Search

In many parts of the world floods occur more often and increase in size. In the tropics, it is partly or wholly caused by climatological factors, in-situ soil types (as soils with low infiltration rate are vulnerable to flooding); inadequate drainage network, topography and human factors. Gombe town is situated within an elevation of 628 m and 361 m above sea level (a.s.l). Topography is mainly mountainous, undulating and hilly with open plains and mean slope gradient of 5°, considered to be a high gradient for unprotected soils. This causes high surface runoff leading to excessive flooding and formation of gullies, cutting deep trenches that result in the destruction of residential houses and environmental disasters throughout Gombe town. The research work assessed gully erosion from high vulnerable sections in Gombe town affected by high fluvial floods. Field measurement was done using 50 m tape, GPS, satellite images and laboratory analysis. Laboratory analysis of soil particles sizes showed that mean particle sizes were 74.9 %, 14.1 % and 11.0 % for sand, silt and clay respectivly; the textural class for the entire study site was sandy clay. Porosity from the entire study area contains low volume of voids relative to the volume of solids. Bulk density was slightly high compared to the standards values. The soil chemical properties of the soil pH for the entire site mean (ESM) was 6.42. This indicates that the soils are slightly acidic which affect microbial activities on organic matter that enhance the binding of soils to resists erosivity of fluvial floods. People resorts to using vegetative cover of Ipomoe Carnea plant as mitigation measures to protect their vulnerable houses and farms from gully erosions because the stems interweaves and forms a thick cover that diffuses the high velocity water flow into laminar flow. The weaved stems traps, blocks and prevents the flood transported materials(soil, humus, gravels) in between the stems thereby prevents and slows soil erosion to the nearest minimum., У багатьох частинах світу повені відбуваються все частіше та збільшуються в розмірах. У тропіках це частково або повністю спричинене кліматичними факторами, типами ґрунтів на місці (оскільки ґрунти з низькою швидкістю інфільтрації вразливі до затоплення); неадекватна дренажна мережа, рельєф і людський фактор. Місто Гомбе розташоване на висоті 628 м і 361 м над рівнем моря. Рельєф в основному гористий, хвилястий та горбистий з відкритими рівнинами та середнім ухилом схилу 5°, що вважається високим ухилом для незахищених ґрунтів. Це спричиняє високий поверхневий стік, що призводить до надмірних повеней та утворення ярів, прорізання глибоких траншей, що призводить до руйнування житлових будинків і екологічних катастроф у всьому місті Гомбе. Проведена дослідницька робота оцінювала ерозію яру на вразливих ділянках міста Гомбе, які постраждали від сильних річкових повеней. Польові вимірювання проводилися за допомогою 50-метрової стрічки, GPS, супутникових зображень і лабораторного аналізу. Лабораторний аналіз розмірів часток ґрунту показав, що середні розміри частинок становили 74,9 %, 14,1 % та 11,0 % для піску, мулу та глини, відповідно; текстурним класом для всієї досліджуваної ділянки була піщана глина. Пористість усієї досліджуваної області містить низький об’єм пустот відносно об’єму твердих речовин. Насипна щільність була дещо високою порівняно зі стандартними значеннями. Хімічні властивості ґрунту мали середнє значення рН ґрунту для всієї ділянки (ESM), що становило 6,42. Це вказує на те, що ґрунти є злегка кислими, що впливає на активність мікробів на органічних речовинах, які посилюють зв’язування ґрунтів, щоб протистояти ерозії річкових паводків. Люди вдаються до використання рослинного покриву рослини Ipomoe Carnea як заходів пом’якшення, щоб захистити свої вразливі будинки та ферми від балкової ерозії, оскільки стебла переплітаються та утворюють товстий покрив, який розсіює високошвидкісний потік води в ламінарний потік. Сплетені стебла затримують, блокують та запобігають затопленню транспортованих матеріалів (ґрунту, гумусу, гравію) між стеблами, тим самим запобігаючи та уповільнюючи ерозію ґрунту до мінімуму.

Greece, like the rest of the Mediterranean countries, faces wildland fires every year. Besides their short-term socioeconomic impacts, ecological destruction, and loss of human lives, forest fires also increase the burnt areas’ risk of flash flood phenomena, as the vegetation, which acted in a protective way against runoff and soil erosion, is massively removed. Among the most severe wildland fire events in Greece were those of summer 2021, which were synchronous to the very severe heat waves that hit the broader area of the Balkan Peninsula. More than 3600 km2 of land was burnt and a significant amount of natural vegetation removed. Three of the burnt areas are examined in this work, namely, Attica, Northern Euboea, and the Peloponnese, in order to assess their risk of future flash flood events. The burnt areas were mapped, and their geological and geomorphological features studied. Flash flood hazard assessment was accomplished through a Boolean logic-based model applied through Geographic Information Systems (GIS) software, which allowed the prioritization of the requirement for protection by identifying which locations were most prone to flooding. The largest part of our study areas is characterized by geomorphological and geological conditions that facilitate flash flood events. According to our findings, in almost all study areas, the regions downstream of the burnt areas present high to very high flash flood hazard, due to their geomorphological and geological features (slope, drainage density, and hydrolithology). The only areas that were found to be less prone to flood events were Vilia and Varimpompi (Attica), due to their gentler slope inclinations and overall geomorphological characteristics. It is known that vegetation cover acts protectively against flash floods. However, in this case, large areas were severely burnt and vegetation is absent, resulting in the appearance of flash floods. Moreover, imminent flooding events are expected to be even more intense in the areas downstream of the burnt regions, possibly bearing even worse impacts on the local population, infrastructure, etc.

In China, flash floods are one of the main natural disasters causing loss of life and damage to infrastructure. The threat of flash floods is exacerbated with climate change and increased human activities, such that the number of disasters has shown a clear upward trend in recent years. However, due to the scarcity of instrumental data or overly short timeseries, we are still lacking critical data to understand spatio-temporal patterns and driving factors of extreme flash floods. This missing knowledge is however crucial for a proper management of these hazards, especially in remote mountain environments. In forested catchments, dendrogeomorphology allows the reconstruction of past process activity based on growth disturbances (GDs) in trees that have been affected by past flash floods. Therefore, in our study, for the first time, we reconstruct past flash floods in the Qilian Mountains, northeast Tibetan Plateau, over past centuries. To this end, we sampled 99 Qinghai spruce (Picea crassifolia) trees affected by flash floods, with a total of 194 increment cores, and identified 302 GDs induced by past flash floods. These GDs have been caused by at least 21 flash floods that we are able to reconstruct over the last 170 years. The position of GDs within tree rings and the intra-seasonal dating of past events also allowed discussion of the likely synoptic situations that may have led to the triggering of flash floods in the past. Logistic regression analysis confirms that significant correlation exists between cumulative maximum 5-day August–September precipitation and reconstructed flash floods, which is corresponding to the majority of scars and related tangential rows of traumatic resin ducts (TRDs) found in the latewood portion of growth rings. These results support the idea that abundant precipitation occurring at the end of the summer season and early fall is the key factor driving flash floods in our study area. Our research not only fills the gaps regarding historical flash flood histories in the Qilian Mountains, but also provides a scientific basis for the region’s response to climate change and flood prevention and reduction., This work was supported by the National Natural Science Foundation of China [Grant No. 41977392], the National Key R&D Program of China [Grant No. 2019YFA0606602], the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA20090000), and Qilian Mountain National Park Qinghai Province management bureau. Jiazhi Qie was financed by the China Scholarship Council

Coherence change detection (CCD) is a remote sensing technique used to map phenomena that, under certain conditions, can be directly related to changes in Interferometric SAR (InSAR) coherence. Mapping the areas affected by sediment transport events in arid environments is one of the most common applications of CCD. However, the reliability of these maps remains an unsolved issue. This paper focuses on verifying that InSAR coherence is indeed able to detect all the fluvial sediment transport events that have actually mobilised sediments in arid environments by building a classification model and validating its results. The proposed methodology is tested in three study areas in Salar de Atacama, Chile, using three years of Sentinel data plus a fourth year for validation, and meteorological records of rainfall, the relative humidity of the air and snow cover. The results prove that InSAR coherence can be used to remotely detect sediment transport events related to flash floods in arid environments, that it might have a greater detection ability than meteorological records and that the perpendicular baseline does have a relevant effect on the InSAR coherence that needs to be considered. All these findings will increase the reliability of maps based on InSAR coherence. In addition, the proposed method will allow focusing the mapping tasks only on the relevant dates and, once calibrated, the classification model will enable the automatised remote detection of new events.

The Brague River basin (68 km2) is located on the French Mediterranean coast. It experiences a high risk of flash floods. The potential efficacy and efficiency of flood protection strategies based on green (Nature Based Solutions: NBS) or grey (civil-engineering) measures, as well as their co-benefits, are studied in this chapter. Two NBS flood alleviation strategies combine both small natural water retention areas, along with a widening of the river corridor. Two more classical grey scenarios were based on large wood-trapping racks, and another based on retention dams. This chapter synthesizes (i) the flood risk assessment; (ii) the estimation of total costs; (iii) how benefits related to each strategy were estimated. Benefits were evaluated with both a top-down method (avoided damages and transfer of valuations made elsewhere for co-benefits) and with a bottom-up approach surveying citizen willingness to pay. The cost-benefit analysis demonstrates that costs are higher than the avoided damage, and that co-benefits are much higher than avoided damage for most strategies and for both approaches. Depending on the number of household considered in the co-benefits valuation, the balance may reach higher benefits than costs for NBS strategies, though not for the grey solution based on large dams.

