Marine disaster risk prevention area early warning grading method based on offshore environment

Abstract

According to the offshore environment-based marine disaster risk prevention area early warning grading method and device provided by the invention, the disaster risk level of the risk prevention area can be automatically determined without artificial participation, so that the labor cost can be reduced, and the risk prevention efficiency can be improved. The method can improve the efficiency of determining the disaster risk level of the risk prevention area, then, the disaster risk level of each seawall in the risk prevention area is considered, and when the disaster risk level of any seawall is determined, the disaster risk level of the risk prevention area is determined. The wind element data of the area where the seawall is located, the sea wave element data of the area where the seawall is located and the tide level element data of the area where the seawall is located are considered, so that the consideration factors are more comprehensive, and the accuracy of determining the disaster risk level of any seawall can be improved; and the accuracy of determining the disaster risk level of the risk prevention area can be improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method and device for early warning and grading marine disaster risk prevention zones based on nearshore and offshore environments. Background Art

[0002] During storm surge disasters, coastal marine risk prevention areas are at risk of dike overflow and inundation. Therefore, it is necessary to know in advance whether there is a risk of dike overflow. If there is a risk of dike overflow, it is necessary to predict the possible disaster risk level in the risk prevention area so that disaster prevention decisions can be made in advance.

[0003] However, the current method of predicting the disaster risk level of a risk prevention area is that forecasters predict the disaster risk level of the risk prevention area through manual experience.

[0004] However, the accuracy of forecasters' predictions of disaster risk levels in risk prevention areas based on manual experience is low. Summary of the Invention

[0005] This application illustrates a method and device for early warning and grading of marine disaster risk prevention zones based on nearshore and offshore environments.

[0006] In the first aspect, the present application provides a method for early warning and grading marine disaster risk prevention zones based on nearshore and offshore environments, the method comprising:

[0007] Acquire multiple target seawalls included in the target risk prevention area;

[0008] For any one of the multiple target seawalls, wind factor data for the area where the target seawall is located, wave factor data for the area where the target seawall is located, and tide level factor data for the area where the target seawall is located are obtained, and a disaster risk level of the target seawall is obtained based on the wind factor data, the wave factor data, and the tide level factor data;

[0009] The disaster risk level of the target risk prevention area is determined according to the disaster risk level of each target seawall among the multiple target seawalls.

[0010] In an optional implementation, obtaining a plurality of target seawalls within a target risk prevention area includes:

[0011] Determine the multiple sub-areas included in the target risk prevention area;

[0012] A plurality of target seawalls included in each sub-area are determined.

[0013] In an optional implementation, determining the disaster risk level of the target risk prevention area according to the disaster risk level of each target seawall among the multiple target seawalls includes:

[0014] For any sub-area among the multiple sub-areas, screening the disaster risk level of each target seawall included in the sub-area respectively; determining the disaster risk level of the sub-area according to the disaster risk level of each target seawall included in the sub-area;

[0015] The disaster risk level of the target risk prevention area is determined according to the disaster risk level of each sub-area in the multiple sub-areas.

[0016] In an optional implementation, determining the disaster risk level of the sub-area according to the disaster risk level of each target seawall included in the sub-area includes:

[0017] Selecting the highest disaster risk level among the disaster risk levels of the target seawalls within the sub-area;

[0018] The disaster risk level of the sub-area is determined according to the selected highest level of disaster risk level.

[0019] In an optional implementation, determining the disaster risk level of the target risk prevention area according to the disaster risk level of each sub-area in the multiple sub-areas includes:

[0020] Selecting the highest disaster risk level from the disaster risk levels of each sub-area in the plurality of sub-areas;

[0021] The disaster risk level of the target risk prevention area is determined based on the highest level of disaster risk level screened.

[0022] In an optional implementation, obtaining the disaster risk level of the target seawall based on the wind element data, the wave element data, and the tide level element data includes:

[0023] Obtaining a wind warning level for the target seawall according to the wind element data;

[0024] Obtaining a wave warning level of the target seawall according to the wave element data;

[0025] Obtaining a tide level warning level for the target seawall according to the tide level element data;

[0026] The disaster risk level of the target seawall is determined according to the wind warning level, the wave warning level, and the tide warning level.

[0027] In an optional implementation, determining the disaster risk level of the target seawall according to the wind warning level, the wave warning level, and the tide warning level includes:

[0028] The disaster risk level of the target seawall is calculated according to the wind warning level, the wave warning level, and the tide warning level according to the following formula:

[0029] S=α*A+β*B+γ*C;

[0030] In the above formula, S is the disaster risk level of the target seawall, A is the wind warning level, B is the wave warning level, C is the tide warning level, α is the preset weight corresponding to the wind, β is the preset weight corresponding to the wave, and γ is the preset weight corresponding to the tide.

[0031] In a second aspect, the present application provides a marine disaster risk prevention zone early warning and grading device based on a nearshore or offshore environment, the device comprising:

[0032] A first acquisition module is used to acquire multiple target seawalls included in the target risk prevention area;

[0033] a second acquisition module configured to acquire, for any one of the plurality of target seawalls, wind element data, wave element data, and tidal element data of an area where the target seawall is located; and a third acquisition module configured to acquire a disaster risk level of the target seawall based on the wind element data, the wave element data, and the tidal element data.

[0034] The determination module is used to determine the disaster risk level of the target risk prevention area according to the disaster risk level of each target seawall among the multiple target seawalls.

