Flood Drivers Research Articles

Compounding Effects of Fluvial Flooding and Storm Tides on Coastal Flooding Risk in the Coastal-Estuarine Region of Southeastern China

In coastal areas of southeastern China, multiple flood drivers such as river flow, precipitation and coastal water level can lead to compound flooding which is often much greater than flooding simulated by one flood driver in isolation. Bivariate probability distributions accounting for compound flooding from river discharge and sea level were constructed based on MvCAT (Multivariate Copula Analysis Toolbox) combined with goodness of fit tests in 15 coastal-estuarine regions of Southeastern China. Flood typing-based bivariate probability distributions considering multiple flood-generating mechanisms were also built. Our results indicated that the performance of flood typing-based bivariate distribution was not significantly better than the bivariate probability distribution in coastal-estuarine regions based on the Mann–Whitney U test; the compounding effects of river discharge and sea level had limited impact on bivariate return periods, but had greater impact on coastal flooding risk in terms of design values. Ignoring compounding effects of river discharge and sea level leads to significant underestimation of design values. The results suggest that the compounding effect of river discharge and sea level should be considered when calculating design values in coastal flood risk assessment.

Investigating the interaction of waves and river discharge during compound flooding at Breede Estuary, South Africa

Abstract. Recent studies have drawn special attention to the significant dependencies between flood drivers and the occurrence of compound flood events in coastal areas. This study investigates compound flooding from tides, river discharge (Q), and specifically waves using a hydrodynamic model at the Breede Estuary, South Africa. We quantify vertical and horizontal differences in flood characteristics caused by driver interaction and assess the contribution of waves. Therefore, we compare flood characteristics resulting from compound flood scenarios to those in which single drivers are omitted. We find that flood characteristics are more sensitive to Q than to waves, particularly when the latter only coincides with high spring tides. When interacting with Q, however, the contribution of waves is high, causing 10 %–12 % larger flood extents and 45–85 cm higher water depths, as waves caused backwater effects and raised water levels inside the lower reaches of the estuary. With higher wave intensity, the first flooding began up to 12 h earlier. Our findings provide insights on compound flooding in terms of flood magnitude and timing at a South African estuary and demonstrate the need to account for the effects of compound events, including waves, in future flood impact assessments of open South African estuaries.

A quantitative multi-hazard risk assessment framework for compound flooding considering hazard inter-dependencies and interactions

Multi-hazard risk assessment may provide comprehensive analysis of the impact of multiple hazards but still needs to resolve major challenges in three aspects: (1) proper consideration of hazard inter-dependency, (2) physically based modelling of hazard interactions, and (3) fully quantitative risk assessment to show the probability of loss. Compound flooding is a typical multi-hazard problem that involves the concurrence of multiple hazard drivers, e.g. heavy rainfall, extreme river flow, and storm surge. These hazard drivers may result from the same weather system and are thus statistically inter-dependent, physically overlayed and interacted in the same region. This paper aims to address the mentioned challenges and develop an integrated assessment framework to quantify compound flood risk. The framework is constructed based on the three typical components in disaster risk assessment, i.e. hazard, vulnerability and exposure analysis. In hazard analysis, joint probability and return period distributions of the three hazard drivers of compound flooding are estimated using Copula functions with hazard dependency analysis, which are then used to generate random multi-hazard events to drive a 2D high-performance hydrodynamic model to produce probabilistic inundation maps and frequency-inundation curves. Vulnerability and exposure analysis provides damage functions of the elements at risk, which are used to quantify multi-hazard risk with the frequency-inundation curves. The framework is applied in the Greater London and its downstream Thames estuary to demonstrate its capability to analyse hazard interactions and inter-dependencies to produce fully quantitative risk assessment results such as risk curves quantifying the probability of loss and risk maps illustrating the annual expected loss of residential buildings.

