Uncertainty in the extreme flood magnitude estimates of large-scale flood hazard models

Abstract. Global-scale River Models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representation of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash–Sutcliffe Efficiency coefficient decreased by more than 35 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions in finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings are universal and can be extended to global-scale simulations. These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

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

Journal of Disaster Research ◽

10.20965/jdr.2016.p1128 ◽

2016 ◽

Vol 11 (6) ◽

pp. 1128-1136 ◽

Cited By ~ 3

Author(s):

Youngjoo Kwak ◽

◽

Yoichi Iwami ◽

Keyword(s):

Climate Change ◽

Risk Assessment ◽

Flood Risk ◽

Large Scale ◽

Flood Hazard ◽

Data Availability ◽

Flood Risk Assessment ◽

Daily Data ◽

Extreme Flood ◽

River Flood

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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Simulating historical flood events at the continental scale: observational validation of a large-scale hydrodynamic model

Natural Hazards and Earth System Science ◽

10.5194/nhess-21-559-2021 ◽

2021 ◽

Vol 21 (2) ◽

pp. 559-575

Author(s):

Oliver E. J. Wing ◽

Andrew M. Smith ◽

Michael L. Marston ◽

Jeremy R. Porter ◽

Mike F. Amodeo ◽

...

Keyword(s):

Large Scale ◽

River Flow ◽

Flood Hazard ◽

Model Performance ◽

Water Levels ◽

Hazard Models ◽

Flood Events ◽

Design Flood ◽

Validation Data ◽

Continental Scale

Abstract. Continental–global-scale flood hazard models simulate design floods, i.e. theoretical flood events of a given probability. Since they output phenomena unobservable in reality, large-scale models are typically compared to more localised engineering models to evidence their accuracy. However, both types of model may share the same biases and so not validly illustrate their predictive skill. Here, we adapt an existing continental-scale design flood framework of the contiguous US to simulate historical flood events. A total of 35 discrete events are modelled and compared to observations of flood extent, water level, and inundated buildings. Model performance was highly variable, depending on the flood event chosen and validation data used. While all events were accurately replicated in terms of flood extent, some modelled water levels deviated substantially from those measured in the field. Despite this, the model generally replicated the observed flood events in the context of terrain data vertical accuracy, extreme discharge measurement uncertainties, and observational field data errors. This analysis highlights the continually improving fidelity of large-scale flood hazard models, yet also evidences the need for considerable advances in the accuracy of routinely collected field and high-river flow data in order to interrogate flood inundation models more comprehensively.

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Simulating historical flood events at the continental-scale: observational validation of a large-scale hydrodynamic model

10.5194/nhess-2020-344 ◽

2020 ◽

Author(s):

Oliver E. J. Wing ◽

Andrew M. Smith ◽

Michael L. Marston ◽

Jeremy R. Porter ◽

Mike F. Amodeo ◽

...

Keyword(s):

Large Scale ◽

River Flow ◽

Flood Hazard ◽

Model Performance ◽

Water Levels ◽

Hazard Models ◽

Flood Events ◽

Design Flood ◽

Validation Data ◽

Continental Scale

Abstract. Continental–global scale flood hazard models simulate design floods: theoretical flood events of a given probability. Since they output phenomena unobservable in reality, large-scale models are typically compared to more localised engineering models to evidence their accuracy. However, both types of model may share the same biases and so not validly illustrate predictive skill. Here, we adapt an existing continental-scale design flood framework of the contiguous US to simulate historical flood events. 35 discrete events are modelled and compared to observations of flood extent, water level, and inundated buildings. Model performance was highly variable depending on the flood event chosen and validation data used. While all events were accurately replicated in terms of flood extent, some modelled water levels deviated substantially from those measured in the field. In spite of this, the model generally replicated the observed flood events in the context of terrain data vertical accuracy, extreme discharge measurement uncertainties, and observational field data errors. This analysis highlights the continually improving fidelity of large-scale flood hazard models, yet also evidences the need for considerable advances in the accuracy of routinely collected field and high river flow data in order to interrogate flood inundation models more comprehensively.

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Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

Hydrology and Earth System Sciences ◽

10.5194/hess-21-5143-2017 ◽

2017 ◽

Vol 21 (10) ◽

pp. 5143-5163 ◽

Cited By ~ 12

Author(s):

Cherry May R. Mateo ◽

Dai Yamazaki ◽

Hyungjun Kim ◽

Adisorn Champathong ◽

Jai Vaze ◽

...

Keyword(s):

Spatial Resolution ◽

Large Scale ◽

Flood Hazard ◽

Regional Scale ◽

Global Scale ◽

Test Case ◽

Computational Power ◽

Flow Capacity ◽

Extreme Flood ◽

Simulation Results

Abstract. Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash–Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

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

Natural Hazards and Earth System Science ◽

10.5194/nhess-18-2859-2018 ◽

2018 ◽

Vol 18 (11) ◽

pp. 2859-2876 ◽

Cited By ~ 4

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.

