Extreme Flood Events Research Articles

On the Use of Weather Generators for the Estimation of Low-Frequency Floods under a Changing Climate

The present work presents a methodology based on the use of stochastic weather generators (WGs) for the estimation of high-return-period floods under climate change scenarios. Applying the proposed methodology in a case study, Rambla de la Viuda (Spain), satisfactory results were obtained through the regionalization of the bias-corrected EUROCORDEX climate projections and the integration of this information into the parameterization of the WG. The generated synthetic data series fed a fully distributed hydrological model to obtain the future flood quantiles. The results obtained show a clear increase in the precipitation extreme quantiles for the two analyzed projections. Although slightly reducing the annual amount of precipitation, variations between 4.3% for a return period of 5 years in the mid-term projection and 19.7% for a return period of 100 years in the long-term projection have been observed. In terms of temperatures, the results point to clear increases in the maximum and minimum temperatures for both projections (up to 3.6 °C), these increases being greater for the long-term projection, where the heat waves intensify significantly in both magnitude and frequency. Finally, although rivers may present, in general, with lower flows during the year, flood quantiles experience an increase of 53–58% for high return periods, which reach values of up to 145% when we move to smaller catchments. All this combined translates into substantial shifts in the river flow regimes, increasing the frequency and magnitude of extreme flood events.

Ensemble Forecasts of Extreme Flood Events with Weather Forecasts, Land Surface Modeling and Deep Learning

Integrating numerical weather forecasts that provide ensemble precipitation forecasts, land surface hydrological modeling that resolves surface and subsurface hydrological processes, and artificial intelligence techniques that correct the forecast bias, known as the “meteo-hydro-AI” approach, has emerged as a popular flood forecast method. However, its performance during extreme flood events across different interval basins has received less attention. Here, we evaluated the meteo-hydro-AI approach for forecasting extreme flood events from headwater to downstream sub-basins in the Luo River basin during 2010–2017, with forecast lead times up to 7 days. The proposed meteo-hydro approach based on ECMWF weather forecasts and the Conjunctive Surface-Subsurface Process version 2 land surface model with a spatial resolution of 1 km captured the flood hydrographs quite well. Compared with the ensemble streamflow prediction (ESP) approach based on initial conditions, the meteo-hydro approach increased the Nash-Sutcliffe efficiency of streamflow forecasts at the three outlet stations by 0.27–0.82, decreased the root-mean-squared-error by 22–49%, and performed better in reliability and discrimination. The meteo-hydro-AI approach showed marginal improvement, which suggested further evaluations with larger samples of extreme flood events should be carried out. This study demonstrated the potential of the integrated meteo-hydro-AI approach for ensemble forecasting of extreme flood events.

Post-Analysis of Daniel Extreme Flood Event in Thessaly, Central Greece: Practical Lessons and the Value of State-of-the-Art Water-Monitoring Networks

Storm Daniel initiated on 3 September 2023, over the Northeastern Aegean Sea, causing extreme rainfall levels for the following four days, reaching an average of about 360 mm over the Peneus basin, in Thessaly, Central Greece. This event led to extensive floods, with 17 human lives lost and devastating environmental and economic impacts. The automatic water-monitoring network of the HIMIOFoTS National Research Infrastructure captured the evolution of the phenomenon and the relevant hydrometeorological (rainfall, water stage, and discharge) measurements were used to analyse the event’s characteristics. The results indicate that the average rainfall’s return period was up to 150 years, the peak flow close to the river mouth reached approximately 1950 m3/s, and the outflow volume of water to the sea was 1670 hm3. The analysis of the observed hydrographs across Peneus also provided useful lessons from the flood-engineering perspective regarding key modelling assumptions and the role of upstream retentions. Therefore, extending and supporting the operation of the HIMIOFoTS infrastructure is crucial to assist responsible authorities and local communities in reducing potential damages and increasing the socioeconomic resilience to natural disasters, as well as to improve the existing knowledge with respect to extreme flood-simulation approaches.