The Precautionary Principles of the Potential Risks of Compound Events in Danish Municipalities

The risk of compound events describes potential weather and climate events in which the combination of multiple drivers and hazards consolidate, resulting in extreme socio-economic impacts. Compound events affecting exposed societies can therefore be deemed a crucial security risk. Designing appropriate preparation proves difficult, as compound events are rarely documented. This paper explores the understanding and practices of climate risk management related to compound events in specific Danish municipalities vulnerable to flood hazards (i.e., Odense, Hvidovre, and Vejle). These practices illuminate that different understandings of compound events steer risk attitudes and consequently decisions regarding the use of different policy instruments. Through expert interviews supported by policy documents, we found that the municipalities understand compound events as either a condition or situation and develop precautionary strategies to some extent. Depending on their respective geographical surroundings, they observe compound events either as no clear trend (Odense), a trend to be critically watched (Hvidovre), or already as a partial reality (Vejle). They perceive flood drivers and their combinations as major physical risks to which they adopt different tailor-made solutions. By choosing a bottom-up approach focusing on local governance structures, it demonstrated that the mismatch between responsibility and capacity and the ongoing separation of services related to climatic risks in the Danish municipality context need to be critically considered. The findings highlight that the complex challenge of compound events cannot be solved by one (scientific) discipline alone. Thus, the study advocates a broader inclusion of scientific practices and increased emphasis on local focus within compound event research to foster creative thinking, better preparation, and subsequently more effective management of their risks.

Sustained Wind Forcing and Water Level Anomalies in Annapolis, Maryland

Abstract Like many coastal communities throughout the mid-Atlantic region, relative sea level rise and accelerating instances of coastal nuisance flooding are having a tangible negative impact on economic activity and infrastructure in Annapolis, Maryland. The drivers of coastal nuisance flooding, in general, are a superposition of global, regional, and local influences that occur across spatial and temporal scales that determine water levels relative to a coastal datum. Most of the research to date related to coastal flooding has been focused on high-impact episodic events, decomposing the global and regional drivers of sea level rise, or assessing seasonal-to-interannual trends. In this study, we focus specifically on the role of short-duration (hours) meteorological wind forcing on water level anomalies in Annapolis. Annapolis is an ideal location to study these processes because of the orientation of the coast relative to the prevailing wind directions and the long record of reliable data observations. Our results suggest that 3-, 6-, 9-, and 12-h sustained wind forcing significantly influences water level anomalies in Annapolis. Sustained wind forcing out of the northeast, east, southeast, and south is associated with positive water level anomalies, and sustained wind forcing out of the northwest and north is associated with negative water level anomalies. While these observational results suggest a relationship between sustained wind forcing and water level anomalies, a more robust approach is needed to account for other meteorological variables and drivers that occur across a variety of spatial and temporal scales. Significance Statement Coastal nuisance flooding, often the result of positive water level anomalies, is having a negative economic impact in Annapolis, Maryland. Coastal flooding research has primarily focused on high-impact episodic events, trends in sea level rise, or seasonal to interannual variability in flooding. In this study we show that short-duration wind forcing (≤12 h) likely has a significant impact on both positive and negative water level anomalies in Annapolis. While this was empirically known by local stakeholders, in this study we attempt to quantify the relationship. These results could help local stakeholders to mitigate against economic and infrastructure losses resulting from coastal nuisance flooding.

Contrasting scaling relationships of extreme precipitation and streamflow to temperature across the United States

Recent studies have reached inconsistent conclusions from scaling analysis about whether flood or extreme precipitation is more sensitive to warming climate. To explain the reasons behind the inconsistency, here we first used scaling analysis to illustrate how extreme daily precipitation and streamflow scale with daily air temperature across the Continental United States (CONUS). We found both similar and opposite scaling in extreme precipitation and streamflow. It indicates based on scaling analysis, the sensitivity of extreme streamflow to warming climate can be either similar, higher or lower to that of extreme precipitation. We further explored why there are contrasting scaling relationships in the CONUS. Generally, the similar scaling was found in regions where the timing of extreme precipitation and streamflow is correspondent, as well as with similar temporal evolution in extreme event timing and magnitude, e.g., the west coast and southern plains, implying extreme precipitation is the dominant driver of local floods. However, for regions with dissimilar scaling in extreme precipitation and streamflow (e.g., Rocky Mountains, southern plains), the characteristics of extreme streamflow show large difference to those of extreme precipitation, and the temporal evolution of extreme streamflow timing and magnitude are more correlated with factors/processes such as soil moisture and snowmelt. This study reflects that the contrasting scaling relationships of extreme precipitation and streamflow are oriented from the local hydro-climatological specifics. Using scaling analysis to compare the sensitivity of extreme precipitation and streamflow to warming climate is not suitable. Instead, we should focus more on local flood generating mechanisms or flood drivers when investigating floods in the changing climate.

