Hydrodynamic environment forecasting method and system for green navigation of coastal ship

Abstract

The invention provides a hydrodynamic environment forecasting method and system for green navigation of coastal ships, and relates to the technical field of navigation. Aiming at the problem of relatively low accuracy of a forecast result in the prior art, the method comprises the steps of obtaining a calculation boundary condition; monitoring mark stations are arranged at the key positions, and actually-measured hydrodynamic environment data and actually-measured storm data are obtained; establishing a tide wave coupling numerical model according to calculation boundary conditions, and performing model calibration according to measured data; the calibrated tidal current wave coupling numerical model outputs initial environment forecast data according to calculation boundary conditions; comparing the actually measured real-time data with the initial environment forecast data to obtain forecast deviation; and dynamically correcting the calibrated tide wave coupling numerical model in a periodic manner according to the forecast deviation, and correcting the tide wave coupling numerical model to output final environment forecast data according to calculation boundary conditions. The periodic dynamic correction mode accurately adapts to the change characteristics of tidal current and waves, small deviation of each period is eliminated in time, and the accuracy of a forecast result is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of navigation technology, and in particular to a water power environment prediction method and system for coastal ship green navigation. BACKGROUND

[0002] Coastal water power environment is the main reason affecting the energy consumption and emission of ship navigation, and the water power environment mainly includes tidal current and wave. Influenced by multiple factors such as tides, ocean currents, monsoons, etc., it has strong spatio-temporal variability. When sailing against the waves, the wave impact frequency increases, and the resistance rises significantly; when sailing against the current, the ship needs additional power to maintain speed, and the oil consumption will also increase accordingly. If the coastal water power environment can be accurately predicted, the ship can be guided to choose the favorable spatio-temporal water power environment, which can achieve significant energy-saving and emission-reducing effect and help the ship green navigation.

[0003] The current coastal water power environment prediction field has gradually formed a composite technology system taking numerical simulation as the core, combining data assimilation technology to improve data precision, and supplemented by intelligent algorithm to optimize the prediction process. This system can integrate multi-source observation data and numerical calculation results, and basically meet the basic needs of the accuracy and real-time of the coastal water power environment prediction at the present stage. However, the data assimilation of the prediction method in the prior art is a static optimization of the numerical simulation results, and the core parameters of the prediction model are not adjusted. The adaptability of the fixed parameter prediction model to the dynamic changes of the coastal water power environment is poor, and the small deviation continues to accumulate with the time dimension, eventually forming a significant cumulative error. Due to the lack of dynamic real-time correction, the accuracy of the prediction results is low, which cannot meet the core needs of high-precision and long-period water power environment prediction for ship green navigation.

[0004] Therefore, it is of great significance to develop a water power environment prediction method and system for coastal ship green navigation to improve the accuracy of the prediction results. SUMMARY

[0005] In order to solve the problem of low accuracy of prediction results due to lack of dynamic real-time correction in the prior art, the present application provides a water power environment prediction method for coastal ship green navigation, which specifically includes the following steps: S1, obtaining the calculation boundary condition of the target coastal water area; S2, arranging monitoring stations at key positions of the target coastal water area, obtaining measured water power environment data through the monitoring stations, and obtaining measured wind wave data through the marine weather observation station; S3, establishing a tidal current wave coupling numerical model according to the calculation boundary condition, the tidal current wave coupling numerical model including a tidal current sub-model and a wave sub-model; S4, calibrate the tidal flow sub-model according to historical data of the measured hydrodynamic environment data, and calibrate the wave sub-model according to measured wave data, and couple the calibrated tidal flow sub-model and the calibrated wave sub-model according to a preset rule to obtain a calibrated tidal flow wave coupling numerical model; the calibrated tidal flow wave coupling numerical model outputs initial environment prediction data according to a calculation boundary condition; S5, compare real-time data of the measured hydrodynamic environment data with the initial environment prediction data to obtain a prediction deviation; and perform periodical dynamic correction on the calibrated tidal flow wave coupling numerical model according to the prediction deviation to obtain a corrected tidal flow wave coupling numerical model. The periodical dynamic correction comprises: controlling the tidal flow sub-model and the wave sub-model in the calibrated tidal flow wave coupling numerical model to output initial environment prediction data according to different periods respectively; obtaining a first period prediction deviation according to the initial environment prediction data output by the first period and first period real-time data of the measured hydrodynamic environment data; correcting the calibrated tidal flow wave coupling numerical model according to the first period prediction deviation, and the tidal flow wave coupling numerical model corrected by the first period prediction deviation predicts initial environment prediction data of a second period; correcting the tidal flow wave coupling numerical model corrected by the first period prediction deviation according to second period real-time data of the measured hydrodynamic environment data and the initial environment prediction data of the second period, and sequentially performing model correction according to each period to realize dynamic correction of the model. S6, the corrected tidal flow wave coupling numerical model outputs final environment prediction data according to a calculation boundary condition.

[0006] Further, in S5, the calibrated tidal flow wave coupling numerical model is corrected according to the prediction deviation to obtain a corrected tidal flow wave coupling numerical model, which comprises: dynamically correcting the tidal flow sub-model in the calibrated tidal flow wave coupling numerical model according to a first set period prediction deviation to obtain a corrected tidal flow sub-model; dynamically correcting the wave sub-model in the calibrated tidal flow wave coupling numerical model according to a second set period prediction deviation to obtain a corrected wave sub-model; and obtaining the corrected tidal flow wave coupling numerical model according to the corrected tidal flow sub-model and the corrected wave sub-model.

[0007] Further, the first set period is a quarter, and the second set period is several days or a week.

