CN115564150A - Oil spill track prediction method based on stokes drift and tide mixing mechanism - Google Patents

Oil spill track prediction method based on stokes drift and tide mixing mechanism Download PDF

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CN115564150A
CN115564150A CN202211553173.7A CN202211553173A CN115564150A CN 115564150 A CN115564150 A CN 115564150A CN 202211553173 A CN202211553173 A CN 202211553173A CN 115564150 A CN115564150 A CN 115564150A
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oil spill
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tide
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stokes
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赵一飞
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CCCC First Harbor Engineering Co Ltd
Tianjin Port Engineering Institute Ltd of CCCC Frst Harbor Engineering Co Ltd
Tianjin Harbor Engineering Quality Inspection Center Co Ltd
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Tianjin Port Engineering Institute Ltd of CCCC Frst Harbor Engineering Co Ltd
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Abstract

The invention discloses an oil spill track prediction method based on stokes shift and tide mixing mechanism, which comprises the steps of firstly correcting a POM (point of sale) model to enable the POM model to include a tide mixing parameterization calculation method; then, operating the corrected POM model at the oil spill accident occurrence time period to obtain the sea surface flow velocity containing the tide mixing influence; inputting the wind field file into a SWAN model, calculating a wave field during an oil spill event by using the SWAN model, and outputting wave parameters; then substituting the wave parameters into a Stokes drift velocity calculation formula to calculate to obtain the Stokes drift velocity; and finally, inputting the terrain file, the wind field file, the obtained sea surface flow velocity containing the tidal mixing influence and the Stokes drift velocity into a GNOME oil spill prediction model, operating the GNOME oil spill prediction model, and recording oil film position information of different time nodes to obtain an oil spill track image. According to the method, the stokes shift and tide mixing mechanism is integrated into the prediction of the oil spill track, so that a prediction result with higher precision is obtained.

Description

Oil spill track prediction method based on stokes drift and tide mixing mechanism
Technical Field
The invention belongs to the technical field of data processing technology and marine oil spill track prediction, and particularly relates to an oil spill track prediction method based on stokes drifting and tide mixing mechanisms.
Background
In recent years, marine oil leakage accidents are increasing due to ship navigation and marine operation, and the risk of oil spill is further increased along with the expansion of the scale of marine oil development. The oil spill accident has the characteristics of strong burst, large pollution range, long duration and high diffusion rate. After an accident happens, whether emergency response can be rapidly and effectively performed plays a key role in controlling pollution and reducing economic loss. The oil spill numerical simulation can accurately and quickly carry out simulation prediction on the oil spill track, and the oil spill model is an effective tool for simulating and predicting the oil pollutants in the sea, and can provide effective decision support for the prevention of accidents and emergency rescue work. A set of complete, accurate and effective oil spill prediction method can predict the movement track and behavior of oil spill after an accident occurs, is one of key technologies of offshore oil spill emergency response, and is also an important component of marine disaster prevention work. Therefore, the efficient oil spill prediction method has important theoretical and practical significance for deepening scientific understanding of the marine oil spill transportation process and improving risk prevention and emergency response capability of oil spill accidents, and plays a key disaster treatment and guarantee role in production behaviors of marine vessel navigation, vessel construction operation and the like.
In the currently applied oil spill simulation and prediction methods, the considered main motion processes are drift and random diffusion, the main driving factors are wind and flow, and the influence of important marine physical processes on oil spill tracks, such as tide mixing and Stokes drift, is neglected. Further improvement of the oil spill track prediction should emphasize the perfection of the marine physical process to obtain more accurate marine hydrological data for use in the oil spill track prediction with higher accuracy.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides an oil spilling track prediction method based on stokes shift and tide mixing mechanisms. The tide mixing phenomenon has obvious influence on ocean circulation, the Stokes drift induced by nonlinear sea waves is an important factor which cannot be ignored when sea surface flow velocity is calculated, the integration of two physical processes can enable a physical ocean model to calculate the sea flow velocity more accurately, flow velocity data used for oil spill track prediction is closer to an actual value, a prediction result with higher precision is obtained, and the defects that a driving factor is single and a physical mechanism is incomplete in the existing oil spill prediction method are overcome.
