A method for predicting migration and evolution risk of crude oil leakage in lake wetland area

Abstract

This invention provides a method for predicting the migration and evolution risk of crude oil spills in lake wetland areas, relating to the field of crude oil spill water pollution detection technology. The method includes: acquiring surface runoff index and oil film coverage thickness index; quantifying the impact of surface runoff on crude oil migration path and determining whether a first water pollution risk feedback is needed; quantifying the impact of crude oil infiltration process on crude oil infiltration path and determining whether a second water pollution risk feedback is needed; quantifying the impact of tributary inflow process on crude oil film migration and diffusion under static conditions and determining whether a third water pollution risk feedback is needed; if so, then perform the third water pollution risk feedback; otherwise, proceed to the next step; quantifying the impact of tributary inflow process on crude oil film diffusion under wind speed and determining whether a fourth water pollution risk feedback is needed; if so, then perform the fourth water pollution risk feedback; otherwise, terminate the process.

Description

Technical Field

[0001] This invention relates to the field of crude oil spill water pollution detection technology, and in particular to a method for predicting the migration and evolution risk of crude oil spills in lake and wetland areas. Background Technology

[0002] Lakes and wetlands, as vital ecosystems, play crucial ecological roles in regulating climate, purifying water, and protecting biodiversity. In the event of an oil spill, the crude oil migrates, seeps into, and spreads in the water, causing devastating damage to lake and wetland ecosystems. Toxic and harmful substances in crude oil pollute the water, leading to water quality deterioration, affecting the survival and reproduction of aquatic organisms, and disrupting the ecological balance. Furthermore, the areas surrounding lakes and wetlands are often important water sources and activity areas for humans; water pollution caused by oil spills directly threatens the safety of drinking water and water for domestic and industrial use. Therefore, conducting risk prediction for the migration and evolution of oil spills in lake and wetland areas is of great significance for improving emergency response capabilities for water pollution and reducing ecological and environmental damage.

[0003] Currently, in existing technologies, the server acquires the intensity of scattered light from the turbidity detection device and the concentration of each air component on the water surface from the odor sensor; when the intensity of scattered light and / or the concentration of at least one air component exceeds a threshold, the server sends a start command to the water quality detection device corresponding to the turbidity detection device or the odor sensor in order to acquire river water quality information.

[0004] However, existing technologies only focus on the immediate determination of concentration exceeding the standard when pollution occurs, and cannot make phased quantitative predictions of changes in the migration path of crude oil driven by surface runoff, the infiltration process in soil media, and the diffusion evolution trend after the formation of an oil film on the water surface. At the same time, existing technologies do not consider factors such as changes in turbulence intensity caused by tributary inflows and the dynamic influence of wind speed on the direction of oil film diffusion. As a result, under complex hydrological and meteorological conditions, the accuracy of pollution risk prediction after crude oil leakage is not high, making it difficult to provide effective decision support for graded early warning and precise intervention. Summary of the Invention

[0005] To address the shortcomings of existing technologies that focus solely on immediate concentration exceedance at the time of pollution occurrence, failing to provide phased quantitative predictions of changes in crude oil migration paths driven by surface runoff, infiltration processes in soil media, and diffusion evolution trends after oil film formation on water surfaces; and to further refrain from considering factors such as turbulence intensity changes caused by tributary inflows and the dynamic impact of wind speed on oil film diffusion direction, resulting in low accuracy in predicting pollution risks after crude oil leaks under complex hydrological and meteorological conditions, thus hindering effective decision support for tiered early warning and precise intervention, this invention provides a method for predicting the migration and evolution risk of crude oil leaks in lake and wetland areas.

[0006] The technical solutions provided by the embodiments of the present invention are as follows:

[0007] The first aspect of this invention provides a method for predicting the migration and evolution risk of crude oil spills in lake wetland areas, comprising:

[0008] S1: Obtain the surface runoff index and oil film coverage thickness index for a specified surface runoff area;

[0009] S2: Based on the surface runoff index and oil film coverage thickness index, determine whether the first water pollution risk feedback is required by quantifying the impact of surface runoff in the specified surface runoff area on the crude oil migration path; if yes, then conduct the first water pollution risk feedback; otherwise, proceed to step S3.

[0010] S3: By quantifying the impact of the crude oil infiltration process in the tributary area on the crude oil infiltration path, determine whether a second water pollution risk feedback is needed; if so, conduct a second water pollution risk feedback; otherwise, proceed to step S4.

[0011] S4: By quantifying the impact of the tributary inflow process in the turbulent tributary region on the migration and diffusion of crude oil film under static conditions, determine whether third-party water pollution risk feedback is required; if so, conduct third-party water pollution risk feedback; otherwise, proceed to step S5.

[0012] S5: By quantifying the impact of the tributary inflow process in the turbulence intensity tributary region on the diffusion of crude oil film under the action of wind speed, determine whether a fourth water pollution risk feedback is required; if so, conduct the fourth water pollution risk feedback; otherwise, end the process.

[0013] A second aspect of this invention provides a crude oil spill migration and evolution risk prediction system for lake wetland areas, comprising:

[0014] processor;

[0015] A memory storing computer-readable instructions, which, when executed by the processor, implement the oil spill migration and evolution risk prediction method for lake wetland areas as described in the first aspect.