[0008] Further, in the S1, the calculated boundary conditions of the target coastal water area are obtained, including: obtaining the terrain boundary conditions of the target coastal water area based on terrain data; obtaining the shore boundary conditions of the target coastal water area based on shoreline data; obtaining the offshore boundary tide level driving conditions of the target coastal water area based on tide data; obtaining the wind field driving boundary conditions of the target coastal water area based on wind speed data; and obtaining the flow velocity boundary conditions of the target coastal water area based on vertical flow velocity data.

[0009] Further, in the S2, the monitoring stations are arranged at key positions in the target coastal water area, including: selecting the monitoring stations in the target coastal water area that have existing and obtainable measured hydrodynamic environmental data; and arranging monitoring stations in the target coastal water area if the monitoring stations that have existing and obtainable measured hydrodynamic environmental data are missing; wherein the point positions of the arranged monitoring stations cover at least the near-shore, off-shore, estuary, channel area, and the area near the tidal wave coupling boundary of the target coastal water area.

[0010] Further, the monitoring stations include shore markers and buoys.

[0011] Further, in the S3, the tidal wave coupling numerical model is established according to the calculated boundary conditions, including: dividing the target coastal water area into unstructured triangular grid cells, setting the grid scale and calculation time step according to the calculation accuracy requirement; determining the tidal flow sub-model and the wave sub-model according to the calculated boundary conditions, and coupling the tidal flow sub-model and the wave sub-model according to a predetermined rule; discretely solving the tidal flow sub-model and the wave sub-model in each grid cell to obtain hydrodynamic parameter results; and integrating the hydrodynamic parameter results of each grid cell to obtain the tidal wave coupling numerical model of the target coastal water area.

[0012] Further, after the final environmental prediction data is output by the corrected tidal wave coupling numerical model, the method further includes: performing vector decomposition on the final environmental prediction data; and constructing coastal hydrodynamic environmental prediction annual data according to the decomposed data.

[0013] Further, the vector decomposition on the final environmental prediction data includes: obtaining main channel physical parameters of the target coastal water area, the main channel physical parameters including channel edge longitude and latitude coordinates and beacon longitude and latitude coordinates; determining a ship heading along the channel based on the main channel physical parameters, the heading being consistent with the tangent of the channel direction; and decomposing the final environmental prediction data into ship forward tidal flow data, ship normal tidal flow data, ship forward wave data, and ship normal wave data according to the heading.

[0014] The application further provides a water power environment prediction system for green navigation of a coastal ship, which is used for performing the water power environment prediction method for green navigation of the coastal ship, and comprises: A first acquisition module is configured to acquire a calculation boundary condition of a target coastal water area. A second acquisition module is configured to arrange monitoring stations at key positions of the target coastal water area, acquire measured water power environment data through the monitoring stations, and acquire measured wind and wave data through a marine weather observation station. A model construction module is connected with the first acquisition module and configured to establish a tidal current and wave coupling numerical model according to the calculation boundary condition, wherein the tidal current and wave coupling numerical model comprises a tidal current sub-model and a wave sub-model. A calibration output module is connected with the first acquisition module, the second acquisition module and the model construction module, and configured to calibrate the tidal current sub-model according to historical data of the measured water power environment data, calibrate the wave sub-model according to the measured wind and wave data, obtain a calibrated tidal current and wave coupling numerical model according to a preset rule based on the calibrated tidal current sub-model and the calibrated wave sub-model, and control the calibrated tidal current and wave coupling numerical model to output initial environment prediction data according to the calculation boundary condition. A correction module is connected with the second acquisition module and the calibration output module, and configured to compare real-time data of the measured water power environment data with the initial environment prediction data to obtain a prediction deviation, correct the calibrated tidal current and wave coupling numerical model according to the prediction deviation to obtain a corrected tidal current and wave coupling numerical model, wherein the correction comprises: controlling the tidal current sub-model and the wave sub-model in the calibrated tidal current and wave coupling numerical model to output initial environment prediction data according to different periods respectively, obtaining a first period prediction deviation according to the initial environment prediction data output according to a first period and first period real-time data of the measured water power environment data, correcting the calibrated tidal current and wave coupling numerical model according to the first period prediction deviation, and predicting initial environment prediction data of a second period by the corrected tidal current and wave coupling numerical model after correction of the first period prediction deviation, correcting the corrected tidal current and wave coupling numerical model after correction of the first period prediction deviation according to second period real-time data of the measured water power environment data and the initial environment prediction data of the second period, and sequentially correcting the model according to each period to realize dynamic correction of the model. A final output module is connected with the first acquisition module and the correction module, and configured to control the corrected tidal current and wave coupling numerical model to output final environment prediction data according to the calculation boundary condition.

[0015] Compared with the prior art, the application has the following beneficial effects: The application obtains a calculated boundary condition of a target coastal water area, measured hydrodynamic environment data and measured wind wave data; a tidal current wave coupling numerical model is established according to the calculated boundary condition. The tidal current sub-model is calibrated according to historical data of the measured hydrodynamic environment data, and the wave sub-model is calibrated according to the measured wind wave data, to obtain a calibrated tidal current wave coupling numerical model. The calculated boundary condition is input into the calibrated tidal current wave coupling numerical model, and the calibrated tidal current wave coupling numerical model outputs initial environment prediction data; real-time data of the measured hydrodynamic environment data and the initial environment prediction data are compared to obtain a prediction deviation; the calibrated tidal current wave coupling numerical model is dynamically modified according to the prediction deviation in different periods to obtain a modified tidal current wave coupling numerical model, and the modified tidal current wave coupling numerical model outputs final environment prediction data according to the calculated boundary condition.

