Probabilistic tsunami early warning system based on data analysis

Abstract

The invention relates to a probabilistic tsunami early warning system based on data analysis, and the system comprises a seismic data obtaining unit which is used for obtaining the monitoring information transmitted by each seismic station in a target region in real time, and a seismic data preprocessing unit which is used for preprocessing the monitoring information, the seismic source position determination unit is used for acquiring a plurality of groups of seismic source estimation positions, combinations of seismic magnitudes corresponding to each seismic source estimation position and probability values of each combination; the tsunami early warning analysis unit is used for obtaining a tsunami time sequence of a coastal output point and a time sequence of a water level station corresponding to each combination, and obtaining a preliminary result of tsunami early warning; and the tsunami parameter analysis unit is used for correcting the initial result of tsunami early warning based on the water level data to obtain a tsunami early warning result for issuing. According to the tsunami early warning system, the tsunami risk distribution of the forecast shore section is quickly given based on the limited data after the earthquake occurs, so that a decision maker can conveniently make a defense plan according to different possibilities.

Description

Technical Field

[0001] The invention belongs to the field of computer technology, and in particular relates to a probabilistic tsunami warning system based on data analysis. Background Art

[0002] Tsunami is a very dangerous tsunami disaster. Since 80% of tsunami disasters in history are caused by submarine earthquakes, how to quickly predict the disasters caused by earthquake tsunamis on the coast has become a global hot issue. The main principle for predicting tsunami disasters is that the speed of waves generated by submarine earthquakes (the source of tsunamis) is faster than the speed of tsunami waves.

[0003] Most existing tsunami warning systems are based on a single source parameter. However, in the short period of time after an earthquake, there are many possibilities for the source parameters. It is necessary to derive the possibility of multiple source parameter combinations based on limited data and quickly release tsunami warning information to the public and decision-making departments. An intelligent tsunami warning system is urgently needed to complete the above task. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In order to solve the above problems in the prior art, the present invention provides a probabilistic tsunami warning system based on data analysis.

[0006] (II) Technical solution

[0007] In order to achieve the above object, the main technical solutions adopted by the present invention include:

[0008] The present invention provides a probabilistic tsunami warning system based on data analysis, comprising:

[0009] The seismic data acquisition unit is used to acquire the monitoring information transmitted by each seismic station in the target area in real time. The monitoring information of each seismic station includes: basic information of the seismic station and monitored seismic wave information;

[0010] A seismic data preprocessing unit is used to preprocess the monitoring information transmitted by the seismic station in real time and obtain the preprocessed early warning data;

[0011] A seismic source location determination unit, used to obtain multiple groups of seismic source estimated locations, combinations of magnitudes corresponding to each seismic source estimated location, and probability values ​​of each combination according to the pre-processed warning data;

[0012] The tsunami warning analysis unit is used to simulate and calculate each combination based on the tsunami numerical model to obtain the tsunami time series of the coastal output point and the time series of the water level station corresponding to each combination; and to perform statistical analysis on the time series of all combinations to obtain the preliminary results of the tsunami warning;

[0013] The tsunami parameter analysis unit is used to obtain the water level data of each water level detection point in the target area, and to correct the preliminary results of the tsunami warning based on the water level data to obtain an updated tsunami warning result.

[0014] Optionally, the basic information of the seismic station includes: the longitude, latitude and depth of the seismic station;

[0015] The monitored seismic wave information includes: whether the seismic wave information is received, and the arrival time and waveform information of the P wave and S wave of the received seismic wave information.

[0016] Optionally, the seismic data preprocessing unit is specifically used to:

[0017] Remove data without seismic wave information from the monitoring information, and remove abnormal information from the seismic wave information to obtain pre-processed warning data;

[0018] Specifically, outliers in seismic wave information are removed, including:

[0019] Group any two station data in the monitoring information to obtain Group the first group; wherein n is the total number of the selected data;

[0020] For each first group, calculate the abnormality E reflecting the abnormality of the transverse plate and longitudinal wave f =max{E f (S),E f (P)},

[0021] The abnormality E f All first groups whose values ​​are greater than the abnormal threshold are regarded as abnormal first groups;

[0022] If there is selected data belonging to a preset number of abnormal first groups at the same time, the monitoring information is removed;

[0023] Where, f is the first group identifier, E f (S) is the shear wave anomaly of the first group of the fth group, E f (P) is the longitudinal wave anomaly of the first group of the fth group, is the longitude of the seismic monitoring station corresponding to the data selected in the fth first group, is the longitude of the seismic monitoring station corresponding to another selected data in the fth first group, is the latitude of the seismic monitoring station corresponding to the data selected in the fth first group, is the latitude of the seismic monitoring station corresponding to another selected data in the fth first group, is the depth of the seismic monitoring station corresponding to the data selected in the fth first group, is the depth of the seismic monitoring station corresponding to another selected data in the fth first group, is the time when the seismic monitoring station corresponding to a selected data in the fth first group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to another selected data in the fth first group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to a selected data in the fth first group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to another selected data in the fth first group detects the longitudinal wave of the seismic wave, v s is the velocity of the shear wave of the seismic wave, v p is the velocity of the longitudinal wave of the seismic wave.

