scholarly journals A flood risk curve development for inundation disaster considering spatio-temporal rainfall distribution

2015 ◽  
Vol 370 ◽  
pp. 57-62 ◽  
Author(s):  
T. Tanaka ◽  
Y. Tachikawa ◽  
K. Yorozu
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Flood Disaster ◽  
Exceedance Probability ◽  
Maximum Rainfall ◽  
Economic Changes ◽  
Risk Curve ◽  
Spatio Temporal ◽  
Annual Maximum Rainfall ◽  
Risk Curves

Abstract. To manage flood disaster with an exceeding designed level, flood risk control based on appropriate risk assessment is essential. To make an integrated economic risk assessment by flood disaster, a flood risk curve, which is a relation between flood inundation damage and its exceedance probability, plays an important role. This research purposes a method to develop a flood risk curve by utilizing a probability distribution function of annual maximum rainfall through rainfall-runoff and inundation simulations so that risk assessment can consider climate and socio-economic changes. Among a variety of uncertainties, the method proposed in this study considered spatio-temporal rainfall distributions that have high uncertainty for damage estimation. The method was applied to the Yura-gawa river basin (1882 km2) in Japan; and the annual economic benefit of an existing dam in the basin was successfully quantified by comparing flood risk curves with/without the dam.

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

Water ◽  
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.

scholarly journals How are flood risk estimates affected by the choice of return-periods?

2011 ◽  
Vol 11 (12) ◽  
pp. 3181-3195 ◽  
Author(s):  
P. J. Ward ◽  
H. de Moel ◽  
J. C. J. H. Aerts
Keyword(s):  
Flood Risk ◽  
Damage Model ◽  
Area Under The Curve ◽  
Flood Management ◽  
Exceedance Probability ◽  
Return Periods ◽  
Inundation Maps ◽  
Risk Estimates ◽  
Risk Curve ◽  
Inundation Extent

Abstract. Flood management is more and more adopting a risk based approach, whereby flood risk is the product of the probability and consequences of flooding. One of the most common approaches in flood risk assessment is to estimate the damage that would occur for floods of several exceedance probabilities (or return periods), to plot these on an exceedance probability-loss curve (risk curve) and to estimate risk as the area under the curve. However, there is little insight into how the selection of the return-periods (which ones and how many) used to calculate risk actually affects the final risk calculation. To gain such insights, we developed and validated an inundation model capable of rapidly simulating inundation extent and depth, and dynamically coupled this to an existing damage model. The method was applied to a section of the River Meuse in the southeast of the Netherlands. Firstly, we estimated risk based on a risk curve using yearly return periods from 2 to 10 000 yr (€ 34 million p.a.). We found that the overall risk is greatly affected by the number of return periods used to construct the risk curve, with over-estimations of annual risk between 33% and 100% when only three return periods are used. In addition, binary assumptions on dike failure can have a large effect (a factor two difference) on risk estimates. Also, the minimum and maximum return period considered in the curve affects the risk estimate considerably. The results suggest that more research is needed to develop relatively simple inundation models that can be used to produce large numbers of inundation maps, complementary to more complex 2-D–3-D hydrodynamic models. It also suggests that research into flood risk could benefit by paying more attention to the damage caused by relatively high probability floods.

Current and future flood risk assessment in the Danube region

2020 ◽  
Author(s):  
Kai Schröter ◽  
Michel Wortmann ◽  
Stefan Lüdtke ◽  
Ben Hayes ◽  
Martin Drews ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Climate Model ◽  
Risk Model ◽  
Future Climate ◽  
Exceedance Probability ◽  
Flood Risk Assessment ◽  
Danube Catchment ◽  
The Future ◽  
Danube Region

<p>Severe hydro-meteorological hazards have been increasing during recent decades and, as a consequence of global change, more frequent and intense events are expected in the future. Climate informed planning of adaptation actions needs both consistent and reliable information about future risks and associated uncertainties, and appropriate tools to support comprehensive risk assessment and management. <br>The Future Danube Model (FDM) is a multi-hazard and risk model suite for the Danube region which provides climate information related to perils such as heavy precipitation, heatwaves, floods and droughts under recent and future climate conditions. FDM has a modular structure with exchangeable components for climate input, hydrology, inundation, risk, adaptation and visualisation. FDM is implemented within the open-source OASIS Loss Modelling Framework, which defines a standard for estimating ground-up loss and financial damage of disaster events or event scenarios. <br>The OASIS lmf implementation of the FDM is showcased for the current and future fluvial flood risk assessment in the Danube catchment. We generate stochastic inundation event sets for current and future climate in the Danube region using the output of several EURO-CORDEX models as climate input. One event set represents 10,000 years of daily climate data for a given climate model, period and representative concentration pathway. With this input, we conduct long term continuous simulations of flood processes using a coupled semi-distributed hydrological and a 1.5D hydraulic model for fluvial floods. Flood losses to residential building are estimated using a probabilistic multi-variable vulnerability model. Effects of adaptation actions are exemplified by scenarios of private precaution. Changes in risk are illustrated with exceedance probability curves for different event sets representing current and future climate on different spatial aggregation levels which are of interest for adaptation planning.</p>

scholarly journals Using Climate Factors to Estimate Flood Economic Loss Risk

2021 ◽  
Author(s):  
Xinjia Hu ◽  
Ming Wang ◽  
Kai Liu ◽  
Daoyi Gong ◽  
Holger Kantz
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Economic Loss ◽  
Assessment Process ◽  
Hunan Province ◽  
Economic Losses ◽  
Exceedance Probability ◽  
Climate Factors ◽  
Precipitation Patterns ◽  
Cross Correlation Analysis

AbstractEstimation of economic loss is essential for stakeholders to manage flood risk. Most flooding events are closely related to extreme precipitation, which is influenced by large-scale climate factors. Considering the lagged influence of climate factors, we developed a flood-risk assessment framework and used Hunan Province in China as an example to illustrate the risk assessment process. The main patterns of precipitation—as a connection between climate factors and flood economic losses—were extracted by the empirical orthogonal function (EOF) analysis. We identified the correlative climate factors through cross-correlation analysis and established a multiple stepwise linear regression model to forecast future precipitation patterns. Risk assessment was done based on the main precipitation patterns. Because the economic dataset is limited, a Monte Carlo simulation was applied to simulate 1000-year flood loss events under each precipitation regime (rainy, dry, normal years) to obtain aggregate exceedance probability (AEP) and occurrence exceedance probability (OEP) curves. We found that precipitation has a strong influence on economic loss risk, with the highest risk in rainy years. Regional economic development imbalances are the potential reason for the varying economic loss risks in different regions of Hunan Province. As the climate indices with at least several months prediction lead time are strong indicators in predicting precipitation, the framework we developed can estimate economic loss risk several months in advance.

Flood Risk Assessment and Forecasting for the Ganges-Brahmaputra-Meghna River Basins

10.1596/28574 ◽  
2017 ◽  
Author(s):  
Satya Priya ◽  
William Young ◽  
Thomas Hopson ◽  
Ankit Avasthi
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
River Basins ◽  
Flood Risk Assessment ◽  
The Ganges
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