[0016] The periodical dynamic modification includes controlling the tidal current sub-model and the wave sub-model in the calibrated tidal current wave coupling numerical model to output initial environment prediction data according to different periods respectively; a first period prediction deviation is obtained according to the initial environment prediction data output by the first period and the first period real-time data of the measured hydrodynamic environment data; the calibrated tidal current wave coupling numerical model is modified according to the first period prediction deviation, and the tidal current wave coupling numerical model modified according to the first period prediction deviation predicts initial environment prediction data of a second period; the tidal current wave coupling numerical model modified according to the first period prediction deviation is modified according to the second period real-time data of the measured hydrodynamic environment data and the initial environment prediction data of the second period, and the model modification is performed according to each period in turn to realize dynamic modification of the model. The periodical dynamic modification can adapt to different variation characteristics of the tidal current and the wave, continuously feedback the measured deviation to the model and iteratively adjust the core parameters during the prediction process, to form a dynamic closed loop of prediction-verification deviation-modified parameter-re-prediction. The periodical dynamic modification mode can accurately adapt to the natural variation law of the tidal current and the wave, timely eliminate the small deviation generated in each round of prediction, avoid the continuous accumulation of errors with the extension of the prediction period from the root, and greatly improve the accuracy of the hydrodynamic environment prediction result.

[0017] In addition, the final environment prediction data can accurately reflect the real distribution characteristics of the tidal current and the wave in the target coastal water area, and can guide ships to avoid high-energy navigation environments such as top current and top wave, and select favorable space-time navigation conditions. The key problems of the prior art, such as prediction error accumulation with period and insufficient accuracy, are solved, and the accuracy and practicality of the coastal hydrodynamic environment prediction are significantly improved. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the specific embodiments or the prior art of the present application, the following will briefly introduce the drawings needed to be used in the specific embodiments or the prior art description. Obviously, the drawings described below are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0019] Figure 1 is a flow chart of a water power environment prediction method for green navigation of a coastal ship provided by an embodiment of the present application; Figure 2 is a comparison curve diagram of the tidal level and the measured tidal level in the calibrated tidal flow sub-model provided by an embodiment of the present application; Figure 3 is a structural schematic diagram of a water power environment prediction system for green navigation of a coastal ship provided by an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described clearly and completely below. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0021] The specific embodiments of the present application will be described below.

[0022] In view of the problem of low accuracy of prediction results in the prior art, the present application obtains calculation boundary conditions; monitoring stations are arranged at key positions to obtain measured water power environment data and measured wind wave data; a tidal flow wave coupling numerical model is established according to the calculation boundary conditions, and the model is calibrated according to the measured data; the calibrated tidal flow wave coupling numerical model outputs initial environment prediction data according to the calculation boundary conditions; the prediction deviation is obtained by comparing the measured real-time data and the initial environment prediction data; the calibrated tidal flow wave coupling numerical model is dynamically corrected according to the prediction deviation in periods, and the tidal flow wave coupling numerical model outputs final environment prediction data according to the calculation boundary conditions. The periodical dynamic correction mode accurately adapts to the change characteristics of the tidal flow and the wave, timely eliminates the slight deviation in each period, and improves the accuracy of the prediction results.

[0023] Embodiment 1 The embodiment of the present application provides a water power environment prediction method for green navigation of a coastal ship, Figure 1 is a flow chart of a water power environment prediction method for green navigation of a coastal ship provided by an embodiment of the present application, as shown in Figure 1 , and specifically includes the following steps: S1, obtain the calculation boundary condition of the target coastal water area.

[0024] The target coastal water area refers to a specific coastal sea area where the hydrodynamic environment prediction is to be carried out, and is the core service area of the ship green navigation. The calculation boundary condition is a core basic parameter set supporting the construction and solution of the tide wave coupling numerical model.

[0025] Specifically, obtaining the calculation boundary condition of the target coastal water area includes obtaining topographic data, shoreline data, tidal data, wind speed data, and vertical flow velocity data of the target coastal water area according to hydrological and meteorological data, topographic survey results, and tidal table data of the sea area. And based on the topographic data, the topographic boundary condition of the target coastal water area is obtained; based on the shoreline data, the shore boundary condition of the target coastal water area is obtained; based on the tidal data, the offshore boundary tidal level driving condition of the target coastal water area is obtained; based on the wind speed data, the wind field driving boundary condition of the target coastal water area is obtained; and based on the vertical flow velocity data, the flow velocity boundary condition of the target coastal water area is obtained.

[0026] Among them, the topographic boundary condition is obtained according to the topographic data, and the topographic boundary condition includes the topographic feature boundary parameter of the target coastal water area, which determines the topographic constraint rule of the water flow and the wave. The shore boundary condition is obtained according to the shoreline data, and the shore boundary condition includes the constraint boundary parameter of the shoreline to the water flow and the wave. The offshore boundary tidal level driving condition is obtained according to the tidal data, which includes the boundary parameter of the offshore tidal level driving the tidal flow of the target coastal water area. The wind field driving boundary condition is obtained according to the wind speed data, which includes the boundary parameter of the wind field driving the wave generation and propagation. The flow velocity boundary is converted from the vertical flow velocity data, which includes the boundary parameter of the initial flow velocity distribution of the target coastal water area.

[0027] By obtaining the calculation boundary condition of the target coastal water area, accurate input basis is provided for the subsequent model construction, ensuring that the model fits the actual geographical, hydrological, and meteorological characteristics of the target sea area.