The technical scheme adopted by the invention is as follows:
a method for predicting an oil spill track based on stokes shift and tide mixing mechanism comprises the following steps:
step 1, modifying the POM model, and adding a tide mixing parameterization equation into a turbulence closed equation in the POM model to enable the POM model to contain a parameterization calculation method of tide mixing;
step 2, operating the corrected POM model at the oil spill accident occurrence time period to obtain the sea surface flow velocity containing the tide mixing influence;
step 3, inputting the wind field file into a SWAN model, calculating a wave field during an oil spill event by using the SWAN model, and outputting wave parameters;
step 4, substituting the wave parameters obtained in the step 3 into a Stokes drift velocity calculation formula to calculate and obtain the Stokes drift velocity;
and step 5, inputting the terrain file, the wind field file, the sea surface flow velocity containing the tide mixing influence obtained in the step 2 and the Stokes drift velocity obtained in the step 4 into a GNOME oil spill prediction model, operating the model, and recording oil film position information of different time nodes to obtain an oil spill track image.
In the above technical solution, in step 1, a tide mixing parameterized equation is added to a turbulence closed equation in the POM model, and the modified turbulence closed equation is obtained as follows:
Figure 459386DEST_PATH_IMAGE001
（1）
Figure 120175DEST_PATH_IMAGE002
（2）
in the above formula:t 0 is the time;U 0 、V 0 、W 0 respectively in a Cartesian coordinate systemx 0 、y 0 、z 0 A component of flow velocity in the direction;ρis the density after the adiabatic decay rate correction,ρ 0 is the density of the seawater, and is,gis the acceleration of gravity;qis the energy of the turbulence,lis the turbulent mixing length;A H is thatq 2 、q 2 lThe horizontal diffusion coefficient of (d);K H 、K q to representq 2 、q 2 lThe vertical diffusion coefficient of (a) is,
Figure 200126DEST_PATH_IMAGE003
is a wall approximation function;B 1 、E 1 、E 3 is a constant of experience that is,E 1 =E 3 =1.8、B 1 =16.6；K M is the vertical turbulent mixing coefficient,K tidal is the wet mix factor;
Figure 22589DEST_PATH_IMAGE004
（3）
in the formula (3), the reaction mixture is,
Figure 181300DEST_PATH_IMAGE005
in order to achieve a high mixing efficiency,
Figure 645779DEST_PATH_IMAGE005
=0.2，q 1 in order to be able to determine the rate of tidal energy dissipation,q 1 =0.3，ρ 0 the density of the seawater is shown as the density of the seawater,Nin order to be the buoyancy frequency,Ein order to provide for a flux of tidal energy,Fis a vertical dissipation function;
frequency of buoyancyNDensity output according to POM modelThe data are obtained by the following specific calculation formula:
Figure 580237DEST_PATH_IMAGE006
（4）
wherein the content of the first and second substances,gin order to be the acceleration of the gravity,ρ 0 is the density of seawater;
said flux of tidal energyEThe calculation formula of (a) is as follows:
Figure 839180DEST_PATH_IMAGE007
（5）
wherein the content of the first and second substances,ρ 1 is the reference density of seawater;N b is the sea floor buoyancy frequency;
Figure 593509DEST_PATH_IMAGE008
is the average tidal flow velocity, obtained from the output of the Princeton ocean model;κ=2 pi/(2000), which is the characteristic wave number of the terrain;h 2 representing the sea floor roughness, calculated from the terrain profile data, representing the mean square of the height deviation from a polynomial fitting plane to the actual terrain, said polynomial fitting plane being represented as:L=a+bx+cy+dxy，a、b、c、dare all parameters;
the vertical dissipation functionFThe calculation formula of (a) is as follows:
Figure 471467DEST_PATH_IMAGE009
（6）
wherein the content of the first and second substances,His the total height of the water column;ζis the scale of the vertical dissipation and,ζ=500；Zthe negative value of the water depth value.
