scholarly journals IMPROVED COASTAL FLOOD RISK ESTIMATES THROUGH INTEGRATED JPM AND COUPLED PHYSICS APPROACH

2020 ◽  
pp. 21
Author(s):  
Jeffrey Melby ◽  
Abigail Stehno ◽  
Thomas C. Massey ◽  
Shubhra Misra ◽  
Norberto Nadal-Caraballo ◽  
...  
Keyword(s):  
Hurricane Katrina ◽  
Flood Risk ◽  
Large Scale ◽  
Epistemic Uncertainty ◽  
Joint Probability ◽  
Probability Method ◽  
Probability Models ◽  
Hydrodynamic Models ◽  
Construction Engineering ◽  
Super Computer

Large scale flood risk computation has enjoyed a metamorphosis since Hurricane Katrina. Improved characterization of risk is the result of improved computational capabilities due to super computer capacity combined with coupled regional hydrodynamic models, improved local hydrodynamic models, improved joint probability models, inclusion of the most important uncertainties, metamodels and increased computational capacity for stochastic simulation. Improvements in our understanding of, and the ability to model, the coupled hydrodynamics of surge and waves has been well documented as has been improvements in the joint probability method with optimal sampling (JPM-OS) for synthesizing synthetic tropical cyclones (TC) that correctly span the practical hazard probability space. However, maintaining the coupled physics and multivariate probability integrity through the entire flood risk computation while incorporating epistemic uncertainty has had relatively little attention. This paper addresses this latter topic within the context of the Sabine Pass to Galveston Bay, TX Pre-Construction, Engineering and Design, Hurricane Coastal Storm Surge and Wave Hazard Assessment.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/qYFTO6l7UME

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

2018 ◽  
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.

Development and application of efficient methods for the forward propagation of epistemic uncertainty and sensitivity analysis within complex broad-scale flood risk system modelsThis article is one of a selection of papers published in this Special Issue on Hydrotechnical Engineering.

2010 ◽  
Vol 37 (7) ◽  
pp. 955-967 ◽  
Author(s):  
B. P. Gouldby ◽  
P. B. Sayers ◽  
M. C. Panzeri ◽  
J. E. Lanyon
Keyword(s):  
Sensitivity Analysis ◽  
Flood Risk ◽  
Large Scale ◽  
Epistemic Uncertainty ◽  
Data Gathering ◽  
Future Research ◽  
Special Issue ◽  
Flood Probability ◽  
Output Quantity ◽  
Selection Of

Increasingly, an understanding of flood risk across regions and nations, and an ability to explore how these might change in time, is seen as a prerequisite to effective and efficient flood risk management. In response, specific flood risk analysis methods have been developed that are both accurate and fast to run. Although widely acknowledged as desirable, it has not previously been possible to quantify the uncertainty associated with the assessed flood probability, consequence, or risk. To help overcome this deficiency, an efficient method for the propagation of epistemic uncertainties through large-scale flood risk system models has been developed and trialed for three pilot catchments. The approach is allied to an efficient sensitivity analysis that enables the influence of individual uncertainties on the output quantity of risk to be isolated, enabling future research, development, and data-gathering efforts to be focused.

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

2018 ◽  
Vol 18 (8) ◽  
pp. 2127-2142 ◽  
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.

scholarly journals Risk to life due to flooding in post-Katrina New Orleans

2015 ◽  
Vol 15 (1) ◽  
pp. 59-73 ◽  
Author(s):  
A. Miller ◽  
S. N. Jonkman ◽  
M. Van Ledden
Keyword(s):  
Hurricane Katrina ◽  
New Orleans ◽  
Flood Risk ◽  
Large Scale ◽  
Central Area ◽  
Protection System ◽  
Risk Level ◽  
Individual Risk ◽  
Loss Of Life ◽  
The Individual

Abstract. Since the catastrophic flooding of New Orleans due to Hurricane Katrina in 2005, the city's hurricane protection system has been improved to provide protection against a hurricane load with a 1/100 per year exceedance frequency. This paper investigates the risk to life in post-Katrina New Orleans. In a flood risk analysis the probabilities and consequences of various flood scenarios have been analyzed for the central area of the city (the metro bowl) to give a preliminary estimate of the risk to life in the post-Katrina situation. A two-dimensional hydrodynamic model has been used to simulate flood characteristics of various breaches. The model for estimation of fatality rates is based on the loss of life data for Hurricane Katrina. Results indicate that – depending on the flood scenario – the estimated loss of life in case of flooding ranges from about 100 to nearly 500, with the highest life loss due to breaching of the river levees leading to large flood depths. The probability and consequence estimates are combined to determine the individual risk and societal risk for New Orleans. When compared to risks of other large-scale engineering systems (e.g., other flood prone areas, dams and the nuclear sector) and acceptable risk criteria found in literature, the risks for the metro bowl are found to be relatively high. Thus, despite major improvements to the flood protection system, the flood risk to life of post-Katrina New Orleans is still expected to be significant. Indicative effects of reduction strategies on the risk level are discussed as a basis for further evaluation and discussion.

