Extreme Flood Events Research Articles

Extreme flood events in the western Mediterranean: integrating numerical MODelling and flood records in KARST systems (MODKARST project)

Changes in rainfall patterns are a direct consequence of the current climate change. Climate projections indicate an intensification of extreme rainfall events, which will directly affect social, ecological, and economic systems. One of the greatest challenges of climate science is to understand, model, and predict the variability of floods. The uncertainties in projected rainfall are still high, and even higher in Mediterranean areas where the climate is characterized by extreme and sudden rainfall events. The instrumental record is too short to correctly estimate flood return periods. Thus, geological records are required to better understand the long term variability, at millennial to decadal scales, of natural extreme flood events. MODKARST is a MSCA-GF project awarded by the European Union, to develop a quantitative flood database for the Western Mediterranean realm based on speleothems. The action plans to infer past flood events from the last 18 ka based on detrital layers recorded in stalagmites from 5 different caves in the north of Spain, in combination with karst hydraulic models and water-level monitoring. MODKARST will help to better disentangle the relation between flood recurrence and climate changes, and will shed light on how to better predict the variability of floods in the context of present-day global warming.

Quantifying the Impacts of Dry–Wet Combination Events on Vegetation Vulnerability in the Loess Plateau under a Changing Environment

Extreme drought and flood events, as well as their combined events, pose significant challenges to global sustainable socio-economic development and ecological health. However, the impact of dry–wet combination events (DWCEs) on vegetation vulnerability remains to be investigated. The Loess Plateau (LP) was selected as the study area to explore the response time of vegetation to precipitation index changes by optimal correlation coefficient; then, the impact of different DWCEs on vegetation vulnerability under moderate and severe scenarios was analyzed; finally, a vegetation loss probability model was constructed based on the copula function and Bayesian framework, to quantify the vegetation loss probability under DWCEs stress. The results indicate that: (1) normalized difference vegetation index (NDVI) shows an upward trend in spring, summer, and autumn, with the proportion of areas are 90.5%, 86.2%, and 95.4%, respectively, and show an insignificant trend in winter; (2) the response time of vegetation to precipitation index changes tends to be one or two seasons; (3) moderate scenarios have more influence than severe scenarios, dry-to-wet events (DWEs), wet-to-dry events (WDE) and continuous dry events (CDE) in spring-summer have a significant impact on summer vegetation of Ningxia and Shanxi, and WDE and CDE have a higher impact on autumn vegetation. (4) in terms of the probability of vegetation loss, DWE, and CDE cause higher losses to summer vegetation, while WDE and CDE cause higher losses to autumn vegetation. This study quantifies the impact of adjacent seasonal DWCE stress on future vegetation vulnerability.

Climate projections of oceanographic variables in the Exclusive Economic Zone of Ecuador: A 21st century perspective to inform impact and adaptation assessment

Climate projections of ocean variables are essential to inform adaptation strategies and plans involving open and coastal oceanic regions. Assessment of baseline and projections of sea surface temperature (SST), pH, dissolved oxygen (DO), mean sea level (MSL), waves coastal flooding within Ecuador’s Exclusive Economic Zone, including Galapagos Islands are reported herein. With different magnitudes of change, both near-future (2021–2050) and far-future projections (2051–2080) show a statistically robust increase in SST, MSL rise and a reduction in pH, a proxy for acidification. In contrast, DO decrease is only observed in surface (0–100 m) but not in subsurface waters (100–400 m). The likelihood of extreme sea level events in the coastal cities of La Libertad, Manta and Esmeraldas would remain almost unchanged for near-future projections (2026–2045) whereas, for end-of-century projections (2081–2100), historical 1 in a 100-year extreme flooding events would become yearly occurrences. The generated data product offers a state-of-the-art research and management tool for the 21st century under the combined stressors of global climate change. Since the eastern Tropical Pacific Ocean is one of the most productive and biodiverse worldwide due to the equatorial upwelling system, possible impacts on marine biodiversity, social, and economic systems are discussed.

