Extreme Flash Flood Research Articles

Extreme flash flood susceptibility mapping using a novel PCA-based model stacking approach

This study introduces an efficient methodology for model stacking, incorporating six diverse machine learning and statistical models alongside principal component analysis (PCA). The approach is applied for the flash flood susceptibility mapping within the Karkheh Basin in Iran. The selected models include random forest (RF), boosted regression trees (BRT), support vector machine (SVM), artificial neural networks (ANN), generalized additive model (GAM), and the least absolute shrinkage and selection operator (Lasso), with RF also serving as the meta-model for the stacking. The results revealed significant correlations among the predictions of the individual models, which could potentially impact the meta-model’s efficacy. To address this, PCA was applied to the model predictions to generate de-correlated components as inputs for the meta-model, thereby enhancing prediction accuracy and robustness. Evaluation based on the area under the receiver operating characteristic (AUROC) curve demonstrated that the GAM outperformed all other individual models with the highest accuracy score of 0.924. In contrast, the RF and ANN models had the lowest accuracy, both registering at 0.872. However, the performance disparity across models was minimal. Notably, the PCA-based stacking approach (0.936) surpassed both traditional model stacking (0.912) and the performances of all individual models, advocating for its use in enhancing predictive accuracy. These findings endorse the PCA-stacking method over conventional stacking techniques. Nonetheless, further research across varied applications is warranted to generalize its efficacy.

Hydrometeorological controls of and social response to the 22 October 2019 catastrophic flash flood in Catalonia, north-eastern Spain

Abstract. On 22 October 2019, the Francolí River basin in Catalonia, north-eastern Spain, experienced a heavy precipitation event that resulted in a catastrophic flash flood, causing six fatalities. Few studies comprehensively address both the physical and human dimensions and their interrelations during extreme flash flooding. This research takes a step forward towards filling this gap in knowledge by examining the alignment among all these factors. The hydrometeorological factors are investigated using the new Triangle-based Regional Atmospheric Model, radar-derived precipitation estimates, post-flood field and gauge observations, and the Kinematic Local Excess Model. The social dimension is assessed by examining the relationship between catchment dynamics and warning response times and by quantifying human behaviour during the course of the flash flood through a post-event citizen science campaign. Results reveal that a persistent south-easterly airflow brought low-level moisture and established convective instability in the region, while local orography was instrumental to triggering deep moist convection. A convective train promoted intense, copious, and prolonged precipitation over the north-western catchment headwaters. Basin response was significantly modulated by the very dry initial soil moisture conditions. After the long-lasting rainfall, an acute burst of precipitation resulted in extreme flash flooding. Fast and abrupt increases in streamflow affect small spatial scales and leave limited time for the effective implementation of protective measures. The institutional organization–protection–prevention cycle unfolded at the spatial and temporal scales typically dominated by the meteorological rather than hydrological scales. Although the citizen science campaign reveals the effectiveness of the warnings in reaching the population living in the most affected areas, a significant proportion of the respondents expressed a lack of adequate information or were unfamiliar with the intended meaning. In addition, a majority of the interviewees did not perceive any significant threat to life or property. In view of these results, this study identifies potential areas for improving social preparedness for similar natural hazards in the future.

Enhanced groundwater availability through rainwater harvesting and managed aquifer recharge in arid regions

Climate change in desert areas and semi-arid watersheds may offer a promising solution for the water scarcity problem that Bedouins and local inhabitants face. This study investigated the integrated water resources management in arid and semi-arid regions using rainwater harvesting in combination with the managed aquifer recharge (RWH-MAR) technique. The study also used recharge wells and storage dams to achieve the sustainability of groundwater supplies in the context of climate change and management of the flow to the Gulf of Suez. Therefore, different return periods of 10, 25, 50, and 100 years were considered for the annual flood volume resulting from those watersheds. Moreover, hydrologic modeling was carried out for the El Qaa plain area, South Sinai, Egypt, using the Watershed Modeling System (WMS) and the groundwater modeling of SEAWAT code. Our findings show that for different scenarios of climate change based on return periods of 10, 25, 50, and 100 years, the aquifer potentiality reached 24.3 MCM (million cubic meters) per year, 28.8 MCM, 36.7 MCM, and 49.4 MCM compared to 21.7 MCM at 2014 with storage of groundwater ranges 11.8%, 32.1%, 69%, and 127.4%, respectively. These findings have significant implications for the system of RWH-MAR and groundwater sustainability in El Qaa Plain, South Sinai. The RWH-MAR proved to be an effective approach that can be applied in different water-stressed and arid regions to support freshwater resources for sustainable future development and food security, as well as protect communities from extreme flash flood events.