[0035] In an optional implementation, the first acquisition module includes:

[0036] A first determining unit is configured to determine a plurality of sub-areas included in a target risk prevention area;

[0037] The second determining unit is configured to determine a plurality of target seawalls included in each sub-area.

[0038] In an optional implementation, the determining module includes:

[0039] a screening unit configured to screen, for any one of the plurality of sub-areas, the disaster risk levels of the target seawalls included in the sub-area; a third determining unit configured to determine the disaster risk level of the sub-area based on the disaster risk levels of the target seawalls included in the sub-area;

[0040] The fourth determining unit is configured to determine the disaster risk level of the target risk prevention area according to the disaster risk level of each sub-area in the multiple sub-areas.

[0041] In an optional implementation, the third determining unit includes:

[0042] A first selection subunit is configured to select the highest disaster risk level among the disaster risk levels of the target seawalls within the sub-area;

[0043] The first determining subunit is configured to determine the disaster risk level of the sub-area according to the selected highest disaster risk level.

[0044] In an optional implementation, the fourth determining unit includes:

[0045] A second selection subunit is configured to select the highest disaster risk level from the disaster risk levels of each sub-area in the plurality of sub-areas;

[0046] The second determining subunit is configured to determine the disaster risk level of the target risk prevention area according to the highest disaster risk level screened.

[0047] In an optional implementation, the third acquisition module includes:

[0048] a first acquiring unit, configured to acquire a wind warning level of the target seawall according to the wind element data;

[0049] A second acquiring unit is configured to acquire a wave warning level of the target seawall according to the wave element data;

[0050] a third acquiring unit, configured to acquire a tide level warning level of the target seawall according to the tide level element data;

[0051] A fifth determining unit is configured to determine the disaster risk level of the target seawall according to the wind warning level, the wave warning level, and the tide warning level.

[0052] In an optional implementation, the fifth determining unit includes:

[0053] The determination subunit is configured to calculate the disaster risk level of the target seawall according to the wind warning level, the wave warning level, and the tide warning level according to the following formula:

[0054] S=α*A+β*B+γ*C;

[0055] In the above formula, S is the disaster risk level of the target seawall, A is the wind warning level, B is the wave warning level, C is the tide warning level, α is the preset weight corresponding to the wind, β is the preset weight corresponding to the wave, and γ is the preset weight corresponding to the tide.

[0056] In a third aspect, the present application shows an electronic device, which includes: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the method described in any of the above aspects.

[0057] In a fourth aspect, the present application shows a non-temporary computer-readable storage medium, which, when the instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to execute the method described in any of the above aspects.

[0058] In a fifth aspect, the present application illustrates a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device is enabled to execute the method as described in any one of the above aspects.

[0059] The technical solution provided by this application may have the following beneficial effects:

[0060] In this application, multiple target seawalls within a target risk prevention area are obtained. For any one of these target seawalls, wind factor data for the area where the target seawall is located, wave factor data for the area where the target seawall is located, and tide factor data for the area where the target seawall is located are obtained. Based on the wind factor data, wave factor data, and tide factor data, a disaster risk level for the target seawall is obtained. Based on the disaster risk level of each of the multiple target seawalls, the disaster risk level of the target risk prevention area is determined.

[0061] Through this application, the disaster risk level of the risk prevention area can be determined automatically without human participation, which can reduce labor costs and improve the efficiency of determining the disaster risk level of the risk prevention area. Secondly, the disaster risk level of the risk prevention area is determined taking into account the disaster risk level of each seawall in the risk prevention area. When determining the disaster risk level of any seawall, the wind element data of the area where the seawall is located, the wave element data of the area where the seawall is located, and the tide level element data of the area where the seawall is located are taken into account. The factors are considered more comprehensively, which can improve the accuracy of the disaster risk level of any seawall determined, and thus improve the accuracy of the disaster risk level of the determined risk prevention area. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a flow chart of a method for early warning and grading marine disaster risk prevention zones based on nearshore and offshore environments in this application.

[0063] Figure 2 It is a flowchart of a method for obtaining multiple target seawalls included in a target risk prevention area of ​​the present application.

[0064] Figure 3 This is a flowchart of a method for determining the disaster risk level of a target risk prevention area in the present application.

[0065] Figure 4 This is a structural block diagram of a marine disaster risk prevention zone early warning and grading device based on nearshore and offshore environments in this application.

[0066] Figure 5 This is a block diagram of an electronic device of the present application.

[0067] Figure 6 This is a block diagram of an electronic device of the present application. DETAILED DESCRIPTION

[0068] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0069] Before introducing the technical solution of this application, the technical terms that may be involved in this application are first explained.

[0070] NWP (Numerical Weather Prediction): It is a method based on the actual atmospheric conditions, which uses large computers to perform numerical calculations and solve fluid mechanics and thermodynamics equations to predict future atmospheric motion and weather phenomena.

[0071] NetCDF (Network Common Data Form): It is a description and encoding standard for array-oriented data suitable for network sharing.

[0072] IDW (Inverse Distance Weighting) interpolation: Things that are closer to each other are more similar than things that are farther away. When predicting a value for any unmeasured location, IDW uses the measurements surrounding the predicted location. The measurements closest to the predicted location have a greater influence on the predicted value than those farther away. IDW assumes that each measured point has a local influence that decreases with distance. Because this method assigns greater weights to points closest to the predicted location, while the weights decrease as a function of distance, it is called IDW.