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Estimating extreme river discharges in Europe through a Bayesian Network

10.5194/hess-2016-250 ◽

2016 ◽

Author(s):

Dominik Paprotny ◽

Oswaldo Morales Nápoles

Keyword(s):

Large Scale ◽

Graphical Model ◽

Flood Hazard ◽

Physical Models ◽

Method Performance ◽

Discharge Data ◽

Dependency Structure ◽

Spatial Coverage ◽

Geographical Characteristics ◽

Better Than

Abstract. Large-scale hydrological modelling of flood hazard requires adequate extreme discharge data. Models based on physics are applied alongside those utilizing only statistical analysis. The former requires enormous computation power, while the latter are most limited in accuracy and spatial coverage. In this paper we introduce an alternate, statistical approach based on Bayesian Networks (BN), a graphical model for dependent random variables. We use a non-parametric BN to describe the joint distribution of extreme discharges in European rivers and variables describing the geographical characteristics of their catchments. Data on annual maxima of daily discharges from more than 1800 river gauge stations were collected, together with information on terrain, land use and climate of catchments that drain to those locations. The (conditional) correlations between the variables are modelled through copulas, with the dependency structure defined in the network. The results show that using this method, mean annual maxima and return periods of discharges could be estimated with an accuracy similar to existing studies using physical models for Europe, and better than a comparable global statistical method. Performance of the model varies slightly between regions of Europe, but is consistent between different time periods, and is not affected by a split-sample validation. The BN was applied to a large domain covering all sizes of rivers in the continent, both for present and future climate, showing large variation in influence of climate change on river discharges, as well as large differences between emission scenarios. The method could be used to provide quick estimates of extreme discharges at any location for the purpose of obtaining input information for hydraulic modelling.

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Combined fluvial and pluvial urban flood hazard analysis: method development and application to Can Tho City, Mekong Delta, Vietnam

Natural Hazards and Earth System Sciences Discussions ◽

10.5194/nhessd-3-4967-2015 ◽

2015 ◽

Vol 3 (8) ◽

pp. 4967-5013 ◽

Cited By ~ 1

Author(s):

H. Apel ◽

O. M. Trepat ◽

N. N. Hung ◽

D. T. Chinh ◽

B. Merz ◽

...

Keyword(s):

Hydrodynamic Model ◽

Urban Areas ◽

Large Scale ◽

Method Development ◽

Flood Hazard ◽

Hazard Analysis ◽

Mekong Delta ◽

Rain Gauge ◽

Convective Precipitation ◽

Can Tho City

Abstract. Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas, and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either fluvial or pluvial flood hazard, studies of combined fluvial and pluvial flood hazard are hardly available. Thus this study aims at the analysis of fluvial and pluvial flood hazard individually, but also at developing a method for the analysis of combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as example. In this tropical environment the annual monsoon triggered floods of the Mekong River can coincide with heavy local convective precipitation events causing both fluvial and pluvial flooding at the same time. Fluvial flood hazard was estimated with a copula based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. Pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data, and a stochastic rain storm generator. Inundation was simulated by a 2-dimensional hydrodynamic model implemented on a Graphical Processor Unit (GPU) for time-efficient flood propagation modelling. All hazards – fluvial, pluvial and combined – were accompanied by an uncertainty estimation considering the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and ways for their usage in flood risk management are outlined.

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A high-resolution large-scale flood hazard and economic risk model for the property loss insurance in Japan

Journal of Flood Risk Management ◽

10.1111/jfr3.12117 ◽

2014 ◽

Vol 9 (2) ◽

pp. 136-153 ◽

Cited By ~ 7

Author(s):

K. Kobayashi ◽

K. Takara ◽

H. Sano ◽

H. Tsumori ◽

K. Sekii

Keyword(s):

High Resolution ◽

Large Scale ◽

Risk Model ◽

Flood Hazard ◽

Economic Risk ◽

Property Loss

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Using 1D HEC-RAS Modeling and LiDAR Data to Improve Flood Hazard Maps Accuracy: A Case Study from Jijia Floodplain (NE Romania)

Water ◽

10.3390/w12061624 ◽

2020 ◽

Vol 12 (6) ◽

pp. 1624 ◽

Cited By ~ 1

Author(s):

Elena Huţanu ◽

Alin Mihu-Pintilie ◽

Andrei Urzica ◽

Larisa Elena Paveluc ◽

Cristian Constantin Stoleriu ◽

...

Keyword(s):

Geographical Information Systems ◽

Large Scale ◽

Flood Hazard ◽

Hydraulic Modeling ◽

Geographical Information ◽

Computer Algorithms ◽

Hazard Maps ◽

Modeling Software ◽

Recurrence Intervals ◽

Flood Hazard Maps

The ability to extract flood hazard settings in highly vulnerable areas like populated floodplains by using new computer algorithms and hydraulic modeling software is an important aspect of any flood mitigation efforts. In this framework, the 1D/2D hydraulic models, which were generated based on a Light Detection and Ranging (LiDAR) derivate Digital Elevation Model (DEM) and processed within Geographical Information Systems (GIS), can improve large-scale flood hazard maps accuracy. In this study, we developed the first flood vulnerability assessment for 1% (100-year) and 0.1% (1000-year) recurrence intervals within the Jijia floodplain (north-eastern Romania), based on 1D HEC-RAS hydraulic modeling and LiDAR derivate DEM with 0.5 m spatial resolution. The results were compared with official flood hazards maps developed for the same recurrence intervals by the hydrologists of National Administration “Romanian Waters” (NARW) based on MIKE SHE modeling software and a DEM with 2 m spatial resolutions. It was revealed that the 1D HEC-RAS provides a more realistic perspective about the possible flood threats within Jijia floodplain and improves the accuracy of the official flood hazard maps obtained according to Flood Directive 2007/60/EC.

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