scholarly journals Brief Communication: Critical Infrastructure impacts of the 2021 mid-July western European flood event

2021 ◽  
Author(s):  
Elco Koks ◽  
Kees Van Ginkel ◽  
Margreet Van Marle ◽  
Anne Lemnitzer
Keyword(s):  
The Netherlands ◽  
Flood Risk ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Critical Infrastructure ◽  
Risk Assessments ◽  
Flood Events ◽  
Infrastructure Systems ◽  
River Flood ◽  
Sewage Systems

Abstract. Germany, Belgium and The Netherlands were hit by extreme precipitation and flooding in July 2021. This Brief Communication provides an overview of the impacts to large-scale critical infrastructure systems and how recovery has progressed during the first six months after the event. The results show that Germany and Belgium were particularly affected, with many infrastructure assets severely damaged or completely destroyed. Impacts range from completely destroyed bridges and sewage systems, to severely damaged schools and hospitals. We find that large-scale risk assessments, often focused on larger (river) flood events, do not find these local, but severe, impacts. This may be the result of limited availability of validation material. As such, this study will not only help to better understand how critical infrastructure can be affected by flooding, but can also be used as validation material for future flood risk assessments.

scholarly journals Response of Extreme Precipitation to Urbanization over the Netherlands

2019 ◽  
Vol 58 (4) ◽  
pp. 645-661 ◽  
Author(s):  
Vahid Rahimpour Golroudbary ◽  
Yijian Zeng ◽  
Chris M. Mannaerts ◽  
Zhongbo Su
Keyword(s):  
The Netherlands ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Daily Precipitation ◽  
Atmospheric Air ◽  
The North ◽  
Circulation Types ◽  
Return Levels ◽  
Air Temperatures ◽  
The North Atlantic Oscillation

AbstractKnowledge of the response of extreme precipitation to urbanization is essential to ensure societal preparedness for the extreme events caused by climate change. To quantify this response, this study scales extreme precipitation according to temperature using the statistical quantile regression and binning methods for 231 rain gauges during the period of 1985–2014. The positive 3%–7% scaling rates were found at most stations. The nonstationary return levels of extreme precipitation are investigated using monthly blocks of the maximum daily precipitation, considering the dependency of precipitation on the dewpoint, atmospheric air temperatures, and the North Atlantic Oscillation (NAO) index. Consideration of Coordination of Information on the Environment (CORINE) land-cover types upwind of the stations in different directions classifies stations as urban and nonurban. The return levels for the maximum daily precipitation are greater over urban stations than those over nonurban stations especially after the spring months. This discrepancy was found by 5%–7% larger values in August for all of the classified station types. Analysis of the intensity–duration–frequency curves for urban and nonurban precipitation in August reveals that the assumption of stationarity leads to the underestimation of precipitation extremes due to the sensitivity of extreme precipitation to the nonstationary condition. The study concludes that nonstationary models should be used to estimate the return levels of extreme precipitation by considering the probable covariates such as the dewpoint and atmospheric air temperatures. In addition to the external forces, such as large-scale weather modes, circulation types, and temperature changes that drive extreme precipitation, urbanization could impact extreme precipitation in the Netherlands, particularly for short-duration events.

scholarly journals The role of spatial dependence for large-scale flood risk estimation

2020 ◽  
Vol 20 (4) ◽  
pp. 967-979 ◽  
Author(s):  
Ayse Duha Metin ◽  
Nguyen Viet Dung ◽  
Kai Schröter ◽  
Sergiy Vorogushyn ◽  
Björn Guse ◽  
...  
Keyword(s):  
Flood Risk ◽  
Spatial Dependence ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Cumulative Distribution ◽  
Risk Assessments ◽  
Return Periods ◽  
Risk Estimates ◽  
Flood Peaks ◽  
Complete Dependence

