CN116482763A - Probabilistic earthquake and tsunami disaster analysis method based on logic tree method - Google Patents
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Abstract
The invention relates to a probabilistic earthquake and tsunami disaster analysis method based on a logic tree method, which comprises the following steps: acquiring an area to be analyzed for the probabilistic earthquake and tsunami disaster analysis method; respectively determining an earthquake tsunami source and a high-precision terrain file according to the area to be analyzed; constructing a parameter logic tree according to the first parameter set and the second parameter set corresponding to the earthquake tsunami source; calculating according to the high-precision terrain file and using a tsunami numerical model to determine a tsunami maximum wave height file; and determining the wave height exceeding probability at each pixel point of the area to be analyzed according to a logic tree method formed by the parameter logic tree, and a plurality of maximum wave height files which are combined and calculated in a probabilistic manner. The probabilistic earthquake and tsunami disaster analysis method based on the logic tree method can reduce the uncertainty of analysis and obviously reduce occupied computing resources.
Description
Technical Field
The invention relates to the field of earthquake and tsunami, in particular to a probabilistic earthquake and tsunami disaster analysis method based on a logic tree method.
Background
Seismic tsunami is a billow caused by a submarine earthquake, a seaside earthquake, or a volcanic eruption. Destructive seismic tsunamis are typically initiated by a back-flushing type ocean bottom seismic above grade 6.5 and with a source depth of less than 20-60 km. Historically, tsunamis induced by ocean bottom earthquakes account for 95% of the historical tsunami events, and therefore it becomes very important how to accurately quantify the risk of tsunamis in the target area.
In the related art, a montecarlo method is generally used for analysis of probabilistic earthquake tsunami. That is, a catalog is created that contains various ocean bottom seismic parameters that may induce destructive seismic tsunamis, and all the earthquakes in the catalog are numerically simulated.
Disclosure of Invention
In order to solve the above-mentioned shortcomings, the invention provides a probabilistic earthquake and tsunami disaster analysis method based on a logic tree method, which comprises the following steps: acquiring an area to be analyzed for the probabilistic earthquake and tsunami disaster analysis method; respectively determining an earthquake tsunami source and a high-precision terrain file according to the area to be analyzed; constructing a parameter logic tree according to the first parameter set and the second parameter set corresponding to the earthquake tsunami source; calculating according to the high-precision terrain file and using a tsunami numerical model to determine a tsunami maximum wave height file; and determining the wave height exceeding probability at each pixel point of the area to be analyzed according to a logic tree method formed by the parameter logic tree, and a plurality of maximum wave height files which are combined and calculated in a probabilistic manner.
Optionally, the determining the earthquake tsunami source according to the area to be analyzed includes: and determining the plate of the area to be analyzed as the earthquake tsunami source according to the SIFT system.
Optionally, the determining, according to the SIFT system, the slab of the area to be analyzed as the first parameter set corresponding to the seismic tsunami source at least includes: longitude and latitude, strike angle, inclination angle and slip angle.
Optionally, the second parameter set includes at least: first parameterSecond parameter->And a third parameterAnd said second parameter +.>And said third parameter->Establishing branches of the parameter logic tree according to the sequence of the adjacent parameter logic tree, wherein the branches are->Annual probability of occurrence in the magnitude interval +.>For the ratio of the number of historically occurring earthquakes at different positions of said panel to the whole panel,/->Probability of a source center being at a random location for an earthquake to occur.
Optionally, the second parameter set further includes: fourth parameterAnd fifth parameter->, wherein ,to be in the region ofjProbability of an earthquake occurring in the building and the depth of the earthquake focus being less than the upper depth limit of the earthquake focus, +.>To be in the region ofjProbability of a primary earthquake occurring in the building and the source mechanism being a thrust type earthquake.
Optionally, the second parameter group establishes the parameter logic tree branches according to the following consecutive order: first parameterSecond parameter->Third parameter->Fourth parameter->And fifth parameter->。
Optionally, the determining a high-precision topographic file according to the area to be analyzed includes: and determining the high-precision terrain file according to the GEBCO.