[0028] S2, monitoring stations are arranged at key positions in the target coastal water area, and real-time hydrodynamic environment data are obtained through the monitoring stations; and real-time wind wave data are obtained through the marine weather observation station. It includes: selecting the monitoring stations in the target coastal water area that have real-time hydrodynamic environment data; if the monitoring stations that have real-time hydrodynamic environment data are missing, monitoring stations are arranged in the target coastal water area; wherein the point positions of the arranged monitoring stations cover at least the nearshore, offshore, estuary, channel area, and the area near the tide wave coupling boundary of the target coastal water area.

[0029] The key positions of the target coastal water area refer to core areas in the target coastal water area that can reflect different water depths, topographies and wave propagation characteristics, and specifically include nearshore, offshore, estuary, channel areas and areas near the tidal current and wave coupling boundary. The monitoring stations are sites or devices for observing coastal hydrodynamic environment data, and the monitoring stations include shore stations and buoys. The marine meteorological observation stations are professional sites for monitoring marine meteorological elements and are carriers for obtaining wind wave measured data. The measured hydrodynamic environment data are actual hydrodynamic data of the target sea area obtained through the monitoring stations, and the measured wind wave data are actual wind wave data of the target sea area obtained through the marine meteorological observation stations.

[0030] By arranging the monitoring stations at the key positions and covering different typical areas of the target sea area, it is ensured that the measured data can reflect the true distribution characteristics of the hydrodynamic and wind wave, and the model calibration deviation caused by one-sided data is avoided. By obtaining the measured hydrodynamic environment data and the measured wind wave data, real historical verification basis is provided for the initial calibration of the subsequent tidal current sub-model and wave sub-model, which is beneficial to the accurate construction of the model.

[0031] S3, establishing a tidal current and wave coupling numerical model according to the calculated boundary conditions, wherein the tidal current and wave coupling numerical model comprises a tidal current sub-model and a wave sub-model.

[0032] The tidal current and wave coupling numerical model is a computer numerical model integrating the tidal current sub-model and the wave sub-model to simulate the coupling effect of tidal current and wave, and is used for simulation and prediction of the hydrodynamic environment of the target coastal water area. The tidal current sub-model is a sub-model constructed based on the continuity equation and momentum equation of fluid mechanics, and is used for simulating the tidal current motion characteristics of the target coastal water area. The wave sub-model is a sub-model constructed based on the wave action conservation equation, driven by Cross Calibrated Multi-Platform (CCMP) and Climate Forecast System Reanalysis (CFSR) numerical meteorological wind data, and is used for simulating the wave motion characteristics of the target coastal water area.

[0033] Specifically, the tidal current and wave coupling numerical model is established according to the calculated boundary conditions, which comprises: dividing the target coastal water area into unstructured triangular grid elements, setting the grid scale and calculation time step according to the calculation accuracy requirement; determining the tidal current sub-model and the wave sub-model according to the calculated boundary conditions, and coupling the tidal current sub-model and the wave sub-model according to a preset rule; discretely solving the tidal current sub-model and the wave sub-model in each grid element to obtain hydrodynamic parameter results; and integrating the hydrodynamic parameter results of each grid element to obtain the tidal current and wave coupling numerical model of the target coastal water area.

[0034] To address the topographical and shoreline characteristics of the target coastal waters, unstructured triangular mesh units are used, with localized densification in key areas such as waterways and estuaries. The mesh scale and computation time step are set according to the required accuracy of the hydrodynamic environment forecast results for the target coastal waters. The computation time step refers to the time interval for iterative solutions of the coupled tidal wave numerical model, and is a core parameter for the model's time-dimensional computational accuracy. By using unstructured triangular meshes, the model adapts to the complex topography and shoreline characteristics of the coastal waters, while localized densification ensures computational accuracy in key areas such as waterways and estuaries.

[0035] By obtaining parameters such as topography, shoreline, and flow velocity from the computational boundary conditions, a tidal current sub-model is constructed using the continuity equation and momentum equation from fluid mechanics. The continuity equation is shown below: ; in, This indicates the water level (m) relative to a certain datum surface. t Indicates time (s). h This indicates the water depth (m) relative to a certain datum surface. u It represents the average vertical velocity (m / s) in the x-direction (i.e., east-west direction). v This represents the average vertical velocity (m / s) in the y-direction (i.e., north-south direction). x Represents the east-west coordinate (m). y Represents the north-south coordinate (m).

[0036] The momentum equation is as follows: The momentum equation in the x-direction is: ; y-momentum equation: ; in, g This represents the acceleration due to gravity (9.8 m / s²). f Coriolis coefficient, f =2 ω sin φ , φ Latitude ω This is the Earth's rotation speed. f b This indicates the coefficient of friction at the bottom. f b = g / C 2 , C This is the Xie Cai coefficient. The turbulent viscosity coefficient of the water flow in the x-direction (m) 2 / s), The turbulent viscosity coefficient of the water flow in the y direction (m) 2 / s).

[0037] The wind speed and other parameters of the driving wind field are obtained by calculating the boundary conditions, and the wave action conservation equation is used to construct the wave sub-model. The wave action conservation equation is as follows: ; Wherein, N represents the wave action amount, is a divergence operator, representing the propagation change of wave action in geographical space, S is a source function expressed in spectral density in the energy balance equation, and sigma is the relative frequency, is the wave group velocity, , is the wave group velocity component of the wave action propagating in the x direction of geographical space, represents the wave group velocity component of the wave action propagating in the y direction of geographical space, represents the wave group velocity component caused by the change of water depth and flow, which quantifies the influence of water depth and flow on the wave relative frequency, and is the key correction data reflecting the frequency change, represents the wave group velocity component caused by wave refraction due to water depth and flow, which quantifies the correction degree of water depth and flow to the wave direction, and is the core data reflecting the wave direction deflection.

