Flash Floods Research Articles

Co-Occurrence of Cyanotoxins and Phycotoxins in One of the Largest Southeast Asian Brackish Waterbodies: A Preliminary Study at the Tam Giang—Cau Hai Lagoon (Vietnam)

The Tam Giang-Cau Hai lagoon (TGCH) in Thua Thien Hue province (Vietnam) is a marsh/lagoon system and ranks among the largest waterbodies in Southeast Asia. It plays a significant role in terms of both socio-economic and environmental resources. However, anthropogenic stress, as well as the discharge of untreated domestic and industrial sewage with agricultural runoff from its three major tributaries, dramatically damages the water quality of the lagoon. Especially after heavy rain and flash floods, the continuous degradation of its water quality, followed by harmful algal and cyanobacterial bloom patterns (HABs), is more perceptible. In this study, several physicochemical factors, cyanotoxins (anatoxins (ATXs), saxitoxins (STXs), microcystins (MCs)), phycotoxins (STXs, okadaic acid (OA), and dinophysistoxins (DTXs)) were analyzed in water and shellfish samples from 13 stations in June 2023 from 13 stations, using enzyme-linked immunosorbent assay (ELISA) kits for the ATXs and STXs, and the serine/threonine phosphatase type 2A (PP2A) inhibition assay kit for the MCs, OA, and DTXs. The results showed for the first time the co-occurrence of freshwater cyanotoxins and marine phycotoxins in water and shellfish samples in this lagoon. Traces of ATXs and STXs were detected in the shellfish and the orders of magnitude were below the seafood safety action levels. However, toxins inhibiting the PP2A enzyme, such as MCs and nodularin (NODs), as well as OA and DTXs, were detected at higher concentrations (maximum: 130.4 μg equiv. MC-LR/kg shellfish meat wet weight), approaching the actionable level proposed for this class of toxin in shellfish (160 μg of OA equivalent per kg of edible bivalve mollusk meat). It is very important to note that due to the possible false positives produced by the ELISA test in complex matrices such as a crude shellfish extract, this preliminary and pilot research will be repeated with a more sophisticated method, such as liquid chromatography coupled with mass spectroscopy (LC-MS), in the upcoming research plan.

Engineering challenges in flash flood mitigation: insights from historical data and community perceptions in Tamanghasset, Algeria

Engineering challenges in flash flood mitigation: insights from historical data and community perceptions in Tamanghasset, Algeria

Assessing flash flood erosion following storm Daniel in Libya

The eastern Mediterranean basin is witnessing increased storm activity impacting populous urban coastal areas that historically were not prone to catastrophic flooding. In the fall of 2023, Storm Daniel struck the eastern coast of Libya, causing unprecedented flash floods with a tragic death toll and large-scale infrastructure damages. We use Sentinel-1A C-band SAR images to characterize the resulting flash flood erosion and sediment load dynamics across the watersheds and to map damages within coastal cities at their outlets. Our results suggest that sediment loading, resulting from surface erosion, increased the density of turbid streams. The above exacerbated the catastrophic impact of the flash floods in the coastal cities of Derna and Susah, where 66% and 48% of their respective urban surface have experienced moderate-to-high damages. Our findings highlight the increased vulnerability of coastal watersheds in arid areas within the eastern Mediterranean basin due to the forecasted increase in hydroclimatic extremes and call for a transformative coastal management approach to urgently implement nature-based solutions and land-use changes to mitigate these rising risks.

Classification of Flood Disaster Risk Areas Using Vegetation Index Calculation and Landsat-8 Satellite Imagery in West Sumatra

One of the Indonesian provinces most vulnerable to flooding catastrophes is West Sumatra. West Sumatra is a province that spans 98°36' to 101°53' East Longitude and 00°54' North Latitude to 03°30' South Latitude. Its total size is roughly 42,297.30 km2, or 4,229,730 hectares, and it is surrounded by around 391 major and small islands. Flash floods and landslides have affected a number of regencies and cities in West Sumatra, including Agam Regency, Tanah Datar Regency, Padang Panjang City, Padang Pariaman Regency, and Padang City. The objective of this study is to use vegetation index estimates based on Landsat-8 satellite images to categorise flood catastrophe risk zones in West Sumatra. NDVI = -0.106 and NDWI = -0.03999, respectively, are examples of vegetation indices that define land as either non-vegetated or sparsely vegetated, and SAVI = 0.0002447 classify areas with water bodies such as rivers/floods.

