CN116029541A - Risk assessment method for extreme weather coastal zone - Google Patents
Risk assessment method for extreme weather coastal zone Download PDFInfo
- Publication number
- CN116029541A CN116029541A CN202210262089.3A CN202210262089A CN116029541A CN 116029541 A CN116029541 A CN 116029541A CN 202210262089 A CN202210262089 A CN 202210262089A CN 116029541 A CN116029541 A CN 116029541A
- Authority
- CN
- China
- Prior art keywords
- wind
- coastal zone
- area
- research area
- sea
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The invention relates to a risk assessment method for an extreme weather coastal zone. Is suitable for the technical field of water conservancy and ocean treatment. The technical scheme adopted by the invention is as follows: a risk assessment method for an extreme weather coastal zone comprises the following steps: acquiring a research area determined by a user, wherein the research area is provided with a sea area and a coastal zone; gridding the sea area in the research area; superposing the measured coordinates and water depth data of the sea area in the research area on a grid of the sea area to construct an underwater topography model of the sea area in the research area; inputting a plurality of typhoon routes logged in a research area into a wind-tide coupling model combined with an underwater topography model of the research area, and predicting tide level values of grid points and time under each wind route; extracting the maximum tide level value of each grid point of the coastal zone position under the action of different wind paths according to the grid point numbers of the coastal zone position; and evaluating disaster risk according to the maximum tide level value of each grid point at the coastal zone position and the sea wall elevation at each position of the coastal zone under the action of different wind paths.
Description
Technical Field
The invention relates to a risk assessment method for an extreme weather coastal zone. Is suitable for the technical field of water conservancy and ocean treatment.
Background
The coastal areas of China are developed in economy and high in population density, and the typhoons are high in tide in period of typhoons, so that huge economic losses and casualties are caused. Therefore, safety of the coastal zone is of great concern. The landing position and landing intensity of typhoons have time and space uncertainties, especially near-shore extreme tide level: when extreme weather encounters an astronomical climax or an upstream flood peak, the tide level will appear to increase non-linearly, further exacerbating the disaster. This results in the same coastal zone, which may be subject to a flood disaster in extreme weather even if the design criteria are met for 30 years or 50 years.
Disclosure of Invention
The invention aims to solve the technical problems that: a risk assessment method for an extreme weather coastal zone is provided, so that the risk of disaster damage of the coastal zone is scientifically assessed.
The technical scheme adopted by the invention is as follows: the extreme weather coastal zone risk assessment method is characterized by comprising the following steps of:
acquiring a research area determined by a user, wherein the research area is provided with a sea area and a coastal zone;
gridding the sea area in the research area;
superposing the measured coordinates and water depth data of the sea area in the research area on a grid of the sea area to construct an underwater topography model of the sea area in the research area;
inputting a plurality of typhoon routes logged in a research area into a wind-tide coupling model combined with an underwater topography model of the research area, and predicting tide level values of grid points and time under each wind route;
extracting the maximum tide level value of each grid point of the coastal zone position under the action of different wind paths according to the grid point numbers of the coastal zone position;
and evaluating disaster risk according to the maximum tide level value of each grid point at the coastal zone position and the sea wall elevation at each position of the coastal zone under the action of different wind paths.
The meshing of the sea area in the investigation region comprises:
the mesh size of the shallow water area on the shore is between 50 and 200m, and the mesh spacing of the deep water area is between 200 and 1000m.
The method for constructing the underwater topography model of the sea area in the research area comprises the steps of: and measuring the water depth difference to the grid node position by using a triangulation difference method.
Inputting a plurality of typhoon routes logged in a research area into a wind-tide coupling model combined with an underwater topography model of the research area, predicting tide level values of grid points and time under each wind route, and comprising the following steps:
selecting the strongest wind route logged in the research area from the optimal wind route set; establishing a route group comprising a plurality of wind routes with different parameters;
inputting an underwater topography model of a sea area in a research area and a selected strongest wind route into a wind-tide coupling model to predict a tide level value in the research area, and adjusting model parameters until the tide level predicted value and an actual measured value at the same position and each time are compared to meet a preset precision requirement;
and inputting each wind path in the wind path group into a wind-tide coupling model with adjusted parameters, and predicting the tide level values of grid points and time under each wind path.
