Typhoon cascade waterlogging sensitivity assessment method and system for coastal water network area

Abstract

The embodiment of the invention provides a typhoon cascade waterlogging sensitivity assessment method and system for a coastal water network area, and the method comprises the steps: carrying out the sub-basin division of a target area, and carrying out the water network grid division through combining with the target area and a sub-basin; obtaining index data of the sub-basins, calculating rainfall-flood-tide coupling sensitivity based on the index data, performing dynamic weighting on the rainfall-flood-tide coupling sensitivity, and calculating a comprehensive sensitivity index; defining encounter indexes of the grid indexes in the water network grids, calculating sensitivity indexes based on the encounter indexes, performing dynamic weighting on the sensitivity indexes, and calculating rainfall flood tide encounter sensitivity indexes; and performing spatial superposition based on the comprehensive sensitivity index and the rainfall flood tide encountering sensitivity index to generate a sensitivity evaluation graph of the target area.

Description

Technical Field

[0001] The present invention relates to the technical field of typhoon disaster research, and particularly to a method and system for evaluating the sensitivity of typhoon cascading waterlogging in coastal water network areas. Background Art

[0002] With the change of typhoon activity trends and the increase of urban and rural exposure and vulnerability, affected by the combined influence of typhoon-triggered heavy rain, mountain torrents, and storm surges, extreme waterlogging events occur frequently, causing huge economic and social losses to the affected areas. This phenomenon, triggered by an initial event and resulting in the expansion of risks and the amplification of disaster losses through the interdependence and association between different disasters, is usually referred to as cascading disasters. Based on this background, conducting an evaluation of the waterlogging sensitivity of urban and rural spaces under typhoon cascading disasters has important practical significance for enhancing spatial resilience and disaster response capabilities.

[0003] However, existing typhoon disaster risk assessment methods mainly use the grid method, multi-scale grid method, or regional division based on administrative regions, and comprehensively evaluate risks using statistical data, historical meteorological data, or disaster loss data based on the framework of "risk = disaster × exposure × vulnerability × response ability". However, these methods are relatively flat, ignoring the impact of cross-level driving factors on the risk distribution, and the evaluation results are not accurate enough. Summary of the Invention

[0004] In view of the problems existing in the prior art, an embodiment of the present invention provides a method for evaluating the sensitivity of typhoon cascading waterlogging in coastal water network areas.

[0005] An embodiment of the present invention provides a method for evaluating the sensitivity of typhoon cascading waterlogging in coastal water network areas, the method comprising: Dividing the target area into sub-watersheds, and combining the target area and sub-watersheds to conduct water network grid division; Obtaining the index data of the sub-watersheds, calculating the coupled sensitivity of rainstorm, flood, and tide based on the index data, dynamically weighting the coupled sensitivity of rainstorm, flood, and tide, and calculating the comprehensive sensitivity index; Defining the encounter index of the grid index in the water network grid, calculating the sensitivity index based on the encounter index, dynamically weighting the sensitivity index, and calculating the rainstorm, flood, and tide encounter sensitivity index; Performing spatial superposition based on the comprehensive sensitivity index and the rainstorm, flood, and tide encounter sensitivity index to generate the sensitivity evaluation map of the target area.

[0006] In one of the embodiments, the method further comprises: Extracting the boundary of the sub-watersheds of the target area based on high-precision DEM data; Taking the sub - watershed boundary as a constraint, and combining the water network data and slope data in the target area to divide the adaptive water network grid.

[0007] In one embodiment, the method further includes: Rainstorm amplification sensitivity, storm surge sensitivity, and flood peak sensitivity; Obtaining the index data of the sub - watershed, and calculating the rain - flood - tide coupling sensitivity based on the index data; Calculating the rainstorm amplification sensitivity based on the elevation of the highest point in the sub - watershed in the index data; Calculating the storm surge sensitivity based on the reclamation area and river - bay distance of the sub - watershed in the index data; Calculating the flood peak sensitivity based on the mountain / plain - slope area in the index data.

