The North Sea is a highly dynamic area, where a tidal current flows over a sandy seabed. It is an intensively used area where various human activities take place. The seabed is rich in oil and gas and there are a lot of oil and gas platforms connected to the shore with pipelines that are mostly buried below the seabed. Telephone and data cables are placed up and in the seabed running from one country to another. Also, since the North Sea is a biological rich area, a lot of fishery takes place. The sand of the seabed is mined and used for large infrastructural projects. As important harbours face the North Sea, intensive shipping takes place and there are many shipping lanes which have to be dredged. Also, large areas are reserved for offshore wind farms and other functions like military terrains. The seabed of the North Sea is not flat, but is shaped in several wavy patterns, ranging from small ripples to large sand banks. Sand banks have a wave length between 1 and 10 km and can have a height of several tens of meters. Somewhat smaller features are sand waves. Their length varies between 100 and 800 m and they can be up to 10 m high from trough to crest. As the North Sea is a very dynamic area, both in natural and a morphological sense, and as many human activities take place here, it is important to know what the large-scale effects of human activities on the seabed will be. Therefore, in this thesis we develop a system that can predict the large-scale effects of human activities on the North Sea seabed on a long timescale. We do this by implementing idealized morphodynamic models in a GIS (Geographical Information System) that also contains data on the North Sea environment. We predict the occurrence of sand banks and sand waves in the North Sea and compare the results with observations of these large-scale bed forms. The results show that in large parts of the North Sea, we are able to correctly predict the occurrence of sand banks and sand waves. (chapter 2 and 3). The models that predict the morphological effects of human activities (chapter 4 and 5) cannot be validated yet. But they are based on the same principles as the models that we use to predict the occurrence of sand banks and sand waves of which the results are compared with observations of large-scale bed forms in the North Sea. It is assumed that the models that predict the effects of human activities, do not show any morphological evolution, if the model that predicts the occurrence of sand banks (chapter 3) does not predict the occurrence of sand banks at this particular location. This because, the 12 underlying mechanism of the models on human activities are based on the same 2DH flow conditions that are necessary for sand bank development. We connect idealized morphodynamic models to the GIS to create a tool that can be used to predict the effects of human activities on the North Sea seabed. The models use sitespecific input to give predictions for an arbitrary location in the North Sea. The first application of this system is large-scale sand extraction. Due to large construction projects like the enlargement of the Rotterdam harbour, the demand for sand is rising and more offshore resources will be used to fulfill the need. This means that more large-scale sand pits will be created in the North Sea. The North Sea is a shallow shelf sea where the tide flows over a sandy bed. Therefore, the presence of sand pits can influence the morphological behaviour of this seabed (chapter 4). The second application is offshore wind farms. We investigate the influence of offshore wind farms on the large-scale morphodynamics of the seabed. The need for sustainable energy is rising, and at the moment wind energy is one of the forms of renewable energy that can be harvested efficiently. We develop a morphodynamic model to investigate the effect of offshore wind farms on the seabed. By implementing the model in the GIS environment, the model allows us to calculate the effects of a wind farm using site-specific and farm design input parameters (chapter 5). By implementing idealized morphodynamic models in a GIS environment we are able to predict the occurrence of large-scale bed forms on the North Sea seabed. Also, by implementing models that predict the effects of human activities in the GIS system, we are able to give an indication of the large-scale morphological effects of these human activities in the North Sea, thereby providing a rapid assessment tool to predict the morphological effects of human activities on the seabed.
|Award date||21 Feb 2008|
|Place of Publication||Enschede|
|Publication status||Published - 21 Feb 2008|