Untitled

Visser, Hubregt J.; Folkert, Rob; Hoekstra, J.; Wolff, J. J. de

doi:10.1023/a:1005516020996

Cited by 80 publications

(24 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The comparison was made by following the parallel models approach first presented by Visser et al (2000) for the example of climate simulations. Merz and Thieken (2009) adopted this approach for the identification of principal uncertainty sources in flood risk calculations.…”

Section: Benchmarking Against Other Selected Uncertainty Factorsmentioning

confidence: 99%

“…A high value of RUR means that the subset contributes significantly to the maximum uncertainty range. Alternatively, a small value of RUR (RUR 100 %) indicates that the subset has a reduced effect on the overall uncertainty (Visser et al, 2000). In the model experiment for this study, we analysed the relative contribution of (a) the spatio-temporal rainfall pattern, (b) the choice of the inundation model and the exposure analysis approach, and (c) the choice of the vulnerability function.…”

Section: Benchmarking Against Other Selected Uncertainty Factorsmentioning

confidence: 99%

See 1 more Smart Citation

Effects of variability in probable maximum precipitation patterns on flood losses

Zischg

Felder

Weingartner

et al. 2018

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. The assessment of the impacts of extreme floods is important for dealing with residual risk, particularly for critical infrastructure management and for insurance purposes. Thus, modelling of the probable maximum flood (PMF) from probable maximum precipitation (PMP) by coupling hydrological and hydraulic models has gained interest in recent years. Herein, we examine whether variability in precipitation patterns exceeds or is below selected uncertainty factors in flood loss estimation and if the flood losses within a river basin are related to the probable maximum discharge at the basin outlet. We developed a model experiment with an ensemble of probable maximum precipitation scenarios created by Monte Carlo simulations. For each rainfall pattern, we computed the flood losses with a model chain and benchmarked the effects of variability in rainfall distribution with other model uncertainties. The results show that flood losses vary considerably within the river basin and depend on the timing and superimposition of the flood peaks from the basin's sub-catchments. In addition to the flood hazard component, the other components of flood risk, exposure, and vulnerability contribute remarkably to the overall variability. This leads to the conclusion that the estimation of the probable maximum expectable flood losses in a river basin should not be based exclusively on the PMF. Consequently, the basin-specific sensitivities to different precipitation patterns and the spatial organization of the settlements within the river basin need to be considered in the analyses of probable maximum flood losses.

show abstract

Section: Benchmarking Against Other Selected Uncertainty Factorsmentioning

confidence: 99%

Section: Benchmarking Against Other Selected Uncertainty Factorsmentioning

confidence: 99%

Effects of variability in probable maximum precipitation patterns on flood losses

Zischg

Felder

Weingartner

et al. 2018

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

Section: Benchmarking Against Other Uncertaintiesmentioning

confidence: 99%

“…Alternatively, a small value of RUR (RUR << 100 %) indicates that the subset has a reduced effect on the overall uncertainty (Visser et al, 2000). 30…”

Section: Benchmarking Against Other Uncertaintiesmentioning

confidence: 99%

Effects of variability in probable maximum precipitation patterns on flood losses

Zischg¹,

Felder²,

Weingartner³

et al. 2018

Preprint

View full text Add to dashboard Cite

Abstract. The assessment of the impacts of extreme floods is important for dealing with residual risk, particularly for critical infrastructure management and for insurance purposes. Thus, modelling of the probable maximum flood (PMF) from probable maximum precipitation (PMP) by coupling hydrologic and hydraulic models has gained interest in recent years.Herein, we examine whether variability in precipitation patterns exceeds or is below other uncertainties in flood loss 15 estimation and if the flood losses within a river basin are related to the probable maximum discharge at the basin outlet. We developed a model experiment with an ensemble of probable maximum precipitation scenarios created by Monte-Carlo simulations. For each rainfall pattern, we computed the flood losses with a model chain and benchmarked the effects of variability in rainfall distribution with other model uncertainties. The results show that flood losses vary considerably within the river basin and depend on the timing and superimposition of the flood peaks from the basin's sub-catchments. In addition 20 to the flood hazard component, the other components of flood risk, exposure and vulnerability, contribute remarkably to the overall variability. This leads to the conclusion that the estimation of the probable maximum expectable flood losses in a river basin should not be based exclusively on the PMF. Consequently, the basin-specific sensitivities to different precipitation patterns and the spatial organisation of the settlements within the river basin need to be considered in the analyses of probable maximum flood losses. 25

show abstract

“…One of the primary factors related to uncertainty in CGMs is that different models can simulate quite different regional changes under the same anthropogenic forcings (Whetton et al 1995;Kittel et al 1998;Giorgi and Francisco 2000) and it is difficult to ascertain which GCMs are most reliable. Often, projections from GCMs are characterized by a low level of confidence and high level of uncertainty (Giorgi and Francisco 2000;Visser et al 2000). Furthermore, previous studies have shown that there can be considerable differences in the accuracy of predictions from different models (Lorenz 1982;Delworth and Knutson 2000).…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of Performance of CMIP3 GCMs in Simulating the East Asian Monsoon Variability

Paul¹,

Hsu²

2012

Terr. Atmos. Ocean. Sci.

View full text Add to dashboard Cite

This study evaluates variability of East Asian Monsoon simulated by 24 coupled general circulation models (GCMs) participating in Coupled Model Inter-comparison Project 3 (CMIP3). Fifty years (1950 -1999) The results indicate that, amplitude of inter-annual component EASM becomes larger after 1980's. The decadal component shows, weakening trend and switching from positive monsoon phase to negative monsoon phase in mid-80s for both EASM and EAWM. The simulated composite differences between weak and strong monsoon decades by models with above mentioned characteristics are compared with observation for further evaluation. The EASM weakening is associated with weaker southwesterly and stronger anti-cyclonic pattern over Western North Pacific and results in more rainfall in south and north China, Korea, Japan and less rainfall in central China. The EAWM weakening is associated with weakening of Siberian High and temperature rise over East Asia. EASM and EAWM matrices are constructed according to the relative merits of GCMs.

show abstract

Untitled

Cited by 80 publications

References 27 publications

Effects of variability in probable maximum precipitation patterns on flood losses

Effects of variability in probable maximum precipitation patterns on flood losses

Effects of variability in probable maximum precipitation patterns on flood losses

Comparative Study of Performance of CMIP3 GCMs in Simulating the East Asian Monsoon Variability

Contact Info

Product

Resources

About