Rainstorm disaster alarm method based on phased array rain measuring radar X wave band

Abstract

The invention discloses a rainstorm disaster alarm method based on an X wave band of a phased array rain measuring radar, and belongs to the technical field of radar observation processing, and the method comprises the steps: obtaining rainfall data obtained through the monitoring of an X wave band radar, carrying out the preprocessing of the rainfall data, carrying out the matrix threshold evaluation analysis of the rainfall data of a target region, and obtaining a risk evaluation result of a whole region. The rainfall data is subjected to multi-moment alarm data continuous inspection and identification based on a risk assessment result, continuous tracking and abnormity elimination of a rainfall process are realized, geographic position and area boundary information is superposed, a rainstorm disaster alarm picture result is generated, and a rainstorm disaster early warning technology based on a phased array rain measurement radar can be formed. Therefore, flood-causing short-term rainstorm alarm information production based on refined rainfall products is realized.

Description

Technical Field

[0001] This application belongs to the field of radar observation and processing technology, specifically, it relates to a method for early warning of rainstorm disasters based on the X-band of phased array rain measuring radar. Background Technology

[0002] In a changing environment, extreme hydrological and meteorological events occur frequently. Among them, torrential rains can cause flash floods, river floods, mudslides, and landslides, seriously endangering the sustainable development of the economy and society. The main factors that induce torrential rain disasters are localized short-term heavy rainfall that is short in duration, evolves rapidly, and is intense. However, the scanning methods and spatiotemporal resolution of traditional rain-measuring radars used by meteorological departments and mechanical rain-measuring radars used by water conservancy departments cannot meet the needs of refined monitoring and early warning for such rainfall systems. Therefore, how to build an effective monitoring and early warning capability for the characteristics of short duration, rapid evolution, and high intensity of torrential rains has become a major problem that water conservancy and river basin flood control urgently need to solve.

[0003] As a new type of productive force in water conservancy, water conservancy rainfall radar, together with meteorological satellites, rain gauges, and hydrological stations, forms a "three-tiered defense" and plays an important role in rainfall and flood monitoring and forecasting and flood and drought disaster prevention. Water conservancy rainfall radar focuses on refined areal rainfall monitoring, forecasting, and early warning. Its main goal is to achieve seamless and refined scanning and measurement of liquid water in the near-surface atmosphere. High-precision monitoring and early warning of flood-causing rainstorms is the foundation for improving the ability to prevent sudden rainstorm and flood disasters. However, it is difficult to achieve early warning of flood-causing rainstorms with short duration, small rainfall area, and rapid evolution based on traditional radar observation. Summary of the Invention

[0004] To address the aforementioned problems and technical deficiencies, this application adopts the following technical solution: a rainstorm disaster warning method based on the X-band of a phased array rainfall radar, comprising the following steps:

[0005] Acquire rainfall data from X-band radar monitoring and preprocess the rainfall data;

[0006] Matrix threshold assessment analysis is performed on rainfall data in the target area to obtain risk assessment results for the entire region.

[0007] Based on the risk assessment results, the continuity of multi-time alarm data of rainfall data is checked and identified to achieve continuous tracking and anomaly removal of precipitation process;

[0008] By overlaying geographic location and regional boundary information, rainstorm disaster warning images are generated.

[0009] Preferably, the precipitation data includes two types with different historical durations: cumulative precipitation over 1 hour and cumulative precipitation over 2 hours prior to the current time. Preprocessing of the precipitation data includes:

[0010] The binary file of rainfall data is scaled and calculated using a linear interpolation function to convert the rainfall data into grid data of 1 km grid, and then cropped to the area size required for rainstorm disaster warning.

[0011] Furthermore, the calculation process using a linear interpolation function is as follows:

[0012] Determine two known points in the rainfall data and ,calculate Time corresponding The value is calculated using the following formula:

[0013]

[0014] in, Given the coordinates of the left endpoint, Given the coordinates of the right endpoint, For the point to be interpolated, This is the interpolation result.

[0015] Preferably, the evaluation and analysis process is as follows:

[0016] Based on technical specifications, alarm thresholds are generated by region and level.

[0017] Based on threshold information regarding the amount and extent of rainfall, each administrative region is assessed for five levels of risk.

[0018] The risk assessment results are overlaid to generate a risk assessment result for the entire region.