The hydrological processes of a catchment are the function of climate, land use and land cover. Changes in either climate or land use or land cover can result in alteration of the catchment’s hydrological processes. In the recent past, Msimbazi catchment in Dar es Salaam has undergone drastic land cover changes mainly due to urbanisation. These land cover changes caused changes in the behaviour of river flow resulting in frequent floods. Therefore, this study analyses the impacts of the changes in land cover due to urbanisation specifically with the changes in river flow, surface run-off and base-flows. Previously generated land cover maps of Msimbazi catchment and a combination of spatial and meteorological climate datasets were used to parameterise the hydrological model (SWAT). The model was calibrated and validated using the Sequential Uncertainty Fitting algorithm (SUFI-2) on a monthly resolution. The results show that there is an increase in surface run-off, mean river flow and the reduction of base-flow with the increase in urbanisation within the catchment. These increase in river flows, surface run-off and reduction of base-flow indicates the likelihood of an increase in flooding events in the catchment.

In July 2018, the province of Attapeuexperienced a major disaster, namely the collapse of the dam on the Xe-Pian Xe-Namnoy river. This incident resulted in loss of life, loss of property and environmental damage. In correcting the mistakesthatoccurred, the Lao governmentcarried out variousdisasterrisk management efforts, especially flash floods. This researchwasinvestigated by descriptive qualitative researchmethodusingliteraturereviewfromvariousjournals and documents related to flash floods in Laos. This study shows the various efforts made by the Lao government and variousrelated stakeholders to reducedisasterriskstartingfrom structural and non- structural mitigation. The Laos governmentalsogivesorders to stakeholders to compensate for lossescaused by the negligence of these stakeholders. The Lao governmentalsoinvolves the Lao people in communitybaseddisasterriskreduction by conductingcommunitypreparedness training. Thus, the communityisbetterprepared to face flash floodsdisasters in the future., {"references":["Abarquez, Imelda and Murshed, Zubair. 2004. Community-Based Disaster Risk Management-Field Practicioner's Handbook. Thailand: Asian Disaster Preparedness Center (ADPC). [Online] http://www.adpc.net/pdr-sea/publications/12Handbk.pdf. Accessed May 10th, 2022","Ashforth, B. E. 2001. Role transitions in organizational life: An identity-based perspective. Lawrence Erlbaum Associates Publishers","Biddle, B. J. 1986. Recent Developments in Role Theory. Annual Review of Sociology, 12, 67-92.","Carter, Nick. 1991. Disaster management: A Disaster Manager's Handbook. ADB : Manila.","DepartemenKelautan dan Perikanan (DKP). 2004. RencanaStrategis Pembangunan Kelautan dan Perikanan 2001-2004. DKP, Jakarta. 96 hal.","Direktorat Jenderal Cipta Karya. 2013. LaporanAkuntabilitas Kinerja InstansiPemerintah","Haghebaert. 2012. Community Practices for Disaster Risk Reduction in Japan. Spinger: Japan","Haghebaert. 2012. Making Aceh Safer Trough Disaster Risk reduction, Panduan PenguranganRisikoBencanaBerbasisKomunitas"]}

A rainfall regionalization method based on variation coefficient was applied with a variant in the construction of flash flood hyetographs with several return periods using the flash flood shape of the historical event that occurred in September 2021 in the Tlalnepantla River basin, Mexico, that caused severe damage to population and its infrastructure in a few hours. The historical flash flood was simulated with a semi-distributed model in the free software HEC-HMS in order to obtain the outflow hydrograph, and the flood plains were obtained with Iber and Hec-Ras 2d software that simulate free surface flow with a two-dimensional analysis. With photographs of the site, it was possible to locate traces of water that were contrasted with they calculated depths; they were concordant. Synthetic design storms were then simulated to estimate their potential consequences on the site.

Since the beginning of the 21st Century, Europe has been affected by destructive floods. European Union Member States have an obligation to develop flood hazard and flood risk maps as support to the Flood Risk Management Plan (FRMP). The main objective of this study is to propose a methodological framework for hazard and risk assessment of pluvial flash floods in Croatia at the catchment level, which can be integrated into the FRMP. Therefore, a methodology based on the source–pathway–consequence approach for flood risk assessment is presented, which complies with the EU Floods Directive. This integrated and comprehensive methodology is based on high-resolution open data available for EU Member States. Three scenarios are defined for a low, medium, and high probability, defined by design storms of different durations. The proposed methodology consists of flood hazard analysis, vulnerability assessment, and risk analysis. Pluvial flash flood hazards are analyzed using a 2D hydrologic–hydraulic model. The flood vulnerability assessment consists of a GIS analysis to identify receptors potentially at risk of flooding and an assessment of susceptibility to potential flood damage using depth–damage curves. Flood risk is assessed both qualitatively in terms of risk levels and quantitatively in terms of direct damages expressed in monetary terms. The developed methodology was applied and tested in a case study in the Gospić catchment in Croatia, which surrounds a small rural town frequently affected by pluvial flash floods.

Since the beginning of the 21st Century, Europe has been affected by destructive floods. European Union Member States have an obligation to develop flood hazard and flood risk maps as support to the Flood Risk Management Plan (FRMP). The main objective of this study is to propose a methodological framework for hazard and risk assessment of pluvial flash floods in Croatia at the catchment level, which can be integrated into the FRMP. Therefore, a methodology based on the source–pathway–consequence approach for flood risk assessment is presented, which complies with the EU Floods Directive. This integrated and comprehensive methodology is based on high-resolution open data available for EU Member States. Three scenarios are defined for a low, medium, and high probability, defined by design storms of different durations. The proposed methodology consists of flood hazard analysis, vulnerability assessment, and risk analysis. Pluvial flash flood hazards are analyzed using a 2D hydrologic–hydraulic model. The flood vulnerability assessment consists of a GIS analysis to identify receptors potentially at risk of flooding and an assessment of susceptibility to potential flood damage using depth–damage curves. Flood risk is assessed both qualitatively in terms of risk levels and quantitatively in terms of direct damages expressed in monetary terms. The developed methodology was applied and tested in a case study in the Gospić catchment in Croatia, which surrounds a small rural town frequently affected by pluvial flash floods.

Bujične poplave nastaju kao posljedica kratkotrajnih oborina velikog intenziteta ili uslijed puknuća/kvara hidrotehničkog objekta ili opreme. Karakterizira ih iznenadna lokalna poplava velikog volumena i kratkog trajanja koja nastaje u razdoblju od nekoliko, obično manje od šest, sati od jake kiše. Posljednjih godina, kao posljedica klimatskih ekstrema, bujične poplave su sve češća pojava pa i na područjima gdje se do sada nisu pojavljivale. Kroz upravljanje rizicima od poplava potrebno je dodatnu pažnju usmjeriti upravo na ovaj tip poplava jer su izuzetno opasne te mogu izazvati velike štete na imovinu i ljude. Kroz aktivnosti na lokalnoj razini bitno je educirati stanovništvo i osvijestiti na moguću opasnost od bujičnih poplava. Također potrebno poduzeti potrebne mjere kako bi se smanjili rizici od bujičnih poplava., Flash floods occur as a result of short-term, high-intensity precipitation or as a result of a failure of a hydrotechnical facility or equipment. They are characterized by a short duration and sudden local flood of large water volume that occurs within a period of several, usually less than six, hours from heavy rain. In recent years, as a result of climate extremes, flash floods are becoming more common, even in areas where they have not occurred before. It is necessary to focus extra attention on this type of floods, through flood risk management, because they are extremely dangerous and can cause damage to property and people. Through activities at the local level, it is important to educate the population and make them aware of the possible danger of flash floods. It is also necessary to take the necessary measures to reduce the risks of flash floods.

We pose the following research question: “what is the effect of flood protection works on flood risk?” To answer this question, we developed a flood risk assessment method that combines the typical hazard assessment via integrated hydrological and hydrodynamic calculations using HEC-HMS and 1D/2D HEC-RAS, respectively, and an original procedure for vulnerability assessment at the building level, which we applied in the town of Mandra in Attica, Greece. We performed calculations for 15 scenarios—combinations of return periods (T = 20, 50, 100, 150, and 200 y) and rain durations (t = 6, 12, and 18 h)—for the conditions of the year 2017, when there were no flood protection works, and today with these works in place. We identified the regions with high flood risk and concluded that the presence of the works caused a decrease in the inundation areas by 53–89%, along with reductions in the maximum water depths, the maximum flow velocities, and the average flood risk in Koropouli Street—the main street of Mandra, which suffered severe damage during the 2017 flood—by 38–62%, 18–52%, and 27–74%, respectively. The effect of the flood protection works increased with the increases in the return period and rain duration, while for the same return period the effect of the rain duration was more pronounced for the smaller return periods.