Flood dynamics on the upper Letaba River, South Africa, deduced from luminescence dating

ABSTRACT The Letaba River is one of several east-flowing rivers in the semiarid region of northeast South Africa. There is strong seasonality of river discharge and patterns of geomorphic behaviour along bedrock- and sediment-dominated reaches in these rivers, and in response to extreme seasonal flood events. This paper presents new luminescence ages on sediment samples from five sites in upper (headwater) reaches of the Letaba River catchment outside of Kruger National Park, South Africa, combined with evidence from reach-scale geomorphology and sediment sample analysis. River reaches are mainly mixed bedrock-alluvial with a patchwork of poorly sorted coarse sand bars overlying an abraded extended bedrock channel system. Luminescence ages from river sediment deposits (n = 13) cluster around three time periods of the last 400 years, 500–1100 BP, and 1400 BP. This suggests different reworked populations are present, which are a result of the partial bleaching of quartz grains and, thus, a mixed luminescence signal as flood-transported sediments are progressively moved from one depositional sink to another. This pattern of luminescence ages is quite different to lowland river systems in the same region where ages on the whole are significantly younger. Flood processes and dynamics in headwater reaches of semiarid rivers are often not considered but can yield a better understanding of system sensitivity to climate and event forcing.

Limits to knickzone retreat and bedrock river incision on the Hawaiian islands

AbstractA knickzone is defined as a waterfall or an oversteepened fluvial reach encompassing a series of waterfalls. Knickzones are remarkable landforms in that they may represent diametrically opposed conditions: either rapid upstream propagation of base‐level fall or a condition of stability and stalled response to base‐level fall. Knickzones on the Hawaiian islands exhibit evidence of both behaviours, and in this study, we explore whether this dichotomy can be explained by a threshold stream power for river incision. Topographic analysis shows that the transition between fluvial hanging valleys, where no measurable upstream retreat from the stream junction or coastline has occurred, and knickzones that have retreated or formed upstream of their outlet can be defined by a range of catchment sizes from ~0.5 to 6 km2. This transition is present on all volcanoes in our analysis regardless of significant base‐level fall, and there is no clear trend of drainage area above knickzones with volcano age. To explain these observations, we hypothesize that knickzones form or stabilize where maximum unit stream power ( ) does not exceed the critical unit stream power required to incise bedrock . Using estimates of a maximum possible flood discharge as a function of drainage area to calculate , we show that drainage areas above knickzones are well described by the theoretical prediction that incision stalls when , where falls in a narrow range from 14 to 40 kW/m2. Furthermore, we demonstrate that knickzone positions are largely insensitive to mean climate conditions, likely reflecting the fact that extreme flood events are either insensitive or inversely correlated with mean annual rainfall.

Impacts of extreme river discharge on coastal dynamics and environment: Insights from high-resolution modeling in the German Bight

The intricate relationship between extreme river discharge and its consequential effects on coastal basins’ environment and dynamics remains a subject of profound significance. The impact of extreme river discharge on coastal basin dynamics and environment is a complex phenomenon, particularly relevant in the context of the German Bight. The inflow of freshwater from rivers into the German Bight plays a crucial role in driving the complex thermohaline circulation. Addressing the challenges posed by local hydro-meteorological extremes, compounded by strong wind waves, currents and tides is vital for comprehensive impact assessment. Utilizing the Geesthacht Coupled cOAstal model SysTem (GCOAST) with high-resolution configuration, we investigate the sensitivity of the thermohaline properties to the river forcings. By incorporating river discharge as lateral land forcing in a coupled hydrodynamic and wave model, we conducted five sensitivity experiments. Our findings reveal that the simulated temperatures closely match measurements in all experiments. The salinity, however, is remarkably sensitive to the variation of freshwater from the rivers Elbe and Ems in the German Bight, causing the haline stratification. The statistical evaluation, as demonstrated by the Taylor diagram at the Marnet DB station, underscores the skill of the Mesoscale Hydrologic Model (mHM) in generating the freshwater discharge that drives the thermohaline characteristics of the German Bight, especially during events like the June 2013 flooding. Significantly, the use of climatological runoff proves to be ineffective in simulating stratification during extreme flooding events. In essence, this investigation enhances our understanding of the pivotal role played by high-frequency river freshwater buoyancy. It emerges as a driving force behind salinity fluctuations during extreme floods, providing valuable insights into coastal dynamics within the German Bight.