[0024] Optionally, the earthquake source location determination unit is specifically configured to:

[0025] Obtaining the estimated location of the earthquake source according to the preprocessed warning data;

[0026] Specifically, any four data in the preprocessed warning data are grouped into a group, and the The second group, wherein k is the total number of the warning data to be processed;

[0027] For each second group, the corresponding estimated source position is calculated by the following equations:

[0028]

[0029] Wherein, g is the second group identifier, is the longitude of the estimated earthquake source position corresponding to the g-th second group, is the latitude of the estimated location of the earthquake source corresponding to the g-th second group, is the depth of the estimated earthquake source position corresponding to the g-th second group, is the longitude of the seismic monitoring station corresponding to a warning data to be processed in the g-th second group, is the longitude of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the longitude of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, is the longitude of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group, is the latitude of the seismic monitoring station corresponding to a warning data to be processed in the g-th second group, is the latitude of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the latitude of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, is the latitude of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group, is the depth of the seismic monitoring station corresponding to a warning data to be processed in the g-th second group, is the depth of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the depth of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, is the depth of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group, is the distance between the seismic monitoring station and the earthquake source corresponding to a warning data to be processed in the g-th second group, is the distance between the seismic monitoring station and the earthquake source corresponding to the second warning data to be processed in the g-th second group, is the distance between the seismic monitoring station and the earthquake source corresponding to the third warning data to be processed in the g-th second group, is the distance between the seismic monitoring station and the earthquake source corresponding to the last warning data to be processed in the g-th second group, is the time when the seismic monitoring station corresponding to a to-be-processed early warning data in the g-th second group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to a to-be-processed early warning data in the g-th second group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to the second early warning data to be processed in the g-th second group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to the second early warning data to be processed in the g-th second group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to the third to-be-processed early warning data in the g-th second group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to the third early warning data to be processed in the g-th second group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group detects the longitudinal wave of the seismic wave, v s is the velocity of the shear wave of the earthquake wave in the region, v p is the velocity of the longitudinal wave of the seismic wave in the region, is the square root of the sum of the squares of the longitude, latitude, and depth of the seismic monitoring station corresponding to a to-be-processed warning data in the g-th second group, is the square root of the sum of the squares of the longitude, latitude, and depth of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the square root of the sum of the squares of the longitude, latitude, and depth of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, It is the square root of the sum of the squares of the longitude, latitude, and depth of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group.

[0030] Optionally, the earthquake source location determination unit is specifically configured to:

[0031] According to the estimated earthquake source position, the difference E between the theoretical time of the longitudinal wave arriving at the i-th station and the actual arrival time of the longitudinal wave recorded at the station is calculated. gi ;

[0032] According to the travel time difference between each earthquake source estimated location and all stations in the target area, the probability P of the earthquake source estimated location is determined. g ;

[0033] And, based on the waveform information in the seismic wave information, the magnitude of each seismic station is estimated, and the magnitude of all seismic stations is statistically analyzed to obtain the probability P of the magnitude m ;

[0034] Combine each earthquake source estimated position and magnitude to obtain multiple groups of earthquake source estimated position and magnitude combinations, namely earthquake parameter combinations, and obtain the probability value P of each combination. gm .

[0035] Optionally, P gm =P g P m ;

[0036] Among them, t i (P) is the arrival time of the P wave recorded by the i-th station, is the distance from the gth earthquake location result to the i-th station, v p is the velocity of the longitudinal waves of the seismic waves in the area.

[0037] N m is the number of stations with magnitude m, and N is the total number of seismic stations.

[0038] Optionally, the tsunami warning analysis unit is specifically used to:

[0039] The database stores the tsunami time series of all pre-acquired earthquake parameter combinations at the predicted shore output points and tsunami water level recording stations;

[0040] Matching the earthquake parameter combination obtained in the earthquake position determination unit with that in the database, obtaining the coastal output point tsunami time series and the water level station time series of each coastal output point corresponding to each combination obtained in the earthquake position determination unit;

[0041] By statistically analyzing the tsunami time series of each output point and the time series of the water level station, we can obtain tsunami time series with different probabilities and weighted average tsunami time series;

[0042] The tsunami time series with different probabilities and the weighted average tsunami time series are taken as the preliminary results of tsunami warning.

[0043] Optionally, the tsunami parameter analysis unit is specifically used to:

[0044] Obtain water level data around each seismic station in the target area;

[0045] Preprocessing the water level data,

[0046] Traversing the preprocessed water level data, determining the mean of the preprocessed water level data included in each data window, wherein the data window includes m preprocessed water level data, and m is the maximum number of water level data in a preset window;

[0047] The maximum mean value is determined as the maximum amplitude of the tsunami, and the starting time of the window corresponding to the maximum mean value is determined as the arrival time of the tsunami;

[0048] According to the maximum tsunami amplitude and the tsunami amplitude near the arrival time of the tsunami, the preliminary results of the tsunami warning are re-weighted and the final tsunami warning results are selected.

[0049] Optionally, the tsunami parameter analysis unit is specifically used to:

[0050] For any water level station i that obtains records, take the maximum tsunami amplitude as the center, and take (m / 2-1) points before and after to obtain a time series ts with a length of m i ;

[0051] For any source parameter combination j, i.e., the earthquake parameter combination j obtained in the earthquake location determination unit, with the maximum tsunami amplitude as the center, (m / 2-1) points are taken before and after to obtain a time series ts with a length of m j ; and determine whether the following conditions are met:

[0052] ∑(ts i -ts j )<ε

[0053] Where ε is a preset value. Based on the warning area and the distribution information of water level stations, if the conditions are met, the source parameter combination will be retained. If the conditions are not met, the source parameter combination will be eliminated and the weights of each group of source parameters will be recalculated to correct the tsunami time series with different probabilities and the weighted average tsunami time series to obtain the final tsunami warning result.

