Ignoring spatial dependence misestimates flood risk at the European scale

2020 ◽  
Author(s):  
Viet Dung Nguyen ◽  
Ayse Duha Metin ◽  
Lorenzo Alfieri ◽  
Sergiy Vorogushyn ◽  
Bruno Merz
Keyword(s):  
Return Period ◽  
Flood Risk ◽  
Spatial Dependence ◽  
Large Scale ◽  
Spatial Scales ◽  
Tail Dependence ◽  
Flood Protection ◽  
Economic Losses ◽  
Dependence Structure ◽  
Spatial Homogeneity

<p>Flooding is a major problem worldwide causing many fatalities and economic losses. The quantification of flood risk can be difficult for large spatial scales due to its spatial variability. The traditional risk assessment approaches assuming unrealistic spatial homogeneity of flood return period for the entire catchment are often used and hence in many cases lead to misleading results especially for large-scale applications. In this study, we aim at investigating the influences of spatial dependence in flood risk estimation over national and continental scales by comparing the assessments under three spatial dependence assumptions: modelled dependence (MD), complete dependence (CD) and complete independence (CI) of flow return periods. In order to achieve the aim, we develop a copula-based model representing the dependence structure of annual maximum stream flow (AMS) at 507 stations (with basin area > 500km2) across Europe and use it to generate long-term (10000 years) spatially coherent AMS at these locations. The generated series at multiple sites are then used for estimating associated flood loss considering two levels (with and without) of flood protection. The flood risk is estimated and aggregated for the representative 3 regions (England, Germany and Europe) and for the three dependence assumptions considering also the role of tail dependence of the used copulas. The results highlight that ignoring spatial dependence misestimates flood risk. The deviation from the modelled risk (under-/over-estimation) depends differently on the assumptions of spatial dependence, tail dependence, flood protection level and spatial scales. For example, under CD assumption for 200-year return period and considering flood protection, approximately 2.5-, 3- and 3.5-fold overestimation of flood risk in England, Germany and Europe, respectively, is found.</p>

scholarly journals Unraveling Long-Term Flood Risk Dynamics Across the Murray-Darling Basin Using a Large-Scale Hydraulic Model and Satellite Data

2022 ◽  
Vol 3 ◽  
Author(s):  
Serena Ceola ◽  
Alessio Domeneghetti ◽  
Guy J. P. Schumann
Keyword(s):  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Spatial Scales ◽  
Mitigation Strategies ◽  
Economic Losses ◽  
Human Society ◽  
Murray Darling Basin ◽  
Flooded Areas

River floods are one of the most devastating extreme hydrological events, with oftentimes remarkably negative effects for human society and the environment. Economic losses and social consequences, in terms of affected people and human fatalities, are increasing worldwide due to climate change and urbanization processes. Long-term dynamics of flood risk are intimately driven by the temporal evolution of hazard, exposure and vulnerability. Although needed for effective flood risk management, a comprehensive long-term analysis of all these components is not straightforward, mostly due to a lack of hydrological data, exposure information, and large computational resources required for 2-D flood model simulations at adequately high resolution over large spatial scales. This study tries to overcome these limitations and attempts to investigate the dynamics of different flood risk components in the Murray-Darling basin (MDB, Australia) in the period 1973–2014. To this aim, the LISFLOOD-FP model, i.e., a large-scale 2-D hydrodynamic model, and satellite-derived built-up data are employed. Results show that the maximum extension of flooded areas decreases in time, without revealing any significant geographical transfer of inundated areas across the study period. Despite this, a remarkable increment of built-up areas characterizes MDB, with larger annual increments across not-flooded locations compared to flooded areas. When combining flood hazard and exposure, we find that the overall extension of areas exposed to high flood risk more than doubled within the study period, thus highlighting the need for improving flood risk awareness and flood mitigation strategies in the near future.

scholarly journals Flood Risk Assessment and Quantification at the Community and Property Level in the State of Iowa

2021 ◽  
Author(s):  
Enes Yildirim ◽  
Ibrahim Demir
Keyword(s):  
Risk Assessment ◽  
High Resolution ◽  
Flood Risk ◽  
Large Scale ◽  
Spatial Scales ◽  
The United States ◽  
Flood Risk Assessment ◽  
Study Region ◽  
Study Results ◽  
Flood Maps