[0008] In one embodiment, the method further includes: Normalizing the data of the rain - flood - tide coupling sensitivity, calculating the corresponding information entropy and weight through the normalized data, and calculating the comprehensive sensitivity index by synthesizing the normalized rain - flood - tide coupling sensitivity data and the corresponding weight.

[0009] In one embodiment, the method further includes: Boundary sensitivity and middle - position sensitivity; Defining the encounter index of the grid index in the water network grid, and calculating the sensitivity index based on the encounter index, including: Calculating the boundary sensitivity based on the minimum distance from the grid cell to the slope boundary and the minimum distance from the grid cell to the tidal shoreline in the encounter index; Calculating the middle - position sensitivity based on the distance from the grid cell to the mid - point of the tidal shoreline in the encounter index.

[0010] In one embodiment, the method further includes: Assigning weights to the comprehensive sensitivity index and the rain - flood - tide encounter sensitivity index, calculating the grid comprehensive sensitivity, and taking corresponding risk measures based on the risk - level interval corresponding to the comprehensive sensitivity.

[0011] An embodiment of the present invention provides a typhoon - cascade waterlogging sensitivity assessment system for coastal water network areas. The system includes: A division module, configured to divide the target area into sub - watersheds, and combine the target area and the sub - watersheds to divide the water network grid; A sub - watershed module, configured to obtain the index data of the sub - watershed, calculate the rain - flood - tide coupling sensitivity based on the index data, dynamically assign weights to the rain - flood - tide coupling sensitivity, and calculate the comprehensive sensitivity index; A grid module, which is used to define the encounter index of grid indicators in the water network grid, calculate the sensitivity index based on the encounter index, dynamically weight the sensitivity index, and calculate the rain-flood-tide encounter sensitivity index; An evaluation module, which is used to perform spatial superposition based on the comprehensive sensitivity index and the rain-flood-tide encounter sensitivity index to generate a sensitivity evaluation map of the target area.

[0012] In one embodiment, the system further includes: An extraction module, which is used to extract the sub-basin boundary of the target area based on high-precision DEM data; An adaptive division module, which is used to take the sub-basin boundary as a constraint and combine the water network data and slope data in the target area to divide the adaptive water network grid.

[0013] An embodiment of the present invention provides an electronic device, including a processor and a memory; The processor is connected to the memory; The memory is used to store executable program codes; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the method described in one or more embodiments.

[0014] An embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned typhoon cascading waterlogging sensitivity assessment method for coastal water network areas are implemented.

[0015] In view of the above, in one or more embodiments of this specification, the sub-basins of the target area are divided, and the water network grid is divided in combination with the target area and sub-basins; the index data of the sub-basins are obtained, the rain-flood-tide coupling sensitivity is calculated based on the index data, and the rain-flood-tide coupling sensitivity is dynamically weighted to calculate the comprehensive sensitivity index; the encounter index of grid indicators in the water network grid is defined, the sensitivity index is calculated based on the encounter index, and the sensitivity index is dynamically weighted to calculate the rain-flood-tide encounter sensitivity index; spatial superposition is performed based on the comprehensive sensitivity index and the rain-flood-tide encounter sensitivity index to generate a sensitivity evaluation map of the target area. In this way, binary risk-driven analysis can be realized through the linkage of sub-basins and water network grids, and in actual analysis, combined with the specific conditions of the land-sea base surface, basin characteristics, and urban and rural construction, accurate and comprehensive cross-level risk assessment results can be provided. Description of the Drawings

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0017] Figure 1 It is a flowchart of a typhoon cascading waterlogging sensitivity assessment method for coastal water network areas provided by an embodiment of this specification.

[0018] Figure 2 It is a schematic structural diagram of a typhoon cascading waterlogging sensitivity assessment system for coastal water network areas provided by an embodiment of this specification.