Hospitalization Rates Among Dialysis Patients During Hurricane Katrina

2012 ◽  
Vol 27 (4) ◽  
pp. 325-329 ◽  
Author(s):  
David Howard ◽  
Rebecca Zhang ◽  
Yijian Huang ◽  
Nancy Kutner
Keyword(s):  
Hurricane Katrina ◽  
Large Scale ◽  
Service Use ◽  
Hospital Admissions ◽  
Gulf Coast ◽  
The United States ◽  
Time Varying ◽  
Dialysis Patients ◽  
Hospitalization Rates ◽  
The Impact

AbstractIntroductionDialysis centers struggled to maintain continuity of care for dialysis patients during and immediately following Hurricane Katrina's landfall on the US Gulf Coast in August 2005. However, the impact on patient health and service use is unclear.ProblemThe impact of Hurricane Katrina on hospitalization rates among dialysis patients was estimated.MethodsData from the United States Renal Data System were used to identify patients receiving dialysis from January 1, 2001 through August 29, 2005 at clinics that experienced service disruptions during Hurricane Katrina. A repeated events duration model was used with a time-varying Hurricane Katrina indicator to estimate trends in hospitalization rates. Trends were estimated separately by cause: surgical hospitalizations, medical, non-renal-related hospitalizations, and renal-related hospitalizations.ResultsThe rate ratio for all-cause hospitalization associated with the time-varying Hurricane Katrina indicator was 1.16 (95% CI, 1.05-1.29; P = .004). The ratios for cause-specific hospitalization were: surgery, 0.84 (95% CI, 0.68-1.04; P = .11); renal-related admissions, 2.53 (95% CI, 2.09-3.06); P < .001), and medical non-renal related, 1.04 (95% CI, 0.89-1.20; P = .63). The estimated number of excess renal-related hospital admissions attributable to Katrina was 140, representing approximately three percent of dialysis patients at the affected clinics.ConclusionsHospitalization rates among dialysis patients increased in the month following the Hurricane Katrina landfall, suggesting that providers and patients were not adequately prepared for large-scale disasters.Howard D, Zhang R, Huang Y, Kutner N. Hospitalization rates among dialysis patients during Hurricane Katrina. Prehosp Disaster Med. 2012;27(4):1-5.

scholarly journals Joint impact of rainfall and tidal level on flood risk in a coastal city with a complex river network: a case study of Fuzhou City, China

2013 ◽  
Vol 17 (2) ◽  
pp. 679-689 ◽  
Author(s):  
J. J. Lian ◽  
K. Xu ◽  
C. Ma
Keyword(s):  
Flood Risk ◽  
Joint Probability ◽  
Heavy Precipitation ◽  
River Network ◽  
Flood Frequency ◽  
Combined Effect ◽  
Multiple Sources ◽  
Tidal Level ◽  
Sea Levels ◽  
Coastal Cities

Abstract. Coastal cities are particularly vulnerable to flood under multivariable conditions, such as heavy precipitation, high sea levels, and storms. The combined effect of multiple sources and the joint probability of extremes should be considered to assess and manage flood risk better. This paper aims to study the combined effect of rainfall and the tidal level of the receiving water body on flood probability and severity in Fuzhou City, which has a complex river network. Flood severity under a range of precipitation intensities, with return periods (RPs) of 5 yr to 100 yr, and tidal levels was assessed through a hydrodynamic model verified by data observed during Typhoon Longwang in 2005. According to the percentages of the river network where flooding occurred, the threshold conditions for flood severity were estimated in two scenarios: with and without working pumps. In Fuzhou City, working pumps efficiently reduce flood risk from precipitation within a 20-yr RP. However, the pumps may not work efficiently when rainfall exceeds a 100-yr RP because of the limited conveyance capacity of the river network. Joint risk probability was estimated through the optimal copula. The joint probability of rainfall and tidal level both exceeding their threshold values is very low, and the greatest threat in Fuzhou comes from heavy rainfall. However, the tidal level poses an extra risk of flood. Given that this extra risk is ignored in the design of flood defense in Fuzhou, flood frequency and severity may be higher than understood during design.

