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.

An embodiment provides a device for measuring a fluid parameter of fluid flow in a channel, including: a transmitter; at least one receiver; a processor operatively coupled to the at least one transmitter and the at least one receiver; a memory device that stores instructions executable by the processor to: transmit, using the transmitter, directed energy carrying a signal toward a surface of a fluid in a fluid channel, so as to produce one or more reflections from the fluid surface; detect, by the at least one receiver, one or more received signals associated with the one or more reflections so produced; determine, based upon a measurement beam comprising characteristics of the transmitted and received signals, one or more fluid parameters to be measured using a processor of the device; and associate, using a processor of the device, the one or more fluid parameters with a channel segment. Other embodiments are described and claimed.

An ocean current measurement method, includes: acquiring three-dimensional coordinates measured by four GNSS (Global Navigation Satellite System) positioning modules on the surface drifting buoy and attitude data of the surface drifting buoy measured by an attitude sensor; correcting the three-dimensional coordinates measured by the four GNSS positioning modules based on the attitude data; optimizing the corrected three-dimensional coordinates of the four GNSS positioning modules according to the mounting positions; converting the optimized three-dimensional coordinates of the four GNSS positioning modules into latitude and longitude coordinates; and calculating coordinates of the surface drifting buoy, an instantaneous flow velocity and flow direction of ocean current and sea surface elevation through the latitude and longitude coordinates of the four GNSS positioning modules. The coordinates with higher precision can be obtained, and the flow velocity, flow direction and sea surface elevation of the sea area where the buoy is located can be measured.

The present disclosure provides an in-situ observation system for a bottom boundary layer (BBL) over a shallow-water cohesive seabed and an arrangement method thereof. It establishes a low-cost and easy-operation hydraulic pile foundation system (2), which can ensure the piling depth to achieve the anti-settling and stability. The stainless-steel sticks are assembled freely to construct the interference-free observation unit (1). As the porous discs are used between the feet of the observation unit (1) and the top of the bottom piles, the observation system can be accurately fixed to the pile foundation. It is thus not limited by the self-weight and can integrate various instruments upon requirement. The components in this system can be easily obtained and conveniently maintained. The present disclosure has the advantages of low-cost and stability, can be widely used for long-term in-situ observation of the BBL.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for estimating wave properties of a body of water. A computer-implemented system obtains measurement data for a duration of time from an inertial measurement unit (IMU) onboard an underwater device, generates model input data based on at least the measurement data obtained at the plurality of time points, and processes the model input data to generate model output data indicating one or more wave properties using a machine-learning model. The system further determines, based on at least the one or more wave properties, whether the device is safe to be deployed.

Devices, systems and methods for real-time wave monitoring are described. One example system for real-time monitoring of wave conditions includes a plurality of buoys, wherein each of the plurality of buoys comprises a sensor array configured to continuously monitor one or more characteristics of the wave conditions, a transceiver configured to transmit, to a remote server, information corresponding to the one or more characteristics of the wave conditions over a wireless communication channel, and a tether that physically couples the buoy to an anchor, wherein the information from each of the plurality of buoys is combined with a user preference to provide a user with a message regarding the wave conditions in response to a user request, and wherein a duration between the user request and transmission of the information from each of the plurality of buoys is less than a predetermined value.

Disclosed is a seepage meter device, which is capable of detecting groundwater seepage fluxes to surface water bodies in a variety of aquatic environments. The device comprises a seepage meter body and an electronics component.

According to at least one aspect, a river velocity estimation system is provided. The river velocity estimation system includes one or more components executable by at least one processor that are configured to receive terrain information and at least one image including a river, identify an area of interest in the at least one image that includes the river, identify a course of the river and a boundary of the river based on the area of interest in the at least one image, estimate a slope of the river based on the terrain information, determine a hydraulic radius of the river based on the boundary of the river and the course of the river, and estimate a flow rate of water in the river based on at least the slope of the river and the hydraulic radius of the river.

The present invention discloses a new submerged buoy data acquisition system, including a battery compartment, a main control processor, a GPS receiver, a gigabit Ethernet interface module, and a plurality of data acquisition boards, where the GPS receiver is connected to the main control processor, and the main control processor is connected to a host computer by using the gigabit Ethernet interface module; the data acquisition board includes a hydrophone sensor, a front-end drive circuit, an AD conversion circuit, a clock module, a DA conversion circuit, an FPGA, an ARM processor, and a storage module; the hydrophone sensor is connected to the AD conversion circuit by using the front-end drive circuit, the AD conversion circuit is connected to the FPGA, the FPGA is connected to the ARM processor, the storage module is connected to the ARM processor, the DA conversion circuit is connected to the FPGA and the clock module, the clock module is connected to the FPGA, and the ARM processor is connected to the main control processor. The present invention improves acquisition performance of the submerged buoy data acquisition system, and implements synchronous acquisition and control of the entire system.

Wakeboat hull control systems and methods are provided to permit the accurate reproduction of a wake behind a wakeboat. The onboard wake control system receives data from a draft measuring system. Incorporation of the data from the draft measuring system permits accurate reproduction of a wake behind the wakeboat after a change in an onboard variable such as the number, weight or position of passengers, the weight or position of cargo and the position of trim tabs or amount/location of ballast.