[0038] The tidal flow sub-model and the wave sub-model are coupled by preset rules. The preset rules include: the tidal flow sub-model provides water depth data and flow velocity field data to the wave sub-model as the core basic input for the wave sub-model to calculate the wave motion characteristics based on the wave action conservation equation; the wave sub-model feeds back the mass flux and radiation stress generated by wave action to the tidal flow sub-model, so as to quantify the driving and influence of wave on tidal flow, and realize accurate simulation of the wave-current coupling effect. At the same time, for the wave energy change process represented by the source function S of the energy balance of the wave sub-model, considering the actual physical phenomenon that the wave will be broken and energy dissipated in the propagation process, the energy loss in this process is numerically simulated by two quantization parameters, white cap dissipation term and bottom friction term, so as to restore the energy attenuation law of wave due to surface breaking and seabed friction. In addition, in order to ensure the stability of the coupling calculation, the coupling time step of the tidal flow sub-model and the wave sub-model needs to be matched, and the message passing interface (Message Passing Interface, MPI) parallel computing technology is used to improve the solving efficiency of the whole coupled numerical model.

[0039] The continuity equation and momentum equation of the tidal flow sub-model and the wave action conservation equation of the wave sub-model are discretized and solved in each unstructured triangular grid cell by using the finite volume method, that is, the continuous control equation is converted into discrete algebraic equation to obtain the hydrodynamic parameter results of each grid cell. The hydrodynamic parameter results include the water levelζ , flow rate u / v and other parameters, and wave action N, wave height, wave direction and other parameters in the wave sub-model. The tidal flow, wave hydrodynamic parameter results of all grid units are summarized to form parameter distribution covering the entire target coastal water area, and finally a complete numerical model reflecting the coupling effect of tidal flow and wave is constructed.

[0040] S4, calibrate the tidal flow sub-model according to the historical data of the measured hydrodynamic environment data, and calibrate the wave sub-model according to the measured wind wave data, and couple the calibrated tidal flow sub-model and the calibrated wave sub-model according to the coupling preset rule in the above embodiment to obtain the calibrated tidal flow wave coupling numerical model; the calibrated tidal flow wave coupling numerical model outputs the initial environmental prediction data according to the calculation boundary condition.

[0041] The results of tidal level, flow rate and flow direction calculated by the tidal flow sub-model are compared with the measured hydrodynamic environment historical data, and the parameters such as eddy viscosity coefficient and friction coefficient are adjusted according to the accuracy requirements in the standard technical regulations until the accuracy requirements are met. The wind speed, wind direction and wave height calculated by the wave sub-model are compared with the measured wind wave data driven by the CCMP / CFSR numerical meteorological wind data, and if the deviation exceeds the reasonable range, the model parameters are adjusted until the calculation results fit the measured data.

[0042] Exemplary, Figure 2 is a comparison curve of the calibrated tidal level in the tidal flow sub-model and the measured tidal level, the measured value represents the measured hydrodynamic environment historical data, and the calculated value represents the data output by the calibrated tidal flow sub-model, which is Figure 2 It can be seen that the data output by the calibrated tidal flow sub-model is close to the measured value, and the change trend is consistent. By calibrating and correcting the model parameter deviation through the measured historical data, the simulation accuracy of the model for the target sea area hydrodynamic environment is improved. The calibrated model can reduce the cumulative error caused by the extension of the prediction period, and lay a core foundation for subsequent dynamic correction and high-precision prediction.

[0043] The above calculation boundary condition is taken as the core input parameter and is imported into the tidal flow wave coupling numerical model calibrated by the measured hydrodynamic environment historical data and the measured wind wave data. The calibrated tidal flow wave coupling numerical model is based on the continuity equation and momentum equation of the tidal flow sub-model, the wave action conservation equation of the wave sub-model, the coupling rule and the finite volume method discrete solving rule. The hydrodynamic environment of the target coastal water area is numerically simulated and calculated, and the initial environmental prediction data covering the core elements of the target coastal water area such as tidal flow and wave are output.

[0044] S5, comparing the real-time data of the measured hydrodynamic environment data with the initial environment prediction data to obtain a prediction deviation; performing periodical dynamic correction on the calibrated tidal current wave coupling numerical model according to the prediction deviation to obtain a corrected tidal current wave coupling numerical model.

[0045] The periodical dynamic correction comprises: controlling the tidal current sub-model and the wave sub-model in the calibrated tidal current wave coupling numerical model to output the initial environment prediction data according to different periods respectively; obtaining a first period prediction deviation according to the initial environment prediction data output in the first period and the first period real-time data of the measured hydrodynamic environment data; correcting the calibrated tidal current wave coupling numerical model according to the first period prediction deviation, and the tidal current wave coupling numerical model corrected by the first period prediction deviation predicts the initial environment prediction data in a second period; correcting the tidal current wave coupling numerical model corrected by the first period prediction deviation according to the second period real-time data of the measured hydrodynamic environment data and the initial environment prediction data in the second period, and sequentially performing model correction according to each period to realize dynamic correction of the model.

[0046] Specifically, the method comprises: performing dynamic correction on the tidal current sub-model in the calibrated tidal current wave coupling numerical model according to the prediction deviation of a first set period to obtain a corrected tidal current sub-model; performing dynamic correction on the wave sub-model in the calibrated tidal current wave coupling numerical model according to the prediction deviation of a second set period to obtain a corrected wave sub-model; and obtaining the corrected tidal current wave coupling numerical model according to the corrected tidal current sub-model and the corrected wave sub-model.

