was 2.1 million cubic meters as calculated from the surveyed topography for the pools and depressions areas, which trapped that flash flood. The wadi is dominated by surface runoff as the percolation into the underlying alluvium is very limited due to the occurrence of thick Pliocene clays few meters below the surface. Furthermore, the seepage of waste water from “Al Saaf Drain” into the artificial depressions of the clay quarries has created massive ponds which are susceptible to breaching by the flash floods. Therefore, the interaction of flash floods with the water bodies in the catchment must be prevented in order to advert any negative environmental consequences. Moreover, the cultivation of edible crops with the waste water is being practiced; this research has suggested specific mitigation measures to be taken to achieve sustainability for the water resources management. [ABSTRACT FROM AUTHOR]

Flash floods are widely recognized as one of the most devastating natural hazards in the world, therefore prediction of flash flood-prone areas is crucial for public safety and emergency management. This research proposes a new methodology for spatial prediction of flash floods based on Sentinel-1 SAR imagery and a new hybrid machine learning technique. The SAR imagery is used to detect flash flood inundation areas, whereas the new machine learning technique, which is a hybrid of the firefly algorithm (FA), Levenberg⁻Marquardt (LM) backpropagation, and an artificial neural network (named as FA-LM-ANN), was used to construct the prediction model. The Bac Ha Bao Yen (BHBY) area in the northwestern region of Vietnam was used as a case study. Accordingly, a Geographical Information System (GIS) database was constructed using 12 input variables (elevation, slope, aspect, curvature, topographic wetness index, stream power index, toposhade, stream density, rainfall, normalized difference vegetation index, soil type, and lithology) and subsequently the output of flood inundation areas was mapped. Using the database and FA-LM-ANN, the flash flood model was trained and verified. The model performance was validated via various performance metrics including the classification accuracy rate, the area under the curve, precision, and recall. Then, the flash flood model that produced the highest performance was compared with benchmarks, indicating that the combination of FA and LM backpropagation is proven to be very effective and the proposed FA-LM-ANN is a new and useful tool for predicting flash flood susceptibility.

In the mountainous area of the Red Sea region in southeastern Egypt, the development of new mining activities or/and domestic infrastructures require reliable and accurate information about natural hazards particularly flash flood. This paper presents the assessment of flash flood hazards in the Abu Dabbab drainage basin. Remotely sensed data were used to delineate the alluvial active channels, which were integrated with morphometric parameters extracted from digital elevation models (DEM) into geographical information systems (GIS) to construct a hydrological model that provides estimates about the amount of surface runoff as well as the magnitude of flash floods. The peak discharge is randomly varied at different cross-sections along the main channel. Under consistent 10 mm rainfall event, the selected cross-section in middle of the main channel is prone to maximum water depth at 80 cm, which decreases to nearly 30 cm at the outlet due to transmission loss. The estimation of spatial variability of flow parameters within the catchment at different confluences of the constituting sub-catchments can be considered and used in planning for engineering foundations and linear infrastructures with the least flash flood hazard. Such information would, indeed, help decision makers and planning to minimize such hazards.

This study uses an integrated approach, bringing together geographic information system (GIS), remote sensing, and rainfall-runoff modeling, to assess the urbanization impact on flash floods in arid areas. Runoff modeling was carried out as a function of the catchment characteristics and the maximum daily rainfall parameters. Land-use types were extracted from the supervised classification of SPOT-5 (2010) and Landsat-8 (2015) satellite images and were validated during field checks. Catchment morphometric characteristics were carried out using the correlated Topaz and Arc-Hydro tools. Maximum floods of the catchment were evaluated by coupling GIS and remote sensing with Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) hydrologic modeling. Peak discharges were estimated, and the abstraction losses were computed for different return periods. The model results were calibrated according to actual runoff event. The research shows that rapid urbanization adversely affects hydrological processes, since the sprawl on the alluvial channels is significant. This reduces infiltration into the underlying alluvium and increases runoff, leading to higher flood peaks and volumes even for short duration low intensity rainfall. To retain a considerable amount of water and sediments in these arid areas, construction of small dams at the fingertip channels at the outlet of the lower order sub-basins is recommended. [ABSTRACT FROM AUTHOR]