The establishing of the wind path group comprising a plurality of wind paths with different parameters comprises the following steps:
and establishing a wind route group by adjusting any one or more of a wind route landing position, a central air pressure and a central air speed based on the strongest wind route.
The method for evaluating disaster risk according to the maximum tide level value of each grid point of the coastal zone position and the sea wall elevation of each position of the coastal zone under the action of different wind paths comprises the following steps:
judging the number of wind routes which can cause the flood dike according to the maximum tide level value of each grid point of the coastal zone position and the elevation of the seawall of each position under the action of different wind routes, and taking the ratio of the number of wind routes which can cause the flood dike to the total number contained in the wind route group as the disaster risk.
An extreme weather coastal zone risk assessment device comprising:
the area determining module is used for acquiring a research area determined by a user, wherein the research area is provided with a sea area and a coastal zone;
the sea area gridding module is used for gridding the sea area in the research area;
the terrain model construction module is used for superposing measured coordinates and water depth data of the sea area in the research area on grids of the sea area to construct an underwater terrain model of the sea area in the research area;
the model prediction module is used for inputting a plurality of typhoon routes logged in a research area into a wind-tide coupling model combined with an underwater topography model of the research area, and predicting tide level values of grid points and time under each wind route;
the data extraction module is used for extracting the maximum tide level value of each grid point of the coastal zone position under the action of different wind paths according to the grid point number of the coastal zone position;
and the risk assessment module is used for assessing the disaster risk according to the maximum tide level value of each grid point of the coastal zone position and the sea wall elevation of each position of the coastal zone under the action of different wind paths.
A maximum tide level distribution display method is characterized in that: displaying a map corresponding to the research area, and displaying the coastal zone in the research area in different colors, wherein the colors of the coastal zone are determined according to the maximum tide level values of grid points of the coastal zone position under the action of different wind paths in the extreme weather coastal zone risk assessment method.
A storage medium having stored thereon a computer program executable by a processor, characterized by: the computer program when executed implements the steps of the extreme weather coastal zone risk assessment method.
A computer device having a memory and a processor, the memory having stored thereon a computer program executable by the processor, characterized by: the computer program when executed implements the steps of the extreme weather coastal zone risk assessment method.
The beneficial effects of the invention are as follows: according to the method, an extreme weather wind-tide coupling model is established based on actual underwater topography data, wind path groups with different landing positions and landing intensities are established according to historical wind paths, the maximum tide level under the action of each wind path is simulated numerically, and compared with the current coastal zone elevation, the disaster risk of the coastal zone is analyzed quantitatively. According to the wind-tide coupling model, nonlinear interaction between wind and tide is considered, so that the tide level simulation precision is improved. The invention can comprehensively reflect the disaster situation of the coastal zone and provides technical support for disaster prevention and reduction of water conservancy and oceanic water environment treatment engineering of the coastal zone.
Drawings
Fig. 1 is a flow chart of an embodiment.
FIG. 2 is an example of a wind-moisture coupled numerical model range and computational grid provided by an embodiment.
Fig. 3 is a diagram of a coastal zone wind path moving coil provided by an embodiment.
Fig. 4 is a graph showing a comparison of predicted and measured values of the sea level of a plurality of observation stations according to an embodiment.
Fig. 5 shows the maximum tidal level distribution of the coastal zone under different routes provided by the examples.
Detailed Description
As shown in fig. 1, the present embodiment is an extreme weather coastal zone risk assessment method, which specifically includes the following steps:
s1, acquiring a research area determined by a user, wherein the research area is provided with a sea area and a coastal zone. Storm surge is a hydrodynamic phenomenon with larger movement scale, so the range of a research area is more than 5 degrees in the longitude and latitude directions.
S2, establishing triangular or orthogonal curve grids by using Delft-3d according to the position and the range of the research area, gridding the sea area in the research area, wherein the grid size of the shallow water area near the shore is preferably 50-200 m, and the grid spacing of the deep water area can be enlarged to 300-500 m (as shown in figure 2).
Obtaining chart data of a corresponding range according to the position of a research area, and registering the chart by using Mapinfo software; then, picking up shore line coordinates, measuring point coordinates and water depth data by using Mapinfo software; the shoreline data is imported into Delft-3d, and sea areas in the research area are gridded through a grid, local encryption, deletion and other tools.