Mixed response of trace element concentrations in fluvial sediments to a flash flood in a former mining area

BackgroundFloods, especially flash floods, are the major transporting agent for fluvial sediments, whose pollution is a global concern. As floods result in the dispersion of and exposure to these sediments, a profound understanding of sedimentary dynamics during flood events and the related pollutant dispersion is of relevance. However, the characteristics of extreme flood events concerning pollutant dynamics are insufficiently known so far.ResultsIn a Central European catchment impacted by intense industrial activities and former mining, over the course of five years, we surveyed six high-discharge events, five of them approx. bankfull discharge and one major flash flood event, supplemented by sampling of bank sediments. Fluvial sediments were analyzed for elemental composition by X-Ray fluorescence and for grain size distribution of the fine faction by laser diffraction. By applying a local enrichment factor, trace metal(loid) signatures in these sample sets were compared. Furthermore, Positive Matrix Factorization was used to investigate the trace metal(loid)s’ sources.The sediments deposited by minor flooding had continual trace metal(loid) signatures. However, for the extreme event, significant divergencies arose and persisted for the following years: The enrichment of anthropogenically influenced elements increased, with a slowly decreasing trend in the subsequent two years. Naturally dominated metal(oid)s decrease in enrichment without indicating a return to original levels. In contrast, other elements were insensitive to the extreme event. Positive Matrix Factorization identified anthropogenic influences in elements originating from copper and lead processing and mining activities. Furthermore, bed sediments and a natural background factor were found to dominate the non-anthropogenically influenced metal(loid)s.ConclusionsIn between extreme events, winnowing processes slowly alter the elemental composition of bed sediments. The depletion of such sediments due to the flash flood proves catchment-wide flushing, which induces a natural resetting of the geochemical signals. This ability to renew is an integral part of resilience in fluvial systems. This mechanism is disturbed by industrial activities in floodplains. The exceptional flooding reaches infrastructure that is assumed to be safe and, therefore, unprotected. These additional sources can shift flood sediments’ trace metal(loid) signature, which has a long-lasting impact on the catchment sediments. However, the modifications depend on the flooding extent, possible emitters, and protection measures.

Enhancing Flood Risk Management: A Comprehensive Review on Flood Early Warning Systems with Emphasis on Numerical Modeling

During recent decades there has been an increase in extreme flood events and their intensity in most regions, mainly driven by climate change. Furthermore, these critical events are expected to intensify in the future. Therefore, the improvement of preparedness, mitigation, and adaptation counterparts is mandatory. Many scientific fields are involved in this task, but from a meteorological and hydrological perspective, one of the main tools that can contribute to mitigating the impact of floods is the development of Early Warning Systems. In this sense, this paper presents a scientific literature review of some of the most representative Flood Early Warning Systems worldwide, many of which are currently fully operational, with a special focus on the numerical modeling component when it is developed and integrated into the system. Thus, from basic to technically complex, and from basin or regional to continental or global scales of application, these systems have been reviewed. In this sense, a brief description of their main features, operational procedures, and implemented numerical models is also depicted. Additionally, a series of indications regarding the key aspects of the newly developed FEWSs, based on recent trends and advancements in FEWSs development found in the literature, are also summarized. Thus, this work aims to provide a literature review useful to scientists and engineers involved in flood analysis to improve and develop supporting tools to assist in the implementation of mitigation measures to reduce flood damage for people, goods, and ecosystems and to improve the community resilience.

What controls river widening? Comparing large and extreme flood events

AbstractExtreme (i.e., centennial‐scale) floods are by definition rare and can therefore be difficult to study. As a result, case studies of response to extreme floods can provide unique insights. On 15 November 2021, the Nicola River in British Columbia, Canada, experienced a 200‐year flood that increased the average width of the Nicola River by more than 50% (35 m), leaving the only highway in the region impassable for nearly 12 months. This research assesses the spatial variability of erosion along a 71‐km‐long segment of the Nicola River during a period with a large flood (2015–2018) and a second period containing the extreme flood in 2021 (2018–2021). We use a random forest statistical analysis to explore the most important valley and channel characteristics affecting relative widening during both periods. Unit stream power, gradient and valley confinement were the primary determinants of erosion during the extreme flood, whereas vegetation cover, channel pattern and surficial material were less important. Erosion during the large flood event was not related to these variables, with channel pattern providing a better indication of widening potential. As the Nicola River is flanked by erodible glacial deposits, this work provides important insight into river response in the paraglacial environments that are common throughout much of Canada and the northern United States, as well as Europe and Asia, but less intensely studied. In these settings, the geomorphic response to large floods may not be representative of the potential erosion (and infrastructure impacts) that can occur during extreme events, which destabilize glacial terraces in confined reaches. Historical observations should therefore be used with caution in paraglacial settings as extreme events may not be captured in available data, creating a perception of stability in confined reaches that may have the potential to erode dramatically during extreme events.