scholarly journals Large-scale flood risk assessment using a coupled model chain

2016 ◽  
Vol 7 ◽  
pp. 11005 ◽  
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

scholarly journals Towards risk-based flood management in highly productive paddy rice cultivation – concept development and application to the Mekong Delta

2018 ◽  
Vol 18 (11) ◽  
pp. 2859-2876 ◽  
Author(s):  
Nguyen Van Khanh Triet ◽  
Nguyen Viet Dung ◽  
Bruno Merz ◽  
Heiko Apel
Keyword(s):  
Land Use ◽  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Mekong Delta ◽  
Flood Management ◽  
Paddy Rice ◽  
Rice Cultivation ◽  
Spatially Explicit ◽  
Risk Maps

Abstract. Flooding is an imminent natural hazard threatening most river deltas, e.g. the Mekong Delta. An appropriate flood management is thus required for a sustainable development of the often densely populated regions. Recently, the traditional event-based hazard control shifted towards a risk management approach in many regions, driven by intensive research leading to new legal regulation on flood management. However, a large-scale flood risk assessment does not exist for the Mekong Delta. Particularly, flood risk to paddy rice cultivation, the most important economic activity in the delta, has not been performed yet. Therefore, the present study was developed to provide the very first insight into delta-scale flood damages and risks to rice cultivation. The flood hazard was quantified by probabilistic flood hazard maps of the whole delta using a bivariate extreme value statistics, synthetic flood hydrographs, and a large-scale hydraulic model. The flood risk to paddy rice was then quantified considering cropping calendars, rice phenology, and harvest times based on a time series of enhanced vegetation index (EVI) derived from MODIS satellite data, and a published rice flood damage function. The proposed concept provided flood risk maps to paddy rice for the Mekong Delta in terms of expected annual damage. The presented concept can be used as a blueprint for regions facing similar problems due to its generic approach. Furthermore, the changes in flood risk to paddy rice caused by changes in land use currently under discussion in the Mekong Delta were estimated. Two land-use scenarios either intensifying or reducing rice cropping were considered, and the changes in risk were presented in spatially explicit flood risk maps. The basic risk maps could serve as guidance for the authorities to develop spatially explicit flood management and mitigation plans for the delta. The land-use change risk maps could further be used for adaptive risk management plans and as a basis for a cost–benefit of the discussed land-use change scenarios. Additionally, the damage and risks maps may support the recently initiated agricultural insurance programme in Vietnam.

scholarly journals The challenge of forecasting high streamflows 1–3 months in advance with lagged climate indices in southeast Australia

2014 ◽  
Vol 14 (2) ◽  
pp. 219-233 ◽  
Author(s):  
J. C. Bennett ◽  
Q. J. Wang ◽  
P. Pokhrel ◽  
D. E. Robertson
Keyword(s):  
Large Scale ◽  
Bayesian Model Averaging ◽  
Emergency Services ◽  
Joint Probability ◽  
Model Averaging ◽  
Climate Indices ◽  
Warning Systems ◽  
Forecast Period ◽  
Considerable Benefit ◽  
Probability Modelling

Abstract. Skilful forecasts of high streamflows a month or more in advance are likely to be of considerable benefit to emergency services and the broader community. This is particularly true for mesoscale catchments (< 2000 km2) with little or no seasonal snowmelt, where real-time warning systems are only able to give short notice of impending floods. In this study, we generate forecasts of high streamflows for the coming 1-month and coming 3-month periods using large-scale ocean–atmosphere climate indices and catchment wetness as predictors. Forecasts are generated with a combination of Bayesian joint probability modelling and Bayesian model averaging. High streamflows are defined as maximum single-day streamflows and maximum 5-day streamflows that occur during each 1-month or 3-month forecast period. Skill is clearly evident in the 1-month forecasts of high streamflows. Surprisingly, in several catchments positive skill is also evident in forecasts of large threshold events (exceedance probabilities of 25%) over the next month. Little skill is evident in forecasts of high streamflows for the 3-month period. We show that including lagged climate indices as predictors adds little skill to the forecasts, and thus catchment wetness is by far the most important predictor. Accordingly, we recommend that forecasts may be improved by using accurate estimates of catchment wetness.

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