Event generation for probabilistic flood risk modelling: multi-site peak flow dependence model vs. weather-generator-based approach

Abstract. Flood risk assessment is an important prerequisite for risk management decisions. To estimate the risk, i.e. the probability of damage, flood damage needs to be either systematically recorded over a long period or modelled for a series of synthetically generated flood events. Since damage records are typically rare, time series of plausible, spatially coherent event precipitation or peak discharges need to be generated to drive the chain of process models. In the present study, synthetic flood events are generated by two different approaches to modelling flood risk in a meso-scale alpine study area (Vorarlberg, Austria). The first approach is based on the semi-conditional multi-variate dependence model applied to discharge series. The second approach relies on the continuous hydrological modelling of synthetic meteorological fields generated by a multi-site weather generator and using an hourly disaggregation scheme. The results of the two approaches are compared in terms of simulated spatial patterns of peak discharges and overall flood risk estimates. It could be demonstrated that both methods are valid approaches for risk assessment with specific advantages and disadvantages. Both methods are superior to the traditional assumption of a uniform return period, where risk is computed by assuming a homogeneous return period (e.g. 100-year flood) across the entire study area.

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Event generation for probabilistic flood risk modelling: multi-site peak flow dependence model vs weather generator based approach

10.5194/nhess-2019-340 ◽

2020 ◽

Author(s):

Benjamin Winter ◽

Klaus Schneeberger ◽

Sergiy Vorogushyn

Keyword(s):

Risk Assessment ◽

Return Period ◽

Flood Risk ◽

Weather Generator ◽

Process Models ◽

Flood Events ◽

Entire Study ◽

Advantages And Disadvantages ◽

Traditional Assumption ◽

Entire Study Area

Abstract. Flood risk assessment is an important prerequisite for risk management decisions. To estimate the risk, flood damages need to be either systematically recorded over long period or they need to be modelled for a series of synthetically generated flood events. Since damage records are typically rare, time series of plausible, spatially coherent event precipitation or peak discharges need to be generated to drive the chain of process models. In the present study, synthetic flood events are generated by two different approaches to model flood risk in a meso-scale alpine study area (Vorarlberg, Austria). The first approach is based on the semi-conditional multi-variate dependence model applied to discharge series. The second approach is based on the continuous hydrological modelling of synthetic meteorological fields generated by a multi-site weather generator and using an hourly disaggregation scheme. The results of the two approaches are compared in terms of simulated spatial patterns and overall flood risk estimates. It could be demonstrated that both methods are valid approaches for risk assessment with specific advantages and disadvantages. Both methods are superior to the traditional assumption of a uniform return period, where risk is computed by assuming a homogeneous return period (e.g. 100-year flood) across the entire study area.

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Estimating the Probability of Compound Floods in Estuarine Regions

10.5194/hess-2020-456 ◽

2020 ◽

Author(s):

Wenyan Wu ◽

Seth Westra ◽

Michael Leonard

Keyword(s):

Frequency Analysis ◽

Flood Risk ◽

Data Availability ◽

Flood Frequency Analysis ◽

Accurate Estimation ◽

Flood Events ◽

Advantages And Disadvantages ◽

Comparative Review ◽

Flood Probability

Abstract. The quantification of flood risk in estuarine regions relies on accurate estimation of flood probability, which is often challenging due to the rareness of flood events and their multi-causal (or compound) nature. Failure to consider the compounding nature of estuarine floods can lead to significant underestimation of flood risk in these regions. This study provides a comparative review of alternative approaches for estuarine flood estimation; namely, traditional univariate flood frequency analysis applied to both observed historical data and simulated data, and multivariate frequency analysis applied to flood events. Three specific implementations of the above approaches are evaluated on a case study – the estuarine portion of Swan River in Western Australia, highlighting the advantages and disadvantages of each approach. The theoretical understanding of the three approaches, combined with findings from the case study, enable generation of guidance on method selection for estuarine flood probability estimation, recognising issues such as data availability, complexity of the application/analysis process, location of interest within the estuarine region, computational demands and whether or not future conditions need to be assessed.