Fluviomorphic trajectories for dryland ephemeral stream channels following extreme flash floods

AbstractEphemeral alluvial streams pose globally significant flood hazards to human habitation in drylands, but sparse data for these regions limit understanding of the character and impacts of extreme flooding. In this study, we document decadal changes in dryland ephemeral channel patterns at two sites in the lower Colorado River Basin (southwestern United States) that were ravaged by extraordinary flash floods in the 1970s: Bronco Creek, Arizona (1971), and Eldorado Canyon, Nevada (1974). We refer to these two floods as ‘fluviomorphic erasure events’, because they produced blank slates for the channels that were gradually moulded by more frequent but much smaller flood events. We studied georectified aerial photos that span ~60 years at each site to show that both study sites recovered to their pre‐flood condition after ~25 years. We employ channel network metrics: stream‐link area (SLA), geometric braiding index and junction‐node density. Each metric decreased during the short‐duration extreme flood erasure events. Subsequently, a fluviomorphic trajectory at a decadal tempo returned the channels to pre‐flood values. The SLA decreased at rates of 3.6%–4.1% per year in the decade following the floods. The extreme flood events decreased the pre‐flood geometric braiding index at the two sites by 56%–68%, and it took 15–24 years for this index to recover to pre‐flood values. In contrast, it took 30–35 years for the channels to recover to a uniform pre‐flood channel form, as indicated by the spatial distribution of bars and junction nodes. Our results document baseline examples of ephemeral stream channel evolution trajectories, as future climatic change will likely accelerate increases in the magnitudes and frequencies of extreme floods and geomorphic erasure events.

Cumulative sedimentation hazard map of urban areas subject to hyperconcentrated flash flood: A case study of Suide County in the Wuding River basin, China

AbstractFlash floods can carry substantial sediment, posing significant sedimentation hazards in hilly cities. The sedimentation hazard map can reproduce the sediment thickness and extent of an extreme events scenario, playing an important role in sediment risk management. However, current research primarily focuses on modeling the inundation area and depth of floods, while studying sedimentation hazard caused by flash floods in urban areas remains insufficient. This paper aims to address this gap by utilizing a numerical model that simulates hyperconcentrated flow in hilly urban areas using the two‐dimensional hydro‐sediment‐morphological model to compile the cumulative sedimentation hazard map. The model, built upon the open‐source TELEMAC‐MASCARET framework, incorporates Zhang Hongwu's formula to simulate sediment‐carrying capacity, particularly suitable for hyper‐sediment concentration near the riverbed. This paper uses the data of extreme flash flood events in the Wuding River basin in 2017 to simulate and compile the cumulative sedimentation hazard map. The hazard map delineates the sedimentation hazard extent and level attributable to overbank floodplain sedimentation. Notably, the sediment thickness is highest in areas near the levees on both sides of the Dali River. Moreover, the map illustrates the extent of channel erosion resulting from hyperconcentrated floods, which could jeopardize bank stability.

Flood Inundation mapping and mitigation options in data-scarce region of Beledwayne town in the Wabi Shebele River Basin of Somalia

Somalia has experienced extreme flash floods in recent years across the arid regions causing tremendous loss of lives and properties. However, the flood magnitude, depth, and frequency of occurrence are not yet quantified. This is mainly due to scarce datasets in the area. . In this study, integration of observed and Climate Hazards Infrared Precipitation (CHIRP) satellite rainfall products and remote sensing raster data were used to improve hydrological model simulation outputs. The Hydrologic Engineering Center namely HEC-HMS and HEC-RAS models were used to simulate the rainfall-runoff processes and flood inundation, respectively. The land use, soil, slope and Digital Elevation map (DEM) were used to set-up the models and generate outputs. The HEC-HMS model calibration results depict that the model is able to reproduce the observed streamflow The simulated flows generated by the model predicted good agreement with the observed flow with values of 0.79, 0.74, 0.78, and 0.78 evaluated through the Nash and Sutcliffe Efficiency (NSE), Runoff Volume Error (RVE), coefficient of determination (R2), and percentage error of peak flow (PEPF), respectively. The HEC-RAS model result indicates that the maximum flood depth and velocity were obtained at the floodplain area. The peak flood at 50, 100, and 200-year return period using General Extreme Value (GEV) distribution revealed 384m3s-1, 409m3s-1, and 434m3s-1, respectively. The 100-year peak flood discharge in a specific part of the river revealed a flood depth of 7.53m. The provision of Levees as mitigation measures revealed reduction of the flood extent by 35% and suggested as possible flood protection measures for the study area.