Effects of Flooding and Shade on Survival, Growth, and Leaf Gas Exchange of Bottomland Tree Species across the Great Lakes Region (USA)

Forested wetlands are common ecosystems within the Great Lakes region (Michigan, Minnesota, and Wisconsin), USA. Projected increases in extreme flooding events and shifting disturbance regimes create challenges for tree regeneration. Forest managers are considering the use of enrichment planting to increase tree species diversity, but limited information is available that quantifies the interactions between the flooding and shade tolerances of candidate tree species. We used a microcosm experiment to manipulate shade and flooding conditions to determine the effects on early survival, growth, and leaf gas exchange of 23 different tree species that vary in shade and flood tolerance. Seedlings were planted in pots and placed in 227 L tanks that were randomly assigned to light reduction (full sun, 40% and 70% reduced sunlight) and flood treatments (water levels of 0, 14, or 27 cm below the soil surface). In general, flooding treatments had a greater influence on seedling growth and leaf gas exchange rates than light reduction treatments. Of the species studied, bald cypress (Taxodium distichum (L.) Rich.) was the most flood-tolerant, but American sycamore (Platanus occidentalis L.) and river birch (Betula nigra L.) were also highly tolerant of flooding conditions throughout the entire growing season. The flood tolerances of the remaining species varied, but none were tolerant of water table depths within 14 cm of the soil surface for the entire growing season. Most species did not respond to the shade treatments in terms of early growth, survival, and leaf gas exchange. When considering species for planting in forested wetlands, matching the flood tolerance of candidate species to local site hydrology is an important step.

Using structure from motion for analyzing change detection and flood events in the context of flood preparedness: a case study for the Laufer Muehle area at the Aisch river in Germany for conducting near real-time analyses

Recent flood events (FE) in Germany have shown that the extent and impact of extreme flood events cannot be estimated solely based on numerical models. For analyzing the development of such an event and to develop and implement safety measures more efficiently, additional data must be collected during the event. Within the scope of this research, the possibilities of near real-time recording using an unmanned aerial vehicle (UAV) and data processing with the Structure from Motion (SfM) method were tested in a case study. Different recording parameter combinations were tested in the Laufer Muehle area on the Aisch river in Germany. The focus of the investigations was the identification of a parameter combination that allows a short recording interval for aerial imagery. Based on these findings, the identification of changes in the study area by comparing multitemporal photography (flood prevention), as well as the recording of flooded areas during a FE should be possible. The accuracy analysis of the different parameter combinations between two point clouds as well as the process of change detection was done by a Multiscale Model to Model Cloud Comparison (M3C2) and including ground control points. As a result, a parameter combination was identified which led to the desired results in the study area. The processes were transformed into fully automated and scripted workflows. The results serve as a basis for establishing a workflow for near real-time analyses in future studies.

The impact of tropical sea surface temperature on extreme precipitation in Pakistan during the summer of 2022

In August 2022, Pakistan experienced an unprecedented precipitation event that caused significant damage. Analysis of the observations reveals that this extreme rainfall is primarily driven by anomalous atmospheric zonal advection, resulting in an anomalous water vapor concentration in Pakistan. The climatological meridional advection also contributes to this flooding. Anomalous easterly winds and low-level vertical convection combine to be critical factors contributing to the moisture concentration over the country. Further investigation identifies the air-sea interaction over the tropical Indian Ocean and abnormal warming over the Arabian Sea are crucial factors influencing this extreme flooding event. The concurrent occurrence of a negative Indian Ocean Dipole event and the warming sea surface temperature anomalies in the northern Arabian Sea intensifies the easterly winds over Pakistan, helping to transfer the anomalous water vapor from the remote region into Pakistan, ultimately contributing to the extreme flooding in 2022.