The Dutch province Limburg is characterized by sloping terrain and is therefore prone to serious damages during flash floods. This was also the case for the July 2021 flood event. The study focuses on a detailed hydrological analysis and the generation of deterministic flood forecasts of the tributaries of the Meuse River in Limburg (i.e. Rur, Niers and Swalm rivers). For hydrological modeling, the wflow_sbm model was used which is a distributed hydrological model and its parameters were estimated with the Iterative Hydrography Upscaling (IHU) method and from Pedo Transfer Functions (PTFs). The horizontal hydraulic conductivity fraction (KsatHorFrac) parameter for the Rur catchment was calibrated to generate deterministic forecasts. Due to the significant difference between the observed and the simulated discharges of the Niers and Swalm catchments it was not possible to calibrate their hydrological models. Probable reasons for this difference can be the effects of ground water abstractions for pit mining and other purposes, frequent mowing management in the Niers catchment etc. Therefore forecasts were generated only for the Rur catchment by coupling the wflow model with Delft-FEWS. The forecasts generated using the DWD ICON dataset showed substantial error when compared to the observed discharge. However, for the flood event of 2021, the model predicted high flows 5-6 days ahead of the flood. There was a large overestimation of the peak for the forecast in downstream of the Rur catchment. The sensitivity of the forecast performance by changing KsatHorFrac was also analysed in the end. The findings of the study show several scopes of improvements in the wflow hydrological modeling and flood forecasting of the Meuse tributaries. Future studies based on these recommendations could aid in providing a more accurate flood prediction in this region. Območje Limburga na Nizozemskem z relativno strmo topografijo terena je med poplavami julija 2021 utrpelo veliko poplavno škodo. Magistrska naloga se osredotoča na podrobne hidrološke analize in izdelavo deterministične napovedi poplav pritokov reke Meuse na območju Limburga (prispevna območja rek Rur, Niers in Swalm). Za potrebe hidrološkega modeliranja je bil uporabljen prostorsko distribuiran hidrološki model wflow_sbm, parametri modela so bili ocenjeni z metodo Iterative Hydrography Upscaling (IHU) in s pomočjo Pedo Transfer Function (PTF). Parameter horizontalne hidravlične prevodnosti (KsatHorFrac) v hidrološkem modelu prispevnega območja reke Rur je bil umerjen in na podlagi tega so bile izdelane deterministične hidrološke napovedi. Zaradi znatnih razlik med opazovanimi in simuliranimi pretoki rek Niers in Swalm ni bilo mogoče detajlno umeriti hidroloških modelov za prispevni območji teh dveh rek. Najverjetnejši vzroki za ugotovljena razhajanja med merjenimi in modeliranimi pretoki so velike količine odvzete vode za različne rabe ter izvaje regulacijskih in vzdrževalnih del v strugi reke Niers. Zato so bile hidrološke napovedi izdelane za prispevno območje reke Rur z združeno uporabo modelov wflow in Delft-FEWS. Hidrološke napoved, ustvarjena z uporabo nabora vhodnih hidrometeoroloških podatkov iz baze DWD ICON, so se izkazale kot precej nenatančne. Navkljub slabšim rezultatom simulacij je bil model sposoben za poplavni dogodek, ki se je zgodil leta 2021, napovedal visokovodne razmere 6 dni pred dejanskim pojavom poplavnega dogodka. Simulirane vrednosti pretoka so bile precenjene predvsem v spodnjem delu prispevnega območja reke Rur. Na koncu smo analizirali tudi občutljivost hidroloških napovedi na spremenjene vrednosti parametra KsatHorFraca. Izsledki študije nakazujejo možnosti izboljšav pri hidrološkem modeliranju z uporabo programa wflow in napovedovanju poplav hudourniških pritokov reke Meuse. Nadaljnje študije, ki temeljijo na naših ugotovitvah, bi lahko zagotovile natančnejšo napoved poplav v obravnavani regiji.

Central Italy is characterized by complex orography. The territorial response to heavy precipitation may activate different processes in terms of hydrogeological hazards. Floods, flash floods, and wet mass movements are the main ground effects triggered by heavy or persistent rainfall. The main aim of this work is to present a unique tool that is based on a distributed hydrological model, able to predict different rainfall-induced phenomena, and essential for the civil protection early warning activity. The Cetemps Hydrological Model is applied to the detection of hydrologically stressed areas over a spatial domain covering the central part of Italy during a weather event that occurred in 2014. The validation of three hydrological stress indices is proposed over a geographical area of approximately 64,500 km2 that includes catchments of varying size and physiography. The indices were used to identify areas subject to floods, flash floods, or landslides. Main results showed very high accuracies (~90%) for all proposed indices, with flood false alarms growing downstream to larger basins, but very close to zero in most cases. The three indices can give complementary information about the predominant phenomenon and are able to distinguish fluvial floods from pluvial floods. Nevertheless, the results were influenced by the presence of artificial reservoirs that regulated flood wave propagation, therefore, indices timing slightly worsen downstream in larger basins.

Study region: The Aswan region is a vast plateau in the South of Egypt located 150 m above mean sea level (AMSL). Within this region, the tourist city of Aswan is Egypt's southernmost city, located on the east bank of the Nile River. Study focus: The occurrence of flash floods can severely impact low-lying and densely populated areas. Therefore, highly vulnerable areas require effective mitigation measures to guarantee public safety and preserve archeological sites of great importance. This study investigates the interaction between the soil, surface water, and groundwater in the Aswan region of Egypt. Based on the rainfall analysis and the watershed hydrology, six different scenarios were run using the MODFLOW and Watershed Modeling System (WMS) software, which simulated rainfall recurrence intervals of 2, 5, 10, 25, 50 and 100 years. New hydrological insights for the region: The model's results indicated that an increase in the recurrence interval produced a rise in the groundwater level (GWL) up to 8.82 m (AMSL). Therefore, constructing three dams was proposed as a solution at the three basins of Al- Haytah, Al-Kimab, and Umm-Buwayrat. The proposed solution allows the storage of large volumes of water upstream. It mitigates GWL's rise within and near Aswan City. The presented study can be applied to vulnerable watersheds in arid and semi-arid regions. It can help policymakers to integrate additional sustainable solutions into construction dams and their implementation in development plans.

In considering projections that flooding will increase in the future years due to factors such as climate change and urbanization, the need for dependable and accurate water sensors systems is greater than ever. In this study, the performance of four different water level sensors, including ultrasonic, infrared (IR), and pressure sensors, is analyzed based on innovative characterization and comparative analysis, to determine whether or not these sensors have the ability to detect rising water levels and flash floods at an earlier stage under different conditions. During our exhaustive tests, we subjected the device to a variety of conditions, including clean and contaminated water, light and darkness, and an analogue connection to a display. When it came to monitoring water levels, the ultrasonic sensors stood out because of their remarkable precision and consistency. To address this issue, this study provides a novel and comparative examination of four water level sensors to determine which is the most effective and cost-effective in detecting floods and water level fluctuations. The IR sensor delivered accurate findings; however, it demonstrated some degree of variability throughout the course of the experiment. In addition, the results of our research show that the pressure sensor is a legitimate alternative to ultrasonic sensors. This presents a possibility that is more advantageous financially when it comes to the development of effective water level monitoring systems. The findings of this study are extremely helpful in improving the dependability and accuracy of flood detection systems and, eventually, in lessening the devastation caused by natural catastrophes.

River flooding has been triggering significant damage to lives and infrastructure and is a major worry all around the globe. To lessen these losses, proper planning and management methods need to be deployed. The purpose of this research is to fill a knowledge gap on the effects of reservoirs operation of the Idukki and Idamalyar to Periyar River Basin massive flooding. The proposed methodology is implemented on the Periyar River Basin located in Kerala, India, where severe flooding occurred during monsoon season in the year 2018. In this study, modelling technique has been used in two-step: (1) development of 1D physically based, distributed-parameter model (Soil and Water Assessment Tool, SWAT) to compute the stream flow and estimate the stream discharge at different outlet points; and (2) hybrid model is developed by linking SWAT with a well-known 2D hydrodynamic model (International River Interface Cooperative, iRIC) to display flood scenarios and to identify the flood-prone areas. The ArcSWAT user interface employed in the ArcGIS software was utilized to delineate the river basin. The SWAT model was calibrated and validated on daily and monthly basis at two gauge discharge stations, i.e., Neeleeswaram and Kalady. The statistical coefficients result obtained from SWAT model was in good agreement with the measured values for calibration and validation. The hybrid model simulation results compared with observed flood depth and remote sensing data demonstrated good capability of the model. Agreeable performances of computed results were observed in both flow fields and flood propagations. The result was compared with 2018 flood to check model accuracy and found to be satisfactory. The proposed framework can be utilized as an effective tool for efficient planning and management of natural disasters, such as flash floods.