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Estimating the probability of compound floods in estuarine regions

Hydrology and Earth System Sciences ◽

10.5194/hess-25-2821-2021 ◽

2021 ◽

Vol 25 (5) ◽

pp. 2821-2841

Author(s):

Wenyan Wu ◽

Seth Westra ◽

Michael Leonard

Keyword(s):

Frequency Analysis ◽

Flood Risk ◽

Data Availability ◽

Flood Frequency Analysis ◽

Accurate Estimation ◽

Flood Events ◽

Advantages And Disadvantages ◽

Comparative Review ◽

Flood Probability

Abstract. The quantification of flood risk in estuarine regions relies on accurate estimation of flood probability, which is often challenging due to the rareness of hazardous flood events and their multi-causal (or “compound”) nature. Failure to consider the compounding nature of estuarine floods can lead to significant underestimation of flood risk in these regions. This study provides a comparative review of alternative approaches for estuarine flood estimation – namely, traditional univariate flood frequency analysis applied to both observed historical data and simulated data, as well as multivariate frequency analysis applied to flood events. Three specific implementations of the above approaches are evaluated on a case study – the estuarine portion of Swan River in Western Australia – highlighting the advantages and disadvantages of each approach. The theoretical understanding of the three approaches, combined with findings from the case study, enable the generation of guidance on method selection for estuarine flood probability estimation, recognizing issues such as data availability, the complexity of the application/analysis process, the location of interest within the estuarine region, the computational demands, and whether or not future conditions need to be assessed.

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Risk Assessment of Urban Floods Based on a SWMM-MIKE21-Coupled Model Using GF-2 Data

Remote Sensing ◽

10.3390/rs13214381 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4381

Author(s):

Lidong Zhao ◽

Ting Zhang ◽

Jun Fu ◽

Jianzhu Li ◽

Zhengxiong Cao ◽

...

Keyword(s):

Risk Assessment ◽

Return Period ◽

Flood Risk ◽

Global Climate ◽

Total Loss ◽

Return Periods ◽

Rapid Urbanization ◽

Urban Floods ◽

Urban Flood ◽

Inundation Depth

Global climate change and rapid urbanization have caused increases in urban floods. Urban flood risk assessment is a vital method for preventing and controlling such disasters. This paper takes the central region of Cangzhou city in Hebei Province as an example. Detailed topographical information, such as the buildings and roads in the study area, was extracted from GF-2 data. By coupling the two models, the SWMM and MIKE21, the spatial distribution of the inundation region, and the water depth in the study area under different return periods, were simulated in detail. The results showed that, for the different return periods, the inundation region was generally consistent. However, there was a large increase in the mean inundation depth within a 10-to-30-year return period, and the increase in the maximum inundation depth and inundation area remained steady. The comprehensive runoff coefficient in all of the scenarios exceeded 0.8, indicating that the drainage system in the study area is insufficient and has a higher flood risk. The flood risk of the study area was evaluated based on the damage curve, which was obtained from field investigations. The results demonstrate that the loss per unit area was less than CNY 250/m2 in each return period in the majority of the damaged areas. Additionally, the total loss was mainly influenced by the damaged area, but, in commercial areas, the total loss was highly sensitive to the inundation depth.

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Flood Risk Assessment of Communities to Flood Hazards in Central Niger Delta, Nigeria

Earth & Environmental Science Research & Reviews ◽

10.33140/eesrr.04.01.10 ◽

2021 ◽

Vol 4 (1) ◽

Keyword(s):