[0019] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of this specification. Detailed implementation manners

[0020] Now, the subject matter described herein will be discussed with reference to example embodiments. It should be understood that discussing these embodiments is only to enable those skilled in the art to better understand and thus implement the subject matter described herein, and is not a limitation on the protection scope, applicability, or examples set forth in the claims. The functions and arrangements of the elements discussed can be changed without departing from the protection scope of the content of this specification. Each example can omit, substitute, or add various processes or components as needed. For example, the described method can be executed in a different order from the described order, and each step can be added, omitted, or combined. Additionally, the features described relative to some examples can also be combined in other examples.

[0021] As used herein, the term "including" and its variants represent open terms, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" and "an embodiment" mean "at least one embodiment". The term "another embodiment" means "at least one other embodiment". The terms "first", "second", etc. can refer to different or the same objects. Other definitions, whether explicit or implicit, may be included below. Unless explicitly specified in the context, the definition of a term is consistent throughout the specification.

[0022] As Figure 1 shown, an embodiment of the present invention provides a typhoon cascading waterlogging sensitivity assessment method for coastal water network areas, including: Step S102, dividing the target area into sub - basins, and combining the target area and the sub - basins for water network grid division.

[0023] Specifically, a sub - watershed is an independent water - collecting area divided based on topography in hydrology. All precipitation flows into the same outlet through surface runoff, and its boundary can usually be determined by the ridgeline. The division of sub - watersheds can be achieved by using a Digital Elevation Model (DEM) to extract the river flow direction of the target area through a flow - direction calculation algorithm, determine the river network. Then, noise points in the DEM, such as sunken areas, are eliminated. Next, the outlet of the river network is marked, and starting from the mark, the river watershed is traced against the flow direction, and the sub - watershed boundary is divided accordingly. Among them, when tracing the river flow direction, the upstream contributing area of each pixel can be calculated through the flow - direction raster, and a threshold of the cumulative flow (such as 1000 pixels) is selected according to the regional hydrological characteristics to extract the river channel. And an outlet point is set at the end of the river or the administrative boundary.

[0024] Furthermore, a water - network grid is a refined spatial unit designed for complex water - network areas, used to simulate the process of flood - waterlogging cascade conduction, based on the vector data of the sub - watershed boundary, as well as the water - network data and slope data in the target area. Among them, for the screening of slope data, areas with a slope ≤ 15% can be extracted as areas prone to waterlogging. Then, the flat - slope raster is cropped by the sub - watershed boundary to ensure that the grid is aligned with the hydrological unit, and the vector data of rivers and lakes is overlaid to retain the flat - slope land within a certain range of the water - network. Unique IDs, area, perimeter, central coordinates, etc. are assigned to each grid cell, and the grid is divided according to the rules of river confluences or a fixed area. After the division, the grid can be further improved, such as further patching fragmented grids around the building complex or areas where the boundary between the water - network and the grid does not match. Finally, an adaptive water - network table is output, and the water - network table can also include the overlay layer of the flat - slope land and the grid boundary.

[0025] For example, for a coastal city with complex terrain (30% mountainous area), 32 sub - watersheds and 1200 adaptive water - network grids can be generated.

[0026] Step S104: Obtain the index data of the sub - watershed, calculate the coupling sensitivity of rain - flood - tide based on the index data, dynamically weight the coupling sensitivity of rain - flood - tide, and calculate the comprehensive sensitivity index.

[0027] Specifically, subsequent calculations are based on the index data of sub - basins. The index data may include the highest elevation of the sub - basin extracted from the DEM, the distance from the estuary to the bay mouth (which can be calculated through the intersection of the water system data and the coastline in the DEM), the reclamation area (which can be judged by remote sensing images), the mountain area (slope > 15%), and the flat slope area (slope ≤ 15%). Additionally, when determining the index data, abnormal data can be further verified. For example, when the reclamation area of a certain sub - basin is extremely large (such as exceeding 50% of the total area of the region), it is necessary to verify it in combination with historical land - use data.