[0019] Furthermore, the risk assessment includes:

[0020] Four thresholds t1, t2, t3, and t4 are defined to divide the values ​​into five intervals, t1 <t2<t3<t4

[0021] The matrix elements of the rainfall data are subjected to five levels of threshold discrimination based on four thresholds. The threshold discrimination formula is as follows:

[0022]

[0023] in, Let i be the value of the element in the i-th row and j-th column of the input matrix. The output is the level value, and the level value ranges from {1,2,3,4,5}.

[0024] Furthermore, the continuity verification and identification is achieved by fusing multi-source real-time data with a continuity verification algorithm to check the continuity of grid points exceeding the threshold, thereby enabling continuous tracking and anomaly removal of the precipitation process and providing accurate early warning support for rainstorm disasters.

[0025] Furthermore, the anomaly removal refers to the removal of each element in the rainfall data level index matrix. Perform anomaly removal; if If a value is not equal to 0 and has not been visited, then search for consecutive non-zero elements in 8 directions, mark each non-zero grid point, and calculate the consecutive length L in each direction. d1 ;

[0026] Using the non-zero grid points in the above 8 directions as a reference, search for consecutive non-zero elements in the 8 directions. Mark the unmarked non-zero grid points as newly added non-zero grid points. After traversing the 8 grid points, calculate the newly added consecutive length L in the 8 directions for each grid point. d2 ;

[0027] If L d2 If the value is greater than 0, re-mark the unmarked non-zero grid points as newly added non-zero grid points, until the k-th traversal search no longer encounters any new consecutive lengths, making L... dk =0;

[0028] If L d1 +L d2 +…+L dk If the value is greater than or equal to 9, the connected region is retained, and the remaining retrieved grid points are marked as to be deleted.

[0029] Preferably, the rainstorm disaster warning image result is obtained by filling the rainstorm warning area with intelligent spatial analysis and real-time rendering, which transforms discrete warning signals into spatially identifiable regional risks.

[0030] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the rainstorm disaster warning method based on the X-band of a phased array rain measuring radar as described above.

[0031] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the rainstorm disaster warning method based on the X-band of a phased array rain measuring radar as described above.

[0032] Compared to existing technologies, the beneficial effects of this application are as follows:

[0033] This application integrates real-time radar precipitation estimation products, transforms them into areas required for rainstorm disaster early warning models through spatial scale transformation, and automatically captures grid data and information that meet the conditions for rainstorm disaster warnings and alerts in real time. It accurately estimates rainfall areas that may lead to flooding and issues timely warnings. By overlaying geographical location and regional boundary information, it generates short-term rainstorm warning products with ultra-high spatiotemporal resolution and incorporates them into a database. By combining refined observations from X-band precipitation radar, it transforms quantitative precipitation observation products through regional cropping, spatial interpolation, threshold judgment, continuity verification, regional filling, and mapping to form a rainstorm disaster early warning technology based on phased array precipitation radar. This enables the production of flood-causing short-term rainstorm warning information based on refined precipitation products. Attached Figure Description

[0034] In the attached diagram:

[0035] Figure 1 This is a schematic diagram of the method steps in an embodiment of this application;

[0036] Figure 2 This is a diagram showing the cumulative precipitation over 1 hour and 2 hours at the current time.

[0037] Figure 3 A schematic diagram of gridded early warning data generated for different threshold levels;

[0038] Figure 4 This is a diagram illustrating the effect before and after removing results with fewer than 9 consecutive grid points;

[0039] Figure 5 This is a schematic diagram showing the results of filling in the disaster warning area. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of this application, but not all embodiments. Generally, the components of the embodiments of this application described and shown in the accompanying drawings can be arranged and designed in various different configurations.

[0041] Example 1

[0042] like Figure 1 As shown, a method for early warning of rainstorm disasters based on the X-band of phased array rain-measuring radar includes the following steps:

[0043] Acquire rainfall data from X-band radar monitoring and preprocess the rainfall data;

[0044] The precipitation data includes two types with different historical durations: cumulative precipitation 1 hour and cumulative precipitation 2 hours before the current time.

[0045] Preprocessing of rainfall data includes:

[0046] The binary file of rainfall data is scaled and calculated using a linear interpolation function to convert the rainfall data into grid data of 1 km grid, and then cropped to the area size required for rainstorm disaster warning.

[0047] The calculation process using a linear interpolation function is as follows:

[0048] Determine two known points in the rainfall data and ,calculate Time corresponding The value is calculated using the following formula:

[0049]

[0050] in, Given the coordinates of the left endpoint, Given the coordinates of the right endpoint, For the point to be interpolated, This is the interpolation result.