[0073] See also Figure 1 , shows a flow chart of a method for early warning and grading marine disaster risk prevention zones based on nearshore and offshore environments of the present application, which is applied to electronic equipment and is characterized in that the method includes:

[0074] In step S101 , a plurality of target seawalls included in a target risk prevention area are obtained.

[0075] In this application, a risk prevention area includes multiple seawalls. The seawalls included in each risk prevention area can be counted and recorded in advance. In this way, for the target risk prevention area, the multiple target seawalls included in the target risk prevention area that have been recorded can be searched.

[0076] Each seawall has its own location and occupies a certain area. If the area occupied by a certain seawall is located within a certain risk prevention area, then the certain seawall can be regarded as a seawall included in the certain risk prevention area.

[0077] The risk prevention area can be an area divided manually based on experience.

[0078] In step S102, for any one of the multiple target seawalls, wind element data of the area where the target seawall is located is obtained, wave element data of the area where the target seawall is located is obtained, and tide element data of the area where the target seawall is located is obtained. Based on the wind element data, the wave element data and the tide element data, the disaster risk level of the target seawall is obtained.

[0079] The wind element data of the area where the target seawall is located may include wind element data of the area where the target seawall is located within a period of time in the future after the current moment.

[0080] The ocean wave element data of the area where the target seawall is located may include ocean wave element data of the area where the target seawall is located within a period of time in the future after the current moment.

[0081] The tide level element data of the area where the target seawall is located may include tide level element data of the area where the target seawall is located within a period of time in the future after the current moment.

[0082] The length of the period of time may include 1 hour, 2 hours, 3 hours, 6 hours, 12 hours, 24 hours or 48 hours, etc., and may be determined according to actual circumstances, and this application does not impose any limitation on this.

[0083] In one embodiment of the present application, when obtaining wind element data of the area where the target seawall is located, the wind element data forecasting model with the highest accuracy in forecasting wind element data of the area where the target seawall is located in the historical process can be selected from multiple wind element data forecasting models used to forecast wind element data of the area where the target seawall is located. The wind element data of the area where the target seawall is located is forecasted based on the wind element data forecasting model with the highest accuracy to improve the accuracy of the obtained wind element data of the area where the target seawall is located.

[0084] For example, multiple wind element data forecasting models used to forecast wind element data may include: GRAPES (Global / Regional Assimilation and PrEdiction System, China Meteorological Administration Global Assimilation Forecast System), ECMWF (European Centre for Medium-Range Weather Forecasts, European Center for Medium-Range Weather Forecasts) and GFS (Global Forecast System, U.S. National Centers for Environmental Prediction Global Forecast System), etc.

[0085] In the historical process, at least some of the multiple wind element data forecasting models used to forecast wind element data have been used to predict the wind element data of the area where the target seawall is located. The accuracy of the wind element data of the area where the target seawall is located predicted by each wind element data forecasting model in the recent period (for example, the last month, the last three months, the last six months, the last year or the last two years) can be counted, and the wind element data forecasting model with the highest accuracy in predicting the wind element data of the area where the target seawall is located in the recent period (for example, the last month, the last three months, the last six months, the last year or the last two years) is selected.

[0086] In another embodiment of the present application, when obtaining the wave element data of the area where the target seawall is located, the wave element data prediction model with the highest accuracy in predicting the wave element data of the area where the target seawall is located in the historical process can be selected from multiple wave element data prediction models used to predict the wave element data of the area where the target seawall is located. The wave element data of the area where the target seawall is located is predicted based on the wave element data prediction model with the highest accuracy, so as to improve the accuracy of the obtained wave element data of the area where the target seawall is located.

[0087] For example, multiple ocean wave element data forecasting models used to forecast ocean wave element data may include: Mazu (MazuWave Model, Mazu ocean wave numerical prediction system), ECWAM (cean Wave Model, ECMWF European Center ocean wave model), NMEFC (National Marine Environmental Forecasting Center, National Marine Environmental Forecasting Center) and GRAPES_WW3 (GRAPES Wave Model, National Meteorological Administration Global Assimilation Forecasting System and WW3 Ocean Wave Model Coupling System), etc.

[0088] In the historical process, at least some of the multiple wave element data forecasting models for forecasting wave element data have been used to respectively predict the wave element data of the area where the target seawall is located. The accuracy of the wave element data of the area where the target seawall is located predicted by each wave element data forecasting model in the recent period (for example, the last month, the last three months, the last six months, the last year or the last two years) can be counted, and the wave element data forecasting model with the highest accuracy in predicting the wave element data of the area where the target seawall is located in the recent period (for example, the last month, the last three months, the last six months, the last year or the last two years) is selected.

[0089] In another embodiment of the present application, when obtaining the tide element data of the area where the target seawall is located, the tide element data prediction model with the highest accuracy in predicting the tide element data of the area where the target seawall is located in the historical process can be selected from multiple tide element data prediction models used to predict the tide element data of the area where the target seawall is located. The tide element data of the area where the target seawall is located is predicted based on the tide element data prediction model with the highest accuracy to improve the accuracy of the obtained tide element data of the area where the target seawall is located.

[0090] For example, multiple tide element data forecasting models for forecasting ocean wave element data may include: the global tide forecast service system, the global tide and current numerical prediction subsystem in the global operational oceanographic forecast system, and the East China Sea ocean numerical prediction system.