Prolonged drought periods over the last four decades increase flood intensity in southern Africa

In semi-arid sub-Saharan Africa, climate change and the intensification of human activities have altered the hydrological balance and modified the recurrence of extreme hydroclimatic events, such as droughts and floods. The geomorphological heterogeneity of river catchments across the region, the variable human pressure, and the lack of continuous hydroclimatic data preclude the definition of proper mitigation strategies, with a direct effect on the sustainability of rural communities.Here, for the first time in Africa, we characterize hydrological extreme events using a multidisciplinary approach that includes sedimentary data from dams. We focus on the Limpopo River basin to evaluate which factors control flood magnitude since the 1970. Extreme flood events were identified across the basin in 1988–89, 1995–96, 1999–2000, 2003–04, 2010–11, 2013–14 and 2016–17. The statistical analysis of sedimentary flood records revealed a dramatic increase in their magnitude over the studied period. A positive correlation between maximum river flow and antecedent prolonged drought conditions was found in South Africa and Mozambique. Most importantly, since 1980, we observed the likely decoupling of extreme floods from the magnitude of La Niña events, suggesting that the natural interannual variability driven by El Niño-Southern Oscillation (ENSO) has been disrupted by climate changes and human activities.

An integrative modelling framework for predicting the compound flood hazards induced by tropical cyclones in an estuarine area

In this study, a novel numerical model is first developed, which can simulate compound floods under a framework comprehensively considering the combined effects of tide, river flow, rainfall, and wind. The modelling framework is applied to reproduce an extreme compound flood event in the Pearl River Delta caused by Typhoon Hato (2017). The model is estimated to perform reasonably well, which can yield consistent results compared with observations including winds, water levels, and inundation depths over the study area. Inundation was concentrated on downstream estuaries and floodplains and coastal forcings played a dominant role in this compound event. However, ignoring river and rainfall contributions would result in an underestimation of flood extent and water levels that could be up to 48%. Sensitivity tests indicate that precise calibration of the roughness coefficient is more critical in river and estuarine environments than in land region. This study demonstrates the importance of utilizing an integrative framework to assess and predict compound flooding hazards driven by the effects of tropical cyclones.

The impact of electrical hazards from overhead power lines on urban search and rescue operations during extreme flood events

Accurate flood forecasting and efficient emergency response operations are vital, especially in the case of urban flash floods. The dense distribution of power lines in urban areas significantly impacts search and rescue operations during extreme flood events. However, no existing emergency response frameworks have incorporated the impacts of overhead power lines on lifeboat rescue operations. This study aims to determine the necessity and feasibility of incorporating overhead power line information into an emergency response framework using Manville, New Jersey during Hurricane Ida as a test bed. We propose an integrated framework, which includes a building-scale flood model, urban point cloud data, a human vulnerability model, and network analysis, to simulate rescue operation feasibility during Hurricane Ida. Results reveal that during the most severe point of the flood event, 46% of impacted buildings became nonrescuable due to complete isolation from the road network, and a significant 67.7% of the municipality’s areas that became dangerous for pedestrians also became inaccessible to rescue boats due to overhead power line obstruction. Additionally, we identify a continuous 10-hour period during which an average of 43.4% of the 991 impacted buildings faced complete isolation. For these structures, early evacuation emerges as the sole means to prevent isolation. This research highlights the pressing need to consider overhead power lines in emergency response planning to ensure more effective and targeted flood resilience measures for urban areas facing increasingly frequent extreme precipitation events.

Effect of climate change to characteristic of extreme rainfall over Batanghari watershed

Climate change will cause extreme rainfall, both wet and dry. Extreme rainfall will cause catastrophic floods and droughts. Therefore, it is important to analyse extreme rainfall and flood events in the future. Disasters and environmental issues in the Batanghari watershed include flooding, drought, forest and land fires, sedimentation, and water quality degradation. Therefore, the Batanghari watershed is selected as a study area in this research. Research on climate change in the Batanghari watershed is crucial to understanding the trend of extreme conditions now and in the future. Characteristics of extreme rainfall will be analysed using the climate index that was developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). Results show that climate change in the Batanghari watershed is indicated by increasing 5 of 6 extreme rainfall indices: R95p, R99p, Rx1day, Rx5day, and SDII. An increase in extreme rainfall is correlated with an increase in flood events in the Batanghari watershed in similar periods. The extreme rainfall index that most influences flooding in the Batanghari watershed is PRCPTOT and R99p. Flooding is expected to occur more frequently in the future than it does now. The Batanghari Hilir Sub-watershed is more vulnerable to extreme flooding in the future than other sub-watershed.

