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

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.

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Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

10.5194/nhess-2018-127 ◽

2018 ◽

Cited By ~ 3

Author(s):

Michalis I. Vousdoukas ◽

Dimitrios Bouziotas ◽

Alessio Giardino ◽

Laurens M. Bouwer ◽

Evangelos Voukouvalas ◽

...

Keyword(s):

Climate Change ◽

Risk Assessment ◽

Flood Risk ◽

Large Scale ◽

Epistemic Uncertainty ◽

Coastal Protection ◽

Flood Risk Assessment ◽

Coastal Flood ◽

Coastal Flood Risk ◽

The Impact

Abstract. An upscaling of flood risk assessment frameworks beyond regional and national scales has taken place during recent years, with a number of large-scale models emerging as tools for hotspot identification, support for international policy-making and harmonization of climate change adaptation strategies. There is, however, limited insight on the scaling effects and structural limitations of flood risk models and, therefore, the underlying uncertainty. In light of this, we examine key sources of epistemic uncertainty in the Coastal Flood Risk (CFR) modelling chain: (i) the inclusion and interaction of different hydraulic components leading to extreme sea-level (ESL); (ii) inundation modelling; (iii) the underlying uncertainty in the Digital Elevation Model (DEM); (iv) flood defence information; (v) the assumptions behind the use of depth-damage functions that express vulnerability; and (vi) different climate change projections. The impact of these uncertainties to estimated Expected Annual Damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal and in the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, as well as their absolute/relative changes. We find that uncertainty from ESL contributions, and in particular the way waves are treated, can be higher than the uncertainty of the two greenhouse gas emission projections and six climate models that are used. Of comparable importance is the quality of information on coastal protection levels and DEM information. In the absence of large-extent datasets with sufficient resolution and accuracy the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality.

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Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Natural Hazards and Earth System Science ◽

10.5194/nhess-18-2127-2018 ◽

2018 ◽

Vol 18 (8) ◽

pp. 2127-2142 ◽

Cited By ~ 19

Author(s):

Michalis I. Vousdoukas ◽

Dimitrios Bouziotas ◽

Alessio Giardino ◽

Laurens M. Bouwer ◽

Lorenzo Mentaschi ◽

...

Keyword(s):

Climate Change ◽

Risk Assessment ◽

Flood Risk ◽

Large Scale ◽

Epistemic Uncertainty ◽

Coastal Protection ◽

Flood Risk Assessment ◽

Coastal Flood ◽

Coastal Flood Risk ◽

The Impact

Abstract. An upscaling of flood risk assessment frameworks beyond regional and national scales has taken place during recent years, with a number of large-scale models emerging as tools for hotspot identification, support for international policymaking, and harmonization of climate change adaptation strategies. There is, however, limited insight into the scaling effects and structural limitations of flood risk models and, therefore, the underlying uncertainty. In light of this, we examine key sources of epistemic uncertainty in the coastal flood risk (CFR) modelling chain: (i) the inclusion and interaction of different hydraulic components leading to extreme sea level (ESL), (ii) the underlying uncertainty in the digital elevation model (DEM), (iii) flood defence information, (iv) the assumptions behind the use of depth–damage functions that express vulnerability, and (v) different climate change projections. The impact of these uncertainties on estimated expected annual damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal, and on the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, and their absolute and relative changes. We find that uncertainty from ESL contributions, and in particular the way waves are treated, can be higher than the uncertainty of the two greenhouse gas emission projections and six climate models that are used. Of comparable importance is the quality of information on coastal protection levels and DEM information. In the absence of large datasets with sufficient resolution and accuracy, the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality.

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Effectiveness of water infrastructure for river flood management – Part 1: Flood hazard assessment using hydrological models in Bangladesh

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-370-75-2015 ◽

2015 ◽

Vol 370 ◽

pp. 75-81 ◽

Cited By ~ 5

Author(s):

M. A. Gusyev ◽

Y. Kwak ◽

M. I. Khairul ◽

M. B. Arifuzzaman ◽

J. Magome ◽

...

Keyword(s):

Climate Change ◽

Risk Assessment ◽

Hazard Assessment ◽

Flood Risk ◽

Flood Hazard ◽

Climate Change Impacts ◽

Flood Management ◽

Flood Inundation ◽

Flood Risk Assessment ◽

Flood Hazard Assessment

Abstract. This study introduces a flood hazard assessment part of the global flood risk assessment (Part 2) conducted with a distributed hydrological Block-wise TOP (BTOP) model and a GIS-based Flood Inundation Depth (FID) model. In this study, the 20 km grid BTOP model was developed with globally available data on and applied for the Ganges, Brahmaputra and Meghna (GBM) river basin. The BTOP model was calibrated with observed river discharges in Bangladesh and was applied for climate change impact assessment to produce flood discharges at each BTOP cell under present and future climates. For Bangladesh, the cumulative flood inundation maps were produced using the FID model with the BTOP simulated flood discharges and allowed us to consider levee effectiveness for reduction of flood inundation. For the climate change impacts, the flood hazard increased both in flood discharge and inundation area for the 50- and 100-year floods. From these preliminary results, the proposed methodology can partly overcome the limitation of the data unavailability and produces flood~maps that can be used for the nationwide flood risk assessment, which is presented in Part 2 of this study.