[0091] In the historical process, at least some of the multiple tide element data forecasting models for forecasting tide element data have been used to predict the tide element data of the area where the target seawall is located. The accuracy of the tide element data of the area where the target seawall is located predicted by each tide element data forecasting model in the recent period (for example, the last month, the last three months, the last half year, the last year or the last two years) can be counted, and the tide element data forecasting model with the highest accuracy in predicting the tide element data of the area where the target seawall is located in the recent period (for example, the last month, the last three months, the last half year, the last year or the last two years) is selected.

[0092] In another embodiment of the present application, when obtaining the disaster risk level of the target seawall according to the wind element data, the wave element data, and the tide element data, it can be achieved through the following process, including:

[0093] 1021. Obtain a wind warning level for the target seawall based on the wind element data.

[0094] In one embodiment of the present application, the wind element data includes the wind speed in the area where the target seawall is located. Thus, when obtaining the wind warning level for the target seawall based on the wind element data, a target wind speed interval within which the wind speed falls can be determined from multiple different wind speed intervals. The wind warning level corresponding to the target wind speed interval is searched in the correspondence between wind speed intervals and wind warning levels. The wind warning level for the target seawall is determined based on the found wind warning level. For example, the found wind warning level can be determined as the wind warning level for the target seawall.

[0095] The multiple different wind speed intervals may be pre-set intervals, and the different wind speed intervals do not overlap.

[0096] The correspondence between wind speed intervals and wind warning levels is set in advance. Different wind speed intervals correspond to different wind warning levels. The higher the wind speed interval, the higher the corresponding wind warning level, or the lower the wind speed interval, the lower the corresponding wind warning level.

[0097] In one embodiment of the present application, for any seawall, the area occupied by the seawall is larger and the length is longer. The area occupied by the seawall can be regarded as the area where the seawall is located. The data of the seawall obtained is often vector data. The vector data is irregular discrete data of the seawall, for example, the position points (position coordinates) of multiple vector positions of the seawall in the length direction of the seawall, etc.

[0098] However, the acquired wind element data for the area where the target seawall is located is grid data, and the position points involved in the grid data are often different from the position points of the multiple vector positions of the seawall in the longitudinal direction of the seawall.

[0099] Thus, it is necessary to project the obtained grid data of the wind element data of the area where the target seawall is located onto position points of a plurality of vector positions of the seawall in the longitudinal direction of the seawall.

[0100] For example, for the position point of any vector position of the target seawall in the length direction of the seawall, the inverse distance weighted method is used to project the N (N is a positive integer greater than or equal to 2) grid data of the wind element data of the area where the target seawall is located, which are closest to the position point of any vector position, onto the position point of any vector position, to obtain the wind element data corresponding to the position point of the target seawall at any vector position. The wind element data corresponding to the position point of the target seawall at any vector position include: the wind speed corresponding to the position point of the target seawall at any vector position, and then, in multiple different wind speed intervals, determine the target wind speed interval in which the wind speed corresponding to the position point of the target seawall at any vector position is located, and in the correspondence between the wind speed interval and the wind warning level, find the wind warning level corresponding to the target wind speed interval to obtain the wind warning level corresponding to the position point of the target seawall at any vector position.

[0101] The above operation is also performed for each of the other vector positions of the target seawall in the length direction of the seawall, so as to obtain the wind warning level corresponding to each vector position of the target seawall.

[0102] Then, among the wind warning levels corresponding to the position points of the target seawall at each vector position, the maximum wind warning level is selected and used as the wind warning level of the target seawall.

[0103] 1022. Obtain a wave warning level for the target seawall based on the wave element data.

[0104] In one embodiment of the present application, the wave element data includes the wave speed in the area where the target seawall is located. Thus, when obtaining the wave warning level for the target seawall based on the wave element data, a target wave speed interval within which the wave speed falls can be determined from a plurality of different wave speed intervals. The wave warning level corresponding to the target wave speed interval is searched in the correspondence between wave speed intervals and wave warning levels. The wave warning level for the target seawall is determined based on the found wave warning level. For example, the found wave warning level can be determined as the wave warning level for the target seawall.

[0105] The multiple different wave speed intervals may be pre-set intervals, and the different wave speed intervals do not overlap.

[0106] The correspondence between the wave speed range and the wave warning level is set in advance. Different wave speed ranges correspond to different wave warning levels. The higher the wave speed range, the higher the corresponding wave warning level, and the lower the wave speed range, the lower the corresponding wave warning level.

[0107] In one embodiment of the present application, for any seawall, the area occupied by the seawall is larger and the length is longer. The area occupied by the seawall can be regarded as the area where the seawall is located. The data of the seawall obtained is often vector data. The vector data is irregular discrete data of the seawall, for example, the position points (position coordinates) of multiple vector positions of the seawall in the length direction of the seawall, etc.

[0108] However, the acquired wave element data for the area where the target seawall is located is grid data, and the position points involved in the grid data are often different from the position points of the multiple vector positions of the seawall in the longitudinal direction of the seawall.

[0109] Thus, it is necessary to project the obtained grid data of the wave element data of the area where the target seawall is located onto the position points of multiple vector positions of the seawall in the longitudinal direction of the seawall.

[0110] For example, for the position point of any vector position of the target seawall in the length direction of the seawall, the inverse distance weighted method is used to project the N (N is a positive integer greater than or equal to 2) grid data of the wave element data of the area where the target seawall is located, which are closest to the position point of the any vector position, onto the position point of the any vector position, to obtain the wave element data corresponding to the position point of the target seawall at the any vector position. The wave element data corresponding to the position point of the target seawall at the any vector position include: the wave speed corresponding to the position point of the target seawall at the any vector position, and then, in multiple different wave speed intervals, determine the target wave speed interval within which the wave speed corresponding to the position point of the target seawall at the any vector position is located, and in the correspondence between the wave speed interval and the wave warning level, find the wave warning level corresponding to the target wave speed interval to obtain the wave warning level corresponding to the position point of the target seawall at the any vector position.