Analysing the Impact of Land Subsidence on the Flooding Risk: Evaluation Through InSAR and Modelling

Floods greatly impact human settlements in flood risk areas, such as floodplains and coastal lowlands, following heavy rainfall. The Alto Guadalentin valley, an orogenic tectonic depression, experiences extreme flash floods and land subsidence due to groundwater withdrawal, rendering it one of Europe's fastest subsiding regions. In this study, we compared two 2D flood event models representing different land subsidence scenarios for 1992 and 2016. To determine the flooded area and water depth variations due to land subsidence, the Hydrologic Engineering Centre River Analysis System 2D (HEC-RAS 2D) model was used to simulate flood inundation by the Alto Guadalentin River and its tributaries. Synthetic aperture radar (SAR) satellite (ERS, ENVISAT, and Cosmo-SkyMED) images were employed, along with the interferometric SAR (InSAR) technique, to calculate the magnitude and spatial distribution of land subsidence. By analysing the accumulated subsidence distributions obtained from InSAR, the original topography of the valley in 1992 and 2016 was reconstructed. These digital surface models (DSMs) were then used to generate 2D hydraulic models, simulating flood scenarios in the unsteady mode. The results demonstrated significant changes in the water surface elevation over the 14-year period, with a 2.04 km2 increase in areas with water depths exceeding 0.7 m. These findings were utilized to create a flood risk map and assess the economic flood risk. The data highlight the crucial role of land subsidence in determining the inundation risk in the Alto Guadalentin valley, providing valuable insights for emergency management and civil protection against future potential flooding events.

Co-occurrence of antibiotic and metal resistance in long-term sewage sludge-amended soils: influence of application rates and pedo-climatic conditions

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

Experimental investigations of open-channel flow and velocity to develop a predictive tool from a laboratory small scale to real-world large scale

Open channel flow and velocity behaviour presents a dilemma for drainage systems designers where hydrologic parameters are fluctuating in space and time. The experience of having extreme flash floods almost every year is flustering the need for understanding the flow behaviour at different altitudes. In this study, open channel experimental efforts were made to model flow and velocity profiles. The three-dimensional (3D) open channel flow and velocity profiles are generated at two types of roughness namely steel (smooth) and concrete (rough beds). The experiments included different slope gradients and flow measurements at different distances. The channels slope ranges between 0 and 4.7% with an interval of 0.2%. Multiple linear regression (MLR) was applied to quantify the flow for longer distance while Kriging extrapolation proxy was used to generate 3D surfaces of flow and velocity. The results showed that the flow in concrete channel is decreasing by moving to the end of channel due to higher frictional resistance while it is rising up for the steel channel. In average, the velocity has been increased by 7.4% for steel and 6.1% for concrete channels at a changing slope.

Forecasting soil erosion and sediment yields during flash floods: The disastrous case of Mandra, Greece, 2017

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

Projected Changes in Climate Extremes Using CMIP6 Simulations Over SREX Regions

This paper presents projected changes in extreme temperature and precipitation events by using Coupled Model Intercomparison Project phase 6 (CMIP6) data for mid-century (2036–2065) and end-century (2070–2099) periods with respect to the reference period (1985–2014). Four indices namely, Annual maximum of maximum temperature (TXx), Extreme heat wave days frequency (HWFI), Annual maximum consecutive 5-day precipitation (RX5day), and Consecutive Dry Days (CDD) were investigated under four socioeconomic scenarios (SSP1-2.6; SSP2-4.5; SSP3-7.0; SSP5-8.5) over the entire globe and its 26 Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate ChangeAdaptation (SREX) regions. The projections show an increase in intensity and frequency of hot temperature and precipitation extremes over land. The intensity of the hottest days (as measured by TXx) is projected to increase more in extratropical regions than in the tropics, while the frequency of extremely hot days (as measured by HWFI) is projected to increase more in the tropics. Drought frequency (as measured by CDD) is projected to increase more over Brazil, the Mediterranean, South Africa, and Australia. Meanwhile, the Asian monsoon regions (i.e., South Asia, East Asia, and Southeast Asia) become more prone to extreme flash flooding events later in the twenty-first century as shown by the higher RX5day index projections. The projected changes in extremes reveal large spatial variability within each SREX region. The spatial variability of the studied extreme events increases with increasing greenhouse gas concentration (GHG) and is higher at the end of the twenty-first century. The projected change in the extremes and the pattern of their spatial variability is minimum under the low-emission scenario SSP1-2.6. Our results indicate that an increased concentration of GHG leads to substantial increases in the extremes and their intensities. Hence, limiting CO2 emissions could substantially limit the risks associated with increases in extreme events in the twenty-first century.