Flood risk assessment contributes to identifying at-risk communities and supports mitigation decisions to maximize benefits from the investments. Large-scale risk assessments generate invaluable inputs for prioritizing regions for the distribution of limited resources. High-resolution flood maps and accurate parcel information are critical for flood risk analysis to generate reliable outcomes for planning, preparedness, and decision-making applications. Large-scale damage assessment studies in the United States often utilize the National Structure Inventory (NSI) or HAZUS default dataset, which results in inaccurate risk estimates due to the low geospatial accuracy of these datasets. On the other hand, some studies utilize higher resolution datasets, however they are limited to focus on small scales, for example, a city or a Hydrological United Code (HUC)-12 watershed. In this study, we collected extensive detailed flood maps and parcel datasets for many communities in Iowa to carry out a large-scale flood risk assessment. High-resolution flood maps and the most recent parcel information are collected to ensure the accuracy of risk products. The results indicate that the Eastern Iowa communities are prone to a higher risk of direct flood losses. Our model estimates nearly $10 million in average annualized losses, particularly in large communities in the study region. The study highlights that existing risk products based on FEMA's flood risk output underestimate the flood loss, specifically in highly populated urban communities such as Bettendorf, Cedar Falls, Davenport, Dubuque, and Waterloo. Additionally, we propose a flood risk score methodology for two spatial scales (e.g., HUC-12 watershed, property) to prioritize regions and properties for mitigation purposes. Lastly, the watershed-scale study results are shared through a web-based platform to inform the decision-makers and the public.

scholarly journals Global streamflow and flood response to stratospheric aerosol geoengineering

2018 ◽  
Author(s):  
Liren Wei ◽  
Duoying Ji ◽  
Chiyuan Miao ◽  
John C. Moore
Keyword(s):  
Return Period ◽  
Flood Risk ◽  
Large Scale ◽  
Hydrological Cycle ◽  
Stratospheric Aerosol ◽  
Model Intercomparison ◽  
Geographic Pattern ◽  
Solar Geoengineering ◽  
Intercomparison Project ◽  
Future Warming

Abstract. Flood risk is projected to increase under projections of future warming climates due to an enhanced hydrological cycle. Solar geoengineering is known to reduce precipitation and slowdown the hydrological cycle, and may be therefore be expected to offset increased flood risk. We examine this hypothesis using streamflow and river discharge responses to the representative concentration pathway RCP4.5 and Geoengineering Model Intercomparison Project (GeoMIP) G4 experiments. We also calculate changes in 30, 50, 100-year flood return periods relative to the historical (1960–1999) period under the RCP4.5 and G4 scenarios. Similar spatial patterns are produced for each return period, although those under G4 are closer to historical values than under RCP4.5. Under G4 generally lower streamflows are produced on the western sides of Eurasia and North America, with higher flows on their eastern sides. In the southern hemisphere northern parts of the land masses have lower streamflow under G4, and southern parts increases relative to RCP4.5. So in general solar geoengineering does appear to reduce flood risk in most regions, but the relative effects are largely determined by this large scale geographic pattern. Both streamflow and return period show increased drying of the Amazon under both RCP4.5 and G4 scenarios, with more drying under G4.

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.

scholarly journals Global flood hazard map and exposed GDP comparison: a China case study

2020 ◽  
Author(s):  
Jerom P. M. Aerts ◽  
Steffi Uhlemann-Elmer ◽  
Dirk Eilander ◽  
Philip J. Ward
Keyword(s):  
Return Period ◽  
Flood Hazard ◽  
Regional Scale ◽  
Flood Protection ◽  
Economic Losses ◽  
Return Periods ◽  
Hazard Maps ◽  
High Exposure ◽  
Pluvial Flooding

Abstract. Floods are among the most frequent and damaging natural hazard events in the world. In 2016, economic losses from flooding amounted to $56 bn globally, of which $20 bn occurred in China (Munich Re, 2017). National or regional scale mapping of flood hazard is at present providing an inconsistent and incomplete picture of floods. Over the past decade global flood hazard models have been developed and continuously improved. There is now a significant demand for testing of the global hazard maps generated by these models in order to understand their applicability for international risk reduction strategies and for reinsurance portfolio risk assessments using catastrophe models. We expand on existing methods for comparing global hazard maps and analyse 8 global flood models (GFMs) that represent the current state of the global flood modelling community. We apply our comparison to China as a case study and, for the first time, we include industry models, pluvial flooding, and flood protection standards in the analysis. We find substantial variability between the flood hazard maps in modelled inundated area and exposed GDP across multiple return periods (ranging from 5 to 1500 years) and in expected annual exposed GDP. For example, for the 100 year return period undefended (assuming no flood protection) hazard maps the percentage of total affected GDP of China ranges between 4.4 % and 10.5 % for fluvial floods. For the majority of the GFMs we see only a small increase in inundated area or exposed GDP for high return period undefended hazard maps compared to low return periods, highlighting major limitations in the models’ resolution and their output. The inclusion of industry models which currently model flooding at higher spatial resolution, and which additionally include pluvial flooding, strongly improves the comparison and provides important new benchmarks. Pluvial flooding can increase the expected annual exposed GDP by as much as 1.3 % points. Our study strongly highlights the importance of flood defenses for a realistic risk assessment in countries like China that are characterized by high concentrations of exposure. Even an incomplete (1.74 % of area of China) but locally detailed layer of structural defenses in high exposure areas reduces the expected annual exposed GDP to fluvial and pluvial flooding from 4.1 % to 2.8 %.