[0054] Optionally, the system further comprises:

[0055] The issuing unit is used to generate and issue a tsunami forecast sheet based on the tsunami warning result and a predefined tsunami forecast template.

[0056] (III) Beneficial effects

[0057] The probabilistic tsunami warning system based on data analysis of the present invention can quickly determine the various possible impact ranges and possibilities of a tsunami based on limited data and information after an earthquake occurs, and automatically generates tsunami warning information based on the analysis results and releases it to the public, thereby ensuring the timeliness of tsunami warnings and providing decision makers with a theoretical basis for evacuation. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 A schematic structural diagram of a probabilistic tsunami warning system based on data analysis provided by the present invention;

[0059] Figure 2 A schematic structural diagram of another probabilistic tsunami warning system based on data analysis provided by the present invention. DETAILED DESCRIPTION

[0060] In order to better understand the above technical solution, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a clearer and more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0061] Embodiment 1

[0062] like Figure 1 As shown, the present invention provides a probabilistic tsunami warning system based on data analysis, which can be located in any computing device and specifically includes the following units:

[0063] The seismic data acquisition unit is used to acquire the monitoring information transmitted by each seismic station in the target area in real time. The monitoring information of each seismic station includes: the basic information of the seismic station and the monitored seismic wave information; for example, the basic information of the seismic station includes: the longitude, latitude and depth of the seismic station; the monitored seismic wave information includes: whether the seismic wave information is received, the arrival time and waveform information of the P wave and S wave of the received seismic wave information.

[0064] A seismic data preprocessing unit is used to preprocess the monitoring information transmitted by the seismic station in real time and obtain the preprocessed early warning data;

[0065] A seismic source location determination unit, used to obtain multiple groups of seismic source estimated locations, combinations of magnitudes corresponding to each seismic source estimated location, and probability values ​​of each combination according to the pre-processed warning data;

[0066] The tsunami warning analysis unit is used to simulate and calculate each combination based on the tsunami numerical model to obtain the tsunami time series of the coastal output point and the time series of the water level station corresponding to each combination; and to perform statistical analysis on the time series of all combinations to obtain the preliminary results of the tsunami warning;

[0067] The tsunami parameter analysis unit is used to obtain the water level data of each water level detection point in the target area, and to correct the preliminary results of the tsunami warning based on the water level data to obtain the updated tsunami warning results.

[0068] In addition, the system of this embodiment further includes: a publishing unit; the publishing unit is specifically used to generate a tsunami forecast sheet for publication according to the tsunami warning result and a predefined tsunami forecast template.

[0069] The probabilistic tsunami warning system of this embodiment is based on a limited variety of data and information after an earthquake occurs, quickly determines the various possible impact ranges and possibilities of a tsunami, and automatically generates tsunami warning information based on the analysis results and releases it to the public, ensuring the timeliness of tsunami warnings while providing decision makers with a theoretical basis for evacuation.

[0070] Embodiment 2

[0071] In order to better understand the solution of the above-mentioned embodiment 1, the solution of the above-mentioned embodiment 1 is described in detail below in combination with the accompanying drawings, and the function of each unit is described in detail.

[0072] The seismic data acquisition unit is specifically used to acquire the monitoring information transmitted by each seismic station in the target area in real time. The monitoring information of each seismic station includes: basic information of the seismic station and monitored seismic wave information.

[0073] It is understandable that after an undersea earthquake occurs, due to the rapid propagation speed of seismic waves, multiple nearby seismic monitoring stations (i.e., seismic stations) will be able to quickly receive seismic waves in a short period of time. Seismic waves include transverse waves (i.e., S waves) and longitudinal waves (i.e., P waves). For example, seismic stations can automatically pick up seismic wave information based on historical waveforms through a pre-trained machine learning model. The seismic data acquisition unit then receives the basic information of multiple seismic stations transmitted by the seismic stations and the picked / monitored seismic wave information.

[0074] The basic information of any seismic station (such as seismic monitoring station b) includes: the longitude of any seismic monitoring station (such as the longitude x of seismic monitoring station b); b ), the latitude of any seismic monitoring station (such as the latitude y of seismic monitoring station b b ) and the depth of any seismic monitoring station (e.g., the depth z of seismic monitoring station b b ).

[0075] The seismic wave information monitored by any seismic monitoring station includes: whether the seismic wave information is monitored.

[0076] If seismic wave information is detected, the seismic wave information detected by any seismic monitoring station also includes: the time when the shear wave of the seismic wave is detected (such as the time when the shear wave of the seismic wave is detected by seismic monitoring station b, t b (S)), the time when the longitudinal wave of the seismic wave is detected (such as the time when the longitudinal wave of the seismic wave is detected by the seismic monitoring station b t b (P)).

[0077] In specific implementation, the earthquake data acquisition unit will continuously acquire the basic information of the earthquake monitoring stations in the target area and the monitored earthquake wave information to ensure the comprehensiveness and timeliness of the warning data for tsunami warning.

[0078] The seismic data preprocessing unit is specifically used to preprocess the monitoring information transmitted by the seismic station in real time and obtain the preprocessed early warning data.

[0079] The seismic data preprocessing unit in this embodiment is a unit that continuously acquires data. Whenever data transmitted by the seismic data acquisition unit is acquired, the newly acquired data can be immediately summarized and analyzed with the currently acquired data to effectively remove abnormal values ​​and ensure the accuracy and reliability of subsequent early warning analysis.