Optionally, the determining the tsunami maximum wave height file according to the high-precision terrain file and by calculating using a tsunami numerical model includes: and calculating the high-precision terrain file of the earthquake by using a non-static tsunami numerical model, and determining a tsunami maximum wave height file.
Optionally, the logic tree method formed according to the parameter logic tree, and the probabilistic combination and calculation of a plurality of maximum wave height files determine the wave height override probability at each pixel point of the area to be analyzed, so as to satisfy the following formula:
；
；
wherein ,Ttime range, unit is year;hin a time range for each pixel pointTMaximum wave height of tsunami wave in year;Hfor a specific tsunami wave height;for determining that in time rangeTWhether the pixel point generates maximum wave height within yearhGreater than or equal to a specific wave heightHTsunami of (a); when->When (I)>Equal to 1 when->In the time-course of which the first and second contact surfaces,equal to 0.
Optionally, the probabilistic earthquake and tsunami disaster analysis method based on the logic tree method further comprises the following steps: and drawing a probabilistic earthquake and tsunami disaster analysis map in the area to be analyzed according to the wave height exceeding probability at each pixel point.
The method comprises the steps of optimizing the number of branches in a logic tree by using deterministic parameters contained in a seismic source in a SIFT (Short-term inundation forecast) system, and establishing a simplified seismic catalog which can accurately cover destructive tsunamis, so that a non-static-pressure tsunami numerical model is used for carrying out probabilistic tsunami disaster analysis, and meanwhile, the uncertainty of analysis is reduced and occupied computing resources are remarkably reduced. The probabilistic tsunami disaster analysis can be used for carrying out tsunami disaster evaluation on all places in a range, so that the disaster evaluation is not limited to specific places along the coastal equal-depth line, and the probabilistic tsunami disaster analysis has important guiding function on design planning and risk management of islands and offshore operation platforms with smaller areas.
Drawings
In the following, by way of example, the drawings of exemplary embodiments of the invention are shown, the same or similar reference numbers being used in the various drawings to designate the same or similar elements. In the accompanying drawings:
fig. 1 shows a flowchart of a probabilistic earthquake and tsunami disaster analysis method based on a logic tree method according to an exemplary embodiment of the present invention.
Fig. 2 shows a schematic diagram of a parameter logic tree method of an exemplary embodiment of the present invention.
Fig. 3 shows a flowchart of a further decomposition of a probabilistic earthquake and tsunami disaster analysis method based on a logical tree method according to an exemplary embodiment of the present invention.
Fig. 4 shows a flowchart of a probabilistic earthquake and tsunami disaster analysis method based on a logic tree method according to another embodiment of the present invention.
Detailed Description
The invention will be better explained by the following detailed description of the embodiments with reference to the drawings.
In the present disclosure, the term "and/or" is intended to cover all possible combinations and subcombinations of the listed elements, including any, subcombinations, or all of the elements listed individually, without necessarily excluding other elements. Unless otherwise indicated, the terms "first," "second," and the like are used to describe various elements and are not intended to limit the positional, timing, or importance relationship of these elements, but are merely used to distinguish one element from another. Unless otherwise indicated, the terms "front, rear, upper, lower, left, right" and the like are generally based on the orientation or positional relationship shown in the drawings, and are merely for convenience of description and to simplify the description, and are not to be construed as limiting the scope of the invention.
Fig. 1 schematically shows a flow chart of a probabilistic earthquake and tsunami disaster analysis method based on a logical tree method according to an exemplary embodiment of the present invention.
S102: and acquiring an area to be analyzed for a probabilistic earthquake and tsunami disaster analysis method. The area or range of analysis is selected as desired, e.g., the region of the manila dive zone in the sea area of south China sea, the region of east China sea.
S104: and respectively determining the earthquake tsunami source and the high-precision terrain file according to the area to be analyzed.