[0111] The above operation is also performed for each of the other vector positions of the target seawall in the longitudinal direction of the seawall, thereby obtaining the wave warning level corresponding to each vector position of the target seawall.

[0112] Then, among the wave warning levels corresponding to the position points of the target seawall at each vector position, the largest wave warning level is selected and used as the wave warning level of the target seawall.

[0113] 1023. Obtain the tide level warning level of the target seawall based on the tide level element data.

[0114] In one embodiment of the present application, the tide level element data includes the tide level height of the area where the target seawall is located. Thus, when obtaining the tide level warning level of the target seawall based on the tide level element data, a target tide level height interval within which the tide level height is located can be determined from a plurality of different tide level height intervals. In the correspondence between tide level intervals and tide level warning levels, the tide level warning level corresponding to the target tide level interval is searched. The tide level warning level of the target seawall is determined based on the found tide level warning level. For example, the found tide level warning level is determined as the tide level warning level of the target seawall.

[0115] The multiple different tidal height intervals may be pre-set intervals, and the different tidal height intervals do not overlap.

[0116] The correspondence between the tide height interval and the tide warning level is set in advance. Different tide height intervals correspond to different tide warning levels. The higher the tide height interval, the higher the corresponding tide warning level; or, the lower the tide height interval, the lower the corresponding tide warning level.

[0117] In one embodiment of the present application, for any seawall, the area occupied by the seawall is large and the length is long. The area occupied by the seawall can be regarded as the area where the seawall is located. The relevant data of the seawall obtained is often vector data. The vector data is irregular discrete data of the seawall, for example, the position points (position coordinates) of multiple vector positions of the seawall in the length direction of the seawall, etc.

[0118] However, the acquired tide level element data of the area where the target seawall is located is grid data, and the position points involved in the grid data are often different from the position points of the multiple vector positions of the seawall in the longitudinal direction of the seawall.

[0119] Thus, it is necessary to project the obtained grid data of the tide level element data of the area where the target seawall is located onto the position points of multiple vector positions of the seawall in the length direction of the seawall.

[0120] For example, for the position point of any vector position of the target seawall in the length direction of the seawall, the inverse distance weighted method is used to project the N (N is a positive integer greater than or equal to 2) grid data of the tide element data of the area where the target seawall is located, which are closest to the position point of any vector position, onto the position point of any vector position, to obtain the tide element data corresponding to the position point of the target seawall at any vector position. The tide element data corresponding to the position point of the target seawall at any vector position include: the tide height corresponding to the position point of the target seawall at any vector position, and then, in multiple different tide height intervals, determine the target tide height interval within which the tide height corresponding to the position point of the target seawall at any vector position is located. In the correspondence between the tide height interval and the tide warning level, find the tide warning level corresponding to the target tide height interval to obtain the tide warning level corresponding to the position point of the target seawall at any vector position.

[0121] The above operation is also performed for each of the other vector positions of the target seawall in the length direction of the seawall, so as to obtain the tide level warning level corresponding to each vector position of the target seawall.

[0122] Then, among the tide warning levels corresponding to the position points of the target seawall at each vector position, the largest tide warning level is selected and used as the tide warning level of the target seawall.

[0123] Based on the risk grading method of critical water level threshold, the predicted storm surge level (including water increase) is compared with the design elevation of the seawall to calculate the overtopping risk index. Here, the tidal height risk level of the seawall can be assessed based on this method.

[0124] 1024. Determine the disaster risk level of the target seawall based on the wind warning level, the wave warning level, and the tide warning level.

[0125] In one embodiment of the present application, the disaster risk level of the target seawall can be calculated according to the wind warning level, the wave warning level, and the tide warning level according to the following formula:

[0126] S=α*A+β*B+γ*C.

[0127] In the above formula, S is the disaster risk level of the target seawall, A is the wind warning level, B is the wave warning level, C is the tide warning level, α is the preset weight corresponding to the wind, β is the preset weight corresponding to the wave, and γ is the preset weight corresponding to the tide.

[0128] The preset weight corresponding to the wind is set in advance by the technical personnel according to the actual situation, the preset weight corresponding to the waves is set in advance by the technical personnel according to the actual situation, and the preset weight corresponding to the tide level is set in advance by the technical personnel according to the actual situation. This application does not limit the specific values ​​of the preset weight corresponding to the wind, the preset weight corresponding to the waves, and the preset weight corresponding to the tide level.

[0129] In one embodiment, the sum of the preset weight corresponding to wind, the preset weight corresponding to waves, and the preset weight corresponding to tide level may be equal to a specific value, such as 1 or 2.

[0130] In one example, the preset weight corresponding to wind is 0.2, the preset weight corresponding to waves is 0.2, and the preset weight corresponding to tide level is 0.6.

[0131] Alternatively, the preset weight corresponding to wind is 0.19, the preset weight corresponding to waves is 0.22, and the preset weight corresponding to tide level is 0.59.

[0132] Alternatively, the preset weight corresponding to wind is 0.4, the preset weight corresponding to waves is 0.5, and the preset weight corresponding to tide level is 1.1.