[0016] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0017] In this invention, a graded quantitative judgment system covering the entire chain of "surface runoff migration—soil media infiltration—static oil film diffusion—wind speed-induced diffusion" is constructed. This system quantifies the changes in crude oil migration path driven by surface runoff, the risk of crude oil infiltration driven by groundwater level gradient, the coupled influence of turbulence intensity caused by tributary confluence on oil film diffusion, and the range of oil film diffusion under wind speed in stages. Correspondingly, first to fourth water pollution risk feedback mechanisms are set up. This solves the problems of existing technologies that cannot predict in stages, do not consider the dynamic influence of turbulent tributaries and wind speed, have low prediction accuracy, and are difficult to support graded intervention. It significantly improves the accuracy and environmental adaptability of crude oil leakage pollution risk prediction under complex hydrological and meteorological conditions, and provides effective decision support for graded early warning and precise intervention. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating a method for predicting the migration and evolution risk of crude oil spills in lake and wetland areas, as provided in an embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram of the structure of a crude oil spill migration and evolution risk prediction system for lake wetland areas, provided by an embodiment of the present invention. Detailed Implementation

[0021] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0022] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0023] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0024] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0025] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0026] Reference manual attached Figure 1 The diagram illustrates a flowchart of a method for predicting the migration and evolution risk of crude oil spills in lake wetland areas, provided by an embodiment of the present invention.

[0027] This invention provides a method for predicting the migration and evolution risk of crude oil spills in lake and wetland areas. This method can be implemented using a device for predicting the migration and evolution risk of crude oil spills in lake and wetland areas, which can be a terminal or a server. The processing flow of this method may include the following steps:

[0028] S1: Obtain the surface runoff index and oil film coverage thickness index for a specified surface runoff area.

[0029] Among them, the surface runoff index is used to reflect the driving effect of surface runoff velocity on crude oil migration under the influence of surface slope, and is specifically expressed as the product of surface slope influence factor and surface runoff velocity.

[0030] Among them, the oil film coverage thickness index is used to reflect the degree to which the oil film coverage thickness hinders crude oil migration under the influence of surface roughness. Specifically, it is expressed as the product of the oil film coverage thickness and the surface roughness influence factor.

[0031] S2: Based on the surface runoff index and oil film coverage thickness index, determine whether a first-stage water pollution risk feedback is needed by quantifying the impact of surface runoff in a designated surface runoff area on the crude oil migration path. If yes, conduct the first-stage water pollution risk feedback. Otherwise, proceed to step S3.

[0032] Specifically, the first water pollution risk feedback is used to predict the degree of water pollution risk caused by changes in crude oil migration paths under surface runoff.

[0033] Furthermore, at the end of the oil film diffusion monitoring period, the surface runoff index and oil film coverage thickness index of the designated surface runoff area are obtained, and compared with the preset surface runoff index and oil film coverage thickness index in the database. The preset surface runoff index is represented by the summation and averaging of the historical surface runoff indices at the end of the historical oil film diffusion monitoring periods in the database, and the preset oil film coverage thickness index is represented by the summation and averaging of the historical oil film coverage thickness indices at the end of the historical oil film diffusion monitoring periods in the database. The surface runoff index score and oil film coverage thickness index score are obtained. At the same time, the obtained surface runoff index score and oil film coverage thickness index score are summed and averaged to obtain the surface crude oil migration risk index.

[0034] It should be noted that the surface runoff index reflects the driving effect of surface runoff velocity on crude oil migration under the influence of surface slope, and is represented by the product of the surface slope influence factor and the surface runoff velocity. The oil film cover thickness index reflects the degree of obstruction of crude oil migration by the oil film cover thickness under the influence of surface roughness, and is represented by the product of the oil film cover thickness and the surface roughness influence factor. The surface runoff index score represents the ratio of the surface runoff index of the specified surface runoff area at the end of the oil film diffusion monitoring period to the preset surface runoff index. The oil film cover thickness index score represents the ratio of the oil film cover thickness index of the specified surface runoff area at the end of the oil film diffusion monitoring period to the preset oil film cover thickness index. The surface crude oil migration risk index represents the quantitative data of the risk level of crude oil migration path jointly represented by the surface runoff index and the oil film cover thickness index.

[0035] In one possible implementation, quantifying the impact of surface runoff in a designated surface runoff area on crude oil migration pathways specifically includes:

[0036] The surface runoff index and oil film coverage thickness index were compared with preset surface runoff index and preset oil film coverage thickness index in the database to obtain the surface runoff index score and oil film coverage thickness index score. The surface runoff index score and oil film coverage thickness index score were then summed and averaged to obtain the surface crude oil migration risk index.

[0037] It should be noted that those skilled in the art can set the preset oil film coverage thickness index and the preset surface runoff index according to actual needs, and the present invention does not limit them.

[0038] Specifically, the surface runoff index reflects the driving effect of surface runoff velocity on crude oil migration under the influence of surface slope, the oil film coverage thickness index reflects the degree of obstruction of crude oil migration by oil film coverage thickness under the influence of surface roughness, and the surface crude oil migration risk index represents the quantitative data of the risk level of crude oil migration path jointly expressed by the surface runoff index and the oil film coverage thickness index.

[0039] In one possible implementation, determining whether a first water pollution risk feedback is needed specifically includes:

[0040] If the surface crude oil migration risk indicator meets the first comparison condition, it indicates that the surface crude oil migration risk is within the corresponding risk tolerance range, and the process proceeds to step S3. The first comparison condition indicates that the surface crude oil migration risk indicator is not greater than the preset surface crude oil migration risk indicator in the database.

[0041] If the surface crude oil migration risk indicator meets the second comparison condition, it indicates that the surface crude oil migration risk is within a controllable range, and a first water pollution feedback instruction is sent. The second comparison condition indicates that the surface crude oil migration risk indicator is greater than the preset surface crude oil migration risk indicator in the database, and is also greater than the preset first surface oil film migration risk indicator but not greater than the preset second surface oil film migration risk indicator. The first water pollution feedback instruction is used to prompt the designated personnel to repair the leak point in the specified surface runoff area.