Projected near-future changes in precipitation extremes over Anambra-Imo River Basin inferred from CMIP6 HighResMIP

The southeastern region of Nigeria is susceptible to flood disasters primarily triggered by extreme precipitation with localized impacts. This study uses the output of High-Resolution Model Intercomparison Project (HighResMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to investigate seasonal dependent changes in precipitation extremes in the near future (2031–2050) in the Anambra-Imo River Basin, in the southeastern region of Nigeria. Evaluating the models against observation for the 1995–2014 period, it is found that models reproduced the spatial pattern of the observed annual precipitation extremes over the river basin. Results show that in the near future, annual precipitation extremes will be characterized by a robust increase in annual total precipitation amount (PRCPTOT), maximum 5-day precipitation (RX5day), and heavy precipitation (R10mm). The models project a significant increase in PRCPTOT, RX5day, R10mm, and wet-day intensity (SDII) for the June–July–August (JJA) and September–October–November (SON) seasons. The results demonstrate a robust and higher magnitude increase in precipitation extremes during the SON season. Specifically, PRCPTOT, RX5day, R10mm and SDII are projected to increase by up to 46 mm, 24 mm, 1.2 days and 2.4 mm/day, respectively. Whereas during the March–April-May (MAM) season, the HighResMIP suggests that PRCPTOT, R10mm, and SDII will marginally increase over the eastern part of the Anambra-Imo River Basin. Besides, the December–January–February (DJF) season will be characterized by a marginal increase in the precipitation extremes, especially over the southern fringes of the river basin. We note that in the near future, precipitation extremes in the river basin will be characterized by more intense and less frequent precipitation extremes during the JJA and SON, potentially exacerbating flash flooding in the river basin. Hence, the results of this study may be vital for near-term socio-economic planning and policy decisions that will minimize the impact of flood disasters in the Anambra-Imo River Basin.

Flood Hazard and Risk Assessment of Flash Floods for Petra Catchment Area Using Hydrological and Analytical Hierarchy (AHP) Modeling

Flood Hazard and Risk Assessment of Flash Floods for Petra Catchment Area Using Hydrological and Analytical Hierarchy (AHP) Modeling

A time-space varying distributed unit hydrograph (TS-DUH) for operational flash flood forecasting using publicly-available datasets

Although flash floods originate in upstream (headwater) catchments causing hazards locally, they often occur at short time scales and affect widely while relatively small size catchments respond to intense rainfall systems. Due to the heavy cost of computing and parameterization, high resolution spatially distributed hydrological models are not effectively deployed for global or large-scale flash flood forecasting. This research proposes a Time-Space varying Distributed Unit Hydrograph (TS-DUH) based on publicly-available data for efficient global scale flash flood forecasting. TS-DUH estimates the runoff travel time (and flow velocity) from each location to the catchment outlet based on topographic and hydroclimatic characteristics, while it delineates the runoff-drainage process by emphasizing the heterogeneous and dynamic runoff contribution corresponding to rainfall and soil moisture variations. The excess rainfall is estimated by two methods: the Soil Conservation Service’s (SCS) curve (CN-Runoff), and the widely used Global Flood Monitoring System (GFMS) which provides both long-term (2000-present) well-archived and real-time online global runoff (GFMS-Runoff) prediction based on a distributed hydrological model. TS-DUH is first validated based on 6,324 flash flood events from 281 small-to-medium-sized catchments broadly distributed across the CONUS, using “perfect” precipitation input (i.e., NLDAS-2 for this study). TS-DUH calibrated with GFMS-Runoff shows better performance than using CN-Runoff, with a probability of detection (POD) value of 0.9 for all the events and 71% of them having a KGE metric above 0.5. More importantly, with the real-time satellite rainfall-driven GFMS-Runoff, the long-term (2003–2020) TS-DUH simulation shows better performance than GFMS, indicating promising value in global flash flood prediction of the TS-DUH-integrated GFMS.