[0133] In step S103, the disaster risk level of the target risk prevention area is determined according to the disaster risk level of each target seawall among the multiple target seawalls.

[0134] In one embodiment of the present application, the highest level of disaster risk level can be screened out among the disaster risk levels of each target seawall among the multiple target seawalls, and the disaster risk level of the target risk prevention area can be determined based on the screened highest level of disaster risk level. For example, the highest level of disaster risk level can be determined as the disaster risk level of the target risk prevention area.

[0135] Furthermore, the disaster risk level of the target risk prevention area can provide early warning and decision-making basis for disaster prevention and mitigation in subsequent coastal risk prevention areas.

[0136] Furthermore, the probability-consequence matrix method can be used to combine the probability of storm surge occurrence (historical statistics + climate model) with potential consequences (including population, GDP, and infrastructure density, etc.) to generate a risk heat map for disaster prevention personnel to review and make decisions.

[0137] In this application, multiple target seawalls within a target risk prevention area are obtained. For any one of these target seawalls, wind factor data for the area where the target seawall is located, wave factor data for the area where the target seawall is located, and tide factor data for the area where the target seawall is located are obtained. Based on the wind factor data, wave factor data, and tide factor data, a disaster risk level for the target seawall is obtained. Based on the disaster risk level of each of the multiple target seawalls, the disaster risk level of the target risk prevention area is determined.

[0138] Through this application, the disaster risk level of the risk prevention area can be determined automatically without human participation, which can reduce labor costs and improve the efficiency of determining the disaster risk level of the risk prevention area. Secondly, the disaster risk level of the risk prevention area is determined taking into account the disaster risk level of each seawall in the risk prevention area. When determining the disaster risk level of any seawall, the wind element data of the area where the seawall is located, the wave element data of the area where the seawall is located, and the tide level element data of the area where the seawall is located are taken into account. The factors are considered more comprehensively, which can improve the accuracy of the disaster risk level of any seawall determined, and thus improve the accuracy of the disaster risk level of the determined risk prevention area.

[0139] In another embodiment of the present application, see Figure 2 , step S101 includes:

[0140] In step S201 , a plurality of sub-areas included in a target risk prevention area are determined.

[0141] The area occupied by a risk prevention area is large, or the area occupied is large. The risk prevention area can be divided in advance to obtain multiple sub-areas within the risk prevention area. The multiple sub-areas within the multiple risk prevention areas do not overlap. This application does not limit the way to divide the risk prevention area. It can be divided according to area, or it can be divided according to administrative areas, for example, according to the administrative areas of townships. For example, a risk prevention area includes the township administrative areas of multiple townships, and the township administrative area of ​​each township can be regarded as a different sub-area within a risk prevention area.

[0142] In one embodiment of the present application, a risk prevention area includes multiple township administrative areas, and a township has its own administrative area. After a risk prevention area is manually delineated in advance, if a township administrative area is located within the risk prevention area, then the township administrative area is the township administrative area included in the risk prevention area.

[0143] In one embodiment of the present application, multiple sub-areas corresponding to the target risk prevention area can be searched in the pre-set correspondence between the risk prevention area and the sub-areas included in the risk prevention area, and used as the multiple sub-areas included in the target risk prevention area.

[0144] In the correspondence between the risk prevention area and the sub-areas included in the risk prevention area, one risk prevention area corresponds to multiple sub-areas, the sub-areas corresponding to different risk prevention areas do not overlap, and the multiple sub-areas corresponding to the same risk prevention area do not overlap.

[0145] In step S202, a plurality of target seawalls included in each sub-area are determined.

[0146] In one embodiment of the present application, for any sub-area, multiple seawalls corresponding to the sub-area can be searched in the pre-set correspondence between the sub-area and the seawalls included in the sub-area, and used as the multiple target seawalls included in the sub-area.

[0147] For each of the other sub-regions, perform the above operation in the same way.

[0148] In one embodiment of the present application, a sub-area includes multiple seawalls, and a sub-area has a certain area range. Each seawall has its own position and occupies a certain area. If a seawall is located in a sub-area, then the seawall is the seawall included in the sub-area.

[0149] In the correspondence between the sub-areas and the seawalls included in the sub-areas, one sub-area corresponds to multiple seawalls, the seawalls corresponding to different sub-areas do not overlap, and the multiple seawalls corresponding to the same sub-area do not overlap.

[0150] Through this embodiment, the risk prevention area and the seawall are associated through sub-areas to improve the accuracy of obtaining multiple target seawalls included in the target risk prevention area. For example, the risk prevention area and the seawall are associated through township administrative areas to improve the accuracy of obtaining multiple target seawalls included in the target risk prevention area.

[0151] Accordingly, based on Figure 2In another embodiment of the present application, see Figure 3 , step S103 includes:

[0152] In step S301, for any sub-region among the multiple sub-regions, the disaster risk level of each target seawall included in the sub-region is screened respectively, and the disaster risk level of the sub-region is determined based on the disaster risk level of each target seawall included in the sub-region.

[0153] Among them, the highest level of disaster risk level can be selected from the disaster risk levels of each target seawall included in the sub-area, and then the disaster risk level of the sub-area can be determined based on the selected highest level of disaster risk level. For example, the selected highest level of disaster risk level can be determined as the disaster risk level of the sub-area.

[0154] The same is true for each of the other sub-regions in the plurality of sub-regions.

[0155] In step S302, the disaster risk level of the target risk prevention area is determined according to the disaster risk level of each sub-area in the multiple sub-areas.