The source of the seismic tsunami is first determined. In an exemplary embodiment, SIFT systems provided by the U.S. pacific marine environmental research center ("PMEL, pacific Marine Environmental Laboratory") are preferred, with typical influential slabs of the area to be analyzed as sources of seismic tsunami.
And secondly, determining a high-precision topographic file of the area to be analyzed. In an exemplary embodiment, a high-precision topography file of the region provided by GEBCO ("General Bathymetric Chart of the Oceans") is preferred. Compared with other high-precision topographic files, the high-precision topographic file spatial resolution provided by GEBCO is more suitable for the invention.
S106: and constructing a parameter logic tree according to the first parameter set and the second parameter set corresponding to the earthquake tsunami source.
At present, monte Carlo method is commonly used for establishing an earthquake catalog through probabilistic earthquake and tsunami disaster analysis. The Monte Carlo method first requires the creation of a catalogue of hundreds of thousands or even millions of earthquakes, and then numerical simulation of each earthquake in the catalogue. This approach requires significant computational resources. If a numerical mode with faster computation is used to save computing resources, the computation accuracy is reduced.
Another method for creating seismic catalogues for probabilistic seismic tsunami disaster analysis is the logical tree method. Although the logical tree method creates a smaller number of seismic catalogs, because different seismic scenarios are represented as branches of the logical tree, and the weights of the branches represent different assumptions and interpretations, such assumptions and interpretations require greater certainty. In practice, however, such assumptions and interpretation are typically determined from the seismic tsunami specialist or seismic specialist's questionnaire. Which has a large uncertainty.
Both of the above methods do not accurately and efficiently analyze probabilistic earthquake and tsunami disasters. FIG. 2 illustrates a schematic diagram of a parameter logic tree method of an exemplary embodiment. Branches in the logic tree are simplified by creatively using a first parameter set and a preferable second parameter set corresponding to the earthquake tsunami source in the SIFT system, and a simplified and accurate earthquake catalog which can generate destructive tsunami is built. Wherein the first set of parameters is relatively determined based on the determination of the aforementioned seismic tsunami source. Specifically, the latitude and longitude, strike angle, tilt angle and slip angle of the seismic tsunami source block of the area to be analyzed acquired at the SIFT system constitute a first set of parameters in the exemplary embodiment. In another embodiment, the first parameter set includes: longitude and latitude, strike angle, inclination angle, slip angle, and fracture zone length and width. In a further embodiment, the first parameter set further comprises a plurality of sub-parameter sets, each of the plurality of sub-parameter sets comprising one or more parameters. These first parameter sets have the common feature: is relatively determined based on the determination of the source of the seismic tsunami.
The second parameter set is a non-deterministic parameter set. As shown in connection with fig. 2 and 3.
First, a magnitude interval in which a destructive tsunami is generated is selected according to the region to be analyzed, preferably the magnitude interval is in the range of 6.5 to 9.0, and the magnitude interval is set to 0.1. Wherein each magnitude interval represents the magnitude of that interval by selecting an intermediate magnitudeThe number of magnitude intervals is set to i.