Accounting for uncertainties in compound flood hazard assessment: The value of data assimilation

Compound flood hazard assessment (CFHA) and modeling are prone to various sources of uncertainty including model structure, model parameters, input/forcing data, and those associated with nonlinear interactions among flood drivers. Data assimilation (DA) is an efficient method that helps quantify and reduce uncertainty in many hydrological applications and has proven to be effective in water level (WL) predictions and/or flood forecasts. However, research to date has not yet explored the benefits of DA in coastal to inland transition zones where pluvial, fluvial, and coastal flood drivers interact. Here, we present a DA scheme consisting of the Ensemble Kalman Filter technique and hydrodynamic modeling to provide (i) reliable WL predictions and (ii) accurate (near real-time) flood hazard maps within a 6 h-assimilation cycle. The DA scheme is tested on two well-known compound flood events and study sites in the United States, namely Hurricane Harvey for Galveston Bay and Hurricane Sandy for Delaware Bay. WL predictions and compound flood hazard maps are validated against observational data collected from coastal and inland gauge stations and high-water marks obtained from the U.S. Geological Survey, respectively. We show that DA is an effective method that accounts for all sources of uncertainty, reduces errors in peak WL estimates (up to 0.55 m) and mean absolute bias in CFHA (up to 40%). We conclude that, regardless of the dominant fluvial/pluvial or coastal drivers, DA can improve CFHAs in low-lying areas including coastal to inland transition zones.

Surface runoff response to long-term land use changes: Spatial rearrangement of runoff-generating areas reveals a shift in flash flood drivers

Nowadays, rapid growths of urban areas and associated land use/land cover (LULC) changes notably affect the surface runoff response to rainfall in urbanised catchments. This effect of urbanisation on surface runoff is frequently addressed since it relates to the increasing incidence of pluvial floods worldwide. Studies on this issue commonly assess runoff changes over several most recent decades. However, human-induced factors likely resulted in increased surface runoff and associated flash floods in rural catchments even in the past centuries. Such long-term changes have been rarely studied and thus are not well documented. This paper aims to fill this gap and assess the surface runoff response to LULC changes in a small catchment in southwestern Slovakia over more than two centuries. To meet this goal, we applied the Soil Conservation Service Curve Number (SCS-CN) method. We mapped past (1784) and present (2018) LULC classes based on historical maps and modern remote sensing data. Then, we estimated surface runoff depths for specific design rainstorms for both periods by executing CN method equations in the ArcGIS environment. Results revealed significant changes in surface runoff conditions between evaluated periods. In total, surface runoff magnitudes increased by ~230 and ~ 130% for 40- and 65-mm design rainstorms, respectively, compared to 1784. Moreover, surface runoff values show different spatial patterns on historical and present-day output raster images revealing spatial redistribution of runoff-enhancing and runoff-preventing areas during the evaluated period. Although both infiltration-enhancing and runoff-enhancing effects of LULC changes were identified, the latter effect associated with urbanised lowland areas was recognised as prevailing at present. In contrast, runoff-promoting conditions were associated with hilly vineyard areas in the past. These findings likely have important implications for understanding the past and present LULC-based controls of surface runoff generation and flash floods initiation.