[0042] If the surface crude oil migration risk indicator meets the third comparison condition, indicating that the surface oil film migration risk is uncontrollable, a surface crude oil migration early warning command will be issued. The third comparison condition indicates that the surface crude oil migration risk indicator is greater than the preset second indicator for surface oil film migration risk. The surface crude oil migration early warning command is used to prompt preset personnel to intervene.

[0043] Specifically, if the obtained surface crude oil migration risk indicator meets the first comparison condition, it indicates that the surface crude oil migration risk is within the corresponding allowable risk range, and a risk prediction for the crude oil infiltration stage is performed. The first comparison condition indicates that the obtained surface crude oil migration risk indicator is not greater than the preset surface crude oil migration risk indicator in the database. If the obtained surface crude oil migration risk indicator meets the second comparison condition, it indicates that the surface crude oil migration risk is within a controllable range, and a first water pollution feedback instruction is sent. The second comparison condition indicates that the obtained surface crude oil migration risk indicator is greater than the preset surface crude oil migration risk indicator in the database, and is greater than the preset first surface oil film migration risk indicator but not greater than the preset second surface oil film migration risk indicator. The first water pollution feedback instruction is used to prompt the preset personnel to repair the leakage point in the designated surface runoff area. If the obtained surface crude oil migration risk indicator meets the third comparison condition, it indicates that the surface oil film migration risk is uncontrollable, and a surface crude oil migration early warning instruction is sent. The third comparison condition indicates that the obtained surface crude oil migration risk indicator is greater than the preset second surface oil film migration risk indicator. The surface crude oil migration early warning instruction is used to prompt the preset personnel to intervene.

[0044] It should be noted that those skilled in the art can set the magnitude of the preset surface crude oil migration risk index, the preset surface oil film migration risk first index, and the preset surface oil film migration risk second index according to actual needs, and the present invention does not limit these settings.

[0045] In this embodiment of the invention, by constructing a collaborative quantitative model of surface runoff index and oil film coverage thickness index, and combining it with three-level threshold comparison and differentiated feedback instructions, the invention achieves accurate quantification, dynamic monitoring and graded intervention of water pollution risk caused by changes in crude oil migration path during the surface runoff stage.

[0046] S3: By quantifying the impact of crude oil infiltration processes in the tributary region on the crude oil infiltration path, determine whether a second water pollution risk feedback is needed. If yes, conduct a second water pollution risk feedback. Otherwise, proceed to step S4.

[0047] Specifically, the second water pollution risk feedback is used to predict the degree of water pollution risk caused by the crude oil infiltration process in the corresponding tributary areas and lake and wetland water environments.

[0048] In one possible implementation, quantifying the impact of crude oil infiltration processes in tributary regions on crude oil infiltration pathways specifically includes:

[0049] Soil permeability index and subsurface migration resistance index of the tributary area were obtained and compared with preset soil permeability index and preset subsurface migration resistance index in the database to obtain soil permeability index score and subsurface migration resistance index score. The soil permeability index score and subsurface migration resistance index score were then summed and averaged to obtain the subsurface oil film migration risk index.

[0050] It should be noted that those skilled in the art can set the preset soil permeability index and preset underground migration resistance index according to actual needs, and this invention does not limit them.

[0051] Specifically, at the end of the crude oil infiltration monitoring period, the soil permeability index and the underground migration resistance index of the designated tributary area are obtained and compared with the preset soil permeability index and underground migration resistance index in the database. The preset soil permeability index is represented by the summation and averaging of the historical soil permeability indices at the end of the historical crude oil infiltration monitoring period in the database. The preset underground migration resistance index is represented by the summation and averaging of the historical underground migration resistance indices at the end of the historical crude oil infiltration monitoring period in the database. Soil permeability index score and underground migration resistance index score are obtained. At the same time, the obtained soil permeability index score and underground migration resistance index score are summed and averaged to obtain the underground oil film migration risk index.

[0052] Furthermore, the soil permeability index is used to reflect the driving effect of soil permeability (i.e., the soil's ability to allow fluids to pass through) on crude oil permeation under the influence of groundwater level gradient. It represents the product of the water level gradient influence factor and soil permeability. The underground migration resistance index is used to reflect the degree of obstruction of oil film migration by the difference in medium resistance. It is usually defined and calculated by comparing the migration speed and migration distance of the corresponding oil film under different medium resistances. The difference in medium resistance represents the absolute value of the difference between the actual underground medium resistance corresponding to the crude oil infiltration area and the allowable underground medium resistance in the database. The soil permeability index score represents the ratio of the soil permeability index of the designated tributary area at the end of the oil film diffusion monitoring period to the preset soil permeability index. The underground migration resistance index score represents the ratio of the underground migration resistance index of the designated tributary area at the end of the oil film diffusion monitoring period to the preset underground migration resistance index. The underground oil film migration risk index represents the quantitative data of the risk level of crude oil infiltration into the lake wetland area in the tributary area by the soil permeability index and the underground migration resistance index.

[0053] In one possible implementation, determining whether a second water pollution risk feedback is needed specifically includes:

[0054] If the underground oil film migration risk index reaches the first-level judgment standard, it indicates that the crude oil permeation risk in the tributary area is within the corresponding risk tolerance range, and the process proceeds to step S4. The first-level judgment standard indicates that the underground oil film migration risk index is not greater than the preset underground oil film migration risk index in the database.

[0055] If the underground oil film migration risk index reaches the Level II judgment standard, it indicates that the crude oil seepage risk in the tributary area exceeds the corresponding allowable risk range, and an oil film seepage warning command is issued. The Level II judgment standard indicates that the underground oil film migration risk index is greater than the preset underground oil film migration risk index in the database. The oil film seepage warning command is used to prompt designated personnel to intervene.

