A method of forecasting an ocean state via a multi-scale two-step assimilation of Surface Water Ocean Topography (SWOT) observations. The method may include receiving data associated with a prior ocean state forecast associated with SWOT observations, determining a large-scale increment state variable based on a large scale correction associated with the prior ocean state forecast, and determining a small scale initial input value based on (i) a combination of the background state associated with the prior ocean state forecast and (ii) the determined large-scale increment state variable. The method may include generating, based on the determined small scale initial input value, a small scale correction associated with the prior ocean state forecast, determining a small-scale increment state variable based on the small scale correction, and generating a current ocean state forecast based on at least some of this information.

The present invention relates to an apparatus and a method for predicting the dispersion of hazardous and noxious substances and, more specifically, provides an apparatus and a method for predicting the dispersion of hazardous and noxious substances, the method: checking the components of the hazardous and noxious substances having leaked into the ocean, so as to classify the hazardous and noxious substances into a corresponding classification set among twelve classification sets by means of at least one of vapor pressure, the degradation in water, or density; dividing the classification sets, in which the hazardous and noxious substances are classified, into one dispersion model among an air dispersion model, a seawater dispersion model, and an air/seawater dispersion model according to the dispersion characteristics thereof; acquiring, from a weather center server, the state information of a sea area, which is set to be different according to the divided dispersion models; and predicting a danger radius for the dispersion of the hazardous and noxious substances by using the acquired state information of the sea area, and outputting the same.

The present invention relates to an apparatus and a method for predicting the dispersion of hazardous and noxious substances and, more specifically, provides an apparatus and a method for predicting the dispersion of hazardous and noxious substances, the method: checking the components of the hazardous and noxious substances having leaked into the ocean, so as to classify the hazardous and noxious substances into a corresponding classification set among twelve classification sets by means of at least one of vapor pressure, the degradation in water, or density; dividing the classification sets, in which the hazardous and noxious substances are classified, into one dispersion model among an air dispersion model, a seawater dispersion model, and an air/seawater dispersion model according to the dispersion characteristics thereof; acquiring, from a weather center server, the state information of a sea area, which is set to be different according to the divided dispersion models; and predicting a danger radius for the dispersion of the hazardous and noxious substances by using the acquired state information of the sea area, and outputting the same.

A real-time abnormity-diagnosing and interpolation method for water regime-monitoring data relates to the technical field of monitoring water regime. This method includes the following steps: acquiring water regime-monitoring data, drawing a box plot, recognizing and diagnosing abnormal data in real time based on the box plot, performing grey correlation analysis on other variables related to a predictor variable, building a BP neural network model and making training, applying the BP neural network model to predict water regime-monitoring data in real time, and performing abnormity diagnosis and data interpolation. Adopting this method, we can effectively enhance predicting and monitoring the water regime-monitoring data in real time, and diagnose abnormal data and make interpolations in time, thereby improving the reliability of data, objectively reflecting water regime changes, and effectively guiding engineering scheduling.

A real-time abnormity-diagnosing and interpolation method for water regime-monitoring data relates to the technical field of monitoring water regime. This method includes the following steps: acquiring water regime-monitoring data, drawing a box plot, recognizing and diagnosing abnormal data in real time based on the box plot, performing grey correlation analysis on other variables related to a predictor variable, building a BP neural network model and making training, applying the BP neural network model to predict water regime-monitoring data in real time, and performing abnormity diagnosis and data interpolation. Adopting this method, we can effectively enhance predicting and monitoring the water regime-monitoring data in real time, and diagnose abnormal data and make interpolations in time, thereby improving the reliability of data, objectively reflecting water regime changes, and effectively guiding engineering scheduling.

A high-precision waterway reconstruction method based on a multi-satellite source information coupling is provided. The method includes a determination method for a waterway section, a reconstruction method for a basic waterway section high-precision coupling, a reconstruction method for a fixed waterway section coupling, and a reconstruction method for a river reach waterway terrain. The method fills the gap of surveying and mapping of the waterways based on satellite remote sensing information, extremely improves the perpendicular precision and planar precision of the existing digital surface model of satellites for river waterways, and provides decision support for a water-related emergency rescue in areas lacking data.

A high-precision waterway reconstruction method based on a multi-satellite source information coupling is provided. The method includes a determination method for a waterway section, a reconstruction method for a basic waterway section high-precision coupling, a reconstruction method for a fixed waterway section coupling, and a reconstruction method for a river reach waterway terrain. The method fills the gap of surveying and mapping of the waterways based on satellite remote sensing information, extremely improves the perpendicular precision and planar precision of the existing digital surface model of satellites for river waterways, and provides decision support for a water-related emergency rescue in areas lacking data.

Automated detection of features and/or parameters within an ocean environment using image data. In an embodiment, captured image data is received from ocean-facing camera(s) that are positioned to capture a region of an ocean environment. Feature(s) are identified within the captured image data, and parameter(s) are measured based on the identified feature(s). Then, when a request for data is received from a user system, the requested data is generated based on the parameter(s) and sent to the user system.

Embodiments relate generally to marine geophysical surveying. More particularly, embodiments relate to a wax application system for application of a wax coating to a surface of a streamer. An embodiment may comprise a marine geophysical survey system. The marine geophysical survey system may comprise a streamer and a wax application system operable to receive the streamer on deployment and apply a wax coating to the streamer as the streamer is being deployed from a survey vessel into a body of water.

Embodiments relate generally to marine geophysical surveying. More particularly, embodiments relate to a wax application system for application of a wax coating to a surface of a streamer. An embodiment may comprise a marine geophysical survey system. The marine geophysical survey system may comprise a streamer and a wax application system operable to receive the streamer on deployment and apply a wax coating to the streamer as the streamer is being deployed from a survey vessel into a body of water.