Spatiotemporal Convolutional Approach for the Short-Term Forecast of Hourly Heavy Rainfall Probability Integrating Numerical Weather Predictions and Surface Observations

Abstract The accurate prediction of short-term rainfall, and in particular the forecast of hourly heavy rainfall (HHR) probability, remains challenging for numerical weather prediction (NWP) models. Here, we introduce a deep learning (DL) model, PredRNNv2-AWS, a convolutional recurrent neural network designed for deterministic short-term rainfall forecasting. This model integrates surface rainfall observations and atmospheric variables simulated by the Precision Weather Analysis and Forecasting System (PWAFS). Our DL model produces realistic hourly rainfall forecasts for the next 13 h. Quantitative evaluations show that the use of surface rainfall observations as one of the predictors achieves higher performance (threat score) with 263% and 186% relative improvements over NWP simulations for the first 3 h and the entire forecast hours, respectively, at a threshold of 5 mm h−1. Noting that the optical-flow method also performs well in the initial hours, its predictions quickly worsen in the final hours compared to other experiments. The machine learning model, LightGBM, is then integrated to classify HHR from the predicted hourly rainfall of PredRNNv2-AWS. The results show that PredRNNv2-AWS can better reflect actual HHR conditions compared with PredRNNv2 and PWAFS. A representative case demonstrates the superiority of PredRNNv2-AWS in predicting the evolution of the rainy system, which substantially improves the accuracy of the HHR prediction. A test case involving the extreme flood event in Zhengzhou exemplifies the generalizability of our proposed model. Our model offers a reliable framework to predict target variables that can be obtained from numerical simulations and observations, e.g., visibility, wind power, solar energy, and air pollution.

How to mitigate flood events similar to the 1979 catastrophic floods in the lower Tagus

Abstract. The floods that struck the lower Tagus valley in February 1979 correspond to the most intense floods in this river and affected the largest number of people in a river flow event in Portugal during the last 150 years. In fact, the vast area affected significantly impacted circa 10 000 people in the lower Tagus sector (and an additional 7000 in other regions of Portugal), including thousands of people evacuated or made homeless. In this context, the present study focuses on an in-depth analysis of this event from a hydrodynamic perspective by means of the Iber+ numerical model and on developing strategies to mitigate the flood episodes that occur in the lower section of the Tagus River using the exceptional floods of February 1979 as a benchmark. In this sense, dam operating strategies were developed and analyzed for the most important dam along the Tagus River basin in order to propose effective procedures to take advantage of these infrastructures to minimize the effect of floods. Overall, the numerical results indicate a good agreement with watermarks and some descriptions of the 1979 flood event, which demonstrates the model capability to evaluate floods in the area under study. Regarding flood mitigation, results obtained indicate that the frequency of floods can be reduced with the proposed strategies, which were focused on providing optimal dam operating rules to mitigate flooding in the lower Tagus valley. In addition, hydraulic simulations corroborated an important decrease in water depth and velocity for the most extreme flood events, and also a certain reduction in the flood extension was detected. This confirms the effectiveness of the proposed strategies to help in reducing the flood impact in the lower Tagus valley through the efficient functioning of dams.

Acquisition of disability after age 50 following extreme urban coastal flooding events in India

Acquisition of disability after age 50 following extreme urban coastal flooding events in India

Are extreme floods on the Danube River becoming more frequent? A case study of Bratislava station

Abstract In this study, strong and extreme flood events were analysed on the basis of long-term daily runoff records of winter and summer floods in the Danube River between 1876 and 2020, using the peaks-over-threshold method. Based on the results, the following conclusions can be made: (1) There is a downward trend in strong winter floods, but it is not statistically significant. Additionally, there is an upward trend in summer floods, but this is not statistically significant. (2) There are statistically significant upward trends in extreme events for both the winter and summer seasons. The results have implications for flood protection and disaster management on the Danube River. Regulation of assets in flood-prone areas is essential for minimising economic damage. Public awareness of increasing extreme summer floods is vital for prevention. This study suggests that effective flood risk analysis requires (i) a local- to regional-scale approach to account for spatial variability and (ii) advanced statistical tools for robust detection of climate extremes and estimation of their occurrence rates.