The city of Jeddah (Saudi Arabia) has experienced two catastrophic flash flood events in 2009 and 2011. These flood events had catastrophic effect on human lives and livelihoods around the wadi Muraikh, wadi Qus, wadi Methweb, and wadi Ghulail in which 113 people were dead and with 10,000 houses and 17,000 vehicles were damaged. Thus, a comprehensive flood management is required. The flood management requires information on different aspects such as the hydrological, geotechnical, environmental, social, and economic aspects of flooding. Flood susceptibility mapping for any area helps the decision makers to understand the flood trends and can aid in appropriate planning and flood prevention. In this study, two models were used for the generation of flood susceptibility maps for the Jeddah region. The first model includes bivariate probability analysis (frequency ratio), and the second model uses the multivariate analysis. For the multivariate model, the acquired weights of the FR model were entered into the logistic regression model to evaluate the correlation between flood occurrence and each related factor. This integration will overcome some of the weakness of the logistic regression, and the performance the LR will be enhanced. A flood inventory map was prepared with a total of 127 flood locations. These flood locations were extracted from different sources including field investigation and high-resolution satellite image (IKONOS 1 m). These flood locations were randomly split into two groups, one dataset representing 70 % was used for training the models, and the remaining 30 % was used for models validation. Various independent flood-related factors such as slope, elevation, curvature, geology, landuse, soil drain, and distance from streams were included. The impact of each independent flood-related factors on flooding was evaluated by analyzing each independent factor with the historical flood inventory data. The training and validation datasets were used to evaluate the flood susceptibility maps using the success and the prediction rate methods. The results of the accuracy assessment showed a success rate of 90.4 and 91.6 % and a prediction rate of 89.6 and 91.3 % for FR and ensemble FR and LR models, respectively. In addition, a comparison has been made between real flood events in 2009 and the resultant susceptibility maps. Hence, it is concluded that the FR and ensemble Fr and LR models can provide an acceptable accuracy in the prediction of flood susceptibility in the Saudi Arabia. Our findings indicated that these flood susceptibility maps can assist planners, decision makers, and other agencies to deal with the flood management and planning in the area. [ABSTRACT FROM AUTHOR]

This paper aims to quantify the hydrological parameters for the flash flood event of 17th January 2010 in Sinai using multiple sets of remote sensing data and field work for the nongaged catchments (approximately 2100 sq km) of the wadis affecting Ras Sudr area, which is heavily occupied by numerous oil fields and related activities. The affected areas were visited, and several cross sections of the main active channels were surveyed to estimate the peak discharge rates. The Tropical Rainfall Monitoring Mission (TRMM) data have been used to estimate rainfall parameters for the catchments due to the absence of in situ data. The digital elevation model (DEM) of the Shuttle Radar Topography Mission (SRTM) was used to extract the hydrographic data following standard procedures and techniques of the Geographic Information Systems (GIS). Both of the surveyed and extracted parameters for the active channels were integrated into GIS to estimate the runoff parameters using the open-channel flow equation of Manning’s. The simulated hydrographs show that the total discharge exceeded 5.7 million cubic meters and the peak discharge rate was 70 cubic meters per second. The mitigation of extreme flash flood is possible by altering the natural flow dispersion over the alluvial fan, and conveying the resulting flows into one adjusted channel. [ABSTRACT FROM AUTHOR]

On November 25, 2009, heavy amount of rainfall precipitated in the city of Jeddah that led to floods causing unexpected loss of life (113 person died), and damaged public and private properties (10,000 cars were damaged/destroyed, and many houses, roads, highways, and industrial properties were also affected). The city of Jeddah is located within an independent mega drainage basin with a surface area of 1,760 km. This mega basin is divided into three major sub-basins (northern, middle, and southern). Wadi Qus is located in the southern sub-basin with an area of ~63 km. It passes through many of the neighborhoods such as Al-Harazat, Al-Sawaid, Queza, Al-Mesaid, Al-Haramin Highway, and the King Abdel Aziz University. These areas were severely damaged during the flash flood event in 2009. The current study deals with the determination of the best sites for the construction of flood control dams, followed by a number of detailed studies to ensure that these selected sites are appropriate. Geological, geotechnical, geophysical, and hydrological investigations were conducted to identify the types of rocks, the subsurface conditions, and the geotechnical properties of abutment and subsurface of soil and rock in the dam sites. The study found that there are three locations that can be appropriate for the construction of the flood control dams at Wadi Qus. Hydrological studies indicated that the runoff volumes for sub-basins B1, B2, and B3 are 2,102,709, 1,023,156, and 4,868,304 m, respectively, for 500-year return period and 2,356,081, 1,149,687, and 5,451,123 m, respectively, for 1,000-year return period. Comparing these values with the reservoir volumes calculated from the detailed ground survey with different dam's height, it was found that dam's heights of 15.5, 11.5, and 13.5 m for dams Q, Q, and Q, respectively, are adequate for different basin volumes for 1,000-year return periods. Finally, the conceptual designs have been prepared and recommended for these dams. [ABSTRACT FROM AUTHOR]

Flash floods are one of the most significant natural hazards of today. Due to the complexity of flash flood triggering factors, to prevent or mitigate flood triggered losses, numeric model based flood forecasting models are capable tools to predict stream water levels. The main goal of the current research was to reproduce two flow peaks with the HEC-HMS rainfall-runoff model and test the model sensitivity for various input parameters. To obtain sufficient input data, we monitored soil depth, maximum infiltration rate, soil moisture content, rainfall, time of concentration and flow. To obtain input data, parameters were calculated, measured in the Sás Valley experimental watershed (SW Hungary) or optimized with the built in function of the HEC-HMS. Soil moisture was monitored in the 1.7 km2 pilot catchment over the period between September 2008 and September 2009. HEC-HMS had a good performance reproducing the two events, however simulated flow time series are highly influenced by the antecedent soil moisture, infiltration rate and canopy storage. Outflow modeled data were verified for two flood events (June 4, 2008 and July 9, 2009). The HEC-HMS was over-sensitive for input soil moisture and with increasing input rainfall and increasing outflow, larger simulation errors were observed. [ABSTRACT FROM AUTHOR]

Abstract: Floods, droughts, heat waves, and storms have always been part of human lives because they are a normal part of climate variability. However, the observed trends and projected changes in global climate have the potential to alter patterns of these climatic hazards and extreme weather events. Extreme precipitation is one of the factors that contribute to flash floods, but it is the characteristics of the environment, individuals, and society that can turn these natural phenomena into life-threatening disasters. Past decades of disaster risk research and assessments have lead to many innovative approaches to integrating data across disciplinary domains. Recent advancements in integration of meteorological information with other environmental and social data, using Geographic Information Systems (GIS), allow for integrated spatial assessments of societal vulnerability to weather-related hazards. A case study presented in this article builds on the substantial body of previous and ongoing research that is focused on developing improved methods for characterizing and quantifying vulnerabilities to weather hazards, in general, and extreme precipitation events, in particular. Integrating social science into meteorological research and practice has been a key interdisciplinary direction in the meteorological community. Therefore, with specific attention to integrating spatially explicit information on weather and society, this article focuses on interactions between meteorological and social characteristics of an extreme precipitation event that resulted in a flash flood disaster in Fort Collins, Colorado. Using the data from 1997 Fort Collins, Colorado extreme precipitation event, this study constructs a straightforward methodology for integrating meteorological data with readily available societal information into a GIS-based analysis of vulnerable people and places. With the goal of developing specific, targeted interventions and flash flood preparedness and emergency response actions, the analysis of societal vulnerability presented in this paper is specifically focused on the factors affecting population''s response and coping capacities to an extreme precipitation event. Challenges associated with data limitations and integration of meteorological and societal data, with diverse units and scales, into a standardized relative vulnerability measure are discussed. [Copyright &y& Elsevier]

A lightweight decision support system is presented, oriented also to statistics, useful for assisting weather forecasters and other parties interested in hazard assessment associated with extreme weather. The system can be used in enhancing the warning procedures, ahead of a flood or a flash flood whose probability of occurrence is based on the history of such events in a particular region. A software application has been built that integrates meteorological data with Geographical Information Systems procedures, in a unified informational aggregate. This system stores various types of data related to flood and flash flood events, so it is able to provide the user with any piece of information related to a documented event. It also catalogues any information that users provide it with, to further document a past, or an ongoing event. The system can be used to raise awareness of forecasters over a particular context, before a possibly hazardous situation, and it can also offer automatic warnings and suggestions to those interested in disaster mitigation. [ABSTRACT FROM AUTHOR]