Secondly, the representative magnitude of each magnitude interval is used to calculate the length and width of the corresponding fracture zone and the slippage. The earthquake magnitude will be represented according to the empirical formulaThe conversion into seismic moments: />The method comprises the steps of carrying out a first treatment on the surface of the Then according to the empirical formula, the earthquake momentDeducing the fracture zone area: />The method comprises the steps of carrying out a first treatment on the surface of the Finally, calculating the length and width of the fracture zone by using an aspect ratio formula: />The method comprises the steps of carrying out a first treatment on the surface of the Calculate the slip +.>Shear modulus is +.>The formula is: />；
Again, based on historical seismic records in the United states geological survey USGS ("United States Geological Survey"), the historical seismic events that occur for the plate in S104 are counted and G-R ("Gutenberg-Richter") formula fitting is performed on the data of the historical seismic events, whereinFor the magnitude of jolt->For the corresponding magnitude +.>And satisfies the formula: />；
Determining a first parameter in the second parameter set: annual probability of occurrence for each magnitude interval，
；
wherein ,upper limit of magnitude of earthquake for the plate, < +.>For the lower limit of the magnitude of the earthquake that occurs for this plate, and />Respectively corresponding cumulative distribution functions of the upper limit and the lower limit of the required earthquake magnitude interval> and />The upper limit and the lower limit of the required magnitude range are respectively +.>Constant value obtained for fitting G-R formula, < >>Is a constant value. In the above formula, the annual occurrence probability +.f of each magnitude interval is obtained by subtracting the cumulative distribution functions corresponding to the upper and lower limits of the magnitude interval>。
Determining a second parameter of the second parameter set: the ratio of the historical earthquake quantity at different positions of the plate to the whole plateUsing the history seismic records of the USGS to count the frequency of the actual earthquake occurrence of the plate at different positions, and dividing the plate into plates along the trend of the plate according to the earthquake densityjCalculating the ratio of earthquake occurrence in each area>，
；
wherein ,to at the firstjThe total number of historical earthquakes in each zone,Nis the historical seismic sum for that panel.
In some embodiments, the slabs are divided into a number of slabs according to the spatial density at which the earthquake occurs. For example, in a manila diving band, the manila diving band is divided into upper, middle and lower three blocks according to the spatial density of the occurrence of an earthquake.
Determining a third parameter of the second set of parameters: probability of a seismic event occurring with a seismic source centered at random one location，
；
Wherein the plate is moved along the direction of the platekAliquoting, each aliquoting having a location that is to be considered as the center of the source in the seismic survey, with a probability that one earthquake occurs and the center of the source is at a random location。
Build up number ofThe relative certainty parameters in the seismic catalog are longitude and latitude, trend angle, inclination angle, slip angle, length and width of fracture zone, depth and average slip of the center position of the seismic source.
In the illustrated embodiment, the second set of parameters further includes a fourth parameter: first, thejProbability of a seismic event occurring in a region with a source depth less than the upper source depth limit，
；
wherein ,to at the firstjTotal number of historical earthquakes in each zone, +.>To at the firstjThe depth of the historical seismic source in each area is less than +.>Is a function of the number of earthquakes.
The depth of the source that triggered the seismic tsunami was counted based on historical seismic tsunami recordings ("https:// www.ngdc.noaa.gov/hazel/view/hazards/tsunami/event-search") provided by the national marine and atmospheric administration NOAA ("National Oceanic and Atmospheric Administration"). Because the depth of the seismic source that can induce destructive tsunamis is shallow, it is desirable to determine the upper limit of the depth of the seismic source that can induce tsunamisAnd find +.about.based on the historical seismic record of USGS>。
Further, in the illustrated embodiment, the second set of parameters further includes a fifth parameter: probability of a seismic event and the source mechanism being a thrust type seismic eventNamely the firstjProbability of a thrust type earthquake occurring in each region.
Statistics have been based on historical seismic records (https:// www.globalcmt.org/CMTfiles. Html) in GCMT (Global Centroid Moment Tensor Project), for example, since 1976jCalendar in individual areasStress axis inclination angle of earthquake historyWherein stress axis inclination->More than 50 degrees is a thrust earthquake. Because the parameters of the SIFT plate are the back-flushing type earthquake and the back-flushing type earthquake only causes destructive earthquake tsunami, the statistics is carried outjProbability of occurrence of a thrust earthquake in the individual zones +.>，
；
wherein ,to at the firstjTotal number of historical earthquakes in each zone, +.>To at the firstjThe number of earthquakes in each zone with a historical seismic stress axis dip angle greater than 50 degrees.
In a preferred embodiment, as shown in fig. 2 and 3, the second parameter set includes the first parameter, the second parameter, the third parameter, the fourth parameter, and the fifth parameter at the same time.