Abstract. Flood risk assessments are typically based on scenarios which assume homogeneous return periods of flood peaks throughout the catchment. This assumption is unrealistic for real flood events and may bias risk estimates for specific return periods. We investigate how three assumptions about the spatial dependence affect risk estimates: (i) spatially homogeneous scenarios (complete dependence), (ii) spatially heterogeneous scenarios (modelled dependence) and (iii) spatially heterogeneous but uncorrelated scenarios (complete independence). To this end, the model chain RFM (regional flood model) is applied to the Elbe catchment in Germany, accounting for the spatio-temporal dynamics of all flood generation processes, from the rainfall through catchment and river system processes to damage mechanisms. Different assumptions about the spatial dependence do not influence the expected annual damage (EAD); however, they bias the risk curve, i.e. the cumulative distribution function of damage. The widespread assumption of complete dependence strongly overestimates flood damage of the order of 100 % for return periods larger than approximately 200 years. On the other hand, for small and medium floods with return periods smaller than approximately 50 years, damage is underestimated. The overestimation aggravates when risk is estimated for larger areas. This study demonstrates the importance of representing the spatial dependence of flood peaks and damage for risk assessments.

Rapid Global Exposure Assessment for Extreme River Flood Risk Under Climate Change

2016 ◽  
Vol 11 (6) ◽  
pp. 1128-1136 ◽  
Author(s):  
Youngjoo Kwak ◽  
◽  
Yoichi Iwami ◽  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Data Availability ◽  
Flood Risk Assessment ◽  
Daily Data ◽  
Extreme Flood ◽  
River Flood

Globally, large-scale floods are one of the most serious disasters, considering increased frequency and intensity of heavy rainfall. This is not only a domestic problem but also an international water issue related to transboundary rivers in terms of global river flood risk assessment. The purpose of this study is to propose a rapid flood hazard model as a methodological possibility to be used on a global scale, which uses flood inundation depth and works reasonably despite low data availability. The method is designed to effectively simplify complexities involving hydrological and topographical variables in a flood risk-prone area when applied in an integrated global flood risk assessment framework. The model was used to evaluate flood hazard and exposure through pixel-based comparison in the case of extreme flood events caused by an annual maximum daily river discharge of 1/50 probability of occurrence under the condition of climate change between two periods, Present (daily data from 1980 to 2004) and Future (daily data from 2075 to 2099). As preliminary results, the maximum potential extent of inundation area and the maximum number of affected people show an upward trend in Present and Future.

scholarly journals Enhancement of large-scale flood risk assessments using building-material-based vulnerability curves for an object-based approach in urban and rural areas

2019 ◽  
Vol 19 (8) ◽  
pp. 1703-1722 ◽  
Author(s):  
Johanna Englhardt ◽  
Hans de Moel ◽  
Charles K. Huyck ◽  
Marleen C. de Ruiter ◽  
Jeroen C. J. H. Aerts ◽  
...  
Keyword(s):  
Land Use ◽  
Built Environment ◽  
Rural Areas ◽  
Flood Risk ◽  
Building Material ◽  
Large Scale ◽  
Risk Assessments ◽  
Object Based ◽  
Coarse Information ◽  
Urban And Rural Areas

Abstract. In this study, we developed an enhanced approach for large-scale flood damage and risk assessments that uses characteristics of buildings and the built environment as object-based information to represent exposure and vulnerability to flooding. Most current large-scale assessments use an aggregated land-use category to represent the exposure, treating all exposed elements the same. For large areas where previously only coarse information existed such as in Africa, more detailed exposure data are becoming available. For our approach, a direct relation between the construction type and building material of the exposed elements is used to develop vulnerability curves. We further present a method to differentiate flood risk in urban and rural areas based on characteristics of the built environment. We applied the model to Ethiopia and found that rural flood risk accounts for about 22 % of simulated damage; rural damage is generally neglected in the typical land-use-based damage models, particularly at this scale. Our approach is particularly interesting for studies in areas where there is a large variation in construction types in the building stock, such as developing countries.

scholarly journals Sensitivity of Heavy Precipitation Forecasts to Small Modifications of Large-Scale Weather Patterns for the Elbe River