[0056] Specifically, if the obtained crude oil permeability risk index of the tributary area meets the first-level judgment standard, it indicates that the crude oil permeability risk of the tributary area is within the corresponding allowable risk range, and a static environmental risk prediction for the crude oil film diffusion stage is conducted. The first-level judgment standard indicates that the obtained crude oil permeability risk index of the tributary area is not greater than the preset crude oil permeability risk index of the tributary area in the database. If the obtained crude oil permeability risk index of the tributary area meets the second-level judgment standard, it indicates that the crude oil permeability risk of the tributary area exceeds the corresponding allowable risk range, and an oil film permeation warning instruction is sent. The second-level judgment standard indicates that the obtained crude oil permeability risk index of the tributary area is greater than the preset crude oil permeability risk index of the tributary area in the database. The oil film permeation warning instruction is used to prompt the designated personnel to intervene.

[0057] It should be noted that those skilled in the art can set the magnitude of the preset underground oil film migration risk index and the preset crude oil permeability risk index in the tributary area according to actual needs, and this invention does not limit these settings.

[0058] In this embodiment of the invention, by quantifying the soil permeability index and the underground migration resistance index and constructing a two-level threshold judgment mechanism, the invention achieves accurate identification and graded early warning of the risk of crude oil underground infiltration, effectively making up for the blind spots that surface monitoring cannot cover underground migration paths, and providing a pre-intervention means to block crude oil from seeping into lakes and wetlands.

[0059] S4: By quantifying the impact of the tributary inflow process in the turbulent tributary region on the migration and diffusion of crude oil film under static conditions, determine whether third-party water pollution risk feedback is necessary. If so, conduct third-party water pollution risk feedback. Otherwise, proceed to step S5.

[0060] Among them, the turbulence intensity tributary region refers to a specific water area where the intensity of water turbulence is significantly enhanced due to sudden changes in water flow velocity and disturbances caused by the convergence of flow directions during the process of a tributary merging into the main stream.

[0061] Specifically, the third water pollution risk feedback is used to predict the degree of water pollution risk caused by the migration and diffusion of crude oil film during the tributary inflow process under static conditions.

[0062] In one possible implementation, the degree of influence of the tributary inflow process in the turbulent tributary region on the migration and diffusion of crude oil film under static conditions is specifically included by quantifying the following:

[0063] The proportional deviation between the tributary inflow deviation data of the turbulent intensity tributary region and the preset tributary inflow deviation data in the database is obtained.

[0064] By combining the tributary inflow compensation factor, the degree of deviation of each proportion is compensated, and the results after compensation are coupled to obtain the oil film migration and diffusion risk index.

[0065] Specifically, the designated turbulence intensity tributary region refers to the region where the average water flow velocity in the designated tributary region is greater than the average water flow velocity set in the database at the end of the first oil film diffusion monitoring period. The tributary inflow deviation data includes the average water flow velocity deviation, the oil film diffusion angle deviation, and the oil film surface tension deviation. The oil film migration and diffusion risk index represents the quantification data of the risk level of crude oil film migration and diffusion under static conditions based on the tributary inflow deviation data.

[0066] Specifically, at the end of the first oil film diffusion monitoring period (i.e., the crude oil film migration and diffusion monitoring period corresponding to the static environment), the proportional deviation between the tributary inflow deviation data of the designated turbulence intensity tributary area and the preset tributary inflow deviation data in the database is obtained. At the same time, the tributary inflow compensation factor is combined to compensate for the results of each proportional deviation, and the results after compensation are coupled to obtain the oil film migration and diffusion risk index.

[0067] Furthermore, the designated tributary region for turbulence intensity refers to the region where the average water flow velocity in the designated tributary region at the end of the first oil film diffusion monitoring period is greater than the average water flow velocity set in the database. The tributary inflow deviation data includes average water flow velocity deviation, oil film diffusion angle deviation, and oil film surface tension deviation. The average water flow velocity deviation represents the difference between the average water flow velocity in the designated tributary region at the end of the first oil film diffusion monitoring period and the set average water flow velocity. The oil film diffusion angle deviation represents the angular deviation between the normal to the actual diffusion direction of the oil film in the designated tributary region at the end of the first oil film diffusion monitoring period and the normal to the tributary inflow direction. The oil film surface tension deviation represents the deviation between the average water flow velocity in the designated tributary region at the end of the first oil film diffusion monitoring period and the set average water flow velocity. The difference between the surface tension of the oil film in the designated tributary region and the set surface tension of the oil film at the end of an oil film diffusion monitoring period. The preset tributary inflow deviation data includes the preset average water flow velocity deviation, oil film diffusion angle deviation, and oil film surface tension deviation. The tributary inflow compensation factors include the preset average water flow velocity deviation compensation factor, oil film diffusion angle deviation compensation factor, and oil film surface tension deviation compensation factor. The oil film migration and diffusion risk index represents the quantitative data of the risk level of crude oil film migration and diffusion under static environment based on the tributary inflow deviation data. The oil film migration and diffusion risk index represents the coupling processing result of the average water flow velocity deviation value, the oil film diffusion angle deviation value, and the oil film surface tension deviation value.