[0080] In this embodiment, data without seismic wave information in the monitoring information is removed, and abnormal information in the seismic wave information is removed to obtain pre-processed warning data, that is, warning data to be processed.

[0081] The selection process first selects monitoring data containing earthquake data, that is, data that monitors earthquake wave information. Generally, tsunamis are caused by earthquakes. Therefore, data without earthquake data will not cause earthquakes and therefore has no value for tsunami warnings. The second step is to select data without obvious anomalies. The anomaly here is obtained based on the difference between the calculated earthquake wave velocity and the wave velocity in the data. If the difference is particularly large, it means that there is an anomaly in the data value. The specific process of removing anomalies from the selected data is as follows:

[0082] 1.1, group any two selected data and get Group one group.

[0083] Where n is the total number of selected data.

[0084] For example, the selected data are data 11, data 12, data 13, and data 14. At this time, n=4, and the first grouping obtained has 6 groups, namely {data 11, data 12}, {data 11, data 13}, {data 11, data 14}, {data 12, data 13}, {data 12, data 14}, {data 13, data 14}.

[0085] Any data includes the longitude of the corresponding seismic station (such as the longitude x of seismic station b). b ), the latitude of the corresponding seismic station (e.g. the latitude of seismic station b is y b ), the depth of the corresponding seismic station (such as the depth of seismic station b z b ), the time and wave speed of the shear wave of the seismic wave detected (for example, the time t b (S)), the time and wave speed of the longitudinal wave of the seismic wave detected (such as the time t b (P)).

[0086] 1.2, for each first group, calculate the abnormality E f =max{E f (S),E f (P)}.

[0087] Wherein, f is the first group identifier.

[0088] E f (S) is the shear wave anomaly of the first group of the fth group,

[0089]

[0090] E f (P) is the longitudinal wave anomaly of the first group of the fth group,

[0091]

[0092] is the longitude of the seismic monitoring station corresponding to the data selected in the fth first group, The longitude of the seismic monitoring station corresponding to another selected data in the f-th first group. is the latitude of the seismic monitoring station corresponding to the data selected in the fth first group, The latitude of the seismic monitoring station corresponding to another selected data in the f-th first group. is the depth of the seismic monitoring station corresponding to the data selected in the fth first group, The depth of the seismic monitoring station corresponding to another selected data in the f-th first group.

[0093] is the time when the seismic monitoring station corresponding to a selected data in the fth first group detects the shear wave of the seismic wave, The time when the seismic monitoring station corresponding to another selected data in the f-th first group detected the shear wave of the seismic wave.

[0094] is the time when the seismic monitoring station corresponding to a selected data in the fth first group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to another selected data in the fth first group detects the longitudinal wave of the seismic wave, v s is the velocity of the shear wave of the earthquake wave in the region, v p is the velocity of the longitudinal waves of the seismic waves in the area.

[0095] A first group includes two data, one of which is data No. 1 and the other is data No. 2. The data values ​​in data No. 1 are marked with a 1 in the upper right corner, and the data values ​​in data No. 2 are marked with a 2 in the upper right corner. This embodiment does not specifically limit which one is selected as data No. 1.

[0096] For example, for the first group {data 11, data 12}, if data 11 is data No. 1, then if data 12 is data No. 2. In this case, the longitude of the corresponding seismic monitoring station in data 11 is The latitude of the corresponding seismic monitoring station is The depth of the corresponding seismic monitoring station is The time when the shear wave of the seismic wave is detected is The time when the longitudinal wave of the seismic wave is detected The longitude of the corresponding seismic monitoring station in data 12 is The latitude of the corresponding seismic monitoring station is The depth of the corresponding seismic monitoring station is The time when the shear wave of the seismic wave is detected is

[0097] If data 12 is data No. 1, then if data 11 is data No. 2. In this case, the longitude of the corresponding seismic monitoring station in data 12 is The latitude of the corresponding seismic monitoring station is The depth of the corresponding seismic monitoring station is The time when the shear wave of the seismic wave is detected is The time when the longitudinal wave of the seismic wave is detected The velocity of the longitudinal wave of the detected seismic wave is The longitude of the corresponding seismic monitoring station in data 11 is The latitude of the corresponding seismic monitoring station is The depth of the corresponding seismic monitoring station is The time when the longitudinal wave of the seismic wave is detected

[0098] in, is the distance between the seismic monitoring stations corresponding to the two data in the first group, is the time when the seismic monitoring station corresponding to the two data in the first group detected the seismic shear wave, It is the speed of the seismic shear wave propagating between the seismic monitoring stations corresponding to the two data in the first group, and it is also the speed of the shear wave calculated based on the relevant data values ​​of the two data. is the difference between the calculated shear wave velocity and the regional estimated shear wave velocity. Ideally, this value is 1. In this case, E f (S) = 0, indicating that the data values ​​of the two data in the first group are very accurate. The greater the distance between the ratio and 1 (it can be a positive distance, that is, greater than 1, in which case the calculated shear wave velocity is greater than the estimated shear wave velocity, or a negative distance, that is, less than 1, in which case the calculated shear wave velocity is smaller than the estimated shear wave velocity), the higher the E f The larger the value of (S), the more abnormal the data is.

[0099] Similarly, E f (P) is the abnormal degree of longitudinal wave velocity from the perspective of longitudinal waves, E f The larger the value of (S), the more abnormal the data is.

[0100] E f =max{E f (S),E f (P)}, that is, E f It reflects the most abnormal wave speeds in transverse waves and longitudinal waves.