In the above technical solution, in step 3, the wave parameters include: effective wave height, wavelength, average wave period and wave direction.
In the above technical solution, in step 4, the Stokes shift rate calculation formula is:
Figure 260431DEST_PATH_IMAGE010
（7）
Figure 955855DEST_PATH_IMAGE011
（8）
Figure 463059DEST_PATH_IMAGE012
（9）
in the formula (I), the compound is shown in the specification,U s is the speed of the Stokes shift and,u s is the east component of the Stokes drift velocity,v s is the north component of the Stokes drift velocity,zis a vertical coordinate and is a vertical coordinate,gis the acceleration of the force of gravity and,θis the direction of the wave,H s is the effective wave height,Tis the average period of the waves,λis the wavelength;H s 、T、λ、θall the parameters are calculated by the SWAN ocean wave model in the step 3.
In the above technical solution, in step 5, when the GNOME oil spill prediction model is operated, the set initial conditions include: oil spill, oil type, accident occurrence time, duration and diffusion rate.
The invention has the beneficial effects that: sea surface flow velocity information containing a tide mixing effect is obtained through calculation of the corrected POM model, a Stokes drift velocity is obtained by utilizing a SWAN model and a Stokes drift velocity calculation formula, and flow velocities influenced by two different physical mechanisms are used as input sea water flow velocity data to drive the GNOME model to operate, so that the flow velocity data are closer to an actual value, the sea mixing and Stokes drift mechanisms ignored in the GNOME model operation process are perfected, the output prediction result of the GNOME model is more accurate, and the prediction precision of the model is favorably improved.
Drawings
Fig. 1 is a schematic diagram of the method for predicting the oil spill track based on the stokes shift and tide mixing mechanism.
For a person skilled in the art, other relevant figures can be obtained from the above figures without inventive effort.
Detailed Description
The present invention will be described in further detail with reference to specific examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
As shown in fig. 1, a method for predicting an oil spill track based on stokes shift and tide mixing mechanisms specifically includes the following steps.
Step 1, modifying a POM (Princeton Ocean Model ), adding a tide mixing parameterization equation into a turbulence closed equation in the POM, and enabling the POM to comprise a parameterization calculation method of tide mixing, wherein the modified turbulence closed equation is as follows:
Figure 128396DEST_PATH_IMAGE013
（1）
Figure 37446DEST_PATH_IMAGE014
（2）
in the above formula:t 0 is the time;U 0 、V 0 、W 0 respectively in Cartesian coordinate systemx 0 、y 0 、z 0 A component of flow velocity in the direction;ρis the density after the adiabatic decay rate correction,ρ 0 is the density of the seawater, and is,gis the acceleration of gravity;qis the energy of the turbulence,lis the turbulent mixing length;A H is thatq 2 、q 2 lThe horizontal diffusion coefficient of (d);K H 、K q to representq 2 、q 2 lThe vertical diffusion coefficient of (a) is,
Figure 372613DEST_PATH_IMAGE015
is a wall approximation function;B 1 、E 1 、E 3 is a constant of experience that is,E 1 =E 3 =1.8、B 1 =16.6；K M is the vertical turbulent mixing coefficient,K tidal is the moisture mixing coefficient.
Figure 367113DEST_PATH_IMAGE016
（3）
In the formula (3), the reaction mixture is,
Figure 852453DEST_PATH_IMAGE017
in order to achieve a high mixing efficiency,
Figure 350430DEST_PATH_IMAGE018
=0.2，q 1 in order to be able to determine the rate of tidal energy dissipation,q 1 =0.3，ρ 0 the density of the seawater is shown as the density of the seawater,Nin order to be the buoyancy frequency,Ein order to provide a flux of tidal energy,Fis a vertical dissipation function.
