A method for determining the velocity of a moving fluid surface, which comprises the following steps S1 to S5: S1) taking a sequence of images of the moving fluid surface by at least one camera; S2) comparing a first image from the sequence with a second image from the sequence in order to distinguish moving patterns of the fluid surface from non-moving parts and to obtain a first processed image (im_1f) comprising the moving patterns; S3) comparing a third image from the sequence with a fourth image from the sequence in order to distinguish moving patterns of the fluid surface from non-moving parts and to obtain a second processed image (im_2f) comprising the moving patterns; S4) comparing the first and second processed images in order to determine the spatial displacements of the moving patterns; and S5) determining from the spatial displacements the velocity.

A method and system for determining coastal erosion disaster early warning lines and calculating spatial scope thereof. The method includes determining a coastal erosion rate according to coastal erosion change monitoring data and landform data; and calculating at least one coastal erosion early warning line in coming N years in conventional conditions according to an established coastal erosion rate calculation method; determining the at least one coastal erosion early warning line in N years in extreme conditions by increasing influencing factors of accelerated sea level rise and extreme storm waves and utilizing a determination and calculation method of coastal erosion disaster early warning lines; and obtaining a coastal erosion retreat position and scope and sending early warning based on the coastal erosion rate in conventional conditions and the at least one coastal erosion early warning line in extreme conditions

The present invention relates to a water flow measuring drifting buoy capable of preventing stranding and resisting impact, which includes: a ball-game table-shaped inflation body with a counterweight capable of drifting autonomously in a direction of a main stream of a water flow, wherein the inflation body is provided with at least two inflation connectors, and the inflation connectors are of a cross-shaped structure formed by connecting in a conical distribution with 4 inflation-stabilizing rods uniformly distributed along a circumferential radiation; the counterweight is 4-10 fan-shaped steel plates arranged annularly in the center of the bottom of the inflation body, and the fan-shaped steel plates are flexibly connected to each other to be able to shake. The ball-game table structure used in the present invention is selected by comparing various shapes to push a buoy to the middle of a river where the water flow is turbulent by using the difference in a water flow speed to prevent the water flow from being stranded where the water flow is slow or being blocked by a rock at a river bank so as not to continue the drift. The steel plate of the cross-shaped structure in the fan-shaped distribution is used, so that the buoy can be turned up and continue to drift once it has fallen to the ground, greatly improving the efficiency of drift.

A system for determining a measurement of a discharge of a streamflow in open channel conditions using a velocity-area technique featuring a signal processor configured to receive ADCP measurement signaling containing information about ADCP measurements taken in conjunction with the streamflow, GPS signaling containing information about GPS readings in conjunction with ADCP measurements, and signaling containing information about a projection or virtual tag line using two (2) Global Position System (GPS) locations having start and end latitudes and longitudes at a measurement site in a hydrographic operation for a measurement of a discharge in open channel conditions, and an instantaneous GPS position for a station; and determine control signaling containing information to take the ADCP measurements and the GPS readings in conjunction with the ADCP measurements, as well as corresponding signaling containing information about the measurement of the discharge of the streamflow, based upon a respective distance between each station in relation to the projection or virtual tag line, as well as ADCP signaling and the GPS signaling received, using Differential Global Position System (DGPS) or Real Time Kinematic GPS (RTK GPS).

Disclosed is a tidal current meter that measures the velocity of a tidal current. The tidal current meter includes an oscillator, a calculation section, a depression angle setup section, and a drive section. The oscillator is capable of transmitting an ultrasonic wave into water and receiving the reflection of the transmitted ultrasonic wave. The calculation section calculates the velocity in accordance with the Doppler shift frequency of the reflection received by the oscillator. The depression angle setup section sets a depression angle, that is, the angle formed by the transmission direction of the ultrasonic wave and a horizontal plane. The drive section drives the oscillator in such a manner as to transmit the ultrasonic wave and receive the reflection of the transmitted ultrasonic wave at the depression angle set by the depression angle setup section.

A method and system for determining coastal erosion disaster early warning lines and calculating spatial scope thereof. The method includes determining a coastal erosion rate according to coastal erosion change monitoring data and landform data; and calculating at least one coastal erosion early warning line in coming N years in conventional conditions according to an established coastal erosion rate calculation method; determining the at least one coastal erosion early warning line in N years in extreme conditions by increasing influencing factors of accelerated sea level rise and extreme storm waves and utilizing a determination and calculation method of coastal erosion disaster early warning lines; and obtaining a coastal erosion retreat position and scope and sending early warning based on the coastal erosion rate in conventional conditions and the at least one coastal erosion early warning line in extreme conditions.

A method, device, computing equipment, and storage medium for predicting the drift of the floating object are provided. A method for predicting drift velocity includes: obtaining environmental characteristic parameters at the location of the floating object to be predicted, wherein the environmental characteristic parameters include wave characteristic parameters; inputting the wave characteristic parameters into a deep learning model for wave-induced drift velocity to obtain the wave-induced drift velocity; wherein the deep learning model for wave-induced drift velocity is trained based on first sample drift data, wherein the first sample drift data includes observed drift velocity of sample floating objects, corresponding sample water surface flow characteristic parameters, sample wind characteristic parameters, and sample wave characteristic parameters.

An anchoring device is disclosed providing an easily deployable and removable anchoring point. The anchoring device includes a lower portion configured to be buried into a bottom of a body of water comprising a weighted anchor and at least one spray outlet location upon a bottom surface of the weighted anchor, the spray outlet hole being configured to aid installation and removal of the anchoring device by selectively projecting a spray of water to displace soft debris on the bottom away from the weighted anchor. The anchoring device further includes an upper portion comprising a vertical pole extending upward from the bottom, the pole comprising an anchoring point.

A method, device, computing equipment, and storage medium for predicting the drift of the floating object are provided. A method for predicting drift velocity includes: obtaining environmental characteristic parameters at the location of the floating object to be predicted, wherein the environmental characteristic parameters include wave characteristic parameters; inputting the wave characteristic parameters into a deep learning model for wave-induced drift velocity to obtain the wave-induced drift velocity; wherein the deep learning model for wave-induced drift velocity is trained based on first sample drift data, wherein the first sample drift data includes observed drift velocity of sample floating objects, corresponding sample water surface flow characteristic parameters, sample wind characteristic parameters, and sample wave characteristic parameters.

Described here are systems and methods that utilize visual imagery and an optical flow-based computer vision algorithm to measure river velocity in streams or other flowing bodies of water. The systems and methods described in the present disclosure overcome the barriers of conventional flow measurement techniques by providing a fast, non-intrusive, remote method to measure peak flows.