The Valley of the Kings (KV) is a UNESCO world heritage site with more than thirty opened tombs. Since the first tombs were constructed, at least 24 historical flash flood events has been identified, each of which has been contributed to the destruction and deterioration of the tombs. Recently, most of these tombs have been damaged and inundated after 1994 flood. In order to understand the Geo-environmental impact mainly the past flash floods due to the intensive rainfall storm on the valley of kings and the long-term rock mass behavior under geostatic stresses in selected Horemheb tomb (KV57) and its impact on past failures and current stability, Remote sensing, GIS, LIDAR, 3D finite element stability analysis and rock mass quality assessments had been carried out using advanced methods and codes. Our work provides environmental satellite space views via landviewer Erath Observation System (EOS) Platform with passive and active sensors which include the Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Atmospherically resistant vegetation index (ARVI), Green Chlorophyll Index (GCI), Normalized Burn Ratio (NBR), Normalized Difference Snow Index (NDSI), Light Detection And Ranging (LIDAR) images, Terrain (DEM) Digital Elevation Models, 3D geological maps. In other hand experimental and numerical geotechnical evaluations and modeling of the rock mass of these underground structures and their surroundings have been executed. We estimated the rock mass quality of the different members within the Thebes limestone and Esna shale formations using the mechanical testing and Rock Mass Rating (RMR), rock quality system (Q-system) and Geological Strength Index (GSI) systems. Our recent analyses show that the KV57 rock- cut tomb at Luxor has been cut into poor to very poor quality marl shale masses due to the impact of flash foods. Rock failures of ceilings and pillars were frequently facilitated by local, unfavorably oriented persistent discontinuities, such as tension cracks and faults. Other failures were related to the disintegration of the marl limestone and Esna shale Formations into individual nodules upon weathering. Our data suggest that, in ancient Egypt monumental tomb construction, low-strength rock masses rarely resulted in modifications of the planned tomb design in order to minimise the risk of rock falls and to prevent collapses. The current flood protection measures are not enough. For this two following measures are proposed 1—to rise the current wall by 50 cm. 2—to fill the depression by reshaping bathymetry.

In the context of climate change, extreme rainfall events have greatly increased the frequency and risk of flash floods in the Yellow River Basin. In this study, the heavy rainfall and flash flood processes were studied as a system. Taking the driving factors of the heavy rainfall causing the flash floods as the main focus, the key factors of the heavy rainfall causing typical flash flood processes were identified, and the driving mechanism by which the heavy rainfall caused flash floods was revealed. Through comparative analysis of the rainfall related to 13 floods with peak discharges of greater than 2000 m3/s since measurements began at Baijiachuan hydrological station, it was found that different rainfall factors played a major driving role in the different flood factors. The factor that had the largest impact on the peak discharge was the average rainfall intensity; the factor that had the largest impact on the flood volume was the rainfall duration; and the factor that had the largest impact on the sediment volume was the maximum 1 h rainfall. The ecological construction of soil and water conservation projects on the Loess Plateau has had obvious peak-cutting and sediment-reducing effects on the flood processes driven by medium- and low-intensity rainfall events, but for high-intensity flash floods, the flood-reducing and sediment-reducing effects of these projects have been smaller. Therefore, despite the background of continuous ecological improvement on the Loess Plateau, the possibility of floods with large sediment loads occurring in the middle reaches of the Yellow River still exists.

In tropical regions, deep convective systems are associated with extreme rainfall storms that usually detonate flash floods and landslides in the Andean Colombian region. Several studies have used satellite data to address the structure and formation of tropical convective storms. However, there is a local gap in the characterization, which is essential for a better understanding of flash floods and preparedness, filling a gap in a region with scarce information regarding extreme events. In this work, we assess the deep convective storms in a mountainous region of Colombia using meteorological radar observations between 2014 and 2017. We start by identifying convective and stratiform formations. We refine the convective identification by classifying convective systems into enveloped (contained in a stratiform system) and unenveloped (not contained). Then, we analyze the systems’ temporal and spatial distributions and contrast them with the watersheds’ features. According to our results, unenveloped convective systems have higher reflectivity and hence higher rainfall intensities. Moreover, they also have a well-defined spatial and temporal distribution and are likely to occur in watersheds with elevation gradients of around 2000 m and an aspect contrary to the wind direction. Our assessment of the convective storms is of significant value for the hydrologic community working on flash floods. Moreover, the spatiotemporal description is highly relevant for stakeholders and future local analysis.

Masonry arch bridges constitute a substantial proportion of the existing bridge stock in the UK and elsewhere. Although this durable bridge form often demonstrates good structural performance under normal service loading, bridges spanning watercourses are vulnerable to damage from flood-induced loads. Fluvial flooding generates both hydrostatic and hydrodynamic effects on the arch superstructure in addition to well known-scour effects on the substructure, all of these have the potential to cause structural failure. While research on scour is relatively well advanced, quantification of the hydrodynamics forces on the bridge superstructure is not yet comprehensively understood. Where fast flood flows come into contact with the bridge superstructure, highly transient behaviour is observed, this may develop into violent interactions, particularly where floating debris is involved. This paper explores the novel use of smoothed particle hydrodynamics (SPH) to capture detailed pressure time histories and associated spatial distribution on masonry arches subject to fluvial flooding. SPH uses moving particles to represent the flow and is therefore ideal to simulate highly transient and potentially violent free-surface flows encountered during fast events. A typical arch bridge and representative flood flows are simulated in order to demonstrate the capability of the method. Under typical real-life flood flows, significant hydrodynamic pressures are generated which need to be considered in the assessment of such structures.

International audience

During extreme hydrological conditions such as flood events, sediments and alluvial soils may become re-suspended. As a consequence, the concentration of solid particulate matter (SPM) in the water column increases. As sediments represent a sink for the contaminants, when such perturbation occurs, the toxic substances may be re-dissolved into the water, causing harmful effects to the freshwater habitat. The purpose of this study was to evaluate the release of potentially toxic elements associated to SPM during flash floods. Two sampling sites on the Sava River were chosen: Litija (Slovenia), where the river has still the characteristics of an alpine river, and in Belgrade (Serbia), where Sava is a lowland river with a flat riverbed, slower flow and bigger quantities of fine-grained sediment. The results of the study showed a good correlation between the SPM mass concentration and water level/discharge. At both sampling sites, elevated concentrations of As, Cd, Cr, Cu, Pb, Ni and Zn were determined in SPM, indicating a moderate level of contamination at Litija and a high level at Belgrade. The results demonstrated that during the two investigated flash flood events limited the dissolution of PTE from SPM-bearing particles.

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.

Sendai Framework for 2015-2030 emphasises on the damage and loss assessment needs and its ecosystem level impacts. We have assessed the loss of forest cover and phytomass/carbon pool in the natural forest ecosystems lost due to extreme weather conditions leading flash floods and landslides during Kedarnath tragedy on June 17, 2013 in Mandakini Valley, Uttarakhand in Western Himalaya. We used high resolution satellite IRS LISS IV (5.8 m spatial resolution) of pre-disaster (2012) & post-disaster (2013). Since lost vegetation cannot be ground inventoried, a new approach was developed wherein we used pre-disaster spectral characteristics to identify sample locations in nearby and adjacent to affected areas. We laid 45 geotagged sample plots in May 2014 on both side of the 37 landslide affected areas within a distance of 2 km from river-bed for primary data collection. Above ground biomass and Carbon was estimated using standard protocols and used species-specific volumetric equations and wood density. Above ground biomass varied from 18.05t/ha in Alpine Scrub to 252.95 t/ha in Subtropical forests. Assuming that the biomass increment and spectral properties would not change significantly, we applied several vegetation indices to get best regression model with biomass. We found NDVI (2014) with coefficient of determination (R2) of 0.893, SE± 0.038 with linear function as the best for geospatial modelling of the biomass for pre-flood 2013 and post-flood 2014 situations. Coefficient of determination (R²) between estimated vis-à-vis modelled biomass was 0.8643. It is found that there is a net loss of 52,055.80 tonnes of forest biomass and 24,466.14 tonnes of carbon due to landslides and flash floods. The maximum biomass/carbon was lost in the sub-tropical forests. The loss of forest cover was maximum in subtropical forests.

Two field experiments were conducted at Regional Agricultural Research Station, Tarahara, Nepal during 2012 and 2013 to determine the effect of agronomic management on growth and yield of Swarna Sub1 under flash floods. The first experiment was laid out in a split plot design with three replications; and four different nutrient combinations at nursery as main plots and three age groups of rice seedlings as sub plots. The second experiment was laid out in a randomized complete block design and replicated thrice; with three post flood nutrient doses at six and 12 days after de-submergence (dad). The experiments were complete submerged at 10 days after transplanting for 12 days. The survival percentage, at 21 dad, was significantly higher in plots planted with 35 (90.25%) and 40 (91.58%) days-old seedlings compared to 30 days-old seedlings (81.75%). Plots with 35 days-old seedlings produced 5.15 t ha-1 with advantage of 18.83% over 30 days-old seedlings. Plots with 100-50-50 kg N-P2O5-K2O/ha at nursery recorded the highest grain filling of 79.41% and grain yield of 5.068 t/ha with more benefit. Post flood application of 20-20 N-K20kg/ha at 6 dad resulted in higher plant survival and taller plants, leading to significantly higher grain yield of 5.183 t/ha and straw yield of 5.315 t/ha. Hence, 35-40 days old seedlings raised with 100-50-50 kg N-P2O5-K2O /ha in nursery and the additional application of20-20 kg N-K2O /ha at 6 dad improved plant survival and enhanced yield of Swarna Sub1 under flash flood conditions. The practice has prospects of saving crop loss with getting rice yield above national average yield leading to enhanced food security in the flood prone areas of Nepal.