[0028] Further, rain - flood - tide coupling sensitivity calculations are carried out based on the index data. The sensitivity calculations can include quantifying the sensitivities of three types: heavy rain, storm surge, and flood peak. The above - mentioned three types of sensitivities can reflect the natural risk driving factors of the sub - basin. Among them, the heavy - rain amplification sensitivity can be defined by the highest elevation of the sub - basin. Because the mountain uplifts the moist air flow, resulting in an increase in orographic rain. When the highest elevation of a certain sub - basin is 850m, the heavy - rain amplification sensitivity is 850. The storm - surge sensitivity can be defined by the distance from the estuary to the bay mouth (km) of the sub - basin, the maximum tidal - influence boundary distance (km) within the sub - basin affected by the storm surge, and the reclamation area (km²) within the sub - basin. For the storm - surge sensitivity of the sub - basin, the calculation can be: where, R storm is the storm - surge sensitivity, d bay is the distance from the estuary to the bay mouth, d max is the maximum tidal - influence boundary distance affected by the storm surge, A reclamation is the reclamation area within the sub - basin.

[0029] The flood - peak sensitivity can be defined by the mountain area and the flat - slope area, which is the difference between the mountain area and the flat - slope area.

[0030] Further, after determining the sensitivity data of the three types of heavy rain, storm surge, and flood peak in the sub - basin, index standardization is carried out. For example, for the original values of the heavy - rain amplification sensitivity of 5 sub - basins being [500, 600, 700, 800, 900], after standardization, it can be [0, 0.25, 0.5, 0.75, 1]. Then, calculate the proportion of the standardized indexes of the sub - basins for information - entropy calculation, and calculate the corresponding weights through the information - entropy calculation results. The information entropy measures the degree of index variation and dynamically determines the weights. The specific example calculation process can be, for example: Suppose the standardized values of the heavy - rain amplification sensitivity of 3 sub - basins are [0.8, 0.6, 0.4], then: Proportion calculation: Information - entropy calculation: Weight calculation: Finally, the comprehensive sensitivity index is calculated by combining the weight and the standardized sensitivity. The range is [0, 1].

[0031] Step S106: Define the encounter index of the grid index in the water network grid, calculate the sensitivity index based on the encounter index, dynamically assign weights to the sensitivity index, and calculate the rain-flood-tide encounter sensitivity index.

[0032] Specifically, define the encounter index of the grid index in the water network grid. Since the encounter index can quantify the spatial probability of the intersection of rain, flood, and tide in the water network grid and reflect the impact of terrain and hydrological topology on cascading disasters. Among them, the sensitivity index of the water network grid includes boundary sensitivity and intermediate position sensitivity. For boundary sensitivity, the smaller the sum of the distances from the grid to the slope boundary (≥15%) and the tidal shoreline, the more likely it is to accumulate water and be affected by the tide level backing. Therefore, it is necessary to refer to the sum of two data items: the minimum distance from the encounter index grid cell to the boundary with a slope ≥15%, and the minimum distance from the grid cell to the tidal shoreline as the calculation basis. For intermediate position sensitivity, the closer to the midpoint of the tidal shoreline, the more likely it is to be affected by the superposition of two-way tidal waves and runoff (such as the estuary backing effect). Therefore, it is necessary to refer to the distance from the encounter index grid cell to the midpoint of the tidal shoreline and the corresponding adjustment parameter as the calculation basis. Among them, the minimum distance from the encounter index grid cell to the boundary with a slope ≥15%, the minimum distance from the grid cell to the tidal shoreline, and the distance from the index grid cell to the midpoint of the tidal shoreline can be obtained through DE and remote sensing images.

