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|Impact of climate change on storm surges at the Belgian coast|
Decloedt, L.C. (2011). Impact of climate change on storm surges at the Belgian coast. MA Thesis. K.U. Leuven: Leuven. 92 pp.
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- VLIZ: Non-open access 231826
- VLIZ: Archive VLIZ ARCHIVE A.THES9 
|Document type: Dissertation|
Climatic changes; Models; Storm surge prediction; Storm surges; ANE, Belgium, Belgian Coast [Marine Regions]; ANE, Belgium, Oostende [Marine Regions]; Marine
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This master thesis research focused on investigating the impacts of future climate change on storm surges along the Belgian coast (at Ostend) and this by setting up a range of storm surge prediction models.
First, a variable had to be found which has a high dependence with the surge and from which reproduction (or prediction) of the surge would be possible. The sea level pressure is found to be a good representing parameter for the reproduction of the surge. There is a high negative correlation for the surge with the SLP at the south of the Baltic sea, around the coast of Poland and the Baltic states such as Estonia, Latvia and Lithuania.
Two classification methods, the Automated Lamb classification scheme by Jenkinson and Collison and Principal component analysis and k-means clustering are used to check for causal relationships between the surge height and the sea level pressure. From these methods it became clear that the higher surges occur more frequently for the weather types 'West', 'Northwest' and 'North', where the names of the weather type mainly represent the overall wind direction (based on sea level pressure fields), and the Cluster type 'Atlantic Ridge', which combines the westerly SLP patterns.
There is, however, quite a bit of scatter on the relationship between the surge and the SLP at the Baltic Sea. A set of different models are set up and checked with observational data to get the best possible correlation between the observations and the predicted values from the models. These models use different regression lines and methods (linear regression lines, polynomial regression lines, a model with different submodels for different ranges of the SLP or different submodels based on the weather types, etc.). The correlations between the simulated and observed surges mount up to about 65%. Other parameters are also checked, such as wind and tide parameters, but they don't seem to increase the correlation much.
Additional research for later application is also conducted. This includes checking the predictions of the best models on a daily basis and making the model applicable for flood predictions along the Scheldt Estuary. For this, an analysis is conducted to check the height of the surge peak versus the duration of the surge above a certain threshold value, but also versus the length of the period of consecutive days belonging to the same cluster or weather type. A positive correlation is found between the surge height and the period of consecutive days belonging to weather types that are of relevance from a high surge point of view. In this additional research, the relation between the surge and the rainfall is also studied, indicating a small positive correlation between the surge and the rainfall. Their extremes, however, do not coincide on a daily basis.