[0156] Among them, the highest level of disaster risk level can be screened out from the disaster risk levels of each sub-area in the multiple sub-areas, and then the disaster risk level of the target risk prevention area can be determined based on the screened highest level of disaster risk level. For example, the screened highest level of disaster risk level can be determined as the disaster risk level of the target risk prevention area.

[0157] This application accurately measures the granularity of disaster risk levels to the granularity of seawalls and sub-regions, with a high degree of refinement and high accuracy. For example, this application accurately measures the granularity of disaster risk levels to the granularity of seawalls and sub-regions, with a high degree of refinement and high accuracy.

[0158] It should be noted that for the method embodiments, for simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all optional embodiments, and the actions involved are not necessarily required by this application.

[0159] Reference Figure 4 , shows a marine disaster risk prevention zone early warning and grading device based on the nearshore and offshore environment of the present application, the device comprising:

[0160] A first acquisition module 11 is used to acquire multiple target seawalls included in the target risk prevention area;

[0161] a second acquisition module 12 configured to acquire, for any one of the plurality of target seawalls, wind factor data, wave factor data, and tidal level factor data of an area where the target seawall is located; and a third acquisition module 13 configured to acquire a disaster risk level of the target seawall based on the wind factor data, the wave factor data, and the tidal level factor data.

[0162] The determination module 14 is configured to determine the disaster risk level of the target risk prevention area according to the disaster risk level of each target seawall among the multiple target seawalls.

[0163] In an optional implementation, the first acquisition module includes:

[0164] A first determining unit is configured to determine a plurality of sub-areas included in a target risk prevention area;

[0165] The second determining unit is configured to determine a plurality of target seawalls included in each sub-area.

[0166] In an optional implementation, the determining module includes:

[0167] a screening unit configured to screen, for any one of the plurality of sub-areas, the disaster risk levels of the target seawalls included in the sub-area; a third determining unit configured to determine the disaster risk level of the sub-area based on the disaster risk levels of the target seawalls included in the sub-area;

[0168] The fourth determining unit is configured to determine the disaster risk level of the target risk prevention area according to the disaster risk level of each sub-area in the multiple sub-areas.

[0169] In an optional implementation, the third determining unit includes:

[0170] A first selection subunit is configured to select the highest disaster risk level among the disaster risk levels of the target seawalls within the sub-area;

[0171] The first determining subunit is configured to determine the disaster risk level of the sub-area according to the selected highest disaster risk level.

[0172] In an optional implementation, the fourth determining unit includes:

[0173] A second selection subunit is configured to select the highest disaster risk level from the disaster risk levels of each sub-area in the plurality of sub-areas;

[0174] The second determining subunit is configured to determine the disaster risk level of the target risk prevention area according to the highest disaster risk level screened.

[0175] In an optional implementation, the third acquisition module includes:

[0176] a first acquiring unit, configured to acquire a wind warning level of the target seawall according to the wind element data;

[0177] A second acquiring unit is configured to acquire a wave warning level of the target seawall according to the wave element data;

[0178] a third acquiring unit, configured to acquire a tide level warning level of the target seawall according to the tide level element data;

[0179] A fifth determining unit is configured to determine the disaster risk level of the target seawall according to the wind warning level, the wave warning level, and the tide warning level.

[0180] In an optional implementation, the fifth determining unit includes:

[0181] The determination subunit is configured to calculate the disaster risk level of the target seawall according to the wind warning level, the wave warning level, and the tide warning level according to the following formula:

[0182] S=α*A+β*B+γ*C;

[0183] In the above formula, S is the disaster risk level of the target seawall, A is the wind warning level, B is the wave warning level, C is the tide warning level, α is the preset weight corresponding to the wind, β is the preset weight corresponding to the wave, and γ is the preset weight corresponding to the tide.

[0184] In this application, multiple target seawalls within a target risk prevention area are obtained. For any one of these target seawalls, wind factor data for the area where the target seawall is located, wave factor data for the area where the target seawall is located, and tide factor data for the area where the target seawall is located are obtained. Based on the wind factor data, wave factor data, and tide factor data, a disaster risk level for the target seawall is obtained. Based on the disaster risk level of each of the multiple target seawalls, the disaster risk level of the target risk prevention area is determined.

[0185] Through this application, the disaster risk level of the risk prevention area can be determined automatically without human participation, which can reduce labor costs and improve the efficiency of determining the disaster risk level of the risk prevention area. Secondly, the disaster risk level of the risk prevention area is determined taking into account the disaster risk level of each seawall in the risk prevention area. When determining the disaster risk level of any seawall, the wind element data of the area where the seawall is located, the wave element data of the area where the seawall is located, and the tide level element data of the area where the seawall is located are taken into account. The factors are considered more comprehensively, which can improve the accuracy of the disaster risk level of any seawall determined, and thus improve the accuracy of the disaster risk level of the determined risk prevention area.

[0186] Optionally, an embodiment of the present application also provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and runnable on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0187] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the various processes of the above-described method embodiments are implemented and the same technical effects are achieved. To avoid repetition, the details are not described here. The computer-readable storage medium may be, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0188] Figure 5 8 is a block diagram of an electronic device 800 shown in the present application. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0189] Reference Figure 5 , the electronic device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / output (I / O) interface 812 , a sensor component 814 , and a communication component 816 .

[0190] The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, phone calls, data communications, camera operation, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to perform all or part of the steps of the above-described method. In addition, the processing component 802 may include one or more modules to facilitate interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.