[0033] Furthermore, after calculating the boundary sensitivity and intermediate position sensitivity, similar to the dynamic weight assignment step in step S104 above, the dynamic weight assignment step for the sensitivity index can also include four steps: data standardization, ratio calculation, information entropy calculation, and weight calculation. And calculate the rain-flood-tide encounter sensitivity index based on the weight and the standardized sensitivity data. Among them, the rain-flood-tide encounter sensitivity index can identify the high-risk areas of the intersection of rain, flood, and tide in the water network grid, providing input for subsequent sensitivity analysis of the cascading amplification of waterlogging.

[0034] Step S108: Perform spatial superposition based on the comprehensive sensitivity index and the rain-flood-tide encounter sensitivity index to generate the sensitivity evaluation map of the target area.

[0035] Specifically, vector data aggregation is performed on the comprehensive sensitivity index of the sub-basins and the sensitivity index of the rainstorm-flood-tide encounter of the water network grids. When aggregating, ensure that the sub-basins and grid data are in the same coordinate system for data fusion. Additionally, when performing data fusion, weight distribution can also be carried out for the sub-basins and water network grids. Among them, the weight distribution of the comprehensive sensitivity index of the sub-basins can be 0.6 (set according to specific requirements and not unique), which can reflect the contribution of natural driving factors, and the weight of the sensitivity of the rainstorm-flood-tide encounter of the water network grids can be 0.4, reflecting the interaction between the water network topology and the terrain. During the disaster process, it can also be dynamically adjusted according to specific circumstances.

[0036] Furthermore, after calculating the comprehensive sensitivity based on the data of the sensitivity evaluation map of the target area generated by integration, risk level division can be carried out according to the calculation results. For example, those higher than 0.8 are of the highest level, and it is recommended to set up flood control isolation belts; those lower than 0.2 are of the lowest level and do not require intervention, and the natural state can be maintained. The intermediate levels can be set according to requirements. For example, for a certain grid in the sensitivity evaluation map of the target area with 0.7 (high sensitivity of the sub-basin) and 0.65 (high sensitivity of the grid), the comprehensive value = 0.7×0.6 + 0.65×0.4 = 0.68 → level 4 risk, and the corresponding operation can be to restrict construction and arrange monitoring equipment.

[0037] A typhoon cascading waterlogging sensitivity assessment method for coastal water network areas provided by an embodiment of the present invention divides the target area into sub-basins, and combines the target area and sub-basins to conduct water network grid division; obtains the index data of the sub-basins, calculates the rainstorm-flood-tide coupling sensitivity based on the index data, and dynamically assigns weights to the rainstorm-flood-tide coupling sensitivity to calculate the comprehensive sensitivity index; defines the encounter index of the grid index in the water network grid, calculates the sensitivity index based on the encounter index, and dynamically assigns weights to the sensitivity index to calculate the rainstorm-flood-tide encounter sensitivity index; performs spatial superposition based on the comprehensive sensitivity index and the rainstorm-flood-tide encounter sensitivity index to generate the sensitivity evaluation map of the target area. In this way, through the linkage of sub-basins and water network grids, binary risk-driven analysis can be realized, and in actual analysis, combined with the specific conditions of the sea-land base surface, basin characteristics, and urban and rural construction, accurate and comprehensive cross-level risk assessment results can be provided.

[0038] Please refer to Figure 2 , Figure 2 which is a schematic structural diagram of a typhoon cascading waterlogging sensitivity assessment system provided by an embodiment of the present application. As Figure 2 shown, the system includes: A division module S202, configured to divide the target area into sub-basins, and combine the target area and sub-basins to conduct water network grid division; The sub - basin module S204 is used to obtain the index data of the sub - basin, calculate the rain - flood - tide coupling sensitivity based on the index data, dynamically weight the rain - flood - tide coupling sensitivity, and calculate the comprehensive sensitivity index; The grid module S206 is used to define the encounter index of the grid index in the water network grid, calculate the sensitivity index based on the encounter index, dynamically weight the sensitivity index, and calculate the rain - flood - tide encounter sensitivity index; The evaluation module S208 is used to perform spatial superposition based on the comprehensive sensitivity index and the rain - flood - tide encounter sensitivity index to generate the sensitivity evaluation map of the target area.