Flash floods can demolish infrastructure and property within seconds as they are very sudden. Flash floods are the main cause of the casualties and loss of properties. Existing natural disaster prediction algorithms contains false alarms. Indefinite techniques have been applied to overcome this leading issue in many countries. A competent flood management system must have the potential and tendency to identify the flash floods and atmospheric and climatic changes on early basis with less false alarm rate. Techniques which have been designed for the flash flood investigation may be categorized into following types a. Sensors based direct measurement b. Radar images c. Satellite based X-band images. The proposed research consisted of Artificial intelligence-based decision making for multi-modal sensing (direct measurement from multi-resolution sensors). A combination of sensors like Passive infrared (PIR), water level sensor, ultrasonic sensor, temperature sensor, pressure and altimeter sensors have been integrated on a single device to investigate the flash floods. The use of most suitable pair of measurement sensors can substantially enhance the advantage of more accuracy and reliability compared to a single sensor. In recent trends Particle swarm optimization is very popular for solving stochastic global optimization problems. The data was trained and processed by modified multi-layer feed forward neural network optimized by particle swarm optimization algorithm. Hybrid Modified Particle swarm optimization has been combined with feed forward neural network for the vigorous investigation of flash floods with less false alarm rate. Simulated results showed that the proposed research algorithm Modified multi-layer feed forward neural network optimized by Particle swarm optimization for multi-modal sensing performed very well in terms of evaluation parameters compared to other existing strategies with minimum false alarm ratio. Moreover, modified multi-layer feed forward neural network optimized by article swarm optimization algorithm results have been compared with the cuckoo search, modified cuckoo search, particle swarm optimization and Multi-layer perceptron neural network configurations for the validation purpose.

Resumen Las avenidas torrenciales son una de las amenazas de origen hidrometeorológico de mayor capacidad destructiva en términos de vidas humanas y pérdidas económicas, especialmente en ambientes montañosos y tropicales como Colombia. Sin embargo, no existe en nuestro país un consenso con respecto a la clasificación y terminología de eventos tipo flujos que permita caracterizar adecuadamente estos fenómenos. El presente artículo analiza el impacto, distribución espacial y temporal de dichos eventos en Colombia, y describe sus tipologías con base en las clasificaciones de fenómenos tipo flujo que se encuentran en el estado del arte. Se propone una clasificación de eventos tipo avenida torrencial para Colombia que incluye tres tipos de fenómenos: creciente súbita, inundación de escombros y flujo de escombros. Ideas destacadas: artículo de revisión que propone una clasificación para los eventos tipo avenida torrencial en Colombia a través de un estudio del estado del arte en el tema a nivel mundial y, además, un análisis del impacto, distribución espacial y temporal de las avenidas torrenciales en el país. Abstract Flash floods are one of the most destructive hydro-meteorological threats in terms of human lives and economic losses, especially in mountainous and tropical environments, such as Colombia. However, there is no consensus in our country regarding the terminology and classification of flow-type events that allows for an adequate characterization of these phenomena. The article analyzes the impact and the spatial and temporal distribution of those events in Colombia, and describes their typologies on the basis of state-of-the-art classifications of flow-type phenomena. It proposes a classification of flash flood events in Colombia, which includes three types of phenomena: sudden rise in water level, debris floods, and debris flows. Main Ideas: Review paper that proposes a classification for flash flood events in Colombia through a study of the state-of-the-art research on the matter worldwide, as well as an analysis of the impact and spatial and temporal distribution of flash floods in the country. Resumo As avenidas torrenciais são uma das ameaças de origem hidrometeorológica de maior capacidade destrutiva em termos de vidas humanas e perdas económicas, em especial, em ambientes montanhosos e tropicais como o da Colômbia. Contudo, não existe, em nosso país, um consenso a respeito da classificação e da terminologia de eventos tipo fluxos que permita caracterizar, de forma adequada, esses fenómenos. Este artigo analisa o impacto, a distribuição espacial e temporal desses eventos na Colômbia, e descreve suas tipologias com base nas classificações de fenómenos tipo fluxo que se encontram no estado da arte. É proposta uma classificação de eventos tipo avenida torrencial para o país que incluem três tipos de fenómenos: cheia súbita, inundação de cascalhos e fluxo de cascalhos. Ideias destacadas: artigo de revisão que propõe uma classificação para os eventos tipo avenida torrencial na Colômbia por meio de um estudo do estado da arte no tema no mundo e, além disso, uma análise do impacto, da distribuição espacial e temporal das avenidas torrenciais no país.

As a result of global climate changes, the number of extreme weather events is on the rise. They have a significant impact on both natural and built environments. One of these phenomena in Hungary is flash floods, mainly caused by rapidly occurring convective precipitation zones. Forecasting and examining this phenomenon is very complex. That is why it is hard to prepare for these types of floods, which burdens those performing civil and water defence management. This study presents the practical applicability of theoretical flow accumulation rasters through an example of a plot in Northern Hungary. Using a 5 m resolution digital elevation model (DEM), flow accumulation and other raster files (e.g. watershed and basin) were created and compared to previous official flash floods reports. As a result of these maps and information, high-risk valleys and watersheds were located. Further refinement of this methodology will be examined during my doctoral research by applying terrain and environmental covariates to create a reliable flash flood management system to assist with climate change modelling.

Recent studies have shown that a large portion of flood-associated fatalities are related to the use of vehicles. However, there is limited research on the role of infrastructure and geo-environmental conditions surrounding such incidents. This work exploits a dataset of 40 fatal vehicle-related events caused by flooding in Greece to explore the circumstances, the characteristics of infrastructure and of the surrounding environment and their possible influence in the studied incidents. The results showed that the majority of cases occurred in road segments and river crossings with a variety of design deficiencies related to safety and protection from flooding, including poor signage and lighting as well as the absence of road closures, road barriers and other crucial safety features. In high percentages incidents occurred in isolated/remote sites in rural areas, relatively narrow roads and low quality infrastructure (e.g., ford crossings) with a lack of easy alternate routes and absence of other individuals. In the vast majority of cases, the accidents occurred in small arid catchments drained by ephemeral torrents when experiencing extreme flows. The findings have practical implications as they provide a better understanding of dangerous circumstances and define the high-risk segments of the road, which is helpful in prioritizing and shaping appropriate interventions. © 2022 by the author. Licensee MDPI, Basel, Switzerland.

Funding Information: Author contributions. This work was initialised through ideas and discussions involving all of the authors. Following these discussions, JLR, MB, FS, and MK conceptualised the study. MK carried out the simulations of EFAS RRA, while JLR applied the ReAFFIRM method in the study area for the analysed flood event. JLR, MB, FS, and MK analysed the simulation results. Finally, JLR drafted the original manuscript, which was then reviewed by the co-authors. DST was responsible for funding acquisition and the provision of resources, and MB and DST supervised JLR throughout the development of this study and his doctoral dissertation. Publisher Copyright: © Copyright: Floods can arise from a variety of physical processes. Although numerous risk assessment approaches stress the importance of taking into account the possible combinations of flood types (i.e. compound floods), this awareness has so far not been reflected in the development of early warning systems: existing methods for forecasting flood hazards or the corresponding socio-economic impacts are generally designed for only one type of flooding. During compound flood events, these flood type-specific approaches are unable to identify overall hazards or impacts. Moreover, from the perspective of end-users (e.g. civil protection authorities), the monitoring of separate flood forecasts - with potentially contradictory outputs - can be confusing and time-consuming, and ultimately impede an effective emergency response. To enhance decision support, this paper proposes the integration of different flood type-specific approaches into one compound flood impact forecast. This possibility has been explored through the development of a unified system combining the simulations of two impact forecasting methods: the Rapid Risk Assessment of the European Flood Awareness System (EFAS RRA; representing fluvial floods) and the radar-based ReAFFIRM method (representing flash floods). The unified system has been tested for a recent catastrophic episode of compound flooding: the DANA event of September 2019 in south-east Spain (Depresion Aislada en Niveles Altos, meaning cut-off low). The combination of the two methods identified well the overall compound flood extents and impacts reported by various information sources. For instance, the simulated economic losses amounted to about EUR 670 million against EUR 425 million of reported insured losses. Although the compound impact estimates were less accurate at municipal level, they corresponded much better to the observed impacts than those generated by the two methods applied separately. This demonstrates the potential of such integrated approaches for improving decision support services.

The small spatial and temporal scales at which flash floods occur make predicting events challenging, particularly in data-poor environments where high-resolution weather models may not be available. Additionally, the uptake of warnings may be hampered by difficulties in translating the scientific information to the local context and experiences. Here we use social science methods to characterise local knowledge of flash flooding among vulnerable communities along the flat Lake Malawi shoreline in the district of Karonga, northern Malawi. This is then used to guide a scientific analysis of the factors that contribute to flash floods in the area using contemporary global datasets, including geomorphology, soil and land-use characteristics, and hydro-meteorological conditions. Our results show that communities interviewed have detailed knowledge of the impacts and drivers of flash floods (deforestation and sedimentation), early warning signs (changes in clouds, wind direction, and rainfall patterns), and distinct hydro-meteorological processes that lead to flash flood events at the beginning and end of the wet season. Our analysis shows that the scientific data corroborate this knowledge and that combining local and scientific knowledge provides improved understanding of flash flood processes within the local context. We highlight the potential of linking large-scale global datasets with local knowledge to improve the usability of flash flood warnings.