Frequency of buoyancyNThe density data can be obtained according to the output of the POM model, and the specific calculation formula is as follows:
Figure 387656DEST_PATH_IMAGE019
（4）
wherein the content of the first and second substances,gis the acceleration of the gravity, and the acceleration is the acceleration of the gravity,ρ 0 is the density of seawater.
The tidal energy fluxEThe calculation formula of (a) is as follows:
Figure 603874DEST_PATH_IMAGE020
（5）
wherein the content of the first and second substances,ρ 1 is the reference density of seawater;N b is the sea floor buoyancy frequency;
Figure 751958DEST_PATH_IMAGE021
is the average tidal flow velocity, output by Princeton ocean modelObtaining;
Figure 993190DEST_PATH_IMAGE022
=2 pi/(2000), which is the characteristic wave number of the terrain;h 2 representing the sea floor roughness, calculated from the terrain profile data, representing the mean square of the height deviation from a polynomial fitting plane to the actual terrain, said polynomial fitting plane being represented as:L=a+bx+cy+dxy，a、b、c、dare all parameters.
The vertical dissipation functionFThe calculation formula of (c) is as follows:
Figure 201318DEST_PATH_IMAGE023
（6）
wherein, the first and the second end of the pipe are connected with each other,His the total height of the water column;
Figure 904832DEST_PATH_IMAGE024
is the scale of the vertical dissipation and,
Figure 325449DEST_PATH_IMAGE024
=500；Zthe negative value of the water depth value.
Step 2, operating the corrected POM model in the oil spill accident occurrence period to obtain the sea surface flow velocity containing the tide mixing influenceU tidal 。
And 3, inputting the wind field file into a SWAN model (Simulating Waves Nearsore, sea wave model), calculating a wave field during the oil spill accident by using the SWAN model, and outputting wave parameters.
The wave parameters include: effective wave height, wavelength, wave mean period, and wave direction.
Step 4, substituting the wave parameters obtained in the step 3 into a Stokes drift velocity calculation formula to calculate and obtain the Stokes drift velocity;
the Stokes drift velocity calculation formula is as follows:
Figure 63598DEST_PATH_IMAGE025
（7）
Figure 317993DEST_PATH_IMAGE026
（8）
Figure 508802DEST_PATH_IMAGE027
（9）
in the formula (I), the compound is shown in the specification,U s is the speed of the Stokes shift and,u s is the east component of the Stokes drift velocity,v s is the north component of the Stokes drift velocity,zis a vertical coordinate and is a vertical coordinate,gis the acceleration of the force of gravity and,θis the direction of the wave,H s is the effective wave height, and the effective wave height,Tis the average period of the waves and is,λis the wavelength;H s 、T、λ、θall the parameters are calculated by the SWAN ocean wave model in the step 3.
And step 5, inputting the terrain file, the wind field file, the sea surface flow velocity containing the tide mixing influence obtained in the step 2 and the Stokes drift velocity obtained in the step 4 into a GNOME oil spill prediction model (General NOAA Operational Modeling Environment) and operating the model, and recording oil film position information of different time nodes to obtain an oil spill track image. When the GNOME oil spill prediction model is operated, the set initial conditions comprise: oil spill, oil type, accident occurrence time, duration and diffusion rate. The GNOME oil spill prediction model adopts an Euler-Lagrange particle tracking method to simulate the drift of oil particles, and the motion velocity equation of the oil particles is as follows:
Figure 998690DEST_PATH_IMAGE028
（10）
U t the speed of movement of the oil particles (i.e. the speed of movement of the spill),U w is the wind speed 10m above the sea surface,C w the wind conductivity coefficient is generally 0.03-0.04;U tidal is a sea surface containing the effects of tidal mixingThe flow rate is calculated by the POM model in the step 2;U s is the Stokes drift velocity, calculated in step 4.