Short‐term effects of Storm Daniel on Salmo farioides (Karaman, 1938) in a high‐gradient stream

AbstractClimate change is expected to increase the magnitude, frequency, and intensity of extreme natural phenomena such as droughts and floods. These events can have devastating impacts on aquatic biota, thus there is a dire need to assess species' natural dynamics and to incorporate them into species' conservation actions and flood management decisions. In September 2023, an extreme meteorological event (Storm Daniel) occurred over the eastern Mediterranean, causing unprecedented high flooding events in many streams and rivers of central Greece. Almost 2 months after the event, we investigated the effects of the storm on Salmo farioides in a high‐altitude stream (Kraniotiko stream, Acheloos river basin) by comparing pre‐flood (June and August 2023) with post‐flood (October 2023) data on fish population abundances and size structure. Our results provide direct evidence that the population of S. farioides was almost wipedout from the investigated stream, as post‐flood fish densities were 9.3% of the pre‐flood data (August) densities. Small‐sized individuals (6–10 cm) were extirpated, indicating a 99% decrease during the post‐flood period, totally reversing the increasing trend observed from June to August (pre‐flood period). In conclusion, the profound and rapid decline observed in the population of S. farioides following the extreme flooding event highlights the urgent need for proactive conservation measures and adaptive management strategies to safeguard vulnerable aquatic species in the face of escalating climate‐related challenges.

Tolerance to drought and flooding events provides a competitive advantage for an invasive over a native plant species

Abstract Changes in precipitation patterns are one of the most pervasive components of climate change. It has been suggested that the increased frequency of extreme drought and flooding events could affect the outcome of competition between native and invasive plants. However, empirical evidence for this prediction remains scarce. We combined controlled experiments and field observations in a freshwater floodplain to assess how drought and flooding events affect growth and biomass production of a native and an invasive plant species, grown in monoculture and mixed culture. We used the native Panicum dichotomiflorum and the invasive Urochloa mutica, which are two common grasses that frequently grow in natural floodplains of the Neotropics. The experimental and observational data showed that biomass production, growth and relative dominance of the native species were higher under more stable water levels. By contrast, the invasive species had higher biomass production, growth and relative dominance under extreme drought and flooding conditions. Thus, extremes in precipitation can alter the relative dominance of the two species in favour of the invader. Our study provides comprehensive evidence that water‐level oscillations may negatively impact the performance of the native species, whereas they did not alter the biomass production and growth of the invasive species. Under stable conditions, faster growth of the native species may hinder successful establishment of the invasive species. However, under extreme drought and flooding events, the invader could be favoured. Although our findings are based on the outcome of the interaction between only one native and one invasive plant species, our results suggest that biotic resistance might be higher under stable water conditions.

Microplastics: A potential proxy for tracing extreme flood events in estuarine environments

The transport of microplastics (MPs) is susceptible to being influenced by catchment hydrology; however, there is a notable lack of research on their retention and responses to flood events in estuarine sedimentary records. Herein, we collected two cores in the Yangtze Estuary to explore their microplastic pollution, influencing factors and linkage to flood events. MP abundance exhibited a decreasing trend from the top to the bottom in both cores. Both plastic production and sediment mean grain size showed a significant positive correlation with MP abundance. The sedimentary record displayed a marked surge in MP abundance during the extreme flood period, suggesting a direct influence of flooding on MP deposition. The resuspension of upstream MPs and erosion of land-based MPs by heavy rain might be responsible for this increase. Furthermore, our study identified significant periodicities in MP abundance, closely aligned with the hydrological patterns of the Yangtze River. This study highlights the role of floods in fluvial MP distribution and proposes MPs as a proxy of extreme floods from the 20th century in estuarine environments.