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| Titel |
Predicting location-specific extreme coastal floods in the future climate by
introducing a probabilistic method to calculate maximum elevation of the
continuous water mass caused by a combination of water level variations and
wind waves |
| VerfasserIn |
Ulpu Leijala, Jan-Victor Björkqvist, Milla M. Johansson, Havu Pellikka |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250149784
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| Publikation (Nr.) |
 EGU/EGU2017-14172.pdf |
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| Zusammenfassung |
| Future coastal management continuously strives for more location-exact and precise
methods to investigate possible extreme sea level events and to face flooding hazards
in the most appropriate way. Evaluating future flooding risks by understanding
the behaviour of the joint effect of sea level variations and wind waves is one of
the means to make more comprehensive flooding hazard analysis, and may at first
seem like a straightforward task to solve. Nevertheless, challenges and limitations
such as availability of time series of the sea level and wave height components, the
quality of data, significant locational variability of coastal wave height, as well
as assumptions to be made depending on the study location, make the task more
complicated.
In this study, we present a statistical method for combining location-specific probability
distributions of water level variations (including local sea level observations and global mean
sea level rise) and wave run-up (based on wave buoy measurements). The goal of our method
is to obtain a more accurate way to account for the waves when making flooding hazard
analysis on the coast compared to the approach of adding a separate fixed wave
action height on top of sea level -based flood risk estimates. As a result of our new
method, we gain maximum elevation heights with different return periods of the
continuous water mass caused by a combination of both phenomena, “the green
water”.
We also introduce a sensitivity analysis to evaluate the properties and functioning of our
method. The sensitivity test is based on using theoretical wave distributions representing
different alternatives of wave behaviour in relation to sea level variations. As these wave
distributions are merged with the sea level distribution, we get information on how the
different wave height conditions and shape of the wave height distribution influence the joint
results.
Our method presented here can be used as an advanced tool to minimize over- and
underestimation of the combined effect of sea level variations and wind waves, and to help
coastal infrastructure planning and support smooth and safe operation of coastal cities in a
changing climate. |
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