It should be understood that in the embodiment shown in fig. 2 and 3, the first parameter, the second parameter, the third parameter, the fourth parameter, and the fifth parameter establish the branches of the logic tree in the order shown in the figures. In other embodiments, the order of the first parameter, the fourth parameter, and the fifth parameter may be appropriately adjusted, for example, the logical tree branches may be established according to the order of the second parameter, the third parameter, the first parameter, the fifth parameter, and the fourth parameter.
S108: and calculating according to the high-precision terrain file and using a tsunami numerical model to determine a tsunami maximum wave height file. In an exemplary embodiment, a non-static tsunami numerical model is used in the seismic surveyA kind of electronic deviceThe earthquake is calculated in the area range of the high-precision terrain file to obtain +.>A tsunami maximum wave height file.
S110: determining the wave height exceeding probability at each pixel point of the area to be analyzed according to a logic tree method formed by the parameter logic tree, and a plurality of maximum wave height files which are combined and calculated in a probabilistic manner。
Using logical tree pairsThe overrun probability of each pixel point of the Tsunami maximum wave height file is calculated, and the time range of each pixel point can be calculatedTAmplitude of annual tsunami wavehProbability of exceeding a certain height H, i.e. wave height override probability +.>The calculation formula is as follows:
；
wherein ,Ttime range, unit is year;hin a time range for each pixel pointTMaximum wave height of tsunami wave in year;Hfor a specific tsunami wave height;for determining that in time rangeTWhether the pixel point generates maximum wave height within yearhGreater than or equal to a specific wave heightHTsunami of (a); when->When (I)>Equal to 1 when->In the time-course of which the first and second contact surfaces,equal to 0.
Through verification, by the method, the established parameter logic tree method comprising the parameter logic tree branches formed by the first parameter group and the second parameter group has the result more conforming to the probability of the happened earthquake and tsunami in reality, and meanwhile, the uncertainty in establishing the earthquake and tsunami list can be obviously reduced. In some verification experiments, the submarine earthquake law in the realistic diving zone can be accurately restored by only establishing the earthquake tsunami catalogue with the scene number of hundreds, and compared with the earthquake tsunami catalogue with the scene number of hundreds of thousands established in the related art, the calculation time and the occupied calculation resource are obviously saved. The saved computing resources can be used for improving the precision of numerical simulation and expanding the range of tsunami disaster evaluation.
Fig. 4 schematically shows a flow chart of a probabilistic earthquake and tsunami disaster analysis method based on a logical tree method according to another embodiment of the invention. In comparison to the flow shown in fig. 1, the embodiment shown in fig. 3 further includes S212, which is specifically as follows:
s202: and acquiring an area to be analyzed for the probabilistic earthquake and tsunami disaster analysis method.
S204: and respectively determining an earthquake and tsunami source and a high-precision terrain file according to the area to be analyzed.
S206: and constructing a parameter logic tree according to the first parameter set and the second parameter set corresponding to the earthquake tsunami source.
S208: and calculating according to the high-precision terrain file and using a tsunami numerical model to determine a tsunami maximum wave height file.
S210: and determining the wave height exceeding probability at each pixel point of the area to be analyzed according to a logic tree method formed by the parameter logic tree, and a plurality of maximum wave height files which are combined and calculated in a probabilistic manner.
S212: and drawing a probabilistic earthquake and tsunami disaster analysis map in the area to be analyzed according to the wave height exceeding probability at each pixel point. The wave height override probability of the region to be analyzed can be visually presented using a drawing program.
It will be understood that the invention has been described in terms of several embodiments, and that various changes and equivalents may be made to these features and embodiments by those skilled in the art without departing from the spirit and scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (10)
1. A probabilistic earthquake and tsunami disaster analysis method based on a logic tree method is characterized by comprising the following steps:
acquiring an area to be analyzed for the probabilistic earthquake and tsunami disaster analysis method;
respectively determining an earthquake tsunami source and a high-precision terrain file according to the area to be analyzed;
constructing a parameter logic tree according to the first parameter set and the second parameter set corresponding to the earthquake tsunami source;
calculating according to the high-precision terrain file and using a tsunami numerical model to determine a tsunami maximum wave height file;
and determining the wave height exceeding probability at each pixel point of the area to be analyzed according to a logic tree method formed by the parameter logic tree, and a plurality of maximum wave height files which are combined and calculated in a probabilistic manner.