Predicting the hydraulic response of critical transport infrastructures during extreme flood events

Understanding the effects of extreme floods on critical infrastructures such as bridges is paramount for ensuring safety and resilient design in the face of climate change and extreme events. This study develops robust computational and predictive modeling tools for assessing the impacts of extreme floods on the hydraulic response and structural resilience of bridges. A computational fluid dynamic (CFD) model utilizing RANS equations and k-ω Shear Stress Transport (SST) for simulating supercritical flows is adopted to compute hydrodynamic pressures and the water levels on bridge piers of cylindrical and rectangular shapes during a flood event. The CFD model is validated based on the case study data obtained from the Haj Omran Bridge, built on the Khorramabad River in Iran. The numerical simulations consider hydrological conditions and exclude geotechnical parameters and abutment damages. The numerical results are evaluated based on well-established design guidelines. Machine learning techniques, including Extreme Gradient Boosting (XGBoost), Random Forest (RF), and Support Vector Regression (SVR), optimized with Grid Search Cross-Validation (GSCV), are adopted to enhance the accuracy of hydrodynamic pressure forecasting at bridge piers. The XGBoost model exhibits superior performance (R2 = 0.908, RMSE = 0.0279, and E = 3.41%) compared to the RF and SVR models. All the estimated pressure data by XGBoost falls within ±6 percent error lines, highlighting the model's robustness for out-of-range hydrodynamic pressure prediction. Additionally, an optimized Long Short-Term Memory (LSTM) model is adopted to effectively predict free surface flow profiles (i.e. flood depth) over the bridge (R2 = 0.937 and RMSE = 0.083), demonstrating its potential for practical applications of flood depth predictions over bridge infrastructures. The proposed methodological framework outlined in this study can facilitate modeling the impacts of extreme floods on bridges, enabling robust climate resilience assessment of critical infrastructures.

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.

Experimental And Numerical Inter-Comparison On Green And Gray Mitigation Alternatives In Flooding Reduction In Coastal Region

Coastal communities in low-lying regions are increasingly vulnerable to severe flooding triggered by high surges and large waves. The sea level rise resulting from climate change induces shorelines to encroach onto coastal land, further exacerbating the flooding damage in coastal areas. Thus, it is necessary to implement coastal structures to mitigate the influence of extreme flooding events on coastal communities. Seawalls, submerged breakwaters, and mangrove forests have been widely constructed worldwide to attenuate wave overflows and their impact on near-coast regions. However, studies on the comprehensive inter-comparison of the protective performance of each measure against flooding events to provide guidelines in coastal design and planning have yet to be limited. Therefore, experimental and numerical models were conducted to investigate the efficiency of natural (mangrove forests) and man-made (seawall and submerged breakwater) coastal structures in reducing the forces, pressures, and hydrodynamics generated by overflows in constructed environments.

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.

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.

Quantifying Overtopping Performance Of Green-Gray Hybrid Infrastructure

Wave overtopping of shoreline infrastructure can lead to significant flooding and consequent loss of life, impairment of transportation systems, and ecological damage. Coastal defenses against overtopping traditionally include hard structures, such as seawalls and revetments, and design guidelines for these structures, e.g., the EurOtop manual (Van der Meer et al., 2018), have been developed from empirical studies of overtopping. Recently, natural and nature-based features (NNBF) including mangroves, wetlands, reefs, and other systems have gained attention as alternatives to conventional engineered coastal protection systems. Field observations have identified the potential of emergent vegetation, particularly mangrove forests, to mitigate damage during extreme coastal flood events (Alongi, 2008; Tomiczek et al., 2020). However, there is a lack of research on engineering NNBF systems to achieve specific design requirements for overtopping protection. Hybrid or multi-tiered approaches to shoreline protection have also been proposed, where natural (“green”) features are combined with hardened (“gray”) infrastructure to protect coastlines and near-coast assets from erosion and/or flood-based hazards. For overtopping mitigation, hybrid designs can add the performance provided by emergent vegetation to the services of a revetment or a wall. It is unknown whether the green and gray features in a hybrid system perform independently and can be considered as separate design elements, or if the inclusion of one feature affects the performance of the other such that the hybrid system must be considered as a single, complex design element. This study constructed a large-scale physical model to investigate the overtopping performance of a hybrid system with an idealized Rhizophora mangrove forest seaward of a revetment abutting a vertical wall compared to that performance of the wall fronted by the revetment only, the wall fronted by vegetation only, and the wall alone.