Sensitivity of Estuaries to Compound Flooding

Fluvial and surge-tide extremes can occur synchronously resulting in compound flooding in estuaries, greatly intensifying the hazard. This flood risk has the potential to increase in the future as the frequency, phasing and/or intensity of these drivers change. Improved understanding of how extreme fluvial discharge and surge-tides interact will help inform future flood mitigation methodology. In this paper, therefore, we resolve for the first time intra-estuary sensitivities to fluvial and surge-tide extremes, for two contrasting UK estuaries (Humber and Dyfi). Model simulations at hyper-spatial resolution (< 50 m) using a 2D hydrodynamic model predicted compound flooding hazards based on: (1) present-day extreme events (worst on record); (2) present-day extreme events with shifted timings of the drivers to maximise flooding; and (3) modified drivers representing projected climate change. We found that in a small estuary with short-duration, high-intensity fluvial inputs (Dyfi), flood extent is sensitive to the relative timing of the fluvial and surge-tide drivers. In contrast, the relative timing of these drivers did not affect flooding in a larger estuary with a slower fluvial response to rainfall (Humber). In the Humber, extreme fluvial inputs during a compound hazard actually reduced maximum water depths in the outer estuary, compared with a surge-tide-only event. Projected future changes in these drivers by 2100 will increase compound flooding hazards: simulated sea-level rise scenarios predicted substantial and widespread flooding in both estuaries. However, projected increases in surge-tide behaved differently to sea-level rise of the same magnitude, resulting in a greater seawater influx and more flooding. Increased fluvial volumes were the weakest driver of estuarine flooding. In this paper we show how these interactions are complex and how the hydrodynamics vary considerably between different estuaries and sites within estuaries, making it difficult to generalise, use probabilistic or use 1D approaches for assessing compound flooding hazards. Hence, we contribute new knowledge and methods for catchment-to-coast impact modelling used for flood mitigation strategies.

Assessing the Effects of Climate Change on Compound Flooding in Coastal River Areas

AbstractFlood assessment in coastal river areas is subject to complex dependencies and interactions between flood drivers. In addition, coastal areas are especially vulnerable to climate change, and thus its effects should be considered in the evaluation of future flood hazard. In the present study, we propose a methodology for a robust evaluation of historical and future flooding in coastal river areas. It follows a continuous simulation approach in which a hydrologic‐hydraulic modeling cascade is run for several years, driven by a simultaneous series of flood drivers. The method differs from other existing methodologies in: (a) jointly considering the relevant flood drivers, both coastal and inland, together with their dependencies and interactions, to represent the simultaneous occurrence of extreme water levels correctly, and (b) obtaining local‐scale physically consistent projections of flood drivers to account for future climate change effects on compound flood hazard. The methodology is tested for a coastal river reach in NW Spain. The results show that, although mean sea level rise is usually expected to be the main driver of increased flood hazard, climate change effects on river discharge can play a very significant role in regions with compound flooding potential.

Identification of flood seasonality and drivers across Canada

AbstractFloods are the most frequently occurring natural hazard in Canada. An in‐depth understanding of flood seasonality and its drivers at a national scale is essential. Here, a circular, statistics‐based approach is implemented to understand the seasonality of annual‐maximum floods (streamflow) and to identify their responsible drivers across Canada. Nearly 80% and 70% of flood events were found to occur during spring and summer in eastern and western watersheds across Canada, respectively. Flooding in the eastern and western watersheds was primarily driven by snowmelt and extreme precipitation, respectively. This observation suggests that increases in temperature have led to early spring snowmelt‐induced floods throughout eastern Canada. Our results indicate that precipitation (snowmelt) variability can exert large controls on the magnitude of flood peaks in western (eastern) watersheds in Canada. Further, the nonstationarity of flood peaks is modelled to account for impact of the dynamic behaviour of the identified flood drivers on extreme‐flood magnitude by using a cluster of 74 generalized additive models for location scale and shape models, which can capture both the linear and nonlinear characteristics of flood‐peak changes and can model its dependence on external covariates. Using nonstationary frequency analysis, we find that increasing precipitation and snowmelt magnitudes directly resulted in a significant increase in 50‐year streamflow. Our results highlight an east–west asymmetry in flood seasonality, indicating the existence of a climate signal in flood observations. The understating of flood seasonality and flood responses under the dynamic characteristics of precipitation and snowmelt extremes may facilitate the predictability of such events, which can aid in predicting and managing their impacts.