[0051] Matrix threshold assessment analysis is performed on rainfall data in the target area to obtain risk assessment results for the entire region.

[0052] The evaluation and analysis process is as follows:

[0053] Based on technical specifications, alarm thresholds are generated by region and level.

[0054] Based on threshold information regarding the amount and extent of rainfall, each administrative region is assessed for five levels of risk.

[0055] The risk assessment results are overlaid to generate a risk assessment result for the entire region.

[0056] Risk assessment includes:

[0057] Four thresholds t1, t2, t3, and t4 are defined to divide the values ​​into five intervals, t1 <t2<t3<t4

[0058] The matrix elements of the rainfall data are subjected to five levels of threshold discrimination based on four thresholds. The threshold discrimination formula is as follows:

[0059]

[0060] in, Let i be the value of the element in the i-th row and j-th column of the input matrix. The output is the level value, and the level value ranges from {1,2,3,4,5}.

[0061] Based on the risk assessment results, the continuity of multi-time alarm data of rainfall data is checked and identified to achieve continuous tracking and anomaly removal of precipitation process;

[0062] Continuity verification and identification involves fusing multi-source real-time data with continuity verification algorithms to check the continuity of grid points exceeding a threshold, enabling continuous tracking and anomaly removal of precipitation processes, and providing accurate early warning support for rainstorm disasters.

[0063] Anomaly removal refers to the process of removing anomalies from each element in the rainfall data level matrix. Perform anomaly removal; if If a value is not equal to 0 and has not been visited, then search for consecutive non-zero elements in 8 directions, mark each non-zero grid point, and calculate the consecutive length L in each direction. d1 ;

[0064] Using the non-zero grid points in the above 8 directions as a reference, search for consecutive non-zero elements in the 8 directions. Mark the unmarked non-zero grid points as newly added non-zero grid points. After traversing the 8 grid points, calculate the newly added consecutive length L in the 8 directions for each grid point. d2 ;

[0065] If L d2 If the value is greater than 0, re-mark the unmarked non-zero grid points as newly added non-zero grid points, until the k-th traversal search no longer encounters any new consecutive lengths, making L... dk =0;

[0066] If L d1 +L d2 +…+L dk If the value is greater than or equal to 9, the connected region is retained, and the remaining retrieved grid points are marked as to be deleted.

[0067] Overlaying geographic location and regional boundary information generates rainstorm disaster warning image results.

[0068] The result of rainstorm disaster warning images is to fill in the rainstorm warning area through intelligent spatial analysis and real-time rendering, transforming discrete warning signals into spatially identifiable regional risks.

[0069] Example 2

[0070] Step 1: Pre-processing of precipitation data. The binary files of X-band radar precipitation products are scaled and converted into 1-kilometer grid data using a linear interpolation function. The data is then cropped to the area size required for rainstorm disaster warning. The precipitation data includes two types with different historical durations, including the cumulative precipitation for 1 hour and 2 hours at the current time (00:00).

[0071] Linear interpolation is a method for estimating the intermediate value between two known points. Given two known points... and The goal is to seek Time corresponding The value, its core formula is as follows:

[0072]

[0073] The formula is based on the equation of a straight line between two points (point-slope form), which means that y changes linearly with x in the interval [x0, x1].

[0074] in, Given the coordinates of the left endpoint, Given the coordinates of the right endpoint, For the point to be interpolated, This is the interpolation result.

[0075] Step 2: Identification and extraction of heavy rainfall areas. Threshold analysis of the areal rainfall data matrix of the target area is performed through threshold assessment. Combined with the regional and graded alarm thresholds in the "Technical Regulations for Monitoring Short-Term Heavy Rainfall", five levels of risk are judged for each administrative region based on the threshold information of rainfall amount and range. The results are then superimposed to generate the risk assessment result for the entire region.

[0076] Five levels of threshold discrimination are applied to the matrix elements. Four thresholds, t1, t2, t3, and t4, are defined to divide the values ​​into five intervals, where t1... <t2<t3<t4

[0077] The matrix elements of the rainfall data are subjected to five levels of threshold discrimination based on four thresholds. The threshold discrimination formula is as follows:

[0078]

[0079] in, Let i be the value of the element in the i-th row and j-th column of the input matrix. The output is the level value, and the level value ranges from {1,2,3,4,5}.