[0068] Specifically, the limiting expression for the oil film migration and diffusion risk index W is as follows: In the formula, the average water flow velocity deviation value The specific constraint expression is: Oil film diffusion angle deviation value The specific constraint expression is: Oil film surface tension deviation value The specific constraint expression is: Wherein, W represents the oil film migration and diffusion risk index of the specified turbulence intensity tributary region at the end of the oil film diffusion monitoring period; W1 represents the average water flow velocity deviation of the specified turbulence intensity tributary region at the end of the oil film diffusion monitoring period; W2 represents the oil film diffusion angle deviation of the specified turbulence intensity tributary region at the end of the oil film diffusion monitoring period; W3 represents the oil film surface tension deviation of the specified turbulence intensity tributary region at the end of the oil film diffusion monitoring period; a1 represents the average water flow velocity deviation compensation factor; S1 represents the average water flow velocity deviation of the specified turbulence intensity tributary region at the end of the oil film diffusion monitoring period; and S10 represents the preset average water flow velocity deviation, which is determined by the historical first oil film diffusion monitoring period ending in the database. The results are represented by the summation and averaging of the historical average water flow velocity deviations at the time of the monitoring period. a2 represents the oil film diffusion angle deviation compensation factor, S2 represents the oil film diffusion angle deviation of the specified turbulence intensity tributary region at the end of the oil film diffusion monitoring period, S20 represents the preset oil film diffusion angle deviation, which is represented by the summation and averaging of the historical oil film diffusion angle deviations at the end of the first historical oil film diffusion monitoring period in the database, a3 represents the oil film surface tension deviation compensation factor, S3 represents the oil film surface tension deviation of the specified turbulence intensity tributary region at the end of the oil film diffusion monitoring period, and S30 represents the preset oil film surface tension deviation, which is represented by the summation and averaging of the historical oil film diffusion angle deviations at the end of the first historical oil film diffusion monitoring period in the database.

[0069] Furthermore, the average water flow velocity deviation compensation factor, oil film diffusion angle deviation compensation factor, and oil film surface tension deviation compensation factor represent the degree of influence of the preset average water flow velocity deviation, oil film diffusion angle deviation, and oil film surface tension deviation on each stage, respectively. Specifically, the database stores preset compensation factors corresponding to the average water flow velocity deviation, oil film diffusion angle deviation, and oil film surface tension deviation. These compensation values ​​have a pre-defined mapping relationship with the average water flow velocity deviation, oil film diffusion angle deviation, and oil film surface tension deviation. The average water flow velocity deviation, oil film diffusion angle deviation, and oil film surface tension deviation can be input into this mapping relationship to obtain the corresponding compensation amount. In this example, the values ​​of the average water flow velocity deviation compensation factor, oil film diffusion angle deviation compensation factor, and oil film surface tension deviation compensation factor are typically in the range of 0 to 1, and the sum of the three is 1.

[0070] It should be noted that those skilled in the art can set preset tributary inflow deviation data, preset average water flow velocity deviation, preset oil film diffusion angle deviation, preset oil film surface tension deviation, and preset compensation factor according to actual needs, and the present invention does not limit these settings.

[0071] It should be noted that the risk index of oil film migration and diffusion increases with the increase of the deviation of average water flow velocity, the deviation of oil film diffusion angle, and the deviation of oil film surface tension. When the deviation of average water flow velocity increases, the drag force of water flow on oil film will change, which may change the diffusion direction of oil film, thereby affecting the deviation of oil film diffusion angle. The deviation of oil film diffusion angle will change the contact area and contact mode between oil film and surrounding water, which will change the stress on the surface of oil film, and thus affect the surface tension of oil film.

[0072] Furthermore, a larger deviation in the average water flow velocity indicates a more turbulent flow, which accelerates oil film diffusion, increases its range and speed, and raises the risk of oil film diffusion. A larger deviation in the oil film diffusion angle indicates a greater variation in the actual diffusion direction, potentially causing the oil film to enter undesirable areas, such as sensitive ecological zones, increasing the risk of water pollution in lakes and wetlands. A larger deviation in the oil film surface tension may make the oil film more prone to breaking into smaller droplets, increasing the contact area between the oil film and the water, accelerating the dissolution and emulsification processes in the water, expanding the pollution range, and increasing the risk of oil film diffusion.

[0073] In one possible implementation, determining whether third-party water pollution risk feedback is necessary specifically includes:

[0074] If the oil film migration and diffusion risk index is not greater than the preset oil film migration and diffusion risk index, it indicates that the crude oil film diffusion risk under static environment is within the corresponding allowable range, and proceeds to step S5.

[0075] If the risk index of oil film migration and diffusion is greater than the preset risk index, then third-party water pollution risk feedback and intervention will be carried out.

[0076] In one possible implementation, determining whether third-party water pollution risk feedback is necessary specifically includes:

[0077] If the oil film migration and diffusion risk index is within the closed interval corresponding to the maximum value of the preset oil film migration and diffusion risk index and the historical oil film migration and diffusion risk index, it indicates that the crude oil film diffusion risk under static environment is within the corresponding controllable range, and a third water pollution feedback instruction is sent.

[0078] Specifically, the third water pollution feedback instruction is used to prompt the preset personnel to adjust the opening of the upstream flow valve of the tributary based on the obtained upstream flow valve opening adjustment value, so as to reduce the increase in water flow turbulence caused by drastic changes in flow. The upstream flow valve opening adjustment value is the result obtained by mapping the deviation of the oil film migration and diffusion risk index to the upstream flow valve opening adjustment value in the database.

[0079] Determine if the oil film migration and diffusion risk index is greater than the historical maximum value. If so, send a crude oil film diffusion risk warning command to prompt pre-selected personnel to intervene. Otherwise, complete the third water pollution risk feedback and intervention and proceed to step S5.

[0080] Specifically, the judgment process provides a clear risk response path for monitoring water pollution related to crude oil film diffusion in static environments. By establishing a direct comparison logic between oil film migration and diffusion risk indicators and preset thresholds, it enables accurate identification and efficient response to water pollution caused by oil film diffusion risks triggered by tributary inflows in static environments. Using quantified oil film migration and diffusion risk indicators as the basis for decision-making, the water pollution risk assessment is based on measurable and comparable benchmarks. Through targeted response mechanisms, the proactive control capability of oil film diffusion risks in static environments is strengthened, making water pollution monitoring more targeted and effective in controlling oil film diffusion risks in static environments. This provides key support for building a full-scenario crude oil diffusion water pollution monitoring system.