It should be noted that the Princeton Ocean Model (POM), the sea wave model (SWAN), and the oil spill prediction model (GNOME) according to the present invention are introduced as follows:
princeton Ocean Model (POM)
A three-dimensional oblique pressure original equation numerical value ocean mode adopts a frog leaping finite difference format and a split operator technology, and is widely applied to the simulation of tide, wind-generated current, mixed layers and spring layers, thermohaline circulation, ocean circulation and transportation by scholars at home and abroad. The Princeton ocean model may output flow rate data that is calculated to include the effects of tidal mixing.
Sea wave model (SWAN)
The SWAN model is an abbreviation of simulation Waves nershore, is a third-generation offshore wave numerical calculation model developed by Delft University of Technology (Technology), has gradually matured after years of improvement, and is widely applied to ocean numerical research.
The SWAN model adopts a balance equation based on an energy conservation principle, and not only considers the common characteristics of the third generation sea wave mode, but also fully considers various requirements of the mode in shallow water simulation. The SWAN model adopts a fully-implicit finite difference format, is unconditionally stable, and prevents the calculation of spatial grids and time step length from being restricted; secondly, in each source term of the equilibrium equation, in addition to the wind input, the four-wave interaction, the breaking and friction terms, and the like, the action of deep-induced wave breaking (Depth-induced wave breaking) and the three-wave interaction are considered.
Wave parameters required for calculating the Stokes drift velocity can be output by using the SWAN model, and comprise: effective wave height, wavelength, average wave period and wave direction.
(III) oil spill prediction model (GNOME)
The GNOME (General NOAA Operational Modeling Environment) model was developed by the U.S. National Oceanic and Atmospheric Administration (NOAA). The model can simulate the drift trajectory of oil spill by inputting data such as wind field, flow field, oil product, oil spill amount and the like, and the principle of the model is based on an Euler-Lagrange particle tracking method.
Although the preferred embodiments of the present invention have been described above with reference to the accompanying drawings, the present invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and those skilled in the art can make many modifications without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims (5)

1. A method for predicting an oil spill track based on stokes shift and tide mixing mechanism is characterized by comprising the following steps:
step 1, correcting a POM model, and adding a tide mixing parameterized equation into a turbulence closed equation in the POM model to enable the POM model to contain a tide mixing parameterized calculation method;
step 2, operating the corrected POM model at the oil spill accident occurrence time period to obtain the sea surface flow velocity containing the tide mixing influence;
step 3, inputting the wind field file into a SWAN model, calculating a wave field during an oil spill event by using the SWAN model, and outputting wave parameters;
step 4, substituting the wave parameters obtained in the step 3 into a Stokes drift velocity calculation formula to calculate and obtain the Stokes drift velocity;
and step 5, inputting the terrain file, the wind field file, the sea surface flow velocity containing the tide mixing influence obtained in the step 2 and the Stokes drift velocity obtained in the step 4 into a GNOME oil spill prediction model, operating the model, and recording oil film position information of different time nodes to obtain an oil spill track image.