Risk Assessment ◽

Flood Risk ◽

Disaster Preparedness ◽

Niger Delta ◽

Sampling Technique ◽

Flood Hazards ◽

River Channels ◽

Social Infrastructure ◽

Entire Study ◽

Flood Exposure

The study examined the risk assessment of communities in the Central Niger Delta, Nigeria with a view to employing analytical hierarchical ranking process technique. The study considered the landuse, elevation, soil texture and proximity to active river channels as factors determining flood vulnerability (FV) while factors such as accessibility, social infrastructure, water supply, agriculture, commercial activities and disaster preparedness of communities were used for flood exposure (FE) using purposive sampling technique. Both FV and FE were combined together using UNION Module of ArcGIS 10.5 to produce flood risk map of the Central Niger Delta. Descriptive statistics using frequency and percentages were used for the data analysis. Findings revealed that 20.25%, 51.66% and 28.09% of the entire study area were lowly vulnerable, moderately vulnerable and highly vulnerable to flood. Similarly, 0.3%, 45.7% and 54.8% were lowly exposed, moderately exposed and highly exposed to flood. However, 14.3%, 28.3% and 57.4% of the study area had low flood risk, moderate flood risk and high flood risk respectively. The study concluded that majority of the area in the Central Niger Delta is risky to flood. It is recommended among others that channelization and dredging of River Niger Creeks in the study area are important in order for the river to accommodate more volume of water whenever there is excessive rainfall.

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Climate Change, Flood Risk Prediction and Acute Gastrointestinal Infection in the Republic of Ireland, 2008-2017

10.5194/egusphere-egu2020-10162 ◽

2020 ◽

Author(s):

Martin Boudou ◽

Eimear Cleary ◽

Paul Hynds ◽

Jean O'Dwyer ◽

Patricia Garvey ◽

...

Keyword(s):

Climate Change ◽

Risk Assessment ◽

Return Period ◽

Flood Risk ◽

Geographical Information ◽

Risk Exposure ◽

Flood Risk Assessment ◽

Republic Of Ireland ◽

Risk Probability ◽

The Republic

Environmentally associated infectious diseases, including those driven by extreme weather events, represent a critical challenge for public health as their source and transmission are frequently sporadic and associated mechanisms often not well understood. Over the past decade, the Republic of Ireland (ROI) has persistently reported the highest incidence of confirmed verotoxigenic E. coli (VTEC) and cryptosporidiosis infection in the European Union. Moreover, recent climate projections indicate that the incidence, severity and timing of extreme rainfall events and flooding will increase dramatically over the next century, with Ireland forecast to be the second most affected European country with respect to the mean proportion of the population residing in flood-prone areas by 2100. This study aimed to assess the association(s) between potential flood risk exposure and the spatial occurrence of confirmed VTEC and cryptosporidiosis infection in Ireland over a 10-year period (2008-2017).In 2012, the Irish Office of Public Works (OPW) initiated the National Catchment Flood Risk Assessment and Management (CFRAM) Programme within the framework of the Flood Directive (2007/60/CE), with high-resolution flood maps produced for coastal and fluvial risks and three risk scenarios based on calculated return periods (low, medium and high probability). Small area identifiers (national census area centroids) were used to attach anonymised spatially referenced case data to CFRAM polygons using Geographical Information Systems (GIS) to produce an anonymised dataframe of confirmed infection events linked to geographically explicit flood risk attributes. Generalised linear modelling with binary link functions (infection presence/absence) were used to calculate probabilistic odds ratios (OR) between flood risk (presence/absence and scenarios) and confirmed human infection.Preliminary results indicate a clear relationship between both infections and hydrological risk. Over one third of all infection cases were reported within areas exposed to flood risk (VTEC 948/2755 cases; cryptosporidiosis 1548/4509 cases). Census areas categorised by a high (10-year Return Period) fluvial flood risk probability exhibited significantly higher incidence rates for both VTEC (OR: 1.83, P = 0.0003) and cryptosporidiosis (OR: 1.80, P = 0.0015). Similarly, areas characterised by low (1000-year Return Period) coastal flood risk probability were over twice as likely to report &#8805;1 confirmed case of cryptosporidiosis during the study period (OR: 2.2, P= 0.003). Space-time scan statistics (temporally-specific spatial autocorrelation) indicate an unseasonal peak of cryptosporidiosis cases occurring during April 2016, a majority of which took place within or adjacent to high flood risk areas (56% of total cases), revealing a potential relationship with the exceptional flooding events experienced during winter 2015-2016 (November-January). Further work will seek to identify the individual/combined flood risk (CFRAM) elements most significantly associated with the incidence of infections.Flood risk assessment mapping may represent an innovative approach to assessing the human health impacts of flood risk exposure and climate change. The outcomes of this study will contribute to predictive modelling of VTEC and cryptosporidiosis in Ireland, thus aiding surveillance and control of these diseases in the future, and the causative nature of regional hydrology and climate. &#160;&#160;