scholarly journals Global streamflow and flood response to stratospheric aerosol geoengineering

2018 ◽  
Vol 18 (21) ◽  
pp. 16033-16050 ◽  
Author(s):  
Liren Wei ◽  
Duoying Ji ◽  
Chiyuan Miao ◽  
Helene Muri ◽  
John C. Moore
Keyword(s):  
Return Period ◽  
Flood Risk ◽  
Large Scale ◽  
Hydrological Cycle ◽  
Stratospheric Aerosol ◽  
Model Intercomparison ◽  
Geographic Pattern ◽  
Solar Geoengineering ◽  
Intercomparison Project ◽  
Future Warming

Abstract. Flood risk is projected to increase under future warming climates due to an enhanced hydrological cycle. Solar geoengineering is known to reduce precipitation and slow down the hydrological cycle and may therefore be expected to offset increased flood risk. We examine this hypothesis using streamflow and river discharge responses to Representative Concentration Pathway 4.5 (RCP4.5) and the Geoengineering Model Intercomparison Project (GeoMIP) G4 scenarios. Compared with RCP4.5, streamflow on the western sides of Eurasia and North America is increased under G4, while the eastern sides see a decrease. In the Southern Hemisphere, the northern parts of landmasses have lower streamflow under G4, and streamflow of southern parts increases relative to RCP4.5. We furthermore calculate changes in 30-, 50-, and 100-year flood return periods relative to the historical (1960–1999) period under the RCP4.5 and G4 scenarios. Similar spatial patterns are produced for each return period, although those under G4 are closer to historical values than under RCP4.5. Hence, in general, solar geoengineering does appear to reduce flood risk in most regions, but the overall effects are largely determined by this large-scale geographic pattern. Although G4 stratospheric aerosol geoengineering ameliorates the Amazon drying under RCP4.5, with a weak increase in soil moisture, the decreased runoff and streamflow leads to an increased flood return period under G4 compared with RCP4.5.

scholarly journals Projected Seasonal Changes in Large-Scale Global Precipitation and Temperature Extremes Based on the CMIP5 Ensemble

2020 ◽  
Vol 33 (13) ◽  
pp. 5651-5671 ◽  
Author(s):  
Wang Zhan ◽  
Xiaogang He ◽  
Justin Sheffield ◽  
Eric F. Wood
Keyword(s):  
Extreme Events ◽  
Large Scale ◽  
Climate Models ◽  
Spatial Scales ◽  
Extreme Temperature ◽  
Economic Losses ◽  
Temperature And Precipitation ◽  
Extreme Precipitation Events ◽  
The Future ◽  
Precipitation Events

AbstractOver the past decades, significant changes in temperature and precipitation have been observed, including changes in the mean and extremes. It is critical to understand the trends in hydroclimatic extremes and how they may change in the future as they pose substantial threats to society through impacts on agricultural production, economic losses, and human casualties. In this study, we analyzed projected changes in the characteristics, including frequency, seasonal timing, and maximum spatial and temporal extent, as well as severity, of extreme temperature and precipitation events, using the severity–area–duration (SAD) method and based on a suite of 37 climate models archived in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Comparison between the CMIP5 model estimated extreme events and an observation-based dataset [Princeton Global Forcing (PGF)] indicates that climate models have moderate success in reproducing historical statistics of extreme events. Results from the twenty-first-century projections suggest that, on top of the rapid warming indicated by a significant increase in mean temperature, there is an overall wetting trend in the Northern Hemisphere with increasing wet extremes and decreasing dry extremes, whereas the Southern Hemisphere will have more intense wet extremes. The timing of extreme precipitation events will change at different spatial scales, with the largest change occurring in southern Asia. The probability of concurrent dry/hot and wet/hot extremes is projected to increase under both RCP4.5 and RCP8.5 scenarios, whereas little change is detected in the probability of concurrent dry/cold events and only a slight decrease of the joint probability of wet/cold extremes is expected in the future.

scholarly journals Emergency Disposal Solution for Control of a Giant Landslide and Dammed Lake in Yangtze River, China