Community adaptation to climate-related flooding in Saskatchewan

Sustainable Development Goal 13 advances planning and resilience particularly germane for communities at the forefront of exposure to climate impacts. With the increasing intensity and frequency of climate impacts, including flood, assessing the state of preparedness of communities through review of their policies, is increasingly important. This research used a mixed methods approach to develop community resilience indicators (based on planning for extreme flood events) supplemented by two round tables and six focus groups with community leaders in Saskatchewan.Several Saskatchewan communities were identified as exposed to extreme rainfall events as well as inundation from surrounding rivers and water bodies. Focus group and roundtable participants confirmed that flood events were becoming more frequent in recent years. Cities generally scored higher in resilience, however, some northern communities also scored high. Experience of floods wasn't a necessary prerequisite of flood planning as several communities had robust plans without historical flood experience. Communities that had experienced previous flood events scored higher on indicators of flood preparedness resilience. Two communities that had never experienced floods had high indicators, providing evidence that demonstrated coping capacity is not a necessary precondition of resilience.Explanations for failure to plan included inability to address contributing farming practices, the high cost of infrastructure, climate change denial within communities, and downplaying adaptation to climate change because of its high price tag. A generational divide was identified as concerning, and especially counterproductive to the attraction of young people to rural and remote communities. Solutions identified included expanding partnerships, sharing services within a wider regional community, and supporting capacity and leadership for this. While this research suffers from limitations relating to data availability, more research on why some communities have not yet planned for floods (even though they have experienced them) and a greater geography of study would be beneficial.

Modeling the Impact of Climate Change on Streamflow in the Meghna River Basin: An Analysis Using SWAT and CMIP6 Scenarios

This study assesses future climate change impacts on the hydrologic response of the Upper Meghna River Basin (UMRB), a major river system in Bangladesh. Separate SWAT (Soil and Water Assessment Tool) hydrologic models were developed for the three major sub-basins of the UMRB, i.e., Barak, Meghalaya, and Tripura, considering their unique geographical, hydrological, and land-use characteristics. To evaluate the efficiency of multi-site modeling in providing better model performance, the SWAT models were calibrated at both single and multiple locations. Those models were then simulated to estimate future flows using climate projection data from thirteen CMIP6 General Circulation Models (GCMs) under moderate and extreme emission scenarios, SSP2-4.5, and SSP5-8.5. The results revealed that the annual maximum flow will keep increasing gradually with time. The outlets of the Meghalaya sub-basin will experience a more significant rise in future flow in the upcoming decades compared to the Barak and Tripura sub-basins. Results showed that dry season flows with increases of up to 31–50% would be less affected compared to the wet periods, which could experience increases of up to 47–66%) across the sub-basins by the end of the 21st century under extreme emission projections. Besides an increasing trend in the mean flow, future flows at several outlets also exhibited an escalation in the intensity and frequency of extreme flood events.

A 7000-year record of extreme flood events reconstructed from a threshold lake in southern Norway