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Flood Hazard, Vulnerability and Risk Assessment for Different Land Use Classes Using a Flow Model

Earth Systems and Environment ◽

10.1007/s41748-019-00141-w ◽

2019 ◽

Vol 4 (1) ◽

pp. 225-244 ◽

Cited By ~ 5

Author(s):

Md Abdullah Al Baky ◽

Muktarun Islam ◽

Supria Paul

Keyword(s):

Risk Assessment ◽

Critical Point ◽

Return Period ◽

Flood Risk ◽

Flood Hazard ◽

Flow Simulation ◽

Flood Risk Assessment ◽

Damage Functions ◽

Flood Vulnerability ◽

Different Levels

AbstractThis study is concerned with flood risk that can be assessed by integrating GIS, hydraulic modelling and required field information. A critical point in flood risk assessment is that while flood hazard is the same for a given area in terms of intensity, the risk could be different depending on a set of conditions (flood vulnerability). Clearly, risk is a function of hazard and vulnerability. This study aims to introducing a new approach of assessing flood risk, which successfully addresses this above-mentioned critical issue. The flood risk was assessed from flood hazard and vulnerability indices. Two-dimensional flood flow simulation was performed with Delft3D model to compute floodplain inundation depths for hazard assessment. For the purpose of flood vulnerability assessment, elements at risk and flood damage functions were identified and assessed, respectively. Then, finally flood risk was assessed first by combining replacement values assessed for the elements and then using the depth–damage function. Applying this approach, the study finds that areas with different levels of flood risk do not always increase with the increase in return period of flood. However, inundated areas with different levels of flood depth always increase with the increase in return period of flood. The approach for flood risk assessment adopted in this study successfully addresses the critical point in flood risk study, where flood risk can be varied even after there is no change in flood hazard intensity.

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A Bayesian Network-Based Integrated for Flood Risk Assessment (InFRA)

Sustainability ◽

10.3390/su11133733 ◽

2019 ◽

Vol 11 (13) ◽

pp. 3733 ◽

Cited By ~ 4

Author(s):

Hongjun Joo ◽

Changhyun Choi ◽

Jungwook Kim ◽

Deokhwan Kim ◽

Soojun Kim ◽

...

Keyword(s):

Risk Assessment ◽

Bayesian Network ◽

Disaster Management ◽

Flood Risk ◽

Principal Component ◽

Assessment Method ◽

Flood Damage ◽

Flood Risk Assessment ◽

Operating Characteristics ◽

Analytic Hierarchy

Floods are natural disasters that should be considered a top priority in disaster management, and various methods have been developed to evaluate the risks. However, each method has different results and may confuse decision-makers in disaster management. In this study, a flood risk assessment method is proposed to integrate various methods to overcome these problems. Using factor analysis and principal component analysis (PCA), the leading indicators that affect flood damage were selected and weighted using three methods: the analytic hierarchy process (AHP), constant sum scale (CSS), and entropy. However, each method has flaws due to inconsistent weights. Therefore, a Bayesian network was used to present the integrated weights that reflect the characteristics of each method. Moreover, a relationship is proposed between the elements and the indicators based on the weights called the Integrated Index for Flood Risk Assessment (InFRA). InFRA and other assessment methods were compared by receiver operating characteristics (ROC)-area under curve (AUC) analysis. As a result, InFRA showed better applicability since InFRA was 0.67 and other methods were less than 0.5.

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