Western U.S. Superfloods in the Recent Instrumental Record

AbstractWe examine the characteristics of extremely severe and extensive floods across the Western U.S., which we term superfloods. We develop a system to score each day from 1950 to 2010, across the conterminous U.S. west of the Continental Divide, according to the severity of flooding and the extent of the area affected on that day. In order to augment the available stream gauge data, we incorporate model output runoff from the Variable Infiltration Capacity model aggregated to the HUC‐8 basin level. The superfloods we identify include well‐known events such as the Christmas floods of December 1964. Once the superfloods are identified, we use modeled snow water equivalent and snowmelt in combination with gridded observed precipitation and air temperature to identify superflood drivers. We find that the superfloods fall into three distinct categories: (a) winter events, most of which are associated with Atmospheric Rivers, many enhanced by rain‐on‐snow; (b) late spring floods associated with snowmelt, including some events with rainfall contributions; and (c) rainfall‐driven warm season floods associated with tropical storms (primarily in the Southwest). We find that rainfall is often the primary driver of superfloods, although snowmelt also contributes in rain‐snow transition zones. Regardless of superflood characteristics, extreme conditions in combination are a common feature, including combinations of rainfall and snowmelt as well as successive rainstorms. Our results provide a regional view of flood drivers and how they have combined to produce superfloods across the region over our 61‐year study period.

Global-scale changes to extreme ocean wave events due to anthropogenic warming

Extreme surface ocean waves are often primary drivers of coastal flooding and erosion over various time scales. Hence, understanding future changes in extreme wave events owing to global warming is of socio-economic and environmental significance. However, our current knowledge of potential changes in high-frequency (defined here as having return periods of less than 1 year) extreme wave events are largely unknown, despite being strongly linked to coastal hazards across time scales relevant to coastal management. Here, we present global climate-modeling evidence, based on the most comprehensive multi-method, multi-model wave ensemble, of projected changes in a core set of extreme wave indices describing high-frequency, extra-tropical storm-driven waves. We find changes in high-frequency extreme wave events of up to ∼50%–100% under RCP8.5 high-emission scenario; which is nearly double the expected changes for RCP4.5 scenario, when globally integrated. The projected changes exhibit strong inter-hemispheric asymmetry, with strong increases in extreme wave activity across the tropics and high latitudes of the Southern Hemisphere region, and a widespread decrease across most of the Northern Hemisphere. We find that the patterns of projected increase across these extreme wave events over the Southern Hemisphere region resemble their historical response to the positive anomaly of the Southern Annular Mode. Our findings highlight that many countries with low-adaptive capacity are likely to face increasing exposure to much more frequent extreme wave events in the future.

Uncertainties in Riverine and Coastal Flood Impacts under Climate Change

Climate change can affect different drivers of flooding in low-lying coastal areas of the world, challenging the design and planning of communities and infrastructure. The concurrent occurrence of multiple flood drivers such as high river flows and extreme sea levels can aggravate such impacts and result in catastrophic damages. In this study, the individual and compound effects of riverine and coastal flooding are investigated at Stephenville Crossing located in the coastal-estuarine region of Newfoundland and Labrador (NL), Canada. The impacts of climate change on flood extents and depths and the uncertainties associated with temporal patterns of storms, intensity–duration–frequency (IDF) projections, spatial resolution, and emission scenarios are assessed. A hydrologic model and a 2D hydraulic model are set up and calibrated to simulate the flood inundation for the historical (1976–2005) as well as the near future (2041–2070) and far future (2071–2100) periods under Representative Concentration Pathways (RCPs) 4.5 and 8.5. Future storm events are generated based on projected IDF curves from convection-permitting Weather Research and Forecasting (WRF) climate model simulations, using SCS, Huff, and alternating block design storm methods. The results are compared with simulations based on projected IDF curves derived from statistically downscaled Global Climate Models (GCMs). Both drivers of flooding are projected to intensify in the future, resulting in higher risks of flooding in the study area. Compound riverine and coastal flooding results in more severe inundation, affecting the communities on the coastline and the estuary area. Results show that the uncertainties associated with storm hyetographs are considerable, which indicate the importance of accurate representation of storm patterns. Further, simulations based on projected WRF-IDF curves show higher risks of flooding compared to the ones associated with GCM-IDFs.