The role of storm movement in controlling flash flood response: an analysis of the 28 September 2012 extreme event in Murcia, southeastern Spain

AbstractFlash flooding is strongly modulated by the spatial and temporal variability in heavy precipitation. Storm motion prompts a continuous change of rainfall space-time variability that interacts with the drainage river system, thus influencing the flood response. The impact of storm motion on hydrological response is assessed for the 28 September 2012 flash flood over the semi-arid and medium-sized Guadalentín catchment in Murcia, southeastern Spain. The influence of storm kinematics on flood response is examined through the concept of ‘catchment-scale storm velocity’. This variable quantifies the interaction between the storm system motion and the river drainage network, assessing its influence on the hydrograph peak. By comparing two hydrological simulations forced by rainfall scenarios of distinct spatial and temporal variability, the role of storm system movement on the flood response is effectively isolated. This case study is the first to: (i) show through the catchment-scale storm velocity how storm motion may strongly affect flood peak and timing; and (ii) assess the influence of storm kinematics on hydrological response at different basin scales. In the end, this extreme flash flooding provides a valuable case study of how the interaction between storm motion and drainage properties modulate hydrological response.

Development of remote sensing-based yield prediction models at the maturity stage of boro rice using parametric and nonparametric approaches

This research aims to develop rice yield prediction models using satellite remote sensing-based vegetation indices at the optimum harvesting time before flash flooding. Five relevant vegetation indices, the normalized difference vegetation index (NDVI), normalized difference water index (NDWI), rice growth vegetation index (RGVI), moisture stress index (MSI), and leaf area index (LAI), were used to develop several empirical yield prediction models for rice production. For this research, Sentinel-2 images with 10 m spatial resolution was used for the haor area of Bangladesh. To calibrate and validate the remote sensing images at such large spatial and temporal scales, ground reference data of the vegetation indices were used. The generated models were validated using both parametric (simple and multiple) and nonparametric (artificial neural network, ANN) regression analyses. The crop yield models that were developed using regression analyses showed very significant agreement with the ground reference yield information. The best estimated performances for the RGVI (R2 = 0.44), NDVI (R2=0.63), NDVI (R2 = 0.55), and NDVI (R2 = 0.67) in the simple regression analyses were observed for 2017, 2018, and 2019 and the average of seasons from 2017 to 2019. On the other hand, the composite NDVI-RGVI (R2 = 0.65), NDVI-NDWI (R2 = 0.56), and NDVI-MSI (R2 = 0.69) indices were the best-performing vegetation indices for developing boro rice yield prediction models using multiple regression. Nevertheless, in the ANN-based machine-learning results, NDVI exhibited higher accuracy for the average boro rice season (2017–2019) by using a simple regression approach (R2 = 0.84) and multiple regression analysis (R2 = 0.91) of the average NDVI-MSI composite index. Validation between the actual and predicted yields showed that more than 70% of the study area can be accurately predicted using vegetation indices with ground reference mean yield data. Moreover, in 2018, the predicted yields by using simple and multiple linear regression were 4.25 and 4.23 MT/ha, respectively. The developed models are applicable 118–132 days after planting (DAT) in any similar environment for agricultural practices. Therefore, the yield prediction models of boro rice at the maturity stage can be useful for farm risk management, insurance premium determinations, and relevant stakeholder decision-making to mitigate the effects of extreme flash flood events.

