Development and evaluation of a framework for global flood hazard mapping

Dottori, Francesco; Salamon, Peter; Bianchi, Alessandra; Alfieri, Lorenzo; Feyen, Luc

doi:10.1016/j.advwatres.2016.05.002

Cited by 321 publications

(278 citation statements)

References 44 publications

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“…A limitation is 34 their assumption that no flood protection infrastructure is in place, leading to overestimations of risk 6 . 35 Several studies have assessed flood risk using simple assumptions of current protection standards 3,10,11 .…”

Section: Main Text 33mentioning

confidence: 99%

A global framework for future costs and benefits of river-flood protection in urban areas

et al. 2017

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Section: Main Text 33mentioning

confidence: 99%

A global framework for future costs and benefits of river-flood protection in urban areas

et al. 2017

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“…Large-scale flood risk assessments have emerged during the last decade, with multiple continental or global studies focussing on fluvial risks Dottori et al, 2016bDottori et al, , 2017 and fewer on coastal losses (Hinkel et al, 2014;Hallegatte et al, 2013;Vousdoukas et al, 2018a). The emergence of these assessments comes as a response to the growing demand for upscaled flood risk estimation under present and future scenarios.…”

Section: Introductionmentioning

confidence: 99%

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

Vousdoukas

Bouziotas

Giardino

et al. 2018

Nat. Hazards Earth Syst. Sci.

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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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“…First, while some of the studies employed sophisticated flood inundation models in their framework, most still require discharge outputs which are currently available at much coarser resolution (0.1 to 0.5 • grids in a model comparison by Trigg et al, 2016) from a cascade of GHMs and 1-D GRMs (e.g., works by Pappenberger et al, 2012;Winsemius et al, 2013;Dottori et al, 2016) as inputs. Most of these studies identified the outputs from GHMs and GRMs as major sources of uncertainty.…”

Section: Introductionmentioning

confidence: 99%

“…A model cascade consisting of a regional rainfall-runoff model, a 1-D diffusive wave river routing model, and 2-D raster-based flood inundation model was used by Falter et al (2016) to simulate flood risks at the Elbe River. Dottori et al (2016) used the discharge outputs (available at 0.1 • resolution) from the model cascade of GloFAS (Alfieri et al, 2013) to calculate the discharge maxima at several return periods. The discharge maxima were downscaled to 30 resolution and used as input to CA2D, a 2-D hydraulic model (Dottori and Todini, 2011) to derive global flood hazard maps.…”

Section: Introductionmentioning

confidence: 99%

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

Mateo

Yamazaki

Kim

et al. 2017

Hydrol. Earth Syst. Sci.

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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 globalscale 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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Development and evaluation of a framework for global flood hazard mapping

Cited by 321 publications

References 44 publications

A global framework for future costs and benefits of river-flood protection in urban areas

A global framework for future costs and benefits of river-flood protection in urban areas

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

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

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