Morphometric analysis and risk assessment of flash floods in the Atlas chain of eastern Algeria and the Algerian–Tunisian borders

Morphometric analysis and risk assessment of flash floods in the Atlas chain of eastern Algeria and the Algerian–Tunisian borders

Understanding Multi-Hazard Interactions and Impacts on Small-Island Communities: Insights from the Active Volcano Island of Ternate, Indonesia

Drawing on a case study from Ternate Island, a densely populated volcanic island in Eastern Indonesia, this research illustrates how multi-hazards and extreme weather events are likely to compound and cascade, with serious consequences for sustainable development in small island context. At the heart of Ternate Island sits the active Gamalama volcano, posing a constant eruption threat. Its location within the Ring of Fire further exposes the island to the risks of tsunamis and earthquakes. Additionally, the island’s physical features make it highly susceptible to flooding, landslides, and windstorms. Rapid urbanization has led to significant coastal alterations, increasing exposure to hazards. Ternate’s small-island characteristics include limited resources, few evacuation options, vulnerable infrastructure, and inadequate resilience planning. Combining GIS multi-hazard mapping with a structured survey in 60 villages in Ternate, this case study investigates the multi-hazard exposure faced by the local population and land coverage. The findings suggest significant gaps between village chiefs’ perceptions of the types of hazards and the multi-hazard assessment in each village. Out of 60 village chiefs surveyed, 42 (70%) are aware of earthquake risks, 17 (28%) recognize tsunami threats, and 39 see volcanoes as a danger. GIS assessments show that earthquakes could impact all villages, tsunamis could affect 46 villages (77%), and volcanoes could threaten 39 villages. The hazard map indicates that 32 villages are at risk of flash floods and 37 are at risk of landslides, and extreme weather could affect all villages. Additionally, 42 coastal villages on Ternate Island face potential extreme wave and abrasion disasters, but only 18 chiefs acknowledge extreme weather as a threat. The paper argues that addressing the cognitive biases reflected in the perceptions of community leaders requires transdisciplinary dialogue and engagement.

Extreme weather event causes the death of White-collared Swift Streptoprocne zonaris (Shaw, 1796) (Aves, Apodidae) individuals in sinkholes in the State of Goiás, Brazil

The use of caves and rocky walls is common for some birds, like swifts, to shelter, sleep, nest, feed, and protect themselves from predators, wind, and rain. Several environmental and ecological factors associated with the habits and adaptations of certain species allow birds to use cave environments. The White-collared Swift Streptoprocne zonaris (Shaw, 1796) is distributed from Mexico and the Antilles south to northern Argentina, Paraguay, and southern Brazill, being frequent in areas with waterfalls and river rapids with rocky beds and crystal-clear water. Individuals live in flocks and have the habit of roosting and nesting in damp, dark caves or behind waterfalls. Herein, we aim to report the case and identify the cause of death of S. zonaris individuals found dead in a sinkhole in the State of Goiás, Brazil, in 2020. Global warming resulting from anthropogenic emissions of greenhouse gases can alter the natural fluctuations of atmospheric circulation systems, responsible for rainfall distribution, substantially affecting rainfall and increasing the frequency of heavy rainfall events in some locations. Due to climate change and the increasing frequency of flooding records, we have raised the hypothesis and drawn attention to our record may have been originated due to these climatic events. However, we do not dismiss the hypothesis that the flooding may be due to an extreme event. The fact that S. zonaris spends the night and nests close to water bodies makes the species more susceptible to the effects of a flash flood. Further studies will be able to show the real effects of global warming on the species.

Investigation of the recurrent flash flood events in the Far-North Region of Cameroon

Investigation of the recurrent flash flood events in the Far-North Region of Cameroon

Prediction of flash flood peak discharge in hilly areas with ungauged basins based on machine learning

ABSTRACT Peak discharge is an essential element of hydrological forecasting. Due to rapid outbreaks of flash floods in hilly areas and the lack of measured data, the fast and accurate estimation of peak discharge is crucial for flash flood hazard management. Three machine learning algorithms were applied to estimate peak discharge; this estimation was compared with the results of hydrological–hydraulic models, and the results were verified with measured watershed data. In this paper, 10 hydrological and geomorphological parameters were selected to predict the flood peak discharge in 103 watersheds in Taiyi Mountain North District. The results show that the particle swarm optimization backpropagation (PSO-BP) neural network model outperforms the BP neural network and random forest regression in prediction performance. PSO-BP has a lower mean absolute error (2.51%), root mean square error (3.74%), and mean absolute percentage error (2.74%) than the other models, which indicates that PSO-BP has high prediction accuracy. Importance analysis revealed that rainfall, early impact rainfall, catchment area, and rain intensity are the key input parameters of PSO-BP. The proposed method was confirmed to be a fast and relatively accurate algorithm for estimating the peak discharge of flash floods in ungauged basins.