And S3, superposing the measured coordinates and the water depth data of the sea area in the research area on the grid of the sea area, and constructing an underwater topography model of the sea area in the research area.
And (3) introducing the measured coordinates and the water depth data into Delft-3d, superposing the measured coordinates and the water depth data on the grid, and then utilizing a triangulation method to measure the water depth difference value to the grid node position, thereby completing the construction of the underwater topography model of the sea area in the research area.
S4, inputting a plurality of typhoon routes logged in the research area into a wind-tide numerical model combined with an underwater topography model of the research area, and predicting tide level values of grid points and time under each wind route.
S4-1, selecting a strongest wind route logged in the research area from the wind route set, and establishing a wind route set by adjusting any one or more of a wind route login position, central air pressure and central wind speed based on the strongest wind route.
As shown in fig. 3, the strongest wind route (number: 5612) logged in the investigation region is selected from the wind route set (data such as historical wind route, central air pressure, central air speed and actual measurement value of each time tide level of each observation station is stored), and the movement range 1 hour before the wind logging is drawn according to the wind movement position; and in the range of the moving circle, the wind path groups with different parameters are established by adjusting the position of the real path, the central air pressure and the central air speed.
According to the selected real wind route position, a mobile coil with a radius of 110km is established at a coordinate position 1 hour before wind landing; then taking the real wind route as the center, and arranging 10 routes in parallel at equal intervals in the south and north directions respectively; the true route was then deflected in the forward-west direction and 3 routes were again set to obtain 14 total wind routes (see fig. 3). Then the central air pressure of each route is respectively regulated to +/-5 hpa and +/-10 hpa, and the central air speed is respectively increased by 10 percent W 0 、20％W 0 And 30% W 0 A total of 112 wind path calculation examples were obtained, wherein W 0 The center wind speed of the real route.
S4-2, inputting the selected strongest wind route into a wind-tide nonlinear coupling model constructed based on an underwater topography model of a sea area in a research area, simulating storm tide under a real wind route by using Delft-3d numerical values, predicting the tide level in the research area, and adjusting model parameters according to comparison of model predicted values and measured values until the tide level predicted values and measured values at the same position and at different times are compared with the preset precision requirements (as shown in figure 4).
S4-3, inputting each wind path in the wind path group into a wind-tide coupling model which is subjected to parameter adjustment and meets the precision requirement, and predicting the tide level of each grid point and each time under each wind path.
S5, extracting tide level values under the action of different wind routes from the prediction result of the step S4 according to grid point numbers of the coastal zone positions, determining the maximum tide level value of each grid point of the coastal zone positions, and further obtaining the maximum tide level distribution.
And S6, when the tide level exceeds the elevation of the seawall of the coastal zone, the seawall is subjected to disaster. Judging the number N of wind paths which can cause the breakwater according to the maximum tide level value of each grid point of the coastal zone position and the elevation of the seawall of each position of the coastal zone under the action of N times of different wind paths seawall Disaster risk P caused by wind logging in risk Can be expressed as:
the embodiment also provides an extreme weather coastal zone risk assessment device, which comprises: the system comprises a region determining module, a sea area gridding module, a terrain model constructing module, a model predicting module, a data extracting module and a risk evaluating module.
The regional determining module in this example is configured to obtain a research region determined by a user, where the research region has a sea area and a coastal zone; the sea area gridding module is used for gridding the sea area in the research area; the terrain model construction module is used for superposing measured coordinates and water depth data of the sea area in the research area on grids of the sea area to construct an underwater terrain model of the sea area in the research area; the model prediction module is used for inputting a plurality of typhoon routes logged in a research area into a storm tide-astronomical tide nonlinear coupling model combined with an underwater topography model of the research area, and predicting tide levels of grid points and time under each wind route; the data extraction module is used for extracting the maximum tide level of each grid point of the coastal zone position under the action of different wind paths according to the grid point numbers of the coastal zone position; the risk assessment module is used for assessing disaster risk according to the maximum tide level of each grid point of the coastal zone position and the sea wall elevation of each position of the coastal zone under the action of different wind paths.