[0081] Furthermore, if the obtained oil film migration and diffusion risk index falls within the closed interval corresponding to the maximum value of the preset oil film migration and diffusion risk index and the historical oil film migration and diffusion risk index, it indicates that the crude oil film diffusion risk under static conditions is within the corresponding controllable range. A third water pollution feedback instruction is then sent, prompting the personnel to adjust the upstream flow valve opening of the tributary based on the obtained upstream flow valve opening adjustment value to reduce the increased water turbulence caused by drastic flow changes. The oil film migration and diffusion risk index deviation represents the difference between the preset oil film migration and diffusion risk index and the obtained oil film migration and diffusion risk index. The preset oil film migration and diffusion risk index is represented by the summation and averaging of historical oil film migration and diffusion risk indices for the corresponding historical turbulence intensity tributary region at the end of each historical oil film diffusion monitoring period in the database. The maximum value of the historical oil film migration and diffusion risk index is represented by the summation and averaging of the maximum values ​​of historical oil film migration and diffusion risk indices for the corresponding historical turbulence intensity tributary region at the end of each historical oil film diffusion monitoring period in the database. The upstream flow valve opening adjustment value is the result obtained through the mapping relationship between the oil film migration and diffusion risk index deviation and the upstream flow valve opening adjustment value in the database. If the obtained oil film migration and diffusion risk index is greater than the maximum value of the historical oil film migration and diffusion risk index, a crude oil film diffusion risk warning instruction will be sent to prompt the preset personnel to intervene; otherwise, the third water pollution risk feedback and intervention will be completed and the wind speed environmental risk prediction for the crude oil film diffusion stage will be carried out.

[0082] In this embodiment of the invention, by constructing a multi-factor coupled quantitative model of average water flow velocity deviation, oil film diffusion angle deviation and oil film surface tension deviation, and combining it with graded threshold comparison and differentiated feedback instructions, the invention achieves accurate quantification and dynamic control of the risk of oil film migration and diffusion caused by the inflow of turbulent tributaries, providing a scientific decision-making basis for effective intervention of crude oil film diffusion risk under static environment.

[0083] S5: By quantifying the impact of tributary inflow processes in the turbulent tributary region on crude oil film diffusion under wind speed, determine whether a fourth water pollution risk feedback is needed. If yes, conduct the fourth water pollution risk feedback. Otherwise, terminate the process.

[0084] Specifically, the fourth water pollution risk feedback is used to predict the degree of water pollution risk caused by the migration and diffusion of crude oil film during the tributary inflow process under the influence of wind speed.

[0085] Furthermore, at the end of the second oil film diffusion monitoring period (i.e., the crude oil film migration and diffusion monitoring period corresponding to wind speed), the oil film diffusion area of ​​the designated turbulence intensity tributary region is obtained and compared with the preset oil film diffusion area in the database to obtain the oil film diffusion area fraction. The preset oil film diffusion area is represented by the sum and average of the historical oil film diffusion area areas at the end of the historical second oil film diffusion monitoring periods in the database. The oil film diffusion area reflects the diffusion range of crude oil film in the designated turbulence intensity tributary region under wind speed. The oil film diffusion area fraction represents the quantitative data of the risk level of crude oil film migration and diffusion under wind speed, that is, the ratio of the oil film diffusion area of ​​the designated turbulence intensity tributary region at the end of the second oil film diffusion monitoring period to the preset oil film diffusion area.

[0086] In one possible implementation, the degree of influence of the tributary inflow process in the turbulent tributary region on the diffusion of crude oil film under the action of wind speed is specifically included by quantifying the following:

[0087] The area of ​​the oil film diffusion region in the turbulent intensity tributary region is obtained and compared with the preset oil film diffusion region area in the database to obtain the oil film diffusion region area fraction.

[0088] Specifically, the oil film diffusion area is used to reflect the diffusion range of crude oil film in a tributary region with a specified turbulence intensity under the action of wind speed. The oil film diffusion area fraction represents the quantitative data of the risk level of crude oil film migration and diffusion under the action of wind speed.

[0089] In one possible implementation, determining whether a fourth water pollution risk feedback is needed specifically includes:

[0090] If the area fraction of the oil film diffusion region meets the Level 1 risk condition, it indicates that the risk of crude oil film diffusion under wind speed is under control. The Level 1 risk condition means that the area fraction of the oil film diffusion region is not greater than the preset area fraction of the oil film diffusion region in the database.

[0091] If the area fraction of the oil film diffusion region meets the level 2 risk condition, it indicates that the risk of crude oil film diffusion under wind speed is in an uncontrollable stage, and an oil film migration and diffusion early warning command is sent. The level 2 risk condition means that the area fraction of the oil film diffusion region is greater than the preset area fraction of the oil film diffusion region in the database. The oil film migration and diffusion early warning command is used to prompt preset personnel to intervene and complete the risk prediction of the crude oil film diffusion stage. The risk prediction of the crude oil film diffusion stage includes static environmental risk prediction and wind speed environmental risk prediction.

[0092] Specifically, if the obtained oil film diffusion area fraction meets the Level 1 risk condition, it indicates that the crude oil film diffusion risk under wind speed is in a controllable stage. The Level 1 risk condition means that the obtained oil film diffusion area fraction is not greater than the preset oil film diffusion area fraction in the database. If the obtained oil film diffusion area fraction meets the Level 2 risk condition, it indicates that the crude oil film diffusion risk under wind speed is in an uncontrollable stage, and an oil film migration and diffusion early warning command is sent. The Level 2 risk condition means that the obtained oil film diffusion area fraction is greater than the preset oil film diffusion area fraction in the database. The oil film migration and diffusion early warning command is used to prompt the preset personnel to intervene and complete the risk prediction of the crude oil film diffusion stage. The preset oil film diffusion area fraction is represented by the sum and average of the historical oil film diffusion area fractions at the end of the second historical oil film diffusion monitoring period in the database. The risk prediction of the crude oil film diffusion stage includes static environmental risk prediction and wind speed environmental risk prediction.