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Large-scale flood risk assessment under different development strategies: the Luanhe River Basin in China

Sustainability Science ◽

10.1007/s11625-021-01034-6 ◽

2021 ◽

Author(s):

Jiaheng Zhao ◽

Huili Chen ◽

Qiuhua Liang ◽

Xilin Xia ◽

Jiren Xu ◽

...

Keyword(s):

Climate Change ◽

Risk Assessment ◽

Land Use ◽

Flood Risk ◽

Large Scale ◽

Development Strategies ◽

Flood Risk Assessment ◽

Luanhe River Basin ◽

Development Scenarios ◽

Trade Offs

AbstractIncreasing resilience to natural hazards and climate change is critical for achieving many Sustainable Development Goals (SDGs). In recent decades, China has experienced rapid economic development and became the second-largest economy in the world. This rapid economic expansion has led to large-scale changes in terrestrial (e.g., land use and land cover changes), aquatic (e.g., construction of reservoirs and artificial wetlands) and marine (e.g., land reclamation) environments across the country. Together with climate change, these changes may significantly influence flood risk and, in turn, compromise SDG achievements. The Luanhe River Basin (LRB) is one of the most afforested basins in North China and has undergone significant urbanisation and land use change since the 1950s. However, basin-wide flood risk assessment under different development scenarios has not been considered, although this is critically important to inform policy-making to manage the synergies and trade-offs between the SDGs and support long-term sustainable development. Using mainly open data, this paper introduces a new framework for systematically assessing flood risk under different social and economic development scenarios. A series of model simulations are performed to investigate the flood risk under different land use change scenarios projected to 2030 to reflect different development strategies. The results are systematically analysed and compared with the baseline simulation based on the current land use and climate conditions. Further investigations are also provided to consider the impact of climate change and the construction of dams and reservoirs. The results potentially provide important guidance to inform future development strategies to maximise the synergies and minimise the trade-offs between various SDGs in LRB.

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A Case Study of Flood Risk Evaluation Based on Emergy Theory and Cloud Model in Anyang Region, China

Water ◽

10.3390/w13040420 ◽

2021 ◽

Vol 13 (4) ◽

pp. 420

Author(s):

Zening Wu ◽

Yuhai Cui ◽

Yuan Guo

Keyword(s):

Risk Assessment ◽

Flood Risk ◽

Flood Control ◽

Flood Hazard ◽

Cloud Model ◽

Flood Disaster ◽

Assessment System ◽

Assessment Model ◽

Flood Risk Assessment ◽

Emergy Theory

With the progression of climate change, the intensity and frequency of extreme rainfall have increased in many parts of the world, while the continuous acceleration of urbanization has made cities more vulnerable to floods. In order to effectively estimate and assess the risks brought by flood disasters, this paper proposes a regional flood disaster risk assessment model combining emergy theory and the cloud model. The emergy theory can measure many kinds of hazardous factor and convert them into unified solar emergy (sej) for quantification. The cloud model can transform the uncertainty in flood risk assessment into certainty in an appropriate way, making the urban flood risk assessment more accurate and effective. In this study, the flood risk assessment model combines the advantages of the two research methods to establish a natural and social dual flood risk assessment system. Based on this, the risk assessment system of the flood hazard cloud model is established. This model was used in a flood disaster risk assessment, and the risk level was divided into five levels: very low risk, low risk, medium risk, high risk, and very high risk. Flood hazard risk results were obtained by using the entropy weight method and fuzzy transformation method. As an example for the application of this model, this paper focuses on the Anyang region which has a typical continental monsoon climate. The results show that the Anyang region has a serious flood disaster threat. Within this region, Linzhou County and Anyang County have very high levels of risk for flood disaster, while Hua County, Neihuang County, Wenfeng District and Beiguan District have high levels of risk for flood disaster. These areas are the core urban areas and the economic center of local administrative regions, with 70% of the industrial clusters being situated in these regions. Only with the coordinated development of regional flood control planning, economy, and population, and reductions in the uncertainty of existing flood control and drainage facilities can the sustainable, healthy and stable development of the region be maintained.

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Large-scale flood risk assessment using a coupled model chain

E3S Web of Conferences ◽

10.1051/e3sconf/20160711005 ◽

2016 ◽

Vol 7 ◽

pp. 11005 ◽

Cited By ~ 2

Author(s):

Bruno Merz ◽

Heiko Apel ◽

Nguyen Viet Dung ◽

Daniela Falter ◽

Yeshewatesfa Hundecha ◽

...

Keyword(s):

Risk Assessment ◽

Flood Risk ◽

Large Scale ◽

Coupled Model ◽

Flood Risk Assessment ◽

Model Chain

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

10.31223/x5tc92 ◽

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.

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