The role of landscape planning in reducing damages caused by flood (case study: Nekaroud, Iran)

Traditional flood control methods, such as gray infrastructure, are no longer sufficient to effectively manage flood events independently. Urban and landscape designers have devised design strategies to combat riverine and flash flooding in urban settings. These solutions aim to enhance urban ecological resilience by incorporating provisions for varying water levels within the urban environment. However, limited reviews have specifically explored how landscape architecture strategies can play a more effective and beneficial role in flood control. This paper aims to focus on landscape design solutions for flood adaptation and clarify the parameters in order to reduce vulnerability to floods. It emphasizes the importance of preserving the primary connection between humans and a river, and draws upon knowledge in hydraulics, ecology, flood control practices, and field observation to explore the practical solutions for reducing river floods. Moreover, it investigates the flood control method of Nekaroud in Iran, which serves as an example of inefficient flood control solutions. Surveys showed the significance of the river's position within its context and its fundamental role in enhancing spatial quality during the planning process, particularly in landscape planning. Neglecting this aspect can lead to further problems, such as ecosystem threats and limited access to the riverbank, as observed in the Nekaroud basin. Finally, the paper identifies various challenges facing the flooding at the macro, meso, and micro levels, and proposes landscape design solutions for flood adaptation that prioritize maintaining the river within its main context.

Exploring patterns in precipitation intensity–duration–area–frequency relationships using weather radar data

Abstract. Accurate estimations of extreme precipitation return levels are critical for many hydrological applications. Extreme precipitation is highly variable in both space and time; therefore, to better understand and manage the related risks, knowledge of their probability at different spatial–temporal scales is crucial. We employ a novel non-asymptotic framework to estimate extreme return levels (up to 100 years) at multiple spatial–temporal scales from weather radar precipitation estimates. The approach reduces uncertainties and enables the use of relatively short archives typical of weather radar data (12 years in this case). We focus on the eastern Mediterranean, an area of high interest due to its sharp climatic gradient, containing Mediterranean, semi-arid, and arid areas across a few tens of kilometres, and its susceptibility to flash flood. At-site intensity–duration–area–frequency relations are derived from radar precipitation data at various scales (10 min–24 h, 0.25–500 km2) across the study area, using ellipses of varying axes and orientations to account for the spatial component of storms. We evaluate our analysis using daily rain gauge data over areas for which sufficiently dense gauge networks are available. We show that extreme return levels derived from radar precipitation data for 24 h and 100 km2 are generally comparable to those derived from averaging daily rain gauge data over a similar areal scale. We then analyse differences in multi-scale extreme precipitation over coastal, mountainous, and desert regions. Our study reveals that the power-law scaling relationship between precipitation and duration (simple scaling) weakens for increasing area sizes. This finding has implications for temporal downscaling. Additionally, precipitation intensity varies significantly for different area sizes at short durations but becomes more similar at long durations, suggesting that, in the region, areal reduction factors may not be necessary for computing return levels over long durations. Furthermore, the reverse orographic effect, which causes decreased precipitation for hourly and sub-hourly durations, diminishes for larger areas. Finally, we discuss the effects of orography and coastline proximity on extreme precipitation intensity over different spatial–temporal scales.