[0047] The first set period is a time period set for dynamic correction of the tidal current sub-model, for example, the first set period is a quarter, and the first set period is a core time node for verifying the tidal current prediction deviation and performing dynamic correction. The corrected tidal current sub-model is a tidal current sub-model optimized in precision after being corrected by the prediction deviation in a quarter period. The second set period is a time period set for dynamic correction of the wave sub-model, specifically, the second set period is several days or a week, and the second set period can adapt to the correction time node of the wave short period change characteristics. The corrected wave sub-model is a wave sub-model optimized in precision after being corrected by the prediction deviation in a period of several days or a week.

[0048] At the end of the first set period, the forecast data output by the calibrated tidal current sub-model is compared with the measured tidal current data from buoys and shore markers to calculate the forecast deviation. At the end of the second set period, the forecast data output by the calibrated wave sub-model is compared with the measured wave data to calculate the forecast deviation. Based on the forecast deviation of the first set period, parameters such as the eddy viscosity coefficient and friction coefficient of the tidal current sub-model are adjusted to complete dynamic correction, resulting in the corrected tidal current sub-model. Based on the forecast deviation of the second set period, relevant parameters of the wave sub-model are adjusted to complete dynamic correction, resulting in the corrected wave sub-model. The corrected tidal current sub-model and the corrected wave sub-model are integrated according to preset coupling rules to obtain the corrected tidal current-wave coupled numerical model.

[0049] Differentiated correction cycles are set for the different spatiotemporal variations of tides and waves. Periodic dynamic corrections can adapt to the different changing characteristics of tides and waves. During the forecasting process, measured deviations are continuously fed back to the model, and core parameters are iteratively adjusted, forming a dynamic closed loop of forecasting-verifying deviations-correcting parameters-forecasting again. This dynamic correction mode can accurately adapt to the natural changing patterns of tides and waves, promptly eliminate minor deviations generated in each round of forecasting, and effectively reduce forecast errors.

[0050] S6. The modified tidal wave coupled numerical model outputs the final environmental forecast data based on the calculated boundary conditions.

[0051] After correcting the final environmental forecast data output by the coupled tidal wave numerical model, the process also includes: performing vector decomposition on the final environmental forecast data; and constructing annual coastal hydrodynamic environmental forecast data based on the vector decomposed data.

[0052] Specifically, the final environmental forecast data is decomposed into vectors, including: obtaining the physical parameters of the main channel in the target coastal waters, which include the latitude and longitude coordinates of the channel edge and the navigation mark; determining the course of the ship along the channel based on the main channel physical parameters, with the course consistent with the tangent of the channel direction; and decomposing the final environmental forecast data according to the course into tidal current data in the ship's forward direction, tidal current data in the ship's normal direction, wave data in the ship's forward direction, and wave data in the ship's normal direction.

[0053] The general hydrodynamic environment prediction data is converted into the forward and normal data that fit the actual navigation scene of the ship by vector decomposition of the final environment prediction data, the direct influence of the tidal current and the wave on the ship navigation is accurately quantified, and the problem that the general hydrodynamic environment prediction data cannot directly guide the green navigation of the ship is solved. By constructing the coastal hydrodynamic environment prediction annual database and integrating the hydrodynamic environment prediction data in the whole cycle, the forward and normal hydrodynamic reference that can be directly applied is provided for the ship, the high energy consumption navigation state of the ship is avoided, the energy saving effect is realized, data support is provided for the long-term route planning and energy consumption control of the shipping enterprise, and the development needs of green shipping are met.

[0054] In the embodiment, the calculation boundary condition, the measured hydrodynamic environment data and the measured wind wave data of a target coastal water area are obtained, and a tidal current wave coupling numerical model is established according to the calculation boundary condition. The tidal current sub-model is calibrated according to the historical data of the measured hydrodynamic environment data, and the wave sub-model is calibrated according to the measured wind wave data, to obtain a calibrated tidal current wave coupling numerical model. The calculation boundary condition is input into the calibrated tidal current wave coupling numerical model, and the calibrated tidal current wave coupling numerical model outputs initial environment prediction data. The real-time data of the measured hydrodynamic environment data and the initial environment prediction data are compared to obtain a prediction deviation. The calibrated tidal current wave coupling numerical model is dynamically modified in a period according to the prediction deviation, to obtain a modified tidal current wave coupling numerical model, and the modified tidal current wave coupling numerical model outputs final environment prediction data according to the calculation boundary condition.

[0055] The periodical dynamic modification includes controlling the tidal current sub-model and the wave sub-model in the calibrated tidal current wave coupling numerical model to output initial environment prediction data according to different periods respectively, obtaining a first period prediction deviation according to the initial environment prediction data output by the first period and the first period real-time data of the measured hydrodynamic environment data, modifying the calibrated tidal current wave coupling numerical model according to the first period prediction deviation, and predicting the initial environment prediction data of the second period by the tidal current wave coupling numerical model modified by the first period prediction deviation. The tidal current wave coupling numerical model modified by the first period prediction deviation is modified according to the second period real-time data of the measured hydrodynamic environment data and the initial environment prediction data of the second period, and the model modification is performed according to each period in turn, so as to realize the dynamic modification of the model. The periodical dynamic modification can adapt to the different change characteristics of the tidal current and the wave, continuously feedback the measured deviation to the model and iteratively adjust the core parameters in the prediction process, and form a dynamic closed loop of prediction-verification deviation-modification parameter-re-prediction. This periodical dynamic modification mode can accurately adapt to the natural change law of the tidal current and the wave, timely eliminate the small deviation generated in each round of prediction, avoid the continuous accumulation of errors with the prolongation of the prediction period from the root, and greatly improve the accuracy of the hydrodynamic environment prediction result.