As shown in fig. 5, the present embodiment further provides a method for displaying the maximum tide level distribution in step S5, by displaying a map corresponding to the investigation region, and displaying coastal zones in the investigation region with different colors, where the colors of the coastal zones are determined according to the maximum tide level values of each grid point of the coastal zone position under the action of different wind paths.
The present embodiment also provides a storage medium having stored thereon a computer program executable by a processor, which when executed, implements the steps of the extreme weather coastal zone risk assessment method of the present example.
The present embodiment also provides a computer device having a memory and a processor, the memory having stored thereon a computer program executable by the processor, the computer program when executed performing the steps of the extreme weather coastal zone risk assessment method of the present example.
Claims (10)
1. The extreme weather coastal zone risk assessment method is characterized by comprising the following steps of:
acquiring a research area determined by a user, wherein the research area is provided with a sea area and a coastal zone;
gridding the sea area in the research area;
superposing the measured coordinates and water depth data of the sea area in the research area on a grid of the sea area to construct an underwater topography model of the sea area in the research area;
inputting a plurality of typhoon routes logged in a research area into a wind-tide coupling model combined with an underwater topography model of the research area, and predicting tide level values of grid points and time under each wind route;
extracting the maximum tide level value of each grid point of the coastal zone position under the action of different wind paths according to the grid point numbers of the coastal zone position;
and evaluating disaster risk according to the maximum tide level value of each grid point at the coastal zone position and the sea wall elevation at each position of the coastal zone under the action of different wind paths.
2. The extreme weather coastal zone risk assessment method of claim 1, wherein the meshing of the sea area within the investigation region comprises:
the mesh size of the shallow water area on the shore is between 50 and 200m, and the mesh spacing of the deep water area is between 200 and 1000m.
3. The extreme weather coastal zone risk assessment method of claim 1, wherein the overlaying the measured coordinates and the water depth data of the sea area in the investigation region onto the grid of the sea area creates an underwater topography model of the sea area in the investigation region comprising: and measuring the water depth difference to the grid node position by using a triangulation difference method.
4. The method for risk assessment of extreme weather coastal zone according to claim 1, wherein inputting a plurality of typhoon routes logged in a research area into a wind-tide coupling model combined with an underwater topography model of the research area predicts tide level values of each grid point and each time under each wind route, comprising:
selecting the strongest wind route logged in the research area from the optimal wind route set; establishing a route group comprising a plurality of wind routes with different parameters;
inputting an underwater topography model of a sea area in a research area and a selected strongest wind route into a wind-tide coupling model to predict a tide level value in the research area, and adjusting model parameters until the tide level predicted value and an actual measured value at the same position and each time are compared to meet a preset precision requirement;
and inputting each wind path in the wind path group into a wind-tide coupling model with adjusted parameters, and predicting the tide level values of grid points and time under each wind path.
5. The extreme weather coastal zone risk assessment method of claim 4, wherein the establishing a wind path group comprising a plurality of different parameter wind paths comprises:
and establishing a wind route group by adjusting any one or more of a wind route landing position, a central air pressure and a central air speed based on the strongest wind route.
6. The extreme weather coastal zone risk assessment method according to claim 1, wherein the estimating the disaster risk according to the maximum tide level value of each grid point of the coastal zone position and the coastal elevation of each position of the coastal zone under the action of different wind paths comprises:
judging the number of wind routes which can cause the flood dike according to the maximum tide level value of each grid point of the coastal zone position and the elevation of the seawall of each position under the action of different wind routes, and taking the ratio of the number of wind routes which can cause the flood dike to the total number contained in the wind route group as the disaster risk.
7. A coastal zone typhoon storm surge risk assessment device, comprising:
the area determining module is used for acquiring a research area determined by a user, wherein the research area is provided with a sea area and a coastal zone;
the sea area gridding module is used for gridding the sea area in the research area;
the terrain model construction module is used for superposing measured coordinates and water depth data of the sea area in the research area on grids of the sea area to construct an underwater terrain model of the sea area in the research area;
the model prediction module is used for inputting a plurality of typhoon routes logged in a research area into a wind-tide coupling model combined with an underwater topography model of the research area, and predicting tide level values of grid points and time under each wind route;
the data extraction module is used for extracting the maximum tide level value of each grid point of the coastal zone position under the action of different wind paths according to the grid point number of the coastal zone position;
and the risk assessment module is used for assessing the disaster risk according to the maximum tide level value of each grid point of the coastal zone position and the sea wall elevation of each position of the coastal zone under the action of different wind paths.