Flash floods are considered to be one of the worst weather-related natural disasters. They are dangerous because they are sudden and are highly unpredictable following brief spells of heavy rain. Several qualitative methods exist in the literature for the estimations of the risk level of flash flood hazard within a watershed. This paper presents the utilization of remote sensing data such as enhanced Thematic Mapper Plus (ETM+), Shuttle Radar Topography Mission (SRTM), coupled with geological, geomorphological, and field data in a GIS environment for the estimation of the flash flood risk along the Feiran-Katherine road, southern Sinai, Egypt. This road is a vital corridor for the tourists visiting here for religious purposes (St. Katherine monastery) and is subjected to frequent flash floods, causing heavy damage to man-made features. In this paper, morphometric analyses have been used to estimate the flash flood risk levels of sub-watersheds within the Wadi Feiran basin. First, drainage characteristics are captured by a set of parameters relevant to the flash flood risk. Further, comparison between the effectiveness of the sub-basins has been performed in order to understand the active ones. A detailed geomorphological map for the most hazardous sub-basins is presented. In addition, a map identifying sensitive sections is constructed for the Feiran-Katherine road. Finally, the most influenced factors for both flash flood hazard and critical sensitive zones have been discussed. The results of this study can initiate appropriate measures to mitigate the probable hazards in the area. [ABSTRACT FROM AUTHOR]

In this paper we describe the procedures and data acquisition for flood risk mapping as a first step into an effective flood risk management in Reni. This work is part of a Flemish funded project named "Building capacities for effective flood risk management in the Ukrainian part of the Danube Delta". The aims of this project are 1) share expertise about flood risk mapping, emergency management and damage calculation 2) create better flood prevention and protection plans for the Ukrainian part of the Danube Delta 3) contribute to the set up of an integrated flood risk management plan in line with the WFD and EU Flood Risk Directive and 4) assist with capacity building and community involvement to flood risk management. The area of Reni was chosen as an illustrative case study for several reasons. It is a community where during a flood not only 8000 population and housing are at risk but also a harbour and a water intake for water supply. Many factors need to be taken into account because the risk of flooding comes from two sources. It is caused on the one hand by high water level in the Danube, with associated risk of dike breaches and on the other hand, as an extra threat, the risk for flash floods caused by heavy rainfall runoff from the upstream hills. The combination of both flooding forces can lead to heavy damage during flood events. The flood risk assessment for this region is done in 4 steps. It consists of determining 1) the probability of flooding; 2) determining the flood extent and the flood depth; 3) determining the economic damage due to flooding 4) determining the societal impact due to flooding. For all these steps a lot of data is necessary. Regional authorities and the Meteorological Institute are involved to collect the data. Local stakeholders are involved to be able to assess the damage and societal impacts. Today, not all necessary data for a fully comprehensive flood risk mapping is available. As a result, within this project recommendations for data collection and the use of the existing earth observation, systems are formulated to achieve a more effective risk assessment. It is the aim to create a flood risk map of the region and to present a set of recommendations to be able to set up in the near future an online flood forecasting system. Initial flood risk mapping results are also used to introduce the management concept to stakeholders. [ABSTRACT FROM AUTHOR]

Abstract: In the mountainous area of the Red Sea region in southeastern Egypt, the development of new mining activities or/and domestic infrastructures require reliable and accurate information about natural hazards particularly flash flood. This paper presents the assessment of flash flood hazards in the Abu Dabbab drainage basin. Remotely sensed data were used to delineate the alluvial active channels, which were integrated with morphometric parameters extracted from digital elevation models (DEM) into geographical information systems (GIS) to construct a hydrological model that provides estimates about the amount of surface runoff as well as the magnitude of flash floods. The peak discharge is randomly varied at different cross-sections along the main channel. Under consistent 10mm rainfall event, the selected cross-section in middle of the main channel is prone to maximum water depth at 80cm, which decreases to nearly 30cm at the outlet due to transmission loss. The estimation of spatial variability of flow parameters within the catchment at different confluences of the constituting sub-catchments can be considered and used in planning for engineering foundations and linear infrastructures with the least flash flood hazard. Such information would, indeed, help decision makers and planning to minimize such hazards. [ABSTRACT FROM AUTHOR]

