Consistency of Extreme Flood Estimation Approaches

AbstractEstimations of low-probability flood events are frequently used to plan infrastructure and to determine the dimensions of flood protection measures. Several well-established methods exist for estimating low-probability floods. However, a global assessment of the consistency of these methods...

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Bibliographic Details
Published in:Journal of hydrologic engineering 2019-07, Vol.24 (7)
Main Authors: Felder, Guido, Paquet, Emmanuel, Penot, David, Zischg, Andreas, Weingartner, Rolf
Format: Article
Language:English
Subjects:
Atmospheric precipitations
Case studies
Catchment area
Catchments
Civil engineering
Consistency
Dimensions
Estimation
Extreme values
Flood control
Flood estimation
Flood management
Flood protection
Floods
Hydrology
Maximum probable flood
Measurement methods
Precipitation
Precipitation distribution
Probabilistic methods
Probability theory
Rain
Rainfall runoff
Rainfall simulators
Rainfall-runoff relationships
Runoff
Statistical analysis
Statistical methods
Statistics
Stochasticity
Technical Papers
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Summary:AbstractEstimations of low-probability flood events are frequently used to plan infrastructure and to determine the dimensions of flood protection measures. Several well-established methods exist for estimating low-probability floods. However, a global assessment of the consistency of these methods is difficult to achieve because the “true value” of an extreme flood is not observable. A detailed comparison performed on a given case study brings useful information about the statistical and hydrological processes involved in different methods. In the present study, the following three methods of estimating low-probability floods are compared: a purely statistical method (ordinary extreme value statistics), a statistical method based on stochastic rainfall-runoff simulation (SCHADEX method), and a deterministic method (physically based estimation of the probable maximum flood, PMF). These methods are tested for two different Swiss catchments; the results show that the 10,000-year return level flood estimations exceed the PMF estimations by 3% and 18%. The analysis shows that the plausibility of an extreme flood estimation does not only depend on the applied method but also on its ability to represent flood-triggering processes, including precipitation input, spatio-temporal precipitation distribution, and runoff.
ISSN:1084-0699
1943-5584
DOI:10.1061/(ASCE)HE.1943-5584.0001797