[0039] In another embodiment, a typhoon - cascading waterlogging sensitivity assessment system for coastal water network areas further includes: An extraction module is used to extract the sub - basin boundary of the target area based on high - precision DEM data; An adaptive division module is used to take the sub - basin boundary as a constraint and combine the water network data and slope data in the target area to divide the adaptive water network grid.

[0040] Those skilled in the art can clearly understand that the technical solutions of the embodiments of the present application can be implemented by means of software and / or hardware. The "units" and "modules" in this specification refer to software and / or hardware that can independently complete or cooperate with other components to complete specific functions, where the hardware can be, for example, a Field - Programmable Gate Array (FPGA), an Integrated Circuit (IC), etc.

[0041] Each processing unit and / or module of the embodiments of the present application can be implemented by an analog circuit that implements the functions described in the embodiments of the present application, or can be implemented by software that executes the functions described in the embodiments of the present application.

[0042] See Figure 3 , which shows a schematic structural diagram of an electronic device related to the embodiments of the present application. This electronic device can be used to implement the method in the embodiment shown in Figure 1 . As shown in Figure 3 , the electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0043] Among them, the communication bus 302 is used to realize the connection and communication between these components.

[0044] Among them, the user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may further include a standard wired interface and a wireless interface.

[0045] Among them, the network interface 304 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0046] Among them, the processor 301 may include one or more processing cores. The processor 301 connects various parts within the entire electronic device 300 through various interfaces and circuits. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by calling the data stored in the memory 305, the processor 301 performs various functions of the terminal 300 and processes data. Optionally, the processor 301 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 301 may integrate a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 301 and may be implemented separately by a single chip.

[0047] Among them, the memory 305 may include random access memory (RAM) and may also include read-only memory. Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store the data involved in the above-mentioned method embodiments. Optionally, the memory 305 may further be at least one storage device located far from the aforementioned processor 301. Such asFigure 3 As shown, the memory 305, which is a computer storage medium, may include an operating system, a network communication module, a user interface module, and program instructions.

[0048] In Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an interface for the user to input and obtain the data input by the user; and the processor 301 can be used to call the interactive application program based on image generation stored in the memory 305 and specifically perform the following operations: dividing the target area into sub-watersheds, and combining the target area and the sub-watersheds to perform water network grid division; obtaining the index data of the sub-watersheds, calculating the coupling sensitivity of rainstorm, flood and tide based on the index data, dynamically weighting the coupling sensitivity of rainstorm, flood and tide, and calculating the comprehensive sensitivity index; defining the encounter index of the grid index in the water network grid, calculating the sensitivity index based on the encounter index, dynamically weighting the sensitivity index, and calculating the rainstorm, flood and tide encounter sensitivity index; performing spatial superposition based on the comprehensive sensitivity index and the rainstorm, flood and tide encounter sensitivity index to generate the sensitivity evaluation map of the target area.

[0049] This application also provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the above method are implemented. Among them, the computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nano-systems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0050] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0051] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0052] In several embodiments provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, 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 displayed or discussed couplings or direct couplings or communication connections between each other can be through some service interfaces. The indirect couplings or communication connections of the devices or units can be in electrical or other forms.

[0053] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0054] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0055] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. And the aforementioned memory includes: USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks or optical discs and other media that can store program codes.

[0056] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable memory. The memory can include: flash drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks or optical discs, etc.