2010 ◽  
Vol 11 (3) ◽  
pp. 770-780 ◽  
Author(s):  
Ingo Schlüter ◽  
Gerd Schädler
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Spatiotemporal Variability ◽  
Small Scale ◽  
Synoptic Situation ◽  
Flood Events ◽  
Weather Patterns ◽  
Extreme Precipitation Events ◽  
The Impact ◽  
Precipitation Events

Abstract Extreme flood events are caused by long-lasting and/or intensive precipitation. The detailed knowledge of the distribution, intensity, and spatiotemporal variability of precipitation is, therefore, a prerequisite for hydrological flood modeling and flood risk management. For hydrological modeling, temporal and spatial high-resolution precipitation data can be provided by meteorological models. This study deals with the question of how small changes in the synoptic situation affect the characteristics of extreme forecasts. For that purpose, two historic extreme precipitation events were hindcasted using the Consortium for Small Scale Modeling (COSMO) model of the German Weather Service (DWD) with different grid resolutions (28, 7, and 2.8 km), where the domains with finer resolutions were nested into the ones with coarser resolution. The results show that the model is capable of simulating such extreme precipitation events in a satisfactory way. To assess the impact of small changes in the synoptic situations on extreme precipitation events, the large-scale atmospheric fields were shifted to north, south, east, and west with respect to the orography by about 28 and 56 km, respectively, in one series of runs while in another series, the relative humidity and temperature were increased to modify the amount of precipitable water. Both series were performed for the Elbe flood events in August 2002 and January 2003, corresponding to two very different synoptic situations. The results show that the modeled precipitation can be quite sensitive to small changes of the synoptic situation with changes in the order of 20% for the maximum daily precipitation and that the types of synoptic situations play an important role. While van Bebber weather conditions, of Mediterranean origin, were quite sensitive to modifications, more homogeneous weather patterns were less sensitive.

Simulating catchment scale river discharges and flood events from large scale atmospheric information: Example of the Upper Rhône River (European Alps)

2021 ◽  
Author(s):  
Caroline Legrand ◽  
Benoît Hingray ◽  
Bruno Wilhelm
Keyword(s):  
Time Series ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Climate Models ◽  
Hydrological Model ◽  
European Alps ◽  
Earth System ◽  
Flood Events ◽  
Catchment Scale ◽  
Mountainous Catchments

<p>Floods are highly destructive natural hazards causing widespread impacts on socio-ecosystems. This hazard could be further amplified with the ongoing climate change, which will likely alter magnitude and frequency of floods. Estimating how flood regimes could change in the future is however not straightforward. The classical approach is to estimate future hydrological regimes from hydrological simulations forced by time series scenarii of weather variables for different future climate scenarii. The development of relevant weather scenarii for this is often critical. To be adapted to the critical space and time scales of the considered basins, weather scenarii are thus typically produced from climate models with downscaling models (either dynamic or statistical).</p><p>In this study, we aim to evaluate the capacity of such a simulation chain to reproduce floods observed in the upper Rhône River (10900 km², European Alps) over the last century. The modeling chain is made up of (i) the atmospheric reanalysis ERA-20C (1900-2010), (ii) the statistical downscaling model Analog, and (iii) the glacio-hydrological model GSM-SOCONT (Glacier and Snowmelt SOil CONTribution model; Schaefli et al., 2005). To assess the performance of this modeling chain, the simulated scenarii of mean areal precipitation and temperature are compared to the observed time series over the common period (1961-2010), whereas the discharge scenarii are compared to the reference time series (1920-2010).</p><p>In this presentation, we will discuss (i) the results obtained by the basic Analog method, namely a flood events underestimation due to an underestimation of extreme precipitation values, in particular 3-day and 5-day extreme precipitation, and (ii) the enhanced results obtained by the improved version of Analog SCAMP (Sequential Constructive Atmospheric Analogues for Multivariate weather Predictions; Raynaud et al., 2020) combined to the Schaake Shuffle method.</p><p>References:</p><p>Schaefli, B., Hingray, B., M. Niggli, M., Musy, A. (2005). A conceptual glacio-hydrological model for high mountainous catchments. Hydrology and Earth System Sciences Discussions, European Geosciences Union, 9, 95-109.</p><p>Raynaud, D., Hingray, B., Evin, G., Favre, A.-C., Chardon, J. (2020). Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogues. Hydrology and Earth System Sciences Discussions, European Geosciences Union, 24(9), 4339-4352.</p>

scholarly journals Quantifying the effect of autonomous adaptation to global river flood projections: application to future flood risk assessments