Recent decades have witnessed a shift in the seasonality and frequency of river floods in Norway, primarily attributed to contemporary global warming. Such changes necessitate a more comprehensive understanding of climate-flood dynamics across river systems. A significant challenge in flood risk assessment is that instrumental data records cover only the last few decades and do not capture low-frequency, high-magnitude extremes. Another challenge is the non-stationarity of the leading atmospheric pattern over Scandinavia, the North Atlantic Oscillation (NAO), which requires a spatial understanding of extreme events through time. To address this issue, we use lacustrine sediments from southernmost Norway, aiming to extend flood records beyond the scope of instrumental and historical data by exploring a threshold lake that accumulates flood deposits only when river discharge exceeds a critical level. A multi-proxy approach, which includes X-ray fluorescence (XRF), computed tomography (CT), and magnetic susceptibility (MS), was applied to fingerprint the sediments. We detected thin layers of minerogenic sediments, which we interpreted as slackwater deposits accumulated in a lake environment during extreme flood events. These fine-grained minerogenic bands were quantified using XRF and CT data to reconstruct the frequency of major floods over the past ∼7000 years. The minimum water discharge necessary for transporting sediments into the lake was assessed with the HEC-RAS hydraulic simulation software. Our record shows a high frequency of extreme floods from 7000 to 5000 cal yr BP before a significant decrease from 5000 to 2300 cal yr BP. The frequency has been high since 2300 cal yr BP, with a peak frequency after 1600 CE, coinciding with the Little Ice Age. There is a strong co-variability between a positive NAO index, winter precipitation, and major flood events over the past 120 years. A comparison between our flood record and other palaeorecords suggests that this relationship also holds on multi-millennial time scales.

How extreme hydrological events correspond to climate extremes in the context of global warming: A case study in the Luanhe River Basin of North China

AbstractThe consensus on climate warming is well‐established, and extreme values inherently encapsulate more information than averages. Against the backdrop of frequent extreme climate events, studying extreme values holds profound significance. This study aims to reveal the characteristics of extreme climate events and their role in triggering extreme hydrological events in the typical North China basin, that is, the Luanhe River Basin. Trends of 25 extreme climate indices during 1960–2018 are analysed using the Sen's slope and MK significance test to study the changing characteristics of extreme climate. Characteristics of extreme flood and dry events are examined, encompassing trend analyses at different time scales (seasonal, interannual, decadal) and concentration analysis. Finally, and most significantly, correlation analysis is conducted on extreme climate indices and features of extreme hydrological events, followed by principal component analysis of extreme climate indices, to precisely quantify the impact of extreme climate on the occurrence of extreme hydrological events. The results indicate a warming trend in extreme temperature indices, with a more significant rise in minimum temperatures compared to maximum temperatures. There is a significant decrease in precipitation, but precipitation at higher magnitudes is less affected by the overall reduction in total precipitation. Extreme dry events have markedly increased, particularly concentrated in winter with delayed occurrences, primarily induced by extreme temperature events, that is, warming effects. Conversely, extreme flood events have significantly decreased, mainly concentrated in summer and early autumn, predominantly caused by extreme precipitation and extreme high‐temperature events. The climate and hydrological conditions in the study area have become more extreme and complex. Severe river droughts may occur more frequently in winter, while extreme flooding may happen in summer. Therefore, it is necessary to pay more attention to these developments.

Urbanization enhances channel and surface runoff: A quantitative analysis using both physical and empirical models over the Yangtze River basin

Urbanization has become an irreversible trend and is even more rapid in flood-prone area. However, the responses of both channel runoff and surface runoff to the urbanization and the underlying mechanisms still deserve more in-depth exploration within urban extents with limited data availability. Accordingly, we conducted a comprehensive quantitative analysis of the urbanization effects on channel and surface runoff from both statistical and model-based perspectives over three major urban agglomerations (i.e., Chengyu (CY), middle region of Yangtze River (MRYR), Yangtze River Delta (YRD)) in the Yangtze River Basin. The long-term high-resolution channel and surface runoff under different urbanization scenarios were simulated using both WRF-Hydro and SCS-CN models by integrating multiple remotely sensed, reanalysis, and in-situ datasets. Results demonstrated that the channel runoff increased by 4.4%, 5%, and 12.08% in CY, MRYR, and YRD urban agglomerations, respectively. Meanwhile, the urbanization also contributed to 30%, 21.4%, and 17.7% of the surface runoff changes in three urban agglomerations. Based on the high-resolution local climate zone (LCZ), our results highlighted that the high-rise and middle-rise buildings and compact-arranged regions were more prone to accumulating surface runoff and trigger flooding events due to the weaker infiltration capacity of land surface with the densely distribution of impervious surface. Further machine learning based investigation and case analysis also explored the potential influencing factors and mechanisms of the impact of urbanization on channel and surface runoff. Results in the current research show further evidence that policy makers of urban planning and management need to consider and ensure societal preparedness for extreme runoff and flooding events.

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.