[0056] In addition, the final environmental prediction data can accurately reflect the real distribution characteristics of the tidal current and wave of the target coastal water area, and can guide the ship to avoid high-energy consumption navigation environment such as top flow and top wave, and select favorable space-time navigation conditions. The key problem of cumulative prediction error and insufficient accuracy of the prior art is solved, and the accuracy and practicality of the coastal hydrodynamic environment prediction are significantly improved.

[0057] Embodiment 2 The embodiment of the present application also provides a hydrodynamic environment prediction system for green navigation of a coastal ship, Figure 3 is a structural schematic diagram of a hydrodynamic environment prediction system for green navigation of a coastal ship provided by the embodiment of the present application, as Figure 3 shown, the system comprises: A first acquisition module is configured to acquire the calculation boundary condition of the target coastal water area. A second acquisition module is configured to arrange a monitoring station at a key position of the target coastal water area, acquire measured hydrodynamic environment data through the monitoring station, and acquire measured wind wave data through a marine weather observation station. A model construction module is connected with the first acquisition module, configured to establish a tidal current wave coupling numerical model according to the calculation boundary condition, wherein the tidal current wave coupling numerical model comprises a tidal current sub-model and a wave sub-model. A calibration output module is connected with the first acquisition module, the second acquisition module and the model construction module, configured to calibrate the tidal current sub-model according to the historical data of the measured hydrodynamic environment data, calibrate the wave sub-model according to the measured wind wave data, obtain the calibrated tidal current wave coupling numerical model according to the pre-set rule based on the calibrated tidal current sub-model and the calibrated wave sub-model, and control the calibrated tidal current wave coupling numerical model to output the initial environmental prediction data according to the calculation boundary condition. The correction module is connected with the second acquisition module and the calibration output module, and is configured to compare real-time data of the measured hydrodynamic environment data with the initial environment prediction data to obtain a prediction deviation; and correct the calibrated tidal current and wave coupling numerical model according to the prediction deviation to obtain a corrected tidal current and wave coupling numerical model; wherein the periodical dynamic correction comprises: controlling the tidal current sub-model and the wave sub-model in the calibrated tidal current and wave coupling numerical model to output the initial environment prediction data according to different periods respectively; obtaining a first period prediction deviation according to the initial environment prediction data output by the first period and the first period real-time data of the measured hydrodynamic environment data; correcting the calibrated tidal current and wave coupling numerical model according to the first period prediction deviation; the tidal current and wave coupling numerical model corrected by the first period prediction deviation predicts the initial environment prediction data of a second period; and correcting the tidal current and wave coupling numerical model corrected by the first period prediction deviation according to the second period real-time data of the measured hydrodynamic environment data and the initial environment prediction data of the second period, and sequentially performing model correction according to each period to realize dynamic correction of the model. The final output module is connected with the first acquisition module and the correction module, and is configured to control the corrected tidal current and wave coupling numerical model to output final environment prediction data according to the calculated boundary conditions.

[0058] The coastal ship green navigation hydrodynamic environment prediction system provided by the embodiment has the beneficial effects of the above-mentioned embodiments, and details are not repeated here.

[0059] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the above embodiments, or make equivalent replacement to part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present application.

Claims

1. A hydrodynamic environmental prediction method for green sailing of a coastal vessel, characterized by, The method comprises the following steps: S1, obtaining a calculation boundary condition of a target coastal water area; S2, arranging monitoring stations at key positions of the target coastal water area, obtaining measured hydrodynamic environment data through the monitoring stations, and obtaining measured wind wave data through a marine weather observation station; S3, establishing a tidal wave coupling numerical model according to the calculation boundary condition, wherein the tidal wave coupling numerical model comprises a tidal sub-model and a wave sub-model; S4, calibrating the tidal sub-model according to historical data of the measured hydrodynamic environment data, calibrating the wave sub-model according to the measured wind wave data, coupling the calibrated tidal sub-model and the calibrated wave sub-model according to a preset rule, and obtaining a calibrated tidal wave coupling numerical model; the calibrated tidal wave coupling numerical model outputs initial environment prediction data according to the calculation boundary condition; S5, comparing real-time data of the measured hydrodynamic environment data with the initial environment prediction data to obtain a prediction deviation; performing periodical dynamic correction on the calibrated tidal wave coupling numerical model according to the prediction deviation, and obtaining a corrected tidal wave coupling numerical model; The periodical dynamic correction comprises: controlling the tidal sub-model and the wave sub-model in the calibrated tidal wave coupling numerical model to output initial environment prediction data according to different periods respectively; obtaining a first period prediction deviation according to the initial environment prediction data output by the first period and the first period real-time data of the measured hydrodynamic environment data; correcting the calibrated tidal wave coupling numerical model according to the first period prediction deviation; the tidal wave coupling numerical model corrected according to the first period prediction deviation predicts initial environment prediction data of a second period; correcting the tidal wave coupling numerical model corrected according to the first period prediction deviation according to the second period real-time data of the measured hydrodynamic environment data and the initial environment prediction data of the second period, and sequentially performing model correction according to each period to realize dynamic correction of the model; S6, the corrected tidal wave coupling numerical model outputs final environment prediction data according to the calculation boundary condition.