The article presents a study which cites a new way of modeling flash floods in dryland catchments in the southern Eastern Desert of Egypt. This is done by integrating remote sensing and digital elevation model (DEM) data in a geographical information system (GIS). It uses images of the Wadi Hudain catchment in southern Egypt to infer the hillslope areas contributing flow's flood events. Meanwhile, the flow direction, active channel cross-sectional areas and slope, and flow length were derived via the SRTM3 DEM. The channel flow velocities and the time-area zones of the catchment were estimated using the Manning Equation. Based on results, the marked increase in brightness of channel bed materials within the active channels implies the occurrence of runoff events in the past 20 years.

• We propose a 10-class flash flood impact severity scale. • The proposed severity scale is applied in the impacts of a catastrophic flash flood. • The proposed scale is able to map spatial variations of flash flood impact severity. • The method identifies impact patterns and highlights high-impact areas. • The resulting severity maps can be used for interventions on impact prevention. Flash floods cause some of the most severe natural disasters around the world. The extensive diversity and discontinuity of flash flood impacts, which are controlled mostly by surface properties, lead to major difficulties in obtaining a holistic appraisal and a realistic overview of flash flood effects and their severity and make predicting future impacts a significant challenge. Current practices of describing flood impact severity use a limited set of criteria and assign a qualitative characterization (e.g. major, catastrophic, etc.) to each event. The present study proposes an approach that provides a coherent overview of these effects through the classification of impact types and severity and for the first time mapping their spatial extent in a continuous way across the floodplain. To this end, the flood effects are grouped into 4 categories depending on the affected elements, namely: (i) impacts on built environment (ii) impacts on man-made mobile objects, (iii) impacts on the natural environment (including vegetation, agriculture, geomorphology, and pollution) and (iv) impacts on the human population (entrapments, injuries, fatalities). Each of the four above categories is classified in a system of 10 severity classes that are defined with a logical order of increasing importance of damages forming a severity scale. The scale's application is tested on a catastrophic flood event of 2017 in Mandra, Greece, with a well-described and wide range of impacts, including 24 fatalities. The application allowed the development of high-resolution impact-severity maps that revealed interesting damage patterns and highlighted high severity areas. The resulting maps offer insights on future impacts and indicate a potential to provide the groundwork for targeted prevention measures as well as correlations of impact severity with hydrological aspects of flooding. [ABSTRACT FROM AUTHOR]

Flash floods are widely recognized as one of the most devastating natural hazards in the world, therefore prediction of flash flood-prone areas is crucial for public safety and emergency management. This research proposes a new methodology for spatial prediction of flash floods based on Sentinel-1 SAR imagery and a new hybrid machine learning technique. The SAR imagery is used to detect flash flood inundation areas, whereas the new machine learning technique, which is a hybrid of the firefly algorithm (FA), Levenberg–Marquardt (LM) backpropagation, and an artificial neural network (named as FA-LM-ANN), was used to construct the prediction model. The Bac Ha Bao Yen (BHBY) area in the northwestern region of Vietnam was used as a case study. Accordingly, a Geographical Information System (GIS) database was constructed using 12 input variables (elevation, slope, aspect, curvature, topographic wetness index, stream power index, toposhade, stream density, rainfall, normalized difference vegetation index, soil type, and lithology) and subsequently the output of flood inundation areas was mapped. Using the database and FA-LM-ANN, the flash flood model was trained and verified. The model performance was validated via various performance metrics including the classification accuracy rate, the area under the curve, precision, and recall. Then, the flash flood model that produced the highest performance was compared with benchmarks, indicating that the combination of FA and LM backpropagation is proven to be very effective and the proposed FA-LM-ANN is a new and useful tool for predicting flash flood susceptibility. [ABSTRACT FROM AUTHOR]