[0093] It should be noted that those skilled in the art can set the area of ​​the preset oil film diffusion region and the size of the preset oil film diffusion region area fraction according to actual needs, and the present invention does not limit this.

[0094] In this embodiment of the invention, by quantifying the area of ​​the oil film diffusion region under the action of wind speed and constructing a secondary risk judgment threshold, the invention realizes rapid assessment and graded early warning of the risk of crude oil film diffusion under wind power, providing a precise emergency response basis for the prevention and control of water pollution in lakes and wetlands under dynamic meteorological conditions.

[0095] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0096] In this invention, a graded quantitative judgment system covering the entire chain of "surface runoff migration—soil media infiltration—static oil film diffusion—wind speed-induced diffusion" is constructed. This system quantifies the changes in crude oil migration path driven by surface runoff, the risk of crude oil infiltration driven by groundwater level gradient, the coupled influence of turbulence intensity caused by tributary confluence on oil film diffusion, and the range of oil film diffusion under wind speed in stages. Correspondingly, first to fourth water pollution risk feedback mechanisms are set up. This solves the problems of existing technologies that cannot predict in stages, do not consider the dynamic influence of turbulent tributaries and wind speed, have low prediction accuracy, and are difficult to support graded intervention. It significantly improves the accuracy and environmental adaptability of crude oil leakage pollution risk prediction under complex hydrological and meteorological conditions, and provides effective decision support for graded early warning and precise intervention.

[0097] Reference manual attached Figure 2 The diagram shows a structural schematic of a crude oil spill migration and evolution risk prediction system for lake wetland areas provided by the present invention.

[0098] This invention also provides a crude oil spill migration and evolution risk prediction system 20 for lake and wetland areas, applied to the aforementioned crude oil spill migration and evolution risk prediction method for lake and wetland areas, comprising:

[0099] Processor 201.

[0100] The memory 202 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 201, the method for predicting the migration and evolution risk of crude oil spills in lake wetland areas, as described in the method embodiment, is implemented.

[0101] The crude oil spill migration and evolution risk prediction system 20 for lake and wetland areas provided by the present invention can execute the above-mentioned crude oil spill migration and evolution risk prediction method for lake and wetland areas and achieve the same or similar technical effects. To avoid duplication, the present invention will not elaborate further.

[0102] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0103] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0104] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0105] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0106] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0107] It should be understood that, in various embodiments of the present invention, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0108] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0109] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0110] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0111] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0112] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0113] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0114] This invention provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method for predicting the migration and evolution risk of crude oil spills in lake wetland areas as described in the method embodiments.

[0115] The present invention provides a computer-readable storage medium that can implement the steps and effects of the crude oil spill migration and evolution risk prediction method for lake wetland areas in the above-described method embodiments. To avoid repetition, the present invention will not repeat the details.

[0116] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0117] The following points need to be explained:

[0118] (1) The accompanying drawings of the embodiments of the present invention only involve the structures involved in the embodiments of the present invention. Other structures can refer to the general design.

[0119] (2) For clarity, the thickness of layers or regions is enlarged or reduced in the drawings used to describe embodiments of the invention, i.e., these drawings are not drawn to scale. It is understood that when an element such as a layer, film, region or substrate is referred to as being “above” or “below” another element, the element may be “directly” located “above” or “below” the other element or there may be intermediate elements.

[0120] (3) Where there is no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0121] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for predicting the risk of crude oil leakage migration and evolution in a lake wetland area, characterized in that, include: S1: Obtain the surface runoff index and oil film coverage thickness index for a specified surface runoff area; S2: Based on the surface runoff index and the oil film coverage thickness index, determine whether a first water pollution risk feedback is needed by quantifying the impact of surface runoff in the designated surface runoff area on the crude oil migration path; if so, then conduct the first water pollution risk feedback. Otherwise, proceed to step S3; S3: By quantifying the impact of the crude oil infiltration process in the tributary area on the crude oil infiltration path, determine whether a second water pollution risk feedback is needed; if so, then conduct the second water pollution risk feedback. Otherwise, proceed to step S4; S4: By quantifying the impact of the tributary inflow process in the turbulent tributary region on the migration and diffusion of crude oil film under static conditions, determine whether third-party water pollution risk feedback is required; if so, conduct the third-party water pollution risk feedback; otherwise, proceed to step S5. S5: By quantifying the impact of the tributary inflow process in the turbulent tributary region on the diffusion of crude oil film under the action of wind speed, it is determined whether a fourth water pollution risk feedback is required. If so, proceed with the fourth water pollution risk feedback; otherwise, end the process.

2. The method for predicting the risk of crude oil leakage migration and evolution in a lake-oriented wetland area according to claim 1, characterized in that, The quantification of the impact of surface runoff in the designated surface runoff area on crude oil migration paths specifically includes: The surface runoff index and the oil film coverage thickness index are compared and analyzed with the preset surface runoff index and preset oil film coverage thickness index in the database to obtain the surface runoff index score and the oil film coverage thickness index score; the surface runoff index score and the oil film coverage thickness index score are summed and averaged to obtain the surface crude oil migration risk index.