[0101] 1.3, the abnormality E f All first packets whose values ​​are greater than the abnormal threshold are regarded as abnormal first packets.

[0102] Ideally, E f (S) and E f (P) are all small values ​​close to 0, but due to the sensitivity and accuracy of the monitoring equipment, as well as various factors in the process of seismic wave propagation, E f (S)>0 and / or E f (P)>0, that is, E f >0. Usually, a normal gap range, i.e., abnormal threshold, is set according to the distribution of stations in the region and the geological structure. f If E is less than or equal to the abnormal threshold, the deviation is considered acceptable and the two data in the first group are still considered accurate. f If it is greater than the abnormal threshold, the deviation is considered unacceptable and the two data in the group are abnormal.

[0103] 1.4. If there are selected data belonging to a preset number of abnormal first groups at the same time, they will be eliminated.

[0104] Through step 1.3, all abnormal first groups can be obtained, each of which includes 2 data. At this time, it is not possible to determine which data is abnormal. However, if a data appears in a preset number of abnormal first groups at the same time, it means that it is abnormal.

[0105] For example, if the preset number is 3, then if there is a data that appears in three abnormal groups at the same time, it means that the data is abnormal. In other words, the monitoring data of the seismic station with the highest frequency (or the frequency of occurrence is greater than the specified value) in the abnormal group is abnormal data.

[0106] By removing abnormal data in the warning data to be processed in the above manner, the warning data to be processed is obtained.

[0107] The warning data to be processed in this embodiment does not include invalid data (ie, data that does not contain earthquake data) or abnormal data, so the accuracy of the final warning can be guaranteed by performing tsunami warning using the warning data to be processed.

[0108] The earthquake source location determination unit is specifically used to obtain multiple groups of earthquake source estimated locations, the combination of magnitudes corresponding to each earthquake source estimated location, and the probability value of each combination based on the pre-processed warning data.

[0109] The earthquake source location determination unit in this embodiment is also a unit for continuous calculation and processing. Whenever the data transmitted by the earthquake data preprocessing unit is obtained, the newly obtained data can be immediately summarized and analyzed with the currently obtained data to determine the earthquake source location. The earthquake source location determination unit can also read the latest data obtained by the earthquake data preprocessing unit during this period of time at regular intervals, and then summarize the latest data with the currently obtained data to determine the earthquake source location.

[0110] The specific process may include:

[0111] 2.1, calculate the estimated earthquake source position, i.e., the earthquake location result, based on the early warning data to be processed.

[0112] Sequentially group any four of the pending warning data into a group, and obtain The second group, wherein k is the total number of the warning data to be processed;

[0113] That is to say, the prerequisite for executing step 2.1 is that the number of pending warning data needs to be greater than or equal to 4. If the number of pending warning data is less than 4, you can wait for a while (such as 1 minute, etc.) and then determine whether the number of pending warning data is greater than or equal to 4. This is because the seismic data preprocessing unit continuously acquires data, and the source location determination unit will add the latest data acquired by the warning data acquisition unit to the currently obtained data for processing. If the current number of pending warning data is less than 4, then as the seismic data preprocessing unit continues to acquire, the condition that the number of pending warnings is greater than or equal to 4 may be met in the future, and then step 2.1 is executed.

[0114] In addition, even if the number of current pending warning data is greater than or equal to 4, after the seismic data preprocessing unit obtains the latest data, the earthquake source position determination unit can also add it to the current pending warning data and then execute step 2.1. That is to say, the earthquake source position determination unit will repeatedly determine the earthquake source position based on the data obtained by the seismic data preprocessing unit, and then continuously update the earthquake source position until a earthquake source position that is considered accurate is obtained.

[0115] In addition, in step 2.1, the warning data to be processed will be divided into A second group.

[0116] For example, there are 6 warning data to be processed, namely data 21, data 22, data 23, data 24, data 25, and data 26. At this time, k=6.

[0117] The corresponding second groupings are 15, namely {data 21, data 22, data 23, data 24}, {data 21, data 22, data 23, data 25}, {data 21, data 22, data 23, data 26}, {data 21, data 22, data 24, data 25}, {data 21, data 22, data 24, data 26}, {data 21, data 22, data 25, data 26}, {data 21, data 23, data 24, data 25}, {data data 21, data 23, data 24, data 26}, {data 21, data 23, data 25, data 26}, {data 21, data 24, data 25, data 26}, {data 22, data 23, data 24, data 25}, {data 22, data 23, data 24, data 26}, {data 22, data 23, data 25, data 26}, {data 22, data 24, data 25, data 26}.

[0118] 2.2, for each second group, the corresponding earthquake source estimated position is calculated by the following equations:

[0119]

[0120] Wherein, g is the second group identifier.

[0121] is the longitude of the estimated earthquake source position corresponding to the g-th second group, is the latitude of the estimated location of the earthquake source corresponding to the g-th second group, is the depth of the estimated earthquake source position corresponding to the g-th second group.

[0122] h g is the number of warning data to be processed in the g-th second group. For example, for group {data 21, data 22, data 23, data 24}, h g =4.

[0123] is the longitude of the seismic monitoring station corresponding to a warning data to be processed in the g-th second group, is the longitude of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the longitude of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, is the longitude of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group.

[0124] is the latitude of the seismic monitoring station corresponding to a warning data to be processed in the g-th second group, is the latitude of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the latitude of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, is the latitude of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group.