Corrigendum: Comparison of two hydrodynamic models for their rain-on-grid technique to simulate flash floods in steep catchment

Corrigendum: Comparison of two hydrodynamic models for their rain-on-grid technique to simulate flash floods in steep catchment

Combined use of physically based hydrological model and empirical models to improve parameterisation of erosion processes in a flash flood prone catchment

AbstractThis study assesses the effectiveness of a distributed physically based hydrological model (MARINE) to investigate erosion estimation during flash floods compared with other widely used empirical models derived from the Universal Soil Loss Equation (USLE) like Revised Universal Soil Loss Equation (RUSLE) and Modified Universal Soil Loss Equation (MUSLE). It is carried out on a small catchment in south‐eastern France, the Claduègne catchment. To compare the erosion volumes simulated by the three models, MARINE, MUSLE and RUSLE, a sensitivity analysis on the model parameters is carried out. According to physics‐based simulations, flood events fall into two categories: those dominated by raindrop erosion and those dominated by shear stress erosion. The results show that the erosion simulated by the three methods are comparable, except for events dominated by raindrop erosion suggesting that further research is needed to improve raindrop erosion within MARINE. Simulations from the MARINE model provide access to the spatio‐temporal variability of erosion dynamics during the event and can also be used to produce erosion/deposition maps, which are useful for environmental decision‐makers and planners in identifying areas at risk from erosion and deposition hazards.

Perception and community input towards flash flood management in Mauritius Island

Perception and community input towards flash flood management in Mauritius Island

Impact of natural disaster on agriculture in Tuyen Hoa district, Quang Binh province.

Abstract Climate change is a challenge for people whose livelihoods depend on agricultural production. In particular, the agricultural production activities of people in Tuyen Hoa district, Quang Binh province, were affected by natural disasters. Therefore, it is imperative to assess the natural disaster situation in Tuyen Hoa district by examining farmers’ awareness of potential climate and impacts on the crop and livestock sectors. Data related to climate change were provided by the authorities of Tuyen Hoa district communes and then analyzed in combination with local people’s perceptions using Excel software (2019). Quantitative data collected from semi-structured interviews through 241 farmer household surveys in Tuyen Hoa district was processed using computer software called Statistical Package for Social Sciences (SPSS 26) to calculate the potential impact index of natural disasters on agricultural production. Research results show that: (1) natural disasters (storms, tropical depressions, floods, droughts, Soil salinity) appear with high frequency, but landslides and flash floods have low frequency; (2) the risk of natural disasters impacting crop production is greater than livestock farming. Among them, storms, tropical depressions, floods, and droughts have a high impact. Landslides and flash floods have a low impact. (3) Communes located in the southeast of Tuyen Hoa district have a greater risk of natural disaster impacts than the remaining communes. This result will help local managers make appropriate adaptation measures for climate change and natural disasters locally.

Seismic signature of an extreme hydro-meteorological event in Italy

Flash floods are a major threat for Mediterranean countries and their frequency is expected to increase in the next years due to the climatic change. Civil protection agencies are called to deal with increasing hydrological risk, but existing hydro-meteorological monitoring networks might not be enough for detecting, tracking, and characterizing rapidly evolving floods produced by severe convective storms. Nowadays, hydro-meteorological information in several watersheds particularly in small and mid-size in orographically complex regions or in third-world countries, is still not available or insufficient. To improve our observational capability of these events, we propose to exploit the seismic recordings, which act as opportunistic signals and can complement well-established procedures to early detect the occurrence of flash floods at regional scale. Here, we investigate the hydro-meteorological event that hit central Italy in September 2022 and resulted in a devastating flash flood. We compare seismic data from a national monitoring network with raingauges and hydrometer data. Our evidence suggests that the main stages of the hydro-meteorological events can be tracked by the spatio-temporal evolution of the seismic noise confirming the capability of this multi-sensor approach in detecting and characterizing such kind of events.

Coefficient Analysis of the Alluvial Fan Surface Geometry: A Methodological Approach to Applied Geomorphology

The alluvial fan is a depositional geomorphic surface at the foothills. Most of the alluvial fans in tropical regions are highly dynamic under wet climatic conditions and neotectonic environments. The fans of this region are covered with fertile top soils and deep forests. The soils attack people for agriculture in this region. Presently the continuously growing population pressure causes huge deforestation in these alluvial fan areas for cultivation which causes an accelerating rate of natural hazards like flash floods, landslides, and soil erosion that accelerate the dynamic nature of the fan surfaces. The coefficient analysis helps to understand the dynamic nature of the alluvial fan surface and thus helps to identify the hazard-prone area for planning purposes.