2. The method for analyzing the probabilistic tsunami disaster in earthquake based on the logic tree method as set forth in claim 1, wherein the determining the source of the tsunami in earthquake based on the area to be analyzed comprises:
and determining the plate of the area to be analyzed as the earthquake tsunami source according to the SIFT system.
3. The method for analyzing probabilistic tsunami disaster in earthquake and tsunami disaster based on the logical tree method as set forth in claim 2, wherein determining, according to the SIFT system, the slab of the area to be analyzed as the first parameter set corresponding to the tsunami source at least includes: longitude and latitude, strike angle, inclination angle and slip angle.
4. The method for analyzing probabilistic earthquake and tsunami disaster based on the logical tree method as set forth in claim 3, wherein the second parameter set includes at least: first parameterSecond parameter->And third parameter->And said second parameter +.>And said third parameter->Establishing the parameter logic tree branches according to the sequence adjacent to each other, wherein,
annual probability of occurrence in the magnitude interval +.>For the ratio of the number of historically occurring earthquakes at different positions of said panel to the whole panel,/->Probability of a source center being at a random location for an earthquake to occur.
5. The logic tree based probabilistic earthquake and tsunami disaster analysis method as set forth in claim 4, wherein the second parameter set further comprises: fourth parameterAnd fifth parameter->, wherein ,
to be in the region ofjProbability of an earthquake occurring in the building and the depth of the earthquake focus being less than the upper depth limit of the earthquake focus, +.>To be in the region ofjProbability of a primary earthquake occurring in the building and the source mechanism being a thrust type earthquake.
6. The method for analyzing probabilistic earthquake and tsunami disasters based on a logic tree method according to claim 5, wherein the second parameter set establishes the parameter logic tree branches in the following consecutive order: first parameterSecond parameter->Third parameter->Fourth parameter->And fifth parameter->。
7. The method for analyzing the probabilistic earthquake and tsunami disaster based on the logical tree method as set forth in claim 6, wherein the determining the high-precision topography file according to the area to be analyzed includes: and determining the high-precision terrain file according to the GEBCO.
8. The method for analyzing the disaster of the probabilistic earthquake and tsunami based on the logical tree method as set forth in claim 7, wherein the determining the maximum wave height file of the tsunami based on the high-precision topography file and calculated by using a tsunami numerical model comprises:
and calculating the high-precision terrain file of the earthquake by using a non-static tsunami numerical model, and determining a tsunami maximum wave height file.
9. The method for analyzing probabilistic earthquake and tsunami disasters based on a logic tree method according to claim 8, wherein the logic tree method formed according to the parameter logic tree, and the probabilistic combination and calculation of a plurality of maximum wave height files, determine the wave height overrun probability at each pixel point of the area to be analyzed, and satisfy the following formula:
；
；
wherein ,Ttime range, unit is year;hin a time range for each pixel pointTMaximum wave height of tsunami wave in year;Hfor a specific tsunami wave height;
for determining that in time rangeTWhether the pixel point generates maximum wave height within yearhGreater than or equal to a specific wave heightHTsunami of (a); when->When (I)>Equal to 1; when->When (I)>Equal to 0.
10. The logic tree method based probabilistic earthquake and tsunami disaster analysis method as set forth in claim 9, further comprising:
and drawing a probabilistic earthquake and tsunami disaster analysis map in the area to be analyzed according to the wave height exceeding probability at each pixel point.
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| Title |
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| 杨智博: "中国地震海啸危险性分析", 中国优秀硕士学位论文全文数据库 基础科学辑, pages 010 - 17 * |
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| CN116482763B (en) | 2023-08-25 |
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