Uncertainty in predictions of oil spill trajectories in open sea

A method is introduced to calculate and to account for the uncertainties in the predictions of oil spill trajectories using a classic oil spill model. The method considers the output of the oil spill model as a function of random variables, which are the input parameters, and calculates the standard deviation of the output results which gives a measure of the uncertainty of the model given the uncertainties of the input parameters.Instead of a single trajectory that is calculated by the oil spill model using the mean values of the parameters, a band of trajectories can be defined when various simulations are done taking into account the uncertainties of the input parameters. This band of trajectories defines envelopes of the trajectories that are likely to be followed by the spill given the uncertainties of the input.The method is applied to an oil spill that occurred in open sea near Madeira Islands, in the Atlantic Ocean, in December 1989. The simulations allow the understanding of how a change in the wind direction drove the spill towards the Islands.The envelope of likely trajectories that is obtained with the uncertainty modelling shows a band of trajectories that is in better agreement with the observations than the single trajectory simulated by the oil spill model, based on mean parameters.     

Comparison of two three-dimensional hydrodynamic modeling systems for coastal tidal motion

A comparison of two three-dimensional numerical modeling systems for tidal elevations and velocities in the coastal waters is presented. The two modeling systems are: (1) the Princeton Ocean Model (POM) and (2) the MIKE 3 flow model. The model performance results for Singapore's coastal waters show that the predicted tidal elevations from the two hydrodynamic modeling systems are almost identical and are in very good agreement with field measurement data. The simulated tidal current velocities match well with field measurement data at the selected stations, but it seems that the POM provides the slightly better simulation, compared to the MIKE 3 flow model. The depth profiles of the velocities obtained from the two modeling systems may be greatly different at some time, due to the vertical diffusion coefficient calculated from different turbulent sub-models in the two modeling systems. The POM generally predicts larger peak tidal velocities. The maximum speed differences for the model results from the two modeling systems occur in the top and differ from time to time and from location to location, reaching up to 20%.     

Simulation of Pollutant Transport in Marmaris Bay

The circulation pattern and the pollutant transport in the Marmaris Bay are simulated by the developed three-dimensional baroclinic model. The Marmaris Bay is located at the Mediterranean Sea coast of Turkey. Since the sp ring tidal range is typically 20- 30 cm, the dominant forcing for the circulation and water exchange is due to the wind action. In the Marmaris Bay, there is sea outfall discharging directly into the bay. and that threats the bay water quality significantly. The current patterns in the vicinity of the outfall have been observed by tracking drogues which are moved by currents at different water depths. In the simulations of pollutant transport, the coliforms-counts is used as the tracer. The model provides realistic predictions for the circulation and pollutant transport in the Marmaris Bay. The transport model component predictions well agree with the results of a laboratory model study.     

渤海、黄海强温跃层数值预报模式

文中对前人关于水温垂直结构计算、模拟和预报研究成果进行了评价，并在此基础上建立了考虑海面吸收辐射和透射辐射、地形、风、海流、界面摩擦及其引起的混合作用的强温跃层三维数值预报模式。该模式运行的驱动量仅为风和气温场资料，因而具有较好的实用性；此外，从试报的结果看，效果是令人满意的。     

贡湖及其相关水域风生流模拟研究

在太湖风生流的数值模拟研究的基础上，设计模拟贡湖及其相关水域风生流的套网格数值模式。应用该模式研究不同风情下，梅梁湖，太湖主体湖水对贡湖的影响。     

From 2D TO 3D Through Modelling Based On A Single Image

Three-dimensional modelling from single images remains an interesting topic of investigation in the research community, even though range sensors are becoming a common alternative for the generation of 3D information. The interest in single-image-based modelling is motivated by a wide spectrum of applications such as cultural heritage, civil engineering, urban planning and even criminology. In this paper a complete new production flowline is presented for modelling based on a single image. The modelling process consists of a series of familiar steps in photogrammetry and computer vision: feature extraction, vanishing point computation, camera self-calibration, 3D reconstruction and dimensional analysis. In particular, the methodology developed for single-image-based modelling takes a scientific approach combining several proven techniques with robust estimators. Finally, in order to demonstrate its capabilities, the reported examples include several real situations applied in different contexts.