On Risk Analysis Of Extreme Sea Levels In Falsterbo Peninsula
(2017) In Master's Theses in Mathematical Sciences MASM01 20171Mathematical Statistics
- Abstract
- Coastal protection is vital for protecting infrastructure, coastal environments
and human lives against flooding. Building ecient coastal protection requires a good understanding of maximum sea levels which might occur indifferent time periods in the
future. Extreme value theory provides a mathematical framework for such analyses.
On November 13, 1872 the biggest recorded sea level surge devastated the
Danish, German and Swedish Baltic Sea coast. This master thesis focuses
on estimating the return period of 1872 storm using one-dimensional extreme value analysis based on historical data from the measure stations near
Falsterbo Peninsula. A multivariate extreme value approach is applied to
include covariates such as wind speed and... (More) - Coastal protection is vital for protecting infrastructure, coastal environments
and human lives against flooding. Building ecient coastal protection requires a good understanding of maximum sea levels which might occur indifferent time periods in the
future. Extreme value theory provides a mathematical framework for such analyses.
On November 13, 1872 the biggest recorded sea level surge devastated the
Danish, German and Swedish Baltic Sea coast. This master thesis focuses
on estimating the return period of 1872 storm using one-dimensional extreme value analysis based on historical data from the measure stations near
Falsterbo Peninsula. A multivariate extreme value approach is applied to
include covariates such as wind speed and wave height to further improve
the understanding of which factors affect extreme sea levels.
Fit diagnostics show that the block maxima model based on observations
from Klagshamn measure station provides the best t for the data; hence it
has been used to estimate the return period of the 1872 storm. Wind speed
and wave height from nearby station were used to improve the accuracy of
the analysis in a multivariate framework. (Less) - Popular Abstract (Swedish)
- Rising sea level is very frightening and can cause huge amount of damage,
thus coastal protection is vital for protecting infrastructure, coastal environments and human lives against
flooding. To build effcient coastal protection
one has to know the magnitude of the
flood. Usually one has little information of
flooding since they don't occur very often, hence it can be hard to
know how to build ecient protection. Building protection against
flooding requires a good understanding of the maximum sea level. One can study the
maximum sea level using extreme value theory.
On November 13, 1872 the biggest recorded sea level surge devastated the
Danish, German and Swedish Baltic Sea coast. The storm caused the sea
level to be 2.4... (More) - Rising sea level is very frightening and can cause huge amount of damage,
thus coastal protection is vital for protecting infrastructure, coastal environments and human lives against
flooding. To build effcient coastal protection
one has to know the magnitude of the
flood. Usually one has little information of
flooding since they don't occur very often, hence it can be hard to
know how to build ecient protection. Building protection against
flooding requires a good understanding of the maximum sea level. One can study the
maximum sea level using extreme value theory.
On November 13, 1872 the biggest recorded sea level surge devastated the
Danish, German and Swedish Baltic Sea coast. The storm caused the sea
level to be 2.4 meter above normal and took the lives of 271 people, destroyed
2800 buildings and left 15000 persons homeless. The Falsterbo Peninsula, in
Vellinge municipality in south Sweden, is prone to
ooding since it's lowlying. This master thesis focuses on estimating the return period of 1872
storm surge in Falsterbo using historical sea level data from Sweden's
Meteorological and Hydrological Institute (SMHI) from nearby stations around
Falsterbo Peninsula.
Other factors that might effect extreme sea levels such as wind speed and
wind direction will also be investigated to further improve the understanding
of extreme sea levels, letting us build better coastal protection.
This paper shows that sea level data from Klagshamn station turned out to
be the best accurate estimation of the return period of the sea level that
occurred during the 1872 storm. The paper also presents how one can combine sea levels, wind speed and wave height to further improve the understanding about extreme sea levels, thus letting us build more ecient coastal
protection. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8916021
- author
- Persson, Kevin
- supervisor
- organization
- course
- MASM01 20171
- year
- 2017
- type
- H2 - Master's Degree (Two Years)
- subject
- publication/series
- Master's Theses in Mathematical Sciences
- report number
- LUNFMS-3069-2014
- ISSN
- 1404-6342
- other publication id
- 2017:E29
- language
- English
- id
- 8916021
- date added to LUP
- 2017-06-15 14:00:38
- date last changed
- 2024-09-23 10:42:46
@misc{8916021, abstract = {{Coastal protection is vital for protecting infrastructure, coastal environments and human lives against flooding. Building ecient coastal protection requires a good understanding of maximum sea levels which might occur indifferent time periods in the future. Extreme value theory provides a mathematical framework for such analyses. On November 13, 1872 the biggest recorded sea level surge devastated the Danish, German and Swedish Baltic Sea coast. This master thesis focuses on estimating the return period of 1872 storm using one-dimensional extreme value analysis based on historical data from the measure stations near Falsterbo Peninsula. A multivariate extreme value approach is applied to include covariates such as wind speed and wave height to further improve the understanding of which factors affect extreme sea levels. Fit diagnostics show that the block maxima model based on observations from Klagshamn measure station provides the best t for the data; hence it has been used to estimate the return period of the 1872 storm. Wind speed and wave height from nearby station were used to improve the accuracy of the analysis in a multivariate framework.}}, author = {{Persson, Kevin}}, issn = {{1404-6342}}, language = {{eng}}, note = {{Student Paper}}, series = {{Master's Theses in Mathematical Sciences}}, title = {{On Risk Analysis Of Extreme Sea Levels In Falsterbo Peninsula}}, year = {{2017}}, }