Natural risks, particularly flood risk, are a topical subject in Algeria and throughout the world, particularly given the last major catastrophic floods in Sudan (2020) and North Africa. With the development of the climate change phenomenon in the world, risk management is becoming increasingly necessary for all the actors concerned (decision-makers, technicians, and the population) to identify protection issues. In 2018, in the extreme south of Algeria, In-Guezzam City suffered a devastating flood that caused significant damage and loss of human and material resources. More than 100 homes collapsed, and approximately 345 families were displaced. Currently, there is no research work to assess the hydrological situation and the risk of flooding in this region. Therefore, the main purpose of this study is to shed light on the risk of flash floods in the extreme south of Algeria with more specific attention to the August 2018 floods as well as the climate trends over the past 30 years using Mann–Kendall test and Sen’s Slope Estimator. The chosen approach involves a hydrological study and hydrodynamic modeling using HEC-RAS software. This latter allows for simulating floods using statistical methods and creating several regional flood hazard maps.

Water depths and flow velocities decisively influence the damage caused by flash floods. Geographic Information System (GIS) is a powerful and useful tool, allowing the spa-tial analysis of results obtained by hydraulic modelling, namely from the HEC-RAS/HEC- GeoRAS software. The GIS spatial analysis performed in this study seeks to explain and quantify the spatial relationships between the stream channel features and flow components during flash flood events. Despite these relationships are generically known, there are few studies exploring this subject in different geographic contexts. A 1D hydraulic model was ap-plied in a small watershed in Portugal, providing good results in the definition of floodable areas, water depths and longitudinal velocities. No direct relationship was found between water depths and velocities in the floodable areas; however, negative strong correlations were found between the two flow components along the stream centerlines. Bed slope, channel and flood width, and roughness prove to be highly relevant on the longitudinal varia-tions of water depths and velocities and on the location of maximum values. Increasing peak discharges and return periods (RT) can change the relationships between water depths and velocities at the same location. Results can be improved with more accurate elevation data for stream channels and floodplains.

International audience; During the last 5 years, south-eastern France experienced four deadly Mediterranean flash-floods: one in October 2015, two in November and December 2019 and the last one in October 2020, caused by the Storm Alex. The 2015 and 2019 events mostly affected small coastal catchments of the French Riviera (< 50 km2), characterized by high density urban areas. These events were recently used as case studies for developing flash-flood real-time simulation methods, by coupling hydrologic and hydraulic models. The objective of this work is to test such hydrologic-hydraulic coupling for the simulation of the Alex event on the Vésubie catchment, one of the highly affected catchments. Two challenges will be tackled in this work, by testing the coupling (i) at the regional scale (catchment > 100 km2) and (ii) in the context of significant topographic changes due to the flood. A continuous semi-distributed rainfall-runoff model has been coupled with the Basilisk software, which is based on state-of-the-art 2D hydraulic modelling (well-balanced finite volume method for shallow water equations) with adaptive grid refinement. The streamflow series and inundation extents simulated have be compared with available observations gathered from post-event surveys with a particular focus on two places (Saint-Martin-Vésubie and Roquebilière).

Flash floods are typically associated with short, high-intensity and extreme rain-storms, and they are characterized by short response time and severely impact and damage communities in different areas in China. In order to scientifically assess the risks of flash floods, this paper takes Hubei Province as an example to carry out risk assessment. Based on Pearson correlation coefficient and principal component analysis methods, 14 factors were selected from 98 factors to establish a risk assessment model. The confidence coefficient model and multi-factor superposition method were used to determine the weight of each risk factor, and a risk map of Hubei Province was finally constructed. The results show that medium-high risk areas in Huanggang account for 47.00%, and high-risk areas account for 8.70%, with both areas adding up to more than 50%, followed by more than 40% in Shiyan, E’zhou and Xianning, and more than 30% in Huangshi, Yichang, Xiangyang, Jingmen and Suizhou. The risk level distribution is highly consistent with the location and frequency of flash flood disasters, shows high reliability, and can provide data support for flash flood disaster prevention and control. This study used a quantitative method to determine the key factors affecting flash flood disasters and provides a reference and basis for flash flood risk assessment in other provinces in China.

Roughness is the key parameter for surface runoff simulations. This study aims to determine robust Manning resistance coefficients (𝑛) on the basis of consecutive artificial rainfall experiments on natural hillslopes available in literature, obtained at 22 different sites with different degrees of vegetation cover and type. The Manning resistance coefficient is particularly important in the context of two dimensional (2D) hydraulic heavy rainfall simulations. Since there is a wide range of possible resistance values available leading to significantly different results regarding the accumulation of surface runoff, especially for shallow water depths. The planning of flood protection structures is directly affected by these uncertainties. This work also improves the knowledge between roughness and the shape of the hydrograph allowing a better calibration of infiltration models. As flow velocity, water depth, and infiltration rate were not observed during the rainfall experiments, only the outflow of the test field and rain intensity are known. For this purpose, a framework was developed to parameterize shallow water depth (< 1 cm) -dependent roughness coefficients. To test the robustness of the framework, three different formulations of depth-dependent roughness and a constant Manning coefficient are used by comparing the measured discharge under different rainfall intensities with simulations in a 2D-hydraulic model. We identified a strong dependency of Manning’s 𝑛 on the degree of vegetation cover and -type as well as an influence of consecutive rainfall events. This finally leads to a more robust parameterization of near surface roughness for hydrodynamic modelling, which is particularly important for the simulation of heavy rainfall events.

Flash floods are among the most devastating natural hazards in the world. According to Jamali et al. (2020), they are responsible for nearly 84% of deaths from natural disasters. While flooding from a conventional flood can be anticipated with some lead time, a flash flood is much more rapid and localized, and therefore much more difficult to predict. This is the case in the Mediterranean regions of France. Faced with this problem, the institutions in charge of flood forecasting need quality information and efficient models in order to optimize their responses. Because the rainfall that generates these flash floods is very heterogeneous both in time and space, in addition to the fundamentally non-linear nature of the rainfall-flow relationship, forecasting them remains a very serious challenge. For three decades now, neural networks have proven their efficiency in solving complex and non-linear problems, in particular rainfall-flow relationships in various hydrological situations. Within these types of models, Deep Learning as a learning method that is mainly applied to deep neural networks has proven to be particularly successful in many disciplines. However, because of their black box character, which seems to us rather an advantage considering the lack of knowledge on some hydrological processes, the interest of their application is sometimes questioned.For this reason, this work has applied deep neural networks to flash flood forecasting with three main objectives: the first objective aims at interpreting the parameters of the deep layers of the three types of perceptrons generally used in hydrology: static, directed, recurrent. To do so, this work followed two steps: (i) extracting the parameter values of the optimized models using the "Knowledge eXtraction (KnoX)" method proposed by Kong A Siou et al. (2013); (ii) interpreting these parameters through a comparative analysis of this information with data characterizing some hydrological processes of the watershed; this part has been published in the proceedings of the ITISE 2018 international conference, for the forecasting component, and in a book chapter of the LNCS (Lecture Notes in Computer Sciences) Springer series for the interpretation of the parameters. The second objective is to take into account the spatialization of precipitation and the associated scale effects through deep nested basin modelling. This allowed to extend the forecast lead time that had been achieved by Artigue (2012) from 2 to 3 hours, thanks to the introduction of physical information in the model; this work has been submitted to the journal Water. The third objective, following a dual approach of the first objective, proposes to inject information into the deep layer parameters of the models in order to improve their forecasting performance. If this last objective has not been completely achieved, we note however that it brings benefits for recurrent networks with a significant improvement of forecasting results.This work has highlighted, once again, the quality of the model selection method, which allows not only to make efficient forecasts on the most intense events of the database, but also to achieve a parsimonious deep architecture allowing, thanks to the Levenberg-Marquardt training rule, to train the deep layers without observing any vanishing gradient.; Les crues éclair font partie des risques naturels les plus dévastateurs dans le monde. Selon Jamali et al. (2020), elles sont responsables de près de 84 % des décès causés par les désastres naturels. Si l’inondation par une crue classique peut être anticipée avec un certain délai, une crue éclair est bien plus rapide et localisée, et donc bien plus difficile à prévoir. Tel est le cas des régions méditerranéennes en France. Face à cette problématique, les institutions chargées de la prévision des crues et des inondations ont besoin d’informations de qualité et de modèles performants afin d’optimiser leurs réponses. Du fait que les pluies génératrices de ces crues éclair sont très hétérogènes aussi bien dans le temps que dans l’espace, en sus du caractère fondamentalement non-linéaire de la relation pluie-débit, leur prévision reste un défi très sérieux. Depuis maintenant trois décennies, les réseaux de neurones ont prouvé leur efficacité pour résoudre des problèmes complexes et non linéaires, en particulier les relations pluie-débits dans diverses situations hydrologiques. Au sein de ces types de modèles, le Deep Learning en tant qu’une méthode d’apprentissage qui s’applique principalement aux réseaux de neurones profonds, s’est montré particulièrement performant dans de nombreuses disciplines. Cependant, du fait de leur caractère de boîtes noires, qui nous parait plutôt un avantage compte tenu du manque de connaissance sur certains processus hydrologiques, l’intérêt de leur application est parfois mis en doute.Pour cette raison ce travail a appliqué des réseaux de neurones profonds à la prévision des crues éclair avec trois principaux objectifs : le premier objectif vise l’interprétation des paramètres des couches profondes des trois types de perceptrons généralement utilisés en hydrologie : statique, dirigé, récurrent. Pour ce faire ce travail a suivi deux étapes : (i) extraire les valeurs des paramètres des modèles optimisés en utilisant la méthode « Knowledge eXtraction (KnoX)» proposée par Kong A Siou et al. (2013) ; (ii) interpréter ces paramètres grâce à une analyse comparative de ces informations avec les données caractérisant certains processus hydrologiques du bassin versant ; cette partie a été publiée dans les actes de la conférence internationale ITISE 2018, pour le volet prévision, et dans un chapitre de livre de la série LNCS (Lecture Notes in Computer Sciences) pour l’interprétation des paramètres. Le second objectif est de prendre en compte la spatialisation des précipitations et les effets d’échelle associés grâce à une modélisation profonde par bassins emboités. Ceci a permis d’allonger l’échéance de prévision qui avait été réalisée par Artigue (2012) de 2 à 3 heures, grâce à l’introduction d’information physiques dans le modèle ; ce travail a été soumis à la revue Water. Le troisième objectif, en suivant une approche duale du premier objectif, propose d’injecter de l’information dans les paramètres des couches profondes des modèles afin d’améliorer leur performance en prévision. Si ce dernier objectif n’a pas été complètement atteint on note cependant qu’il apporte des bénéfices pour les réseaux récurrents avec une amélioration des résultats de prévision significative. Ce travail a mis, une fois de plus, en évidence la qualité de la méthode de sélection de modèles, qui permet non seulement de réaliser des prévisions performantes sur les évènements les plus intenses de la base de données, mais aussi d’aboutir à une architecture profonde parcimonieuse permettant, grâce à la règle d’apprentissage de levenberg-Marquardt d’apprendre les couches profondes sans observer d’atténuation du gradient.