[0125] is the depth of the seismic monitoring station corresponding to a warning data to be processed in the g-th second group, is the depth of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the depth of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, is the depth of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group.

[0126] is the distance between the seismic monitoring station and the earthquake source corresponding to a warning data to be processed in the g-th second group, is the distance between the seismic monitoring station and the earthquake source corresponding to the second warning data to be processed in the g-th second group, is the distance between the seismic monitoring station and the earthquake source corresponding to the third warning data to be processed in the g-th second group, is the distance between the seismic monitoring station and the earthquake source corresponding to the last warning data to be processed in the g-th second group.

[0127] is the time when the seismic monitoring station corresponding to a to-be-processed early warning data in the g-th second group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to a to-be-processed early warning data in the g-th second group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to the second early warning data to be processed in the g-th second group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to the third to-be-processed early warning data in the g-th second group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to the third early warning data to be processed in the g-th second group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group detects the shear wave of the seismic wave, The time when the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group detects the longitudinal wave of the seismic wave.

[0128] is the square sum of the longitude, latitude and depth of the seismic monitoring station corresponding to a to-be-processed warning data in the g-th second group, is the square sum of the longitude, latitude and depth of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the square sum of the longitude, latitude and depth of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, It is the sum of the squares of the longitude, latitude and depth of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group.

[0129] 2.3. According to the above group calculation, there are multiple groups of earthquake location results (such as 15 groups of earthquake source estimated positions in the above example). Calculate the difference E between the theoretical time of the longitudinal wave of the g-th earthquake location result arriving at the i-th station and the actual arrival time of the longitudinal wave recorded at the station. gi ;

[0130]

[0131] Among them, t i (P) is the arrival time of the P wave recorded by the i-th station, is the distance from the gth earthquake location result to the i-th station, v p is the velocity of the longitudinal waves of the seismic waves in the area.

[0132] 2.4, calculate the probability of each earthquake location result based on the travel time difference between each earthquake location result and all stations, that is:

[0133]

[0134] 2.5. At the same time, the magnitude of each seismic station is calculated based on the waveform data of each seismic station. N magnitudes can be obtained from N stations. These magnitudes are equal and divided into a group. The probability of each magnitude is further calculated:

[0135]

[0136] Where N m is the number of stations with magnitude m, and N is the total number of stations.

[0137] 2.6. Combine each earthquake location result with the magnitude to obtain multiple combinations of earthquake location results and magnitudes. For example, in the above example, there are 15 groups of earthquake location results. Assuming there are 3 magnitudes, there are 45 groups of earthquake parameter combinations. The probability value P of each combination is gmis the product of the probability of the corresponding positioning result and the magnitude probability: P gm =P g P m .

[0138] The tsunami warning analysis unit is specifically used to simulate and calculate each combination based on the tsunami numerical model to obtain the tsunami time series of the coastal output points and the time series of the water level station corresponding to each combination; and to perform statistical analysis on the time series of all combinations to obtain the preliminary results of the tsunami warning.

[0139] In this embodiment, the database pre-stores the sequences corresponding to each simulated earthquake parameter combination, i.e., the tsunami time sequence of the predicted shore output point and the tsunami water level recording station. That is, the tsunami time sequence of each possible earthquake parameter combination at the predicted shore output point and the tsunami water level recording station is estimated in advance in the database using a known method.

[0140] That is, before an earthquake occurs, all possible earthquake parameter combinations (epicenter location and magnitude) are analyzed through the results of historical earthquake and geological structure research, and the above earthquake parameter combinations are simulated and calculated through the tsunami numerical model to obtain the tsunami time series of the predicted shore output points and surrounding tsunami water level recording stations.

[0141] At this time, the earthquake parameter combinations obtained in the earthquake position determination unit (a total of 45 groups in the above example) are compared one by one with the earthquake parameter combinations in the database, and the numerical simulation results (i.e., time series) corresponding to the closest earthquake parameter combination are determined as the numerical simulation results of each earthquake parameter in the current earthquake position determination unit;

[0142] The numerical simulation results include: the curve of the tsunami amplitude changing with time at each output point on the simulated tsunami warning shore section (tsunami time series) and the tsunami time series of the simulated water level recording station; the probability of each numerical simulation is the probability of the earthquake parameter set.

[0143] By statistically analyzing the tsunami amplitude series set composed of multiple tsunami time series at each forecast point, we can obtain tsunami time series with different probabilities and weighted average tsunami time series, and then obtain the preliminary results of tsunami warning.

[0144] The preliminary results of the above-mentioned tsunami warning are the results of simulation based on the extrapolation of seismic wave information, which may contain deviations and lead to false alarms and other unreliability. Therefore, it is necessary to further correct the preliminary results of the above-mentioned tsunami warning to improve the reliability and accuracy of the tsunami warning results. The accuracy and reliability of the data are guaranteed through verification or correction.

[0145] The tsunami parameter analysis unit is specifically used to obtain the water level data of each water level detection point / water level monitoring station in the target area, and to correct the preliminary results of the tsunami warning based on the water level data to obtain an updated tsunami warning result.

[0146] In this embodiment, the water level data monitored by the water level detection point includes: the longitude and latitude of the water level observation station, whether a tsunami is monitored, and the time series of the tsunami.