2. The method for predicting the oil spill track based on the stokes shift and tide mixing mechanism according to claim 1, wherein the method comprises the following steps: in step 1, adding a tide mixing parameterized equation into a turbulence closed equation in the POM model to obtain a corrected turbulence closed equation:
Figure DEST_PATH_IMAGE001
（1）
Figure DEST_PATH_IMAGE002
（2）
in the above formula:t 0 is the time;U 0 、V 0 、W 0 respectively in Cartesian coordinate systemx 0 、y 0 、z 0 A flow velocity component in the direction;ρis the density after the adiabatic decay rate correction,ρ 0 is the density of the seawater, and is,gis the acceleration of gravity;qit is the energy of the turbulence,lis the turbulent mixing length;A H is thatq 2 、q 2 lThe horizontal diffusion coefficient of (d);K H 、K q representq 2 、q 2 lThe vertical diffusion coefficient of (a) is,
Figure DEST_PATH_IMAGE003
is a wall approximation function;B 1 、E 1 、E 3 is a constant of experience that is,E 1 =E 3 =1.8、B 1 =16.6；K M is the vertical turbulent mixing coefficient of the mixture,K tidal is the wet mix factor;
Figure DEST_PATH_IMAGE004
（3）
in the formula (3), the reaction mixture is,
Figure DEST_PATH_IMAGE005
in order to achieve a high mixing efficiency,
Figure DEST_PATH_IMAGE006
=0.2，q 1 in order to be able to determine the rate of tidal energy dissipation,q 1 =0.3，ρ 0 the density of the seawater is shown as the density of the seawater,Nin order to be the buoyancy frequency,Ein order to provide for a flux of tidal energy,Fis a vertical dissipation function;
the buoyancy frequencyNAccording to the density data output by the POM model, the specific calculation formula is as follows:
Figure DEST_PATH_IMAGE007
（4）
wherein the content of the first and second substances,gin order to be the acceleration of the gravity,ρ 0 is the density of seawater;
the tidal energy fluxEThe calculation formula of (a) is as follows:
Figure DEST_PATH_IMAGE008
（5）
wherein, the first and the second end of the pipe are connected with each other,ρ 1 is the reference density of seawater;N b is the sea floor buoyancy frequency;
Figure DEST_PATH_IMAGE009
is the average tidal flow velocity, obtained from the output of the Princeton ocean model;
Figure DEST_PATH_IMAGE010
=2 pi/(2000), which is the characteristic wave number of the terrain;h 2 representing the sea floor roughness, calculated from the terrain profile data, representing the mean square of the height deviation from a polynomial fit plane to the actual terrain, said polynomial fit plane being represented as:L=a+bx+cy+dxy，a、b、c、dare all parameters;
the vertical dissipation functionFThe calculation formula of (a) is as follows:
Figure DEST_PATH_IMAGE011
（6）
wherein the content of the first and second substances,His the total height of the water column;
Figure DEST_PATH_IMAGE012
is the scale of the vertical dissipation and,
Figure DEST_PATH_IMAGE013
=500；Zthe negative value of the water depth value.
3. The method for predicting the oil spill track based on the stokes shift and tide mixing mechanism according to claim 1, wherein the method comprises the following steps: in step 3, the wave parameters include: effective wave height, wavelength, wave mean period, and wave direction.
4. The method for predicting the oil spill track based on the stokes shift and tide mixing mechanism according to claim 1, wherein the method comprises the following steps: in step 4, the calculation formula of the Stokes drift velocity is as follows:
Figure DEST_PATH_IMAGE014
（7）
Figure DEST_PATH_IMAGE015
（8）
Figure DEST_PATH_IMAGE016
（9）
in the formula (I), the compound is shown in the specification,U s is the speed of the Stokes shift and,u s is the east component of the Stokes drift velocity,v s is the north component of the Stokes drift velocity,zis a vertical coordinate and is a vertical coordinate,gis the acceleration of the force of gravity,θis the direction of the waves,H s is the effective wave height,Tis the average period of the waves and is,λis the wavelength;H s 、T、λ、θall the SWAN models are calculated in the step 3.
5. The method for predicting the oil spill track based on the stokes shift and tide mixing mechanism according to claim 1, wherein the method comprises the following steps: in step 5, when the GNOME oil spill prediction model is operated, the set initial conditions include: oil spill, oil type, accident occurrence time, duration and diffusion rate.
CN202211553173.7A 2022-12-06 2022-12-06 Oil spill track prediction method based on stokes drift and tide mixing mechanism Pending CN115564150A (en)

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