Remote sensing of extreme flash floods over two southern states of India during North-East monsoon season of 2020

An area of low-pressure developed over the west-central Bay of Bengal during the second week of October in 2020. It further intensified into a deep depression and moved gradually towards the north-west resulting in extreme rainfall over Andhra Pradesh and Telangana during October 13–14, 2020. Extreme rainfall events affected both states submerging low-lying regions, triggering home collapses, prompting the evacuation of more than 90,000 people to safer places and causing heavy casualities. This study focuses on monitoring the flood event of Andhra Pradesh and Telangana using satellite observations. Nagarkurnool, Cyberabad, Hyderabad, Khairatabad, LB Nagar, Ranga Reddy and Osmansagar were the most affected districts of the states due to heavy rainfall. Nagarkurnool received the maximum rainfall of about 75 mm at 13:30 UTC on October 13. Hyderabad, Cyberabad and Nagarkurnool recorded cumulative rainfall in excess of 400 mm on October 13, 2020. The sudden and heavy downpour from multiple extreme rain events on October 13 caused high river discharge which resulted in extreme flash floods over these districts. Results reported in this study highlight the significance of remote sensing observations for exploring flash flood events.

Rainfall Modelling using Generalized Extreme Value Distribution with Cyclic Covariate

Increased flood risk is recognized as one of the most significant threats in most parts of the world, resulting in severe flooding events which have caused significant property and human life losses. As there is an increase in the number of extreme flash flood events observed in Klang Valley, Malaysia recently, this paper focuses on modelling extreme daily rainfall within 30 years from year 1975 toyear 2005 in Klang Valley using generalized extreme value (GEV) distribution. Cyclic covariate is introduced in the distribution because of the seasonal rainfall variation in the series. One stationary (GEV) and three nonstationary models (NSGEV1, NSGEV2, and NSGEV3) are constructed to assess the impact of cyclic covariates on the extreme daily rainfall events. The better GEV model is selected using Akaike's information criterion (AIC), bayesian information criterion (BIC) and likelihood ratio test (LRT). The return level is then computed using the selected fitted GEV model. Results indicate that the NSGEV3 model with cyclic covariate trend presented in location and scale parameters provides better fits the extreme rainfall data. The results showed the capability of the nonstationary GEV with cyclic covariates in capturing the extreme rainfall events. The findings would be useful for engineering design and flood risk management purposes.

An integrated approach of flash flood analysis in ungauged Mediterranean watersheds using post‐flood surveys and unmanned aerial vehicles

AbstractThis study analyzes the flash flood event of two ungauged ephemeral streams in Olympiada region (Chalkidiki, North Greece), which occurred at the 21–22 of November 2019. Aim of the study is to reconstruct the specific flash flood event, investigate the causes of flood generation mechanisms, evaluate the performance of SCS‐CN hydrological and HEC‐RAS hydraulic models, investigate the relation between extreme flash floods and human intervention, using the combination of ground and aerial observations obtained from the field survey and unmanned aerial vehicles (UAVs), respectively. The results of the specific discharge ranged between 9 and 11 m3 s−1 km2, values that are typical for flash flood events in Mediterranean region. The comparison between the observed and simulated values of flood extent showed sufficiently good performance of the hydraulic model (CSI = 82%). However, the statistical analysis of the observed and simulated flood depths displayed a flood depth overestimation by the applied model, despite that the values of the used statistic indexes are acceptable (RMSE = 0.35 m, SD = 0.53, NSE = 0.56, PBIAS = 11.26%). The model overestimation of flood depth was attributed to the DEM low resolution and quality. Ground and aerial observations depicted the alluvial fan activation, the alternation of flow paths and the huge sediment transport. Human intervention in main streams, urban sprawl, wet AMC and sediment transport were among the main factors that contributed to the flash flood generation. This integrated approach revealed the necessity of the constant evaluation and validation of hydrological and hydraulic models in small ungauged Mediterranean watersheds and ephemeral streams. The use of UAVs in combination with ground observations and hydraulic simulation could significantly contribute to the enhanced understanding of flash flood mechanisms, in the direction of flood risk mitigation, improvement of the planning efficiency of flood prevent measures, flood hazard estimation, evolution of flood warning systems and floodplain geomorphology analysis.

Monitoring a tropical super cyclone Amphan over Bay of Bengal and nearby region in May 2020

A tropical super cyclone Amphan was formed over Bay of Bengal during third week of May in 2020 and caused devastating impact in West Bengal. Present study focuses on exploring this super cyclone using high resolution accurate precipitation estimates from multi-frequency satellite observations from Meteosat 8. It is reported that low pressure system formed over Bay of Bengal developed into a cyclonic storm on May 16 due to favourable atmospheric conditions. On May 18, this cyclonic storm intensified into a super cyclone with rainfall amount exceeding 600 mm/day. We have examined the diurnal variation of heavy rainfall over severely affected districts of West Bengal after cyclone made a landfall. Purba Medinipur, North and South 24 Parganas, Kolkata, Hooghly and Howrah were most affected districts of the state. Heavy rainfall over few of these districts were in the range of 50–60 mm/h. Purba Medinipur recorded maximum rainfall of about 650 mm on May 20. Extreme rain events at multiple hours on May 20 resulted in heavy cumulative rainfall causing extreme flash flooding and landslides over these districts. Present study highlights the importance of usefulness of near real-time high-resolution satellite observations for exploring extreme events.