3. The method for predicting the risk of crude oil spill migration and evolution in a lake-oriented wetland area according to claim 2, characterized in that, The determination of whether a first water pollution risk feedback is needed specifically includes: If the surface crude oil migration risk index meets the first comparison condition, it indicates that the surface crude oil migration risk is within the corresponding risk allowable range, and proceeds to step S3; the first comparison condition indicates that the surface crude oil migration risk index is not greater than the preset surface crude oil migration risk index in the database. If the surface crude oil migration risk indicator meets the second comparison condition, it indicates that the surface crude oil migration risk is within a controllable range, and a first water pollution feedback instruction is sent; the second comparison condition indicates that the surface crude oil migration risk indicator is greater than the preset surface crude oil migration risk indicator in the database, and is greater than the preset first surface oil film migration risk indicator but not greater than the preset second surface oil film migration risk indicator; the first water pollution feedback instruction is used to prompt preset personnel to repair the leakage point in the designated surface runoff area; If the surface crude oil migration risk indicator meets the third comparison condition, it indicates that the surface oil film migration risk is uncontrollable, and a surface crude oil migration early warning instruction is sent; the third comparison condition indicates that the surface crude oil migration risk indicator is greater than the preset surface oil film migration risk second indicator; the surface crude oil migration early warning instruction is used to prompt preset personnel to intervene.

4. The method for predicting the migration and evolution risk of crude oil leakage in a lake-oriented wetland area according to claim 1, characterized in that, The impact of the crude oil infiltration process in the tributary region on the crude oil infiltration path specifically includes: The soil permeability index and the underground migration resistance index of the tributary area are obtained and compared with the preset soil permeability index and the preset underground migration resistance index in the database to obtain the soil permeability index score and the underground migration resistance index score; the soil permeability index score and the underground migration resistance index score are summed and averaged to obtain the underground oil film migration risk index.

5. The method for predicting the risk of crude oil spill migration and evolution in a lake-oriented wetland area according to claim 4, characterized in that, The determination of whether a second water pollution risk feedback is needed specifically includes: If the underground oil film migration risk index reaches the first-level judgment standard, it indicates that the crude oil permeation risk in the tributary area is within the corresponding risk allowable range, and proceed to step S4; the first-level judgment standard indicates that the underground oil film migration risk index is not greater than the preset underground oil film migration risk index in the database. If the underground oil film migration risk index reaches the secondary judgment standard, it indicates that the crude oil permeation risk in the tributary area exceeds the corresponding risk allowable range, and an oil film permeation warning instruction is sent; the secondary judgment standard indicates that the underground oil film migration risk index is greater than the preset underground oil film migration risk index in the database; the oil film permeation warning instruction is used to prompt preset personnel to intervene.

6. The method for predicting the risk of crude oil spill migration and evolution in a lake-oriented wetland area according to claim 1, characterized in that, The impact of the tributary inflow process in the tributary region, which quantifies the intensity of turbulence, on the migration and diffusion of crude oil film under static conditions specifically includes: The proportional deviation between the tributary inflow deviation data of the turbulent intensity tributary region and the preset tributary inflow deviation data in the database is obtained; By combining the tributary inflow compensation factor, the degree of deviation of each ratio is compensated, and the results of the compensation process are coupled to obtain the oil film migration and diffusion risk index.

7. The method for predicting the risk of crude oil spill migration and evolution in a lake-oriented wetland area according to claim 6, characterized in that, The determination of whether a third-party water pollution risk feedback is needed specifically includes: If the oil film migration and diffusion risk index is not greater than the preset oil film migration and diffusion risk index, it indicates that the crude oil film diffusion risk under the static environment is within the corresponding allowable range, and proceed to step S5. If the oil film migration and diffusion risk index is greater than the preset oil film migration and diffusion risk index, then a third water pollution risk feedback and intervention will be conducted.

8. The method for predicting the risk of crude oil spill migration and evolution in a lake-oriented wetland area according to claim 7, characterized in that, The determination of whether a third-party water pollution risk feedback is needed specifically includes: If the oil film migration and diffusion risk index is within the closed interval corresponding to the maximum value of the preset oil film migration and diffusion risk index and the historical oil film migration and diffusion risk index, it indicates that the crude oil film diffusion risk under the static environment is within the corresponding controllable range, and a third water pollution feedback instruction is sent. Determine whether the oil film migration and diffusion risk index is greater than the maximum value of the historical oil film migration and diffusion risk index; if so, send a crude oil film diffusion risk warning instruction to prompt the preset personnel to intervene; otherwise, complete the third water pollution risk feedback and intervention and proceed to step S5.

9. The method for predicting the risk of crude oil spill migration and evolution in a lake-oriented wetland area according to claim 1, characterized in that, The specific impact of the tributary inflow process in the turbulent tributary region on the diffusion of crude oil film under wind speed, through quantifying the tributary intensity tributary region, includes: The area of ​​the oil film diffusion region in the turbulent intensity tributary region is obtained and compared with the preset oil film diffusion region area in the database to obtain the oil film diffusion region area fraction.

10. The method of claim 1, wherein, The determination of whether a fourth water pollution risk feedback is needed specifically includes: If the area fraction of the oil film diffusion region meets the first-level risk condition, it indicates that the risk of crude oil film diffusion under the action of wind speed is in a controllable stage; the first-level risk condition means that the area fraction of the oil film diffusion region is not greater than the preset area fraction of the oil film diffusion region in the database. If the area fraction of the oil film diffusion region meets the secondary risk condition, it indicates that the risk of crude oil film diffusion under wind speed is in an uncontrollable stage, and an oil film migration and diffusion early warning instruction is sent. The secondary risk condition means that the area fraction of the oil film diffusion region is greater than the preset area fraction of the oil film diffusion region in the database. The oil film migration and diffusion early warning instruction is used to prompt preset personnel to intervene and complete the risk prediction of the crude oil film diffusion stage. The risk prediction of the crude oil film diffusion stage includes static environmental risk prediction and wind speed environmental risk prediction.

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