Flooding Conditions at Aveiro Port (Portugal) within the Framework of Projected Climate Change

Ports constitute a significant influence in the economic activity in coastal areas through operations and infrastructures to facilitate land and maritime transport of cargo. Ports are located in a multi-dimensional environment facing ocean and river hazards. Higher warming scenarios indicate Europe’s ports will be exposed to higher risk due to the increase in extreme sea levels (ESL), a combination of the mean sea level, tide, and storm surge. Located on the west Iberia Peninsula, the Aveiro Port is located in a coastal lagoon exposed to ocean and river flows, contributing to higher flood risk. This study aims to assess the flood extent for Aveiro Port for historical (1979–2005), near future (2026–2045), and far future (2081–2099) periods scenarios considering different return periods (10, 25, and 100-year) for the flood drivers, through numerical simulations of the ESL, wave regime, and riverine flows simultaneously. Spatial maps considering the flood extent and calculated area show that most of the port infrastructures’ resilience to flooding is found under the historical period, with some marginal floods. Under climate change impacts, the port flood extent gradually increases for higher return periods, where most of the terminals are at high risk of being flooded for the far-future period, whose contribution is primarily due to mean sea-level rise and storm surges.

Typhoon Hato's precipitation characteristics based on PERSIANN

Heavy precipitation induced by typhoons is the main driver of catastrophic flooding, and studying precipitation patterns is important for flood forecasting and early warning. Studying the space-time characteristics of heavy precipitation induced by typhoons requires a large range of observation data that cannot be obtained by ground-based rain gauge networks. Satellite-based estimation provides large domains of precipitation with high space-time resolution, facilitating the analysis of heavy precipitation patterns induced by typhoons. In this study, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) satellite data were used to study the temporal and spatial features of precipitation induced by Typhoon Hato, which was the strongest typhoon of 2017 to make landfall in China. The results show that rainfall on the land lasted for six days from the typhoon making landfall to disappearing, reaching the maximum when the typhoon made landfall. Hato produced extremely high accumulated rainfall in South China, almost 300 mm in Guangdong Province and Guangxi Zhuang Autonomous Region and 260 mm in Hainan Province. The rainfall process was separated into three stages and rainfall was the focus in the second stage (5 h before making landfall to 35 h after making landfall).

Key factors influencing the severity of fluvial flood hazard from tropical cyclones

AbstractKnowledge of the key drivers of the severity of river flooding from tropical cyclones (TCs) is vital for emergency preparedness and disaster risk reduction activities. This global study examines landfalling TCs in the decade from 2010 to 2019, to identify those characteristics that influence whether a storm has an increased flood hazard. The highest positive correlations are found between flood severity and the total precipitation associated with the TC. Significant negative correlations are found between flood severity and the translation speed of the TC, indicating that slower moving storms, that rain over an area for longer, tend to have higher flood severity. Larger and more intense TCs increase the likelihood of having a larger area affected by severe flooding but not its duration or magnitude, and it is found that the fluvial flood hazard can be severe in all intensity categories of TC, including those of tropical storm strength. Catchment characteristics such as antecedent soil moisture and slope also play a role in modulating flood severity, and severe flooding is more likely in cases where multiple drivers are present. The improved knowledge of the key drivers of fluvial flooding in TCs can help to inform research priorities to help with flood early warning, such as increasing the focus on translation speed in model evaluation and impact-based forecasting.

Climate Change and Changes in Compound Coastal‐Riverine Flooding Hazard Along the U.S. Coasts

AbstractThe cooccurrence of coastal and riverine flooding leads to compound events with substantial impacts on people and property in low‐lying coastal areas. Climate change could increase the level of compound flood hazard through higher extreme sea levels and river flows. Here, a bivariate flood hazard assessment method is proposed to estimate compound coastal‐riverine frequency under current and future climate conditions. A copula‐based approach is used to estimate the joint return period (JRP) of compound floods by incorporating sea‐level rise (SLR) and changes in peak river flows into the marginal distributions of flood drivers. Specifically, the changes in JRP of compound major coastal‐riverine flooding defined based on simultaneous exceedances above major coastal and riverine thresholds, are explored by midcentury. Subsequently, the increase in the probability of occurrence of at least one compound major coastal‐riverine flooding for a given period of time is quantified. The proposed compound flood hazard assessment is conducted at 26 paired tidal‐riverine stations along the Contiguous United States coast with long‐term data and defined flood thresholds. We show that the northeast Atlantic and the western part of the Gulf coasts are experiencing the highest compound major coastal‐riverine flood probability under current conditions. However, future SLR scenarios show the highest frequency amplification along the southeast Atlantic coast. The impact of changes in peak river flows is found to be considerably less than that of SLR. Climate change impacts, especially SLR, may lead to more frequent compound events, which cannot be ignored for future adaptation responses in estuary regions.

Extreme Floods in the Eastern Part of Europe: Large-Scale Drivers and Associated Impacts

The role of the large-scale atmospheric circulation in producing heavy rainfall events and floods in the eastern part of Europe, with a special focus on the Siret and Prut catchment areas (Romania), is analyzed in this study. Moreover, a detailed analysis of the socio-economic impacts of the most extreme flood events (e.g., July 2008, June–July 2010, and June 2020) is given. Analysis of the largest flood events indicates that the flood peaks have been preceded up to 6 days in advance by intrusions of high Potential Vorticity (PV) anomalies toward the southeastern part of Europe, persistent cut-off lows over the analyzed region, and increased water vapor transport over the catchment areas of Siret and Prut Rivers. The vertically integrated water vapor transport prior to the flood peak exceeds 300 kg m−1 s−1, leading to heavy rainfall events. We also show that the implementation of the Flood Management Plan in Romania had positive results during the 2020 flood event compared with the other flood events, when the authorities took several precaution measurements that mitigated in a better way the socio-economic impact and risks of the flood event. The results presented in this study offer new insights regarding the importance of large-scale atmospheric circulation and water vapor transport as drivers of extreme flooding in the eastern part of Europe and could lead to a better flood forecast and flood risk management.

Connecting Hydrometeorological Processes to Low‐Probability Floods in the Mountainous Colorado Front Range

AbstractEstimating the probabilities of rare floods in mountainous watersheds is challenging due to the hydrometeorological complexity of seasonally varying snowmelt and soil moisture dynamics, as well as spatiotemporal variability in extreme precipitation. Design storm methods and statistical flood frequency analyses often overlook these complexities and how they shape the probabilities of rare floods. This study presents a process‐based approach that combines gridded precipitation, stochastic storm transposition (SST), and physics‐based distributed rainfall‐runoff modeling to simulate flood peak and volume distributions up to the 10,000‐year recurrence interval and to provide insights into the hydrometeorological drivers of those events. The approach is applied to a small mountainous watershed in the Colorado Front Range in the United States. We show that storm transposition in the Front Range can be justified under existing definitions of regional precipitation homogeneity. The process‐based results show close agreement with a statistically based mixture distribution that considers underlying flood drivers. We further demonstrate that antecedent conditions and snowmelt drive frequent peak discharges and rarer flood volumes, while the upper tail of the flood peak distribution appears to be controlled by heavy rainfall and rain‐on‐snow. In particular, we highlight the important role of early fall extreme rainfall in controlling rare flood peaks (but not volumes), despite only one such event having been observed in recent decades. Notwithstanding issues related to the accuracy of gridded precipitation datasets, these findings highlight the potential of SST and process‐based modeling to help understand the relationships between flood drivers and flood frequencies.