The impact of flash-floods on the adjacent marine environment: the case of Mandra and Nea Peramos (November 2017), Greece

The extreme flash-flood of November 2017 in Western Attica, Greece, caused severe damages not only in the landward area, but also in the adjacent marine environment. The study of a number of data, such as visual observations immediately after the catastrophic event, a series of satellite images that demonstrate the movement of the flood-related suspended material, and comparative elemental and hydrocarbon geochemical analyses between the fresh, recently deposited sediments, and the older ones, have shown that an extended part of the Elefsis Bay, particularly the northeastern sector, has experienced a severe modification in its sedimentary and geochemical status, that may have irreversibly affected the already environmentally degraded marine ecosystem of the area.

Update of intensity–duration–frequency curves for Kuwait due to extreme flash floods

Flash floods have devastating power due to their high rainfall intensities and short durations, causing serious damage to infrastructure and human life. Recent observations in the desert environment of Kuwait witnessed an increase in rainfall extremes, and the currently adopted intensity–duration–frequency (IDF) curves constructed three decades ago did not produce reliable design frequencies for existing stormwater drainage systems in residential areas. In this study, the IDF curves for the urban zone of the State of Kuwait were updated with recent records of annual maximum rainfall intensity from January 2006 to December 2017, and the Extreme Value type-I probability distribution was implemented to perform frequency analysis and estimate the design storm. The study concluded that frequent updating of IDF curves is necessary for the examined rainfall data to account for harmonic climatic variations in compliance with sunspot cycles. The updated IDF curves confirmed the pronounced increase in rainfall intensities within short durations of 5–15 min, thereby affecting water-related infrastructure in small urban catchments. Here we call for urgent action to be taken to adopt flood mitigation plans in residential areas to avoid the catastrophic impacts of extreme flash floods.

Reproduction of sediment deposition and prediction of 137Cs concentration in the major urban rivers of Tokyo

Radioactive caesium- 137 (137Cs) can be used as a tracer to infer sediment dynamics due not only to its long radioactive half-life but also its affinity for fine sediment. A novel advanced interpolation assessment was conducted to examine radionuclide activity in terraced land covered with volcanic ash soil in Tokyo, Japan, which had a time-dependent input function and incorporated the effects of mixed-sediment particle dynamic behaviour on radioactive decay. In addition, transport parameters derived from Chernobyl measurements were applied as predictors of the long-term contamination of the cardinal urban rivers by the fallout from the Tokyo Electric Power Fukushima Daiichi Nuclear Power Plant (FDNPP) accident in 2011. The behaviour of suspended sediment substances, incorporating the effects of deposition and pickup, was assessed using a mixed-sediment particle dynamics model. The concentrations of 137Cs adsorbed on fine sediment particles of each size fraction were determined. Removal of 137Cs from the cardinal urban river channel had significant effects on both long-term decline, including extreme flash flood events, and the dynamic and time-dependent behaviours of interspersed 137Cs and sediment activity. A novel advanced interpolation assessment method was used to examine radionuclide activity in terraced land covered with volcanic ash soil in Tokyo, Japan. The assessment procedure has a time-dependent input function and incorporates the effects of mixed-sediment particle dynamics on this time dependence. The results indicated that sediment and 137Cs concentrations could decline more rapidly than observed in the Fukushima and Chernobyl regions. This rate of decrease depended on terraces covered with volcanic ash soil, which incorporated the effects of fine sediment behaviour for particle adsorption. In addition, comparatively large impacts were observed during extreme flash flooding events, which were associated with the land cover of the major urban river catchments in Tokyo. This work provides a new perspective for understanding 137Cs behaviour associated with reproduction of sediment deposition and prediction of 137Cs concentration in the major urban rivers of Tokyo, incorporating the effects of baseline 137Cs behaviour with the impact of sediment particle adsorption in a volcanic ash soil-covered terrace.