[0147] In a possible line-of-sight approach, the tsunami parameter analysis unit may be specifically used to:

[0148] Obtain water level data around each seismic station in the target area;

[0149] Preprocessing the water level data, wherein the preprocessing includes: outlier processing, missing value processing and bandpass filtering processing;

[0150] Traversing the preprocessed water level data, determining the mean of the preprocessed water level data included in each data window, wherein the data window includes m preprocessed water level data, and m is the maximum number of water level data in a preset window;

[0151] The maximum mean value is determined as the maximum amplitude of the tsunami, and the starting time of the window corresponding to the maximum mean value is determined as the arrival time of the tsunami.

[0152] According to the maximum tsunami amplitude and the tsunami amplitude near the arrival time, the earthquake parameters are re-weighted and the tsunami simulation results are selected as the final tsunami warning results.

[0153] In another possible line-of-sight approach, the tsunami parameter analysis unit may be specifically used to:

[0154] For any water level station that obtains records, i.e., water level monitoring station i, take (m / 2-1) points before and after the maximum tsunami amplitude as the center to obtain a time series ts with a length of m i ;

[0155] For any source parameter combination j, the maximum tsunami amplitude generated at the water level station is taken as the center, and (m / 2-1) points are taken before and after to obtain a time series ts with a length of m j ; and determine whether the following conditions are met:

[0156] ∑(ts i -ts j )<ε

[0157] Where ε is a preset value. According to the separately determined warning area and water level station distribution information, if the conditions are met, the source parameter combination is retained. If the conditions are not met, the source parameter combination is eliminated and the weights of each group of source parameters are recalculated, so as to further correct the tsunami time series with different probabilities and the weighted average tsunami time series to obtain the final tsunami warning result.

[0158] The above system uses the information of seismic waves that have arrived in advance in the current tsunami earthquake to perform data analysis, obtain the source location results and magnitude information, and then infer the possible affected areas and time series of the tsunami. At the same time, it uses the currently monitored water level data to correct the areas and time series that may be affected by the tsunami, to ensure the accuracy and reliability of tsunami warnings.

[0159] In the description of this specification, the description of the terms "one embodiment", "some embodiments", "embodiment", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a combined manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0160] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may alter, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A probabilistic tsunami warning system based on data analysis, characterized in that: include: The seismic data acquisition unit is used to acquire the monitoring information transmitted by each seismic station in the target area in real time. The monitoring information of each seismic station includes: basic information of the seismic station and monitored seismic wave information; A seismic data preprocessing unit is used to preprocess the monitoring information transmitted by the seismic station in real time and obtain the preprocessed early warning data; A seismic source location determination unit, used to obtain multiple groups of seismic source estimated locations, combinations of magnitudes corresponding to each seismic source estimated location, and probability values ​​of each combination according to the pre-processed warning data; The tsunami warning analysis unit is used to simulate and calculate each combination based on the tsunami numerical model to obtain the tsunami time series of the coastal output point and the time series of the water level station corresponding to each combination; and to perform statistical analysis on the time series of all combinations to obtain the preliminary results of the tsunami warning; The tsunami parameter analysis unit is used to obtain the water level data of each water level detection point in the target area, and to correct the preliminary results of the tsunami warning based on the water level data to obtain an updated tsunami warning result.

2. The system according to claim 1, characterized in that The basic information of the seismic station includes: the longitude, latitude and depth of the seismic station; The monitored seismic wave information includes: whether the seismic wave information is received, and the arrival time and waveform information of the P wave and S wave of the received seismic wave information.

3. The system according to claim 2, characterized in that The seismic data preprocessing unit is specifically used for: Remove data without seismic wave information from the monitoring information, and remove abnormal information from the seismic wave information to obtain pre-processed warning data; Specifically, outliers in seismic wave information are removed, including: Group any two station data in the monitoring information to obtain Group the first group; wherein n is the total number of the selected data; For each first group, calculate the abnormality E reflecting the abnormality of the transverse plate and longitudinal wave f =max{E f (S),E f (P)}, The abnormality E f All first groups whose values ​​are greater than the abnormal threshold are regarded as abnormal first groups; If there is selected data belonging to a preset number of abnormal first groups at the same time, the monitoring information is removed; Where, f is the first group identifier, E f (S) is the shear wave anomaly of the first group of the fth group, E f (P) is the longitudinal wave anomaly of the first group of the fth group, is the longitude of the seismic monitoring station corresponding to the data selected in the fth first group, is the longitude of the seismic monitoring station corresponding to another selected data in the fth first group, is the latitude of the seismic monitoring station corresponding to the data selected in the fth first group, is the latitude of the seismic monitoring station corresponding to another selected data in the fth first group, is the depth of the seismic monitoring station corresponding to the data selected in the fth first group, is the depth of the seismic monitoring station corresponding to another selected data in the fth first group, is the time when the seismic monitoring station corresponding to a selected data in the fth first group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to another selected data in the fth first group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to a selected data in the fth first group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to another selected data in the fth first group detects the longitudinal wave of the seismic wave, v s is the velocity of the shear wave of the seismic wave, v p is the velocity of the longitudinal wave of the seismic wave.