[0191] The memory 804 is configured to store various types of data to support operations on the device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, images, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0192] The power supply component 806 provides power to the various components of the electronic device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 800.

[0193] The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor can not only sense the boundaries of the touch or slide action, but also monitor the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each front camera and rear camera can be a fixed optical lens system or have a focal length and optical zoom capability.

[0194] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), which is configured to receive external audio signals when the electronic device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal can be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0195] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as a keyboard, click wheel, buttons, etc. These buttons may include but are not limited to: a home button, volume buttons, a start button, and a lock button.

[0196] The sensor assembly 814 includes one or more sensors for providing various aspects of status assessment for the electronic device 800. For example, the sensor assembly 814 can monitor the open / closed state of the device 800, the relative positioning of components, such as the display and keypad of the electronic device 800. The sensor assembly 814 can also monitor the position change of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, the orientation or acceleration / deceleration of the electronic device 800, and the temperature change of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to monitor the presence of nearby objects without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0197] The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 can access a wireless network based on a communication standard, such as WiFi, an operator network (such as 2G, 3G, 4G or 5G), or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast operation information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0198] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0199] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the instructions can be executed by the processor 820 of the electronic device 800 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0200] Figure 6 1 is a block diagram of an electronic device 1900 shown in the present application. For example, the electronic device 1900 can be provided as a server.

[0201] Reference Figure 6 The electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions executable by the processing component 1922, such as an application. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute the instructions to perform the above-described method.

[0202] The electronic device 1900 may further include a power supply component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input / output (I / O) interface 1958. The electronic device 1900 may operate based on an operating system stored in the memory 1932, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, or the like.

[0203] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0204] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0205] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

[0206] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the embodiments of this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0207] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0208] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0209] The units described as separate components may or may not be physically separate, and 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 these units may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0210] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0211] If the functions are implemented in the form of 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 the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

[0212] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for early warning and grading of marine disaster risk prevention areas based on nearshore and offshore environments, characterized in that: The method comprises: Acquire multiple target seawalls included in the target risk prevention area; For any one of the multiple target seawalls, wind factor data for the area where the target seawall is located, wave factor data for the area where the target seawall is located, and tide level factor data for the area where the target seawall is located are obtained, and a disaster risk level of the target seawall is obtained based on the wind factor data, the wave factor data, and the tide level factor data; The disaster risk level of the target risk prevention area is determined according to the disaster risk level of each target seawall among the multiple target seawalls.

2. The method according to claim 1, characterized in that The obtaining of multiple target seawalls within the target risk prevention area includes: Determine the multiple sub-areas included in the target risk prevention area; A plurality of target seawalls included in each sub-area are determined.

3. The method according to claim 2, characterized in that Determining the disaster risk level of the target risk prevention area according to the disaster risk level of each target seawall among the multiple target seawalls includes: For any sub-area among the multiple sub-areas, screening the disaster risk level of each target seawall included in the sub-area respectively; determining the disaster risk level of the sub-area according to the disaster risk level of each target seawall included in the sub-area; The disaster risk level of the target risk prevention area is determined according to the disaster risk level of each sub-area in the multiple sub-areas.

4. The method according to claim 3, characterized in that Determining the disaster risk level of the sub-area according to the disaster risk level of each target seawall included in the sub-area includes: Selecting the highest disaster risk level among the disaster risk levels of the target seawalls within the sub-area; The disaster risk level of the sub-area is determined according to the selected highest level of disaster risk level.

5. The method according to claim 3, characterized in that Determining the disaster risk level of the target risk prevention area according to the disaster risk level of each sub-area in the multiple sub-areas includes: Selecting the highest disaster risk level from the disaster risk levels of each sub-area in the plurality of sub-areas; The disaster risk level of the target risk prevention area is determined based on the highest level of disaster risk level screened.

6. The method according to claim 1, characterized in that The obtaining of the disaster risk level of the target seawall according to the wind element data, the wave element data, and the tide level element data includes: Obtaining a wind warning level for the target seawall according to the wind element data; Obtaining a wave warning level of the target seawall according to the wave element data; Obtaining a tide level warning level for the target seawall according to the tide level element data; The disaster risk level of the target seawall is determined according to the wind warning level, the wave warning level, and the tide warning level.

7. The method according to claim 6, characterized in that Determining the disaster risk level of the target seawall according to the wind warning level, the wave warning level, and the tide warning level includes: The disaster risk level of the target seawall is calculated according to the wind warning level, the wave warning level, and the tide warning level according to the following formula: S=α*A+β*B+γ*C; In the above formula, S is the disaster risk level of the target seawall, A is the wind warning level, B is the wave warning level, C is the tide warning level, α is the preset weight corresponding to the wind, β is the preset weight corresponding to the wave, and γ is the preset weight corresponding to the tide.

8. A marine disaster risk prevention zone early warning and grading device based on the nearshore and offshore environment, characterized in that: The device comprises: A first acquisition module is used to acquire multiple target seawalls included in the target risk prevention area; a second acquisition module configured to acquire, for any one of the plurality of target seawalls, wind element data, wave element data, and tidal element data of an area where the target seawall is located; and a third acquisition module configured to acquire a disaster risk level of the target seawall based on the wind element data, the wave element data, and the tidal element data. The determination module is used to determine the disaster risk level of the target risk prevention area according to the disaster risk level of each target seawall among the multiple target seawalls.

9. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the method according to any one of claims 1 to 7 when executed by the processor.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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