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1939 ◽  
Author(s):  
Guiya Chen ◽  
Xiaofeng Zhao ◽  
Yanlai Zhou ◽  
Shenglian Guo ◽  
Chong-Yu Xu ◽  
...  
Keyword(s):  
Return Period ◽  
Flood Risk ◽  
Large Scale ◽  
Water Volume ◽  
Small Scale ◽  
General Strategy ◽  
Engineering Measures ◽  
Landslide Early Warning ◽  
Dammed Lake ◽  
Giant Landslide

Although landslide early warning and post-assessment is of great interest for mitigating hazards, emergency disposal solutions for properly handling the landslide and dammed lake within a few hours or days to mitigate flood risk are fundamentally challenging. In this study, we report a general strategy to effectively tackle the dangerous situation created by a giant dammed lake with 770 million cubic meters of water volume and formulate an emergency disposal solution for the 25 million cubic meters of debris, composed of engineering measures of floodgate excavation and non-engineering measures of reservoirs/hydropower stations operation. Such a disposal solution can not only reduce a large-scale flood (10,000-year return period, 0.01%) into a small-scale flood (10-year return period, 10%) but minimize the flood risk as well, guaranteeing no death raised by the giant landslide.

scholarly journals FLOPROS: an evolving global database of flood protection standards

2016 ◽  
Vol 16 (5) ◽  
pp. 1049-1061 ◽  
Author(s):  
Paolo Scussolini ◽  
Jeroen C. J. H. Aerts ◽  
Brenden Jongman ◽  
Laurens M. Bouwer ◽  
Hessel C. Winsemius ◽  
...  
Keyword(s):  
Flood Risk ◽  
Spatial Scales ◽  
Climate Change Policy ◽  
Flood Protection ◽  
Current Standard ◽  
Protection Measures ◽  
Global Database ◽  
Spatial Coverage ◽  
Projected Changes ◽  
Model Layer

Abstract. With projected changes in climate, population and socioeconomic activity located in flood-prone areas, the global assessment of flood risk is essential to inform climate change policy and disaster risk management. Whilst global flood risk models exist for this purpose, the accuracy of their results is greatly limited by the lack of information on the current standard of protection to floods, with studies either neglecting this aspect or resorting to crude assumptions. Here we present a first global database of FLOod PROtection Standards, FLOPROS, which comprises information in the form of the flood return period associated with protection measures, at different spatial scales. FLOPROS comprises three layers of information, and combines them into one consistent database. The design layer contains empirical information about the actual standard of existing protection already in place; the policy layer contains information on protection standards from policy regulations; and the model layer uses a validated modelling approach to calculate protection standards. The policy layer and the model layer can be considered adequate proxies for actual protection standards included in the design layer, and serve to increase the spatial coverage of the database. Based on this first version of FLOPROS, we suggest a number of strategies to further extend and increase the resolution of the database. Moreover, as the database is intended to be continually updated, while flood protection standards are changing with new interventions, FLOPROS requires input from the flood risk community. We therefore invite researchers and practitioners to contribute information to this evolving database by corresponding to the authors.

scholarly journals FLOPROS: an evolving global database of flood protection standards

2015 ◽  
Vol 3 (12) ◽  
pp. 7275-7309 ◽  
Author(s):  
P. Scussolini ◽  
J. C. J. H. Aerts ◽  
B. Jongman ◽  
L. M. Bouwer ◽  
H. C. Winsemius ◽  
...  
Keyword(s):  
Flood Risk ◽  
Spatial Scales ◽  
Climate Change Policy ◽  
Flood Protection ◽  
Current Standard ◽  
Protection Measures ◽  
Global Database ◽  
Spatial Coverage ◽  
Projected Changes ◽  
Model Layer

Abstract. With the projected changes in climate, population and socioeconomic activity located in flood-prone areas, the global assessment of the flood risk is essential to inform climate change policy and disaster risk management. Whilst global flood risk models exist for this purpose, the accuracy of their results is greatly limited by the lack of information on the current standard of protection to floods, with studies either neglecting this aspect or resorting to crude assumptions. Here we present a first global database of FLOod PROtection Standards, FLOPROS, which comprises information in the form of the flood return period associated with protection measures, at different spatial scales. FLOPROS comprises three layers of information, and combines them into one consistent database. The Design layer contains empirical information about the actual standard of existing protection already in place, while the Policy layer and the Model layer are proxies for such protection standards, and serve to increase the spatial coverage of the database. The Policy layer contains information on protection standards from policy regulations; and the Model layer uses a validated modeling approach to calculate protection standards. Based on this first version of FLOPROS, we suggest a number of strategies to further extend and increase the resolution of the database. Moreover, as the database is intended to be continually updated, while flood protection standards are changing with new interventions, FLOPROS requires input from the flood risk community. We therefore invite researchers and practitioners to contribute information to this evolving database by corresponding to the authors.

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