8. A maximum tide level distribution display method is characterized in that: displaying a map corresponding to the research area, and displaying the coastal zone in the research area in different colors, wherein the colors of the coastal zone are determined according to the maximum tide level values of grid points of the coastal zone position under the action of different wind paths in the extreme weather coastal zone risk assessment method.
9. A storage medium having stored thereon a computer program executable by a processor, characterized by: the computer program when executed implements the steps of the extreme weather coastal zone risk assessment method.
10. A computer device having a memory and a processor, the memory having stored thereon a computer program executable by the processor, characterized by: the computer program when executed implements the steps of the extreme weather coastal zone risk assessment method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210262089.3A CN116029541A (en) | 2022-03-17 | 2022-03-17 | Risk assessment method for extreme weather coastal zone |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210262089.3A CN116029541A (en) | 2022-03-17 | 2022-03-17 | Risk assessment method for extreme weather coastal zone |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116029541A true CN116029541A (en) | 2023-04-28 |
Family
ID=86076984
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210262089.3A Pending CN116029541A (en) | 2022-03-17 | 2022-03-17 | Risk assessment method for extreme weather coastal zone |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116029541A (en) |
-
2022
- 2022-03-17 CN CN202210262089.3A patent/CN116029541A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Saket et al. | Wave energy potential along the northern coasts of the Gulf of Oman, Iran | |
| Md Ali et al. | Assessing the impact of different sources of topographic data on 1-D hydraulic modelling of floods | |
| KR101942058B1 (en) | Simulation method of sea level rise flooding using Computational Fluid Dynamics and ocean characteristics | |
| CN107194040B (en) | Water quality monitoring network multi-objective optimization deployment method based on bidirectional water flow | |
| CN110414041B (en) | Method and system for establishing storm surge and flood analysis based on GIS technology | |
| Cooper et al. | Incorporating uncertainty of groundwater modeling in sea-level rise assessment: a case study in South Florida | |
| CN112036691A (en) | River mouth area extreme storm surge water level calculation method based on JPM-OS-Q model | |
| CN105844427A (en) | Calculating method for refined assessment on storm tide disaster risks | |
| CN101257424B (en) | Underwater wireless sensor network cover control method based on surface even allocation | |
| CN115439029A (en) | Tsunami disaster key defense area determination method and system | |
| Bernier et al. | Mapping the return periods of extreme sea levels: allowing for short sea level records, seasonality, and climate change | |
| CN115935732A (en) | Multi-source composite disaster inundation risk simulation method for complex tidal river network | |
| Gelder et al. | Regional frequency analysis of extreme wave heights: Trading space for time | |
| KR20160073604A (en) | Method and system for analyzing ocean circulation in coastal areas | |
| CN111666314B (en) | Multi-factor-based storm surge vulnerability assessment method and device and computer equipment | |
| Chacon-Barrantes et al. | A first estimation of tsunami hazard of the Pacific coast of Costa Rica from local and distant seismogenic sources | |
| Hou et al. | Automatic Extraction of Drainage Networks from DEMs Base on Heuristic Search. | |
| Bruno et al. | The influence of interannual variability of mean sea level in the Adriatic Sea on extreme values | |
| CN116029541A (en) | Risk assessment method for extreme weather coastal zone | |
| Koike et al. | Far-field tsunami potential and a real-time forecast system for the Pacific using the inversion method | |
| Crapoulet et al. | Using LiDAR topographic data for identifying coastal areas of northern France vulnerable to sea-level rise | |
| Wang et al. | Simulation of water surge processes and analysis of water surge bearing capacity in Boao Bay, Hainan Island, China | |
| Kerh et al. | Forecasting of nonlinear shoreline variation based on aerial survey map by neural network approach | |
| Sarhan et al. | Prediction of Shoreline Deformation around Multiple Hard Coastal Protection Systems. | |
| CN116523152B (en) | Float drift prediction method, device, equipment and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |