Assessing the impact of climate change on longshore sediment transport along the central Dutch coast using statistical downscaling

A low-lying country as The Netherland is prone to coastal flooding, and its risk may be enhanced by global-warming induced climate change. Sea level rise has been historically considered as the key factor in coastal retreat, but waves also play an important erosive role along the coast, which can also be affected by the changing climate. During the last years, important advances have been achieved in climate modeling, with a very detailed characterization of the different components of the climate system, for the present and for different future scenarios. However, characterization of future o... Mehr ...

Verfasser: Rozas, Carlos
Dokumenttyp: masterThesis
Erscheinungsdatum: 2021
Schlagwörter: Ingeniería y Tecnología
Sprache: unknown
Permalink: https://search.fid-benelux.de/Record/base-27468227
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://hdl.handle.net/10533/253038

A low-lying country as The Netherland is prone to coastal flooding, and its risk may be enhanced by global-warming induced climate change. Sea level rise has been historically considered as the key factor in coastal retreat, but waves also play an important erosive role along the coast, which can also be affected by the changing climate. During the last years, important advances have been achieved in climate modeling, with a very detailed characterization of the different components of the climate system, for the present and for different future scenarios. However, characterization of future ocean waves is still a matter of discussion and ongoing research. In this thesis, a statistical downscaling methodology based on weather types has been chosen to model the present wave climate and explore potential changes in future waves. These changes are quantified in terms of the impact of these variations in the longshore sediment transport. The methodology is applied to Noordwijk, selected as a representative location of the central Dutch coast. The statistical downscaling methodology is based on a classification procedure of the predictor into similar atmospheric patterns over the wave generation areas, namely the weather types. Then, the wave data is grouped according to the occurrence of the weather types. The predictor is built from the sea level pressure fields (SLP) and the squared SLP gradients, while the predictant wave climate is characterized by significant wave height, wave peak period and mean wave direction of wind sea and swell components, resulting in unimodal or bimodal sea states. The chronology of the weather types is modeled using an autoregressive logistic model, which incorporates the seasonality, the interannual variability and the persistence observed from the historical data. For each weather type, wave parameters are modeled using the categorical distribution for the sea-state type, non-parametric kernel density functions for the central-mass regime and two generalized Pareto distributions for ...