[0080] Step 3: Continuity verification and identification of multi-time alarm products. Continuity verification and identification of precipitation is the foundation of multi-time alarm products. It is mainly used to serve the dynamic monitoring, trend analysis, and disaster alarm accuracy improvement of short-term heavy precipitation processes. By integrating multi-source real-time data with continuity verification algorithms, the continuity of grid points exceeding the threshold is verified, realizing the continuous tracking and anomaly elimination of precipitation processes, and providing accurate early warning support for rainstorm disasters.

[0081] For each element in the rank index matrix B ,if ≠0, and has not been visited:

[0082] ① Search for consecutive non-zero elements in 8 directions (up, down, left, right, and 4 diagonals), mark each non-zero grid point, and calculate the consecutive length L in each direction. d1 (d1=1..9);

[0083] ② Using the non-zero grid points among the above 8 directional grid points as a reference, search for consecutive non-zero elements in its 8 directions (up, down, left, right, and 4 diagonals). Mark the unmarked non-zero grid points as newly added non-zero grid points. After traversing the 8 grid points, calculate the newly added consecutive length L in the 8 directions for each grid point. d2 ;

[0084] ③If L d1 If the length is greater than 0, repeat step ② until the k-th search no longer produces any new consecutive lengths, i.e., L. dk =0;

[0085] ④ If L d1 +L d2 +…+L dk If the value is greater than or equal to 9, the connected region is retained, and the remaining retrieved grid points are marked as to be deleted.

[0086] Step 4: Disaster warning area filling and mapping. Through the data reading module, geographic location and regional boundary information are overlaid. The rainstorm warning area filling is transformed into spatially identifiable regional risks (red, orange, yellow, and blue risk levels) through intelligent spatial analysis and real-time rendering, generating rainstorm disaster warning image results.

[0087] Example 3

[0088] From a hardware perspective, this application provides an embodiment of an electronic device containing all or part of the content of a rainstorm disaster warning method based on a phased array rain measurement radar X-band. The electronic device includes a service processor and a distributed memory. The service processor is connected to the memory. The distributed memory stores a service self-management program configured to store machine-readable instructions. The service processor executes the service self-management program. When the instructions are executed by the processor, they implement the rainstorm disaster warning method based on a phased array rain measurement radar X-band as described above.

[0089] From a hardware perspective, in order to effectively improve the flexibility, versatility, and efficiency of data acquisition, this application provides an embodiment of an electronic device containing all or part of the content of a rainstorm disaster early warning method based on a phased array rain measurement radar X-band. The electronic device specifically includes the following components:

[0090] The system comprises a processor, memory, a communications interface, and a bus; wherein the processor, memory, and communications interface communicate with each other via the bus; the communications interface is used to realize information transmission between the core business system, user terminals, and related databases and other related devices of the rainstorm disaster warning method based on phased array rain measurement radar X-band; the logic controller can be a desktop computer, tablet computer, or mobile terminal, etc., and this embodiment is not limited to these.

[0091] In this embodiment, the logic controller can be implemented with reference to the embodiment of the rainstorm disaster warning method based on the X-band of phased array rain measuring radar in the embodiment, the content of which is incorporated here, and repeated parts will not be described again.

[0092] It is understood that the user terminal may include smartphones, tablet electronic devices, network set-top boxes, portable computers, desktop computers, personal digital assistants (PDAs), in-vehicle devices, smart wearable devices, etc., wherein the smart wearable devices may include smart glasses, smartwatches, smart bracelets, etc.

[0093] In practical applications, some parts of the rainstorm disaster warning method based on the X-band phased array rain-measuring radar can be executed on the electronic device side as described above, or all operations can be completed in the client device. The choice can be made based on the processing power of the client device and the limitations of the user's usage scenario, and this application does not impose any limitations on this. If all operations are completed in the client device, the client device may further include a processor.

[0094] The aforementioned client device may have a communication module (i.e., a communication unit) that can communicate with a remote server to achieve data transmission with the server. The server may include a server on the task scheduling center side, and in other implementation scenarios, it may also include a server on an intermediate platform, such as a server on a third-party server platform that has a communication link with the task scheduling center server. The server may include a single computer device, a server cluster composed of multiple servers, or a server structure of a distributed device.

[0095] Example 4

[0096] The embodiments of this application also provide a computer-readable storage medium capable of implementing the rainstorm disaster warning method based on phased array rain measuring radar X-band, where the execution subject is a server or client, as described in the above embodiments. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements all the contents of the rainstorm disaster warning method based on phased array rain measuring radar X-band, where the execution subject is a server or client, as described in the above embodiments.