4. The system according to claim 2, characterized in that The earthquake source location determination unit is specifically used for: Obtaining the estimated location of the earthquake source according to the preprocessed warning data; Specifically, any four data in the preprocessed warning data are grouped into a group, and the The second group, wherein k is the total number of the warning data to be processed; For each second group, the corresponding estimated source position is calculated by the following equations: Wherein, g is the second group identifier, is the longitude of the estimated earthquake source position corresponding to the g-th second group, is the latitude of the estimated location of the earthquake source corresponding to the g-th second group, is the depth of the estimated earthquake source position corresponding to the g-th second group, is the longitude of the seismic monitoring station corresponding to a warning data to be processed in the g-th second group, is the longitude of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the longitude of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, is the longitude of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group, is the latitude of the seismic monitoring station corresponding to a warning data to be processed in the g-th second group, is the latitude of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the latitude of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, is the latitude of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group, is the depth of the seismic monitoring station corresponding to a warning data to be processed in the g-th second group, is the depth of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the depth of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, is the depth of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group, is the distance between the seismic monitoring station and the earthquake source corresponding to a warning data to be processed in the g-th second group, is the distance between the seismic monitoring station and the earthquake source corresponding to the second warning data to be processed in the g-th second group, is the distance between the seismic monitoring station and the earthquake source corresponding to the third warning data to be processed in the g-th second group, is the distance between the seismic monitoring station and the earthquake source corresponding to the last warning data to be processed in the g-th second group, is the time when the seismic monitoring station corresponding to a to-be-processed early warning data in the g-th second group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to a to-be-processed early warning data in the g-th second group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to the second early warning data to be processed in the g-th second group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to the second early warning data to be processed in the g-th second group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to the third to-be-processed early warning data in the g-th second group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to the third early warning data to be processed in the g-th second group detects the longitudinal wave of the seismic wave, is the time when the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group detects the shear wave of the seismic wave, is the time when the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group detects the longitudinal wave of the seismic wave, v s is the velocity of the shear wave of the earthquake wave in the region, v p is the velocity of the longitudinal wave of the seismic wave in the region, is the square root of the sum of the squares of the longitude, latitude, and depth of the seismic monitoring station corresponding to a to-be-processed warning data in the g-th second group, is the square root of the sum of the squares of the longitude, latitude, and depth of the seismic monitoring station corresponding to the second warning data to be processed in the g-th second group, is the square root of the sum of the squares of the longitude, latitude, and depth of the seismic monitoring station corresponding to the third warning data to be processed in the g-th second group, It is the square root of the sum of the squares of the longitude, latitude, and depth of the seismic monitoring station corresponding to the last warning data to be processed in the g-th second group.

5. The system according to claim 4, characterized in that The earthquake source location determination unit is specifically used for: According to the estimated earthquake source position, the difference E between the theoretical time of the longitudinal wave arriving at the i-th station and the actual arrival time of the longitudinal wave recorded at the station is calculated. gi ; According to the travel time difference between each earthquake source estimated location and all stations in the target area, the probability P of the earthquake source estimated location is determined. g ; And, based on the waveform information in the seismic wave information, the magnitude of each seismic station is estimated, and the magnitude of all seismic stations is statistically analyzed to obtain the probability P of the magnitude m ; Combine each earthquake source estimated position and magnitude to obtain multiple groups of earthquake source estimated position and magnitude combinations, namely earthquake parameter combinations, and obtain the probability value P of each combination. gm .

6. The system according to claim 5, characterized in that Among them, r i (P) is the arrival time of the P wave recorded by the i-th station, is the distance from the gth earthquake location result to the i-th station, v p is the velocity of the longitudinal waves of the seismic waves in the region; N m is the number of stations with magnitude m, and N is the total number of seismic stations.

7. The system according to any one of claims 1 to 6, characterized in that: Tsunami warning analysis unit, specifically used for: The database stores the tsunami time series of all pre-acquired earthquake parameter combinations at the predicted shore output points and tsunami water level recording stations; Matching the earthquake parameter combination obtained in the earthquake position determination unit with that in the database, obtaining the coastal output point tsunami time series and the water level station time series of each coastal output point corresponding to each combination obtained in the earthquake position determination unit; By statistically analyzing the tsunami time series of each output point and the time series of the water level station, we can obtain tsunami time series with different probabilities and weighted average tsunami time series; The tsunami time series with different probabilities and the weighted average tsunami time series are taken as the preliminary results of tsunami warning.

8. The system according to claim 7, characterized in that The tsunami parameter analysis unit is specifically used for: Obtain water level data around each seismic station in the target area; Preprocessing the water level data, Traversing the preprocessed water level data, determining the mean of the preprocessed water level data included in each data window, wherein the data window includes m preprocessed water level data, and m is the maximum number of water level data in a preset window; The maximum mean value is determined as the maximum amplitude of the tsunami, and the starting time of the window corresponding to the maximum mean value is determined as the arrival time of the tsunami; According to the maximum tsunami amplitude and the tsunami amplitude near the arrival time of the tsunami, the preliminary results of the tsunami warning are re-weighted and the final tsunami warning results are selected.

9. The system according to claim 7, characterized in that The tsunami parameter analysis unit is specifically used for: For any water level station i that obtains records, take the maximum tsunami amplitude as the center, and take (m / 2-1) points before and after to obtain a time series ts with a length of m i ; For any source parameter combination j, i.e., the earthquake parameter combination j obtained in the earthquake location determination unit, with the maximum tsunami amplitude as the center, (m / 2-1) points are taken before and after to obtain a time series ts with a length of m j ; and determine whether the following conditions are met: ∑(ts i -ts j )<ε Where ε is a preset value. Based on the warning area and water level station distribution information, if the conditions are met, the source parameter combination is retained. If the conditions are not met, the source parameter combination is eliminated and the weights of each group of source parameters are recalculated to correct the tsunami time series with different probabilities and the weighted average tsunami time series to obtain the final tsunami warning result.

10. The system according to claim 1, characterized in that The system further comprises: The issuing unit is used to generate and issue a tsunami forecast sheet based on the tsunami warning result and a predefined tsunami forecast template.

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