[EN] This paper proposes a trivariate methodology for flood frequency estimation. It combines the flood peak, storm magnitude, and initial soil moisture condition (ISMC) as the main flood-related statistical variables to be considered. The semi-arid Mediterranean "Rambla del Poyo" catchment has been used as a representative case study where the influence of the spatio-temporal variability of the storms and the ISMC on floods can lead to differences of up to two orders of magnitude in quantiles when the most commonly used methods are applied. In order to incorporate the main flood-generating mechanisms, the integrated use of a multidimensional storm generator with distributed hydrological modelling is proposed. Flood quantiles are then estimated by combining the maximum flows with the storm magnitude and ISMC in a trivariate probability distribution function through the application of Bayes' theorem and Lagrange's Mean Value theorem. Although the methodology proposed in this paper has been applied and tested in only one case study, it can be extended to other case studies due to its process-based orientation., This research was funded by the Ministry of Science and Innovation of Spain through the research projects TETISMED (CGL2014-58127-C3-3-R) and TETISCHANGE (ref RTI2018-093717-B-I00). The authors thank both AEMET for the daily data and Jucar River Basin Water Authority for the sub-daily data provided for this research. We also thank the Associate Editor and the two anonymous reviewers for their valuable comments that contributed to the improvement of the manuscript.

Great effort has been made over the last few decades to develop and improve methods for monitoring hydrological disasters. Among them, rainfall thresholds, defined as the minimum rainfall conditions that are likely to trigger hydrological disasters, are the most popular tool used to study the relationship between rainfall and hydrological disaster occurrences, highlighted due to their straightforward approach for application in different regions. Some factors make it difficult to determine rainfall thresholds, such as the quality of rainfall and disasters data, and the large distances between the rain gauges and the disaster. To overcome these limitations, the use of satellite-based precipitation products is a way out to characterize rainfall events that trigger disasters. Accordingly, this thesis aims to present an improved method of using a threshold of peak rainfall intensity for robust floods evaluation and warnings by applying probabilistic-based methods and taking into consideration the antecedent conditions. Moreover, this study assesses the quality of satellite-based precipitation products to create rainfall thresholds for floods monitoring. São Paulo State was selected as the study area because is a typical hot spot frequented by landslides and floods. In addition, São Paulo is the richest state in Brazil, with the largest number of floods, flash floods, and sub-daily rainfall data made available by public agencies. Results show that the use of tolerance levels and the delineating of an intermediate threshold by incorporating an exponential curve that relates rainfall intensity and Antecedent Precipitation Index (API) helped reduce significantly many uncertainties in the hydrological disasters monitoring. Moreover, the use of satellite-based products showed to be less accurate compared to rain gauges to characterize extreme rainfall events and delineating the thresholds, tending to underestimate the ground-based precipitation mainly for sub-daily scales. Although underestimating the ground-based data, the satellite-based products can be applied as an alternative source to develop warning systems, especially in areas with a lower density of rain gauges. Overall, the results found in this study showed to be helpful for decision-making by the implementation of flood monitoring and early warning systems, and, consequently to contribute to the development of more robust and/or complex flood models able to minimize the hydrological impacts, whether using ground-based or satellite-based data. Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES Grande esforço está sendo realizado durantes as últimas décadas para desenvolvimento de métodos de monitoramento de desastres hidrológicos. Dentre eles, os limiares de precipitação, definidos como a condição mínima de precipitação que são susceptíveis a deflagração desastres hidrológicos, são a ferramenta mais popular usada para estudar a relação entre precipitação e desastres hidrológicos, destacando-se devido à sua abordagem simples. Alguns fatores dificultam a determinação dos limiares de chuva, como a qualidade dos dados de chuva e desastres, e as grandes distâncias entre as estações pluviométricas e os desastres. Para superar essas limitações, o uso de produtos de precipitação por satélite é uma saída para caracterizar os eventos de chuva que desencadeiam desastres. Consequentemente, esta tese tem como objetivo apresentar um método melhorado para a delimitação de limiares de picos de intensidade de chuva para avaliação e alerta dos desastres, através da aplicação de métodos baseados em probabilística e levando em consideração as condições antecedentes ao desastre. Além disso, avaliar a qualidade dos produtos de precipitação baseados em satélite para criar limites de precipitação para o monitoramento de desastres hidrológicos. O Estado de São Paulo foi escolhido por ser uma região típica para ocorrências de deslizamentos e inundações. Além disso, São Paulo é o estado mais rico do Brasil, com o maior número de registros de inundações e enxurradas, bem como dados pluviométricos subdiários disponibilizados por órgãos públicos. Os resultados mostram que o uso de níveis de tolerância e o delineamento de um limiar intermediário pela incorporação de uma curva exponencial que relaciona a intensidade da chuva e o Índice de Precipitação Antecedente (API) ajudou a reduzir significativamente muitas incertezas no monitoramento de desastres hidrológicos. Além disso, a avaliação dos produtos baseados em satélite mostrou que eles apresentam menor acurácia em relação aos pluviômetros, tendendo a subestimar as medidas observadas in-situ, principalmente, para escalas subdiárias. No entanto, eles podem ser aplicados como fonte alternativa para o desenvolvimento de sistemas de alerta, principalmente, em áreas com menor densidade de pluviômetros. De forma geral, conclui se que os resultados encontrados devem ser úteis na tomada de decisão, na implementação de sistemas de monitoramento e alerta precoce de inundações, e na contribuição para o desenvolvimento de modelos mais robustos e/ou complexos para minimizar os impactos, seja utilizando dados in-situ ou baseados em satélite.

Despite recent technological advances, many parts of the world continue to experience flood disasters accompanied by significant loss of human lives. Understanding how frequent these deadly catastrophes are creates many uncertainties, especially in areas where disaster records are scarce or have short timeframes. It is, however, very important from a preparedness and civil protection standpoint to assess the frequency of such high-mortality events, especially considering the threat of climate change. This work develops a high-mortality flood event database using multiple international sources, covering a relatively long time window (1882–2021), exploring the deadliest floods in the Eastern Mediterranean region, and examining their seasonal distribution, their temporal evolution, and their basic spatial patterns. The study identifies 132 flash flood events (causing ≥10 fatalities) with a return period of only 1.56 years. Additionally, higher-magnitude events (>85th percentile) were found to be less common but still not very rare (return period = 9.1 years). The number of events shows an increase in recent decades, while seasonal and spatial patterns were identified as well. Overall, the findings provide a foundation for understanding how common catastrophic flood events are in the region, are beneficial for policymakers and relevant professionals, and are an important stepping stone towards a complete understanding of how extreme floods have changed in the last century or will change in the near future.