[0097] The embodiments of this application may be provided as methods, apparatus, or computer program products. Therefore, this application may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0098] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0099] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0100] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0101] The embodiments described above are merely preferred embodiments of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications, improvements, and substitutions without departing from the concept of this application, and these all fall within the protection scope of this application.

Claims

1. A method for early warning of rainstorm disasters based on the X-band of a phased array rainfall radar, characterized in that, Includes the following steps: Acquire rainfall data from X-band radar monitoring and preprocess the rainfall data; Matrix threshold assessment analysis is performed on rainfall data in the target area to obtain risk assessment results for the entire region. Based on the risk assessment results, the continuity of multi-time alarm data of rainfall data is checked and identified to achieve continuous tracking and anomaly removal of precipitation process; By overlaying geographic location and regional boundary information, rainstorm disaster warning images are generated.

2. The method for rainstorm disaster early warning based on the X-band of phased array rain measuring radar according to claim 1, characterized in that, The precipitation data includes two types with different historical durations: cumulative precipitation over 1 hour and cumulative precipitation over 2 hours prior to the current time. Preprocessing of the precipitation data includes: The binary file of rainfall data is scaled and calculated using a linear interpolation function to convert the rainfall data into grid data of 1 km grid, and then cropped to the area size required for rainstorm disaster warning.

3. The method for rainstorm disaster early warning based on the X-band of phased array rain-measuring radar according to claim 2, characterized in that, The calculation process using a linear interpolation function is as follows: Determine two known points in the rainfall data and ,calculate Time corresponding The value is calculated using the following formula: in, Given the coordinates of the left endpoint, Given the coordinates of the right endpoint, For the point to be interpolated, This is the interpolation result.

4. The method for rainstorm disaster early warning based on the X-band of phased array rain-measuring radar according to claim 1, characterized in that, The evaluation and analysis process is as follows: Based on technical specifications, alarm thresholds are generated by region and level. Based on threshold information regarding the amount and extent of rainfall, each administrative region is assessed for five levels of risk. The risk assessment results are overlaid to generate a risk assessment result for the entire region.

5. A method for early warning of rainstorm disasters based on the X-band of a phased array rain-measuring radar according to claim 4, characterized in that, The risk assessment includes: Four thresholds t1, t2, t3, and t4 are defined to divide the values ​​into five intervals, t1 <t2<t3<t4 The matrix elements of the rainfall data are subjected to five levels of threshold discrimination based on four thresholds. The threshold discrimination formula is as follows: in, Let i be the value of the element in the i-th row and j-th column of the input matrix. The output is the level value, and the level value ranges from {1,2,3,4,5}.

6. A method for early warning of rainstorm disasters based on the X-band of a phased array rain-measuring radar according to claim 5, characterized in that, The continuity verification and identification method integrates multi-source real-time data with a continuity verification algorithm to check the continuity of grid points exceeding the threshold, thereby enabling continuous tracking and anomaly removal of precipitation processes and providing accurate early warning support for rainstorm disasters.

7. A method for early warning of rainstorm disasters based on the X-band of a phased array rain-measuring radar according to claim 6, characterized in that, The anomaly removal refers to each element in the rainfall data level index matrix. Perform anomaly removal; if If a value is not equal to 0 and has not been visited, then search for consecutive non-zero elements in 8 directions, mark each non-zero grid point, and calculate the consecutive length L in each direction. d1 ; Using the non-zero grid points in the above 8 directions as a reference, search for consecutive non-zero elements in the 8 directions. Mark the unmarked non-zero grid points as newly added non-zero grid points. After traversing the 8 grid points, calculate the newly added consecutive length L in the 8 directions for each grid point. d2 ; If L d2 If the value is greater than 0, re-mark the unmarked non-zero grid points as newly added non-zero grid points, until the k-th traversal search no longer encounters any new consecutive lengths, making L... dk =0; If L d1 +L d2 +…+L dk If the value is greater than or equal to 9, the connected region is retained, and the remaining retrieved grid points are marked as to be deleted.

8. A method for early warning of rainstorm disasters based on the X-band of a phased array rain-measuring radar according to claim 1, characterized in that, The rainstorm disaster warning image result is that the rainstorm warning area is filled through intelligent spatial analysis and real-time rendering, and the discrete warning signal is transformed into a spatially identifiable regional risk.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the rainstorm disaster warning method based on the X-band of phased array rain measuring radar as described in claim 1.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the rainstorm disaster warning method based on the X-band of phased array rain measuring radar as described in claim 1.

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