2. The method of claim 1, wherein, In S5, the calibrated tidal wave coupling numerical model is corrected according to the prediction deviation, and a corrected tidal wave coupling numerical model is obtained, which comprises: performing dynamic correction on the tidal sub-model in the calibrated tidal wave coupling numerical model according to a first set period prediction deviation, and obtaining a corrected tidal sub-model; performing dynamic correction on the wave sub-model in the calibrated tidal wave coupling numerical model according to a second set period prediction deviation, and obtaining a corrected wave sub-model; obtaining the corrected tidal wave coupling numerical model according to the corrected tidal sub-model and the corrected wave sub-model.

3. The method of claim 2, wherein, The first set period is a quarter, and the second set period is several days or a week.

4. The method of claim 1, wherein, In S1, the calculation boundary condition of the target coastal water area is obtained, which comprises: obtaining a topographic boundary condition of the target coastal water area based on topographic data; obtaining a shore boundary condition of the target coastal water area based on shore line data; obtaining an offshore boundary tide level driving condition of the target coastal water area based on tide data; obtaining a wind field driving boundary condition of the target coastal water area based on wind speed data; The flow velocity boundary condition of the target coastal water area is obtained based on the vertical flow velocity data.

5. The method of claim 1, wherein, In the S2, monitoring stations are arranged at key positions of the target coastal water area, including: Selecting monitoring stations in the target coastal water area that have existing and obtainable measured hydrodynamic environment data; If the monitoring stations that have existing and obtainable measured hydrodynamic environment data are missing, monitoring stations are arranged in the target coastal water area; wherein the point positions of the arranged monitoring stations cover at least the near-shore, off-shore, estuary, channel region and the region near the tidal wave coupling boundary of the target coastal water area.

6. The method of claim 5, wherein, The monitoring stations include shore stations and buoys.

7. The method of claim 1, wherein, In the S3, a tidal wave coupling numerical model is established according to the calculated boundary condition, including: The target coastal water area is divided into unstructured triangular grid cells, and the grid size and calculation time step are set according to the calculation accuracy requirement; The tidal flow sub-model and the wave sub-model are determined according to the calculated boundary condition, and the tidal flow sub-model and the wave sub-model are coupled according to a preset rule; The tidal flow sub-model and the wave sub-model are discretely solved in each grid cell to obtain hydrodynamic parameter results; The hydrodynamic parameter results of each grid cell are integrated to obtain the tidal wave coupling numerical model of the target coastal water area.

8. The method of claim 1, wherein, After the final environmental prediction data is output by the corrected tidal wave coupling numerical model, the method further includes: Vector decomposition is performed on the final environmental prediction data; Annual data of the coastal hydrodynamic environment prediction is constructed according to the data after vector decomposition.

9. The hydrodynamic environmental forecasting method for green sailing of a coastal vessel according to claim 8, characterized in that, The vector decomposition of the final environmental prediction data includes: Obtaining the main channel physical parameters of the target coastal water area, including the channel edge latitude and longitude coordinates and the beacon latitude and longitude coordinates; Determining the heading of the ship sailing along the channel based on the main channel physical parameters, wherein the heading is consistent with the tangent of the channel direction; The final environmental prediction data is decomposed into ship forward tidal flow data, ship normal tidal flow data, ship forward wave data and ship normal wave data according to the heading.

10. A hydrodynamic environmental forecasting system for green sailing of a coastal vessel, characterized by The system is used to perform the method of claim 1-9 for predicting the hydrodynamic environment of the coastal ship green navigation, and the system includes: A first obtaining module for obtaining the calculation boundary condition of the target coastal water area; A second obtaining module for arranging monitoring stations at key positions of the target coastal water area, obtaining measured hydrodynamic environment data through the monitoring stations, and obtaining measured wind wave data through the marine weather observation station; A model construction module connected with the first obtaining module, for establishing a tidal wave coupling numerical model according to the calculation boundary condition, wherein the tidal wave coupling numerical model includes a tidal flow sub-model and a wave sub-model; The calibration output module is connected with the first acquisition module, the second acquisition module and the model construction module, configured to calibrate the tidal flow sub-model according to historical data of the measured hydrodynamic environment data, calibrate the wave sub-model according to the measured wind wave data, and obtain the calibrated tidal flow wave coupling numerical model according to the calibrated tidal flow sub-model and the calibrated wave sub-model according to a preset rule; and control the calibrated tidal flow wave coupling numerical model to output initial environment prediction data according to the calculation boundary condition. The correction module is connected with the second acquisition module and the calibration output module, configured to compare real-time data of the measured hydrodynamic environment data with the initial environment prediction data to obtain a prediction deviation; and correct the calibrated tidal flow wave coupling numerical model according to the prediction deviation in a period to obtain a corrected tidal flow wave coupling numerical model; wherein the periodical dynamic correction includes: controlling the tidal flow sub-model and the wave sub-model in the calibrated tidal flow wave coupling numerical model to output the initial environment prediction data according to different periods respectively; obtaining a first period prediction deviation according to the initial environment prediction data output in the first period and first period real-time data of the measured hydrodynamic environment data; correcting the calibrated tidal flow wave coupling numerical model according to the first period prediction deviation, and the tidal flow wave coupling numerical model corrected according to the first period prediction deviation predicts initial environment prediction data in a second period; correcting the tidal flow wave coupling numerical model corrected according to the first period prediction deviation according to second period real-time data of the measured hydrodynamic environment data and the initial environment prediction data in the second period, and sequentially correcting the model according to each period to realize dynamic correction of the model. The final output module is connected with the first acquisition module and the correction module, configured to control the corrected tidal flow wave coupling numerical model to output final environment prediction data according to the calculation boundary condition.

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