[0057] The foregoing describes specific embodiments of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the acts or steps recited in the claims may be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order shown or sequential order to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for evaluating the typhoon - cascade waterlogging sensitivity in coastal water - network areas, the method comprising: Dividing the target area into sub - basins, and conducting water - network grid division in combination with the target area and sub - basins; Obtaining the index data of the sub - basins, calculating the rain - flood - tide coupling sensitivity based on the index data, dynamically weighting the rain - flood - tide coupling sensitivity, and calculating the comprehensive sensitivity index; Defining the encounter index of grid indexes in the water - network grid, calculating the sensitivity index based on the encounter index, dynamically weighting the sensitivity index, and calculating the rain - flood - tide encounter sensitivity index; Performing spatial superposition based on the comprehensive sensitivity index and the rain - flood - tide encounter sensitivity index to generate the sensitivity evaluation map of the target area.

2. The method according to claim 1, wherein The step of dividing the target area into sub - basins and conducting water - network grid division in combination with the target area and sub - basins includes: Extracting the sub - basin boundary of the target area based on high - precision DEM data; Taking the sub - basin boundary as a constraint, and dividing adaptive water - network grids in combination with the water - network data and slope data within the target area.

3. The method according to claim 1, wherein The rain - flood - tide coupling sensitivity includes: Rainstorm amplification sensitivity, storm - surge sensitivity, and flood - peak sensitivity; Obtaining the index data of the sub - basins, and calculating the rain - flood - tide coupling sensitivity based on the index data; Calculating the rainstorm amplification sensitivity based on the elevation of the highest point in the sub - basin in the index data; Calculating the storm - surge sensitivity based on the reclamation area and river - bay distance of the sub - basin in the index data; Calculating the flood - peak sensitivity based on the mountain / plain - slope area in the index data.

4. The method according to claim 3, characterized in that, The step of dynamically weighting the rain - flood - tide coupling sensitivity and calculating the comprehensive sensitivity index includes: Normalizing the data of the rain - flood - tide coupling sensitivity, calculating the corresponding information entropy and weight through the normalized data, and calculating the comprehensive sensitivity index by integrating the normalized rain - flood - tide coupling sensitivity data and the corresponding weight.

5. The method according to claim 1, wherein The calculation of the sensitivity index includes: Boundary sensitivity and middle - position sensitivity; The step of defining the encounter index of grid indexes in the water - network grid and calculating the sensitivity index based on the encounter index includes: Calculating the boundary sensitivity based on the minimum distance from the grid cell to the slope boundary and the minimum distance from the grid cell to the tidal shoreline in the encounter index; Calculating the middle - position sensitivity based on the distance from the grid cell to the mid - point of the tidal shoreline in the encounter index.

6. The method according to claim 1, wherein The method further includes: Assigning weights to the comprehensive sensitivity index and the rain - flood - tide encounter sensitivity index, calculating the grid comprehensive sensitivity, and taking corresponding risk measures based on the risk - level interval corresponding to the comprehensive sensitivity.

7. A typhoon cascading waterlogging sensitivity assessment system for coastal water network areas, characterized in that, The system includes: A division module for dividing the target area into sub - basins and conducting water - network grid division in combination with the target area and sub - basins; A sub - basin module for obtaining the index data of the sub - basins, calculating the rain - flood - tide coupling sensitivity based on the index data, dynamically weighting the rain - flood - tide coupling sensitivity, and calculating the comprehensive sensitivity index; A grid module, which is used to define the encounter index of grid metrics in the water network grid, calculate the sensitivity index based on the encounter index, dynamically weight the sensitivity index, and calculate the rain-flood-tide encounter sensitivity index; An evaluation module, which is used to perform spatial superposition based on the comprehensive sensitivity index and the rain-flood-tide encounter sensitivity index to generate a sensitivity evaluation map of the target area.

8. The system according to claim 7, wherein The system further includes: An extraction module, which is used to extract the sub-basin boundary of the target area based on high-precision DEM data; An adaptive division module, which is used to take the sub-basin boundary as a constraint and combine the water network data and slope data in the target area to divide the adaptive water network grid.

9. An electronic device, including a processor and a memory; The processor is connected to the memory; The memory is used to store executable program code; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the method according to any one of claims 1-6.

10. A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method according to any one of claims 1-6 is implemented.

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