2018 ◽  
Vol 13 (1) ◽  
pp. 014006 ◽  
Author(s):  
Youhei Kinoshita ◽  
Masahiro Tanoue ◽  
Satoshi Watanabe ◽  
Yukiko Hirabayashi
Keyword(s):  
Flood Risk ◽  
Risk Assessments ◽  
Autonomous Adaptation ◽  
River Flood

scholarly journals Coupling a global hydrodynamic algorithm and a regional hydrological model for large-scale flood inundation simulations

2017 ◽  
Vol 49 (2) ◽  
pp. 438-449 ◽  
Author(s):  
Shaochun Huang ◽  
Fred F. Hattermann
Keyword(s):  
Flood Risk ◽  
Large Scale ◽  
Hydrological Model ◽  
Regional Scale ◽  
Risk Assessments ◽  
Flood Inundation ◽  
Coupled Models ◽  
Macro Scale ◽  
Extreme Flood ◽  
Routing Method

Abstract To bridge the gap between 1D and 2D hydraulic models for regional scale assessment and global river routing models, we coupled the CaMa-Flood (Catchment-based Macro-scale Floodplain) model and the regional hydrological model SWIM (Soil and Water Integrated Model) as a tool for large-scale flood risk assessments. As a proof-of-concept study, we tested the coupled models in a meso-scale catchment in Germany. The Mulde River has a catchment area of ca. 6,171 km2 and is a sub-catchment of the Elbe River. The modified CaMa-Flood model routes the sub-basin-based daily runoff generated by SWIM along the river network and estimates the river discharge as well as flood inundation areas. The results show that the CaMa-Flood hydrodynamic algorithm can reproduce the daily discharges from 1991 to 2003 well. It outperforms the Muskingum flow routing method (the default routing method in the SWIM) for the 2002 extreme flood event. The simulated flood inundation area in August 2002 is comparable with the observations along the main river. However, problems may occur in upstream areas. The results presented here show the potential of the coupled models for flood risk assessments along large rivers.

scholarly journals Response of flood events to extreme precipitation: two case studies in Taihu Basin, China

2021 ◽  
Author(s):  
Feiqing Jiang ◽  
Zengchuan Dong ◽  
Yun Luo ◽  
Moyang Liu ◽  
Tao Zhou ◽  
...  
Keyword(s):  
Flood Risk ◽  
Extreme Precipitation ◽  
Flood Control ◽  
Return Periods ◽  
Flood Events ◽  
Copula Functions ◽  
Taihu Basin ◽  
Extreme Flood ◽  
Genetic Mechanisms ◽  
Precipitation Events

Abstract Flood events are typically triggered by extreme precipitation in rain-dominant basins. In this study, to better understand the genetic mechanisms and characteristics of floods, copula functions are used to analyze the response of flood events to extreme precipitation. The coincidence probabilities of the typical extreme flood and precipitation events are calculated; different return periods of their arbitrary combinations are calculated, whereas the dangerous domains for flood control under different return periods are identified; furthermore, flood risk analysis under different extreme precipitation scenarios is performed via their conditional exceedance probabilities. The Xitiaoxi catchment (XC) and Dongtiaoxi catchment (DC) in the Zhexi Region of the Taihu Basin are selected as the study area. The results show that in four scenarios with precipitation frequencies of 80%, 90%, 93.33%, and 95%, the probabilities of the dangerous flood are 9.72%, 10.57%, 10.86%, and 11.01% in the XC, respectively, and 5.91%, 6.31%, 6.44%, and 6.51% in the DC, respectively. This study provides a practical basis and guidance for the computation of rainstorm designs, management of flood control safety, and water resource scheduling in the Taihu Basin.

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