The use of machine learning (ML) for predicting high river flow events is gaining prominence and among its non-trivial design decisions is the definition of the quantitative precipitation estimate (QPE) product included in the input dataset. This study proposes and evaluates the use of multiple concurrent QPEs to improve the performance of a ML model towards the forecasting of the discharge in a flashy urban catchment. Multiple extreme learning machine (ELM) models were trained with distinct combinations of QPEs from radar, reanalysis, and gauge datasets. Their performance was then assessed in terms of goodness of fit and contingency analysis for the prediction of high flows. It was found that multi-QPEs models overperformed the best of its single-QPE counterparts, with gains in Kling-Gupta efficiency (KGE) values up to 4.76% and increase of precision in detecting high flows up to 7.27% for the lead times in which forecasts were considered “useful”. The novelty of these results suggests that the implementation of ML models could achieve better performance if the predictive features related to rainfall data were more diverse in terms of data sources when compared with the currently predominant use of a single QPE product.

Despite the important advances in flood forecasting and protection, floods remain one of the most lethal types of natural hazards. Previous works have explored several factors influencing the risks of flooding to human life and health. However, there is limited research and understanding on indoor flood fatalities and the circumstances under which they occur. This study explores victim-, building-, and situation-related characteristics in order to provide a better understanding of the conditions that lead to flood-related indoor deaths, exploiting a fatality database developed for Greece (1960–2020). The correlation analysis showed that indoor victims, compared with outdoor ones, tend to be older individuals, with high percentages of disabilities. A significant statistical association of the building material, roof type, and distance from the river with the building collapse was also found. The profile of the buildings in which flood fatality occurred was further compared with that of neighboring non-fatal buildings that were inhabited during the flood events. The statistical results indicated that the buildings with a fatality occurrence are mostly single-storey structures, made from masonry as the main building material. The findings have practical implications in risk communication and mitigation in terms of identifying the specific populations, circumstances, settings, and mechanisms that lead to dangerous indoor situations during flooding events.

Zimbabwe has been affected by numerous floods-related disasters in the recent past. These disasters often left rural communities in difficult socioeconomic situations. Floods are among the major water-related hazards and natural disasters worldwide. They are associated with excess rainfall, resulting in river overflow due to climate change . Developing countries constitute a large number of losses caused by water hazards. Thereby, in these countries, the vulnerabilities of households that depend on rain fed agriculture and livestock production for their livelihoods increases. This review paper seeks to establish the association between anthropogenic flash floods and climate change and unearth the impacts; vulnerabilities and adaptation options associated with anthropogenic flash floods in rural Zimbabwe. The study found that numerous anthropogenic activities perpetuate an increase in flood risk. These include littering, river or dam regulation measures, intensified land use and emissions of greenhouse gases, which subsequently result in global climate change. The impacts of flash floods established in the study include drought, food insecurity, displacements, malnutrition and severe effects on subsistence economy. The study concluded that even though most rural communities in Zimbabwe are vulnerable to the effects of floods, they have devised numerous diverse adaptation strategies to cope with the changes in the environment.

The north-west (NW) Mediterranean coastal zone is a populous and well-developed area in which the impact of natural hazards like flash floods and coastal storms can result in frequent and significant damages. Although the occurrence and impacts of such hazards have been widely covered, few studies have considered their combined impact on the region, which would result in more damage. Within this context, this study analyses the occurrence and characteristics of compound extreme events of heavy rainfall episodes (as a proxy for flash floods) and coastal storms (using the maximum significant wave height) along the Catalan coast as a paradigm of the NW Mediterranean. Two different types of events are considered: multivariate, in which the two hazards occur at the same location, and spatially compounding, in which they occur within the same limited time window, and their impacts accumulate at distinct and separate locations. The analysis is regionally performed along a coastline extension of about 600¿km by considering seven coastal sectors and their corresponding river catchment basins. Once the compound events are analysed, the synoptic atmospheric pressure fields are analysed to determine the prevailing weather conditions that generated them. Finally, a Bayesian network is used to fully characterize these events over the territory. The obtained results show that the NW Mediterranean, represented by the Catalan coast, has a high probability of experiencing compound extreme events. Despite the relatively small size of the study area, there are significant variations in the event characteristics along the territory, with the most frequent type being spatially compound, except in the northernmost sectors where multivariate events dominate. These northern sectors also present the highest correlation in the intensity of both hazards. Three representative synoptic situations have been identified as dominant for the occurrence of these events, with different relative importance levels of the compounding drivers (rainfall and waves) and different distributions of impacts across coastal basins. Overall, results obtained from specific events indicated that heavy rainfall is related to the most significant impacts despite having a larger spatial reach. This work has been done in the framework of the M-CostAdapt (CTM2017-83655-C2-1&2-R) research project, funded by the Spanish Ministry of Economy and Competitiveness (MINECO/AEI/FEDER, UE). The authors express their gratitude to IH-Cantabria and Puertos del Estado for supplying wave data, and AEMET and SMC for supplying rain data. Our thanks are given to Montserrat Llasat-Botija for her contribution in the identification of the compound events as well as for all the information about the impacts. Peer Reviewed Objectius de Desenvolupament Sostenible::13 - Acció per al Clima

A hydrometeorological forecasting system has been operating at the Institute of Marine Biological Resources and Inland Waters (IMBRIW) of the Hellenic Centre for Marine Research (HCMR) since September 2015. The system consists of the Advanced Weather Research and Forecasting (WRF-ARW) model, the WRF-Hydro hydrological model, and the HEC-RAS hydraulic–hydrodynamic model. The system provides daily 120 h weather forecasts focusing on Greece (4 km horizontal resolution) and hydrological forecasts for the Spercheios and Evrotas rivers in Greece (100 m horizontal resolution), also providing flash flood inundation forecasts when needed (5 m horizontal resolution). The main aim of this study is to evaluate precipitation forecasts produced in a 4-year period (September 2015–August 2019) using measurements from meteorological stations across Greece. Water level forecasts for the Evrotas and Spercheios rivers were also evaluated using measurements from hydrological stations operated by the IMBRIW. Moreover, the forecast skill of the chained meteorological–hydrological–hydraulic operation of the system was investigated during a catastrophic flash flood in the Evrotas river. The results indicated that the system provided skillful precipitation and water level forecasts. The best evaluation results were yielded during rainy periods. They also demonstrated that timely flash flood forecasting products could benefit flood warning and emergency responses due to their efficiency and increased lead time.

Debris flow events, generated by surface runoff, occur with great frequency in the Dolomites (Northeastern Italian Alps) during the summer season. Summer thunderstorms, which are common in the region, can quickly generate runoff at the base of rocky cliffs, which then entrains and propagates downstream the underlying unconsolidated material. In the past, the main atmospheric feature considered in evaluating the initiation of debris flow events was rainfall. Observations led to the development of rainfall intensity–duration thresholds for sediment mobilization, which compared incoming severe rainfalls with the potential for triggering debris flows. This study works toward the examination of another characteristic of the atmosphere, the atmospheric electric field. In particular, the behavior of the electric field prior to convective rainfall is investigated as an indicator of rainfall intensities capable of triggering debris flows, in a basin near Cortina d’Ampezzo (Italy). Results suggest that prior to bursts of intense rainfall, the electric field derivative frequency distribution exhibits a recurrent pattern roughly half the time. When it occurs, the amplitude of derivative frequency distribution intersects the zero axis twice before rainfall reaches maximum intensity. A regression model is designed which considers the amplitude maximum and the difference in time between the crossings of the zero axis. The validation of this model suggests a mild relationship between electric field and rainfall intensity in an alpine environment.

Flash floods cause severe natural disasters over the world generating property and infrastructures damages, poverty and loss of human life, among others. Mediterranean coastal watersheds are specially sensible to flash floods effects due to their typical drainage basin features (steep slopes, short concentration times, complex orography, etc.) and the high rainfall intensity typical of convective systems. In the present study, the temporal evolution of the hydrological answer in five Mediterranean (SE Spain) ravine basins with sizes from 10.2 km2 to 200.9 km2 were analysed. A sub-daily SWAT model was used at watershed scale to capture the complex hydrological dynamics. Five land use scenarios corresponding to no-urbanization (baseline), 1990, 2000, 2006 and 2012 were evaluated using GIS-based tools. Additionally, statistical significant differences among the studied scenarios were checked employing the Kruskal-Wallis and post-hoc tests based on Mann-Whitney test with BH correction. Our results show that flash flood risks have increased in the studied catchments due to changes in land uses, particularly affected by a large urban growth. Observed changes in soil uses have been important since the sixties of the last century, because of a high demographic and touristic pressure and specially the urban area has enhanced considerably during the last 22 years. Currently, some of these catchments present around 70% of their surface occupied by urban land uses with high population density producing curve number surpasses 85 and 90 levels. The hydrological response of the studied basins changed to higher flow rate peaks and shorter concentration times. Some discharges increased significantly from the baseline land use scenario (≈50 m3/s, 190 m3/s, 380 m3/s) to the most urbanised scenario (≈235 m3/s, 385 m3/s, 940 m3/s), respectively. These findings provide to urban planning policy makers very useful information in the face of flash flood effects, which have cost even human lifes in the studied ravine basins during last years. Financial support was provided partially by the University of Alicante, project GRE17-12. This study also has been conducted within the grant received from the Programa Nacional de Formación de Profesorado Universitario (FPU) conceded by the Spanish Ministry of Science to the first author.