CN108492236B - Multiple current Tsunami disaster appraisal procedure based on Monte Carlo stochastic simulation - Google Patents
Multiple current Tsunami disaster appraisal procedure based on Monte Carlo stochastic simulation Download PDFInfo
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Abstract
The multiple current Tsunami disaster appraisal procedure based on Monte Carlo stochastic simulation that the invention discloses a kind of, method include: that S1 applies a variety of focal shock parameter estimation methods to establish potential tsunami source region seismicity parameters logic tree；S2 establishes tsunami unit source Green's function database using linear tsunami numerical simulation；S3 generates Stochastic earthquake event set according to above-mentioned logic tree, using Monte Carlo stochastic simulation；S4 is simulated using random slippage according to tsunami unit source Green's function database and Stochastic earthquake event set and is generated tsunami wave amplitude collection；Analysis of uncertainty of the S5 according to tsunami wave amplitude collection, to multiple current Tsunami disaster distribution results statistics and result.The above method be able to solve risk evaluation result in the prior art it is higher and can not provide its correspond to probability of happening the problem of, a variety of uncertainties are fused in final assessment result, increase the confidence level of result, operational efficiency is improved simultaneously, policymaker is facilitated targetedly to make prevent and reduce natural disasters deployment and physical construction planning.
Description
Technical field
The invention belongs to Tsunami disaster assessment technologies more particularly to a kind of based on the multiple current of Monte Carlo stochastic simulation
Tsunami disaster appraisal procedure.
Background technique
Since 21st century, multiple earthquake Tsunami disaster is had occurred in the whole world, and direct economic loss is more than 260,000,000,000
Dollar.Wherein, the Japanese 9.0 grades of seismic sea waves of the 9.2 grades of seismic sea waves of Indonesia Sumatra in 2004 and east in 2011 all give locality
Resident living and economic development cause destructive strike.It can be seen that tsunami has become the coastal residence in the threat whole world
One of the natural calamity of people's security of the lives and property most serious.
The core for carrying out Tsunami disaster risk assessment is the tsunami risk intensity of determining a certain assessment area, specifically
Be maximum tsunami wave amplitude, tsunami that the determining assessment area can suffer from climb, depth of immersion etc..
Currently, generalling use certainty assessment technology route in the world to determine tsunami risk.Certainty tsunami risk
Appraisal procedure is mainly inferred to most destructive seismic sea wave source according to historical events, utilizes its biography of tsunami model study
It broadcasts, the process climbed and flooded, provides that impact evaluation region is worst to flood scene, and assess tsunami risk accordingly.It should
The advantages of method be it is simple and easy, can be obtained conclusion often through the simulation of one or several scenes, and conclusion form letter
It is single intuitive.But there is also certain deficiencies for this method: being difficult to provide the probability of happening of these " the worst " so-called scenes, Huo Zheping
Estimate a possibility that different degrees of Tsunami disaster occurs in region (return period).
In addition, the compound conservative of multi-parameter makes the scene probability of happening of these " the worst " minimum, even can not
's.Fig. 1 is the schematic diagram for the tsunami risk that insider assesses marginal basins area using Manila trench " the worst " scene.
Although can intuitively find out which region is influenced maximum by Tsunami disaster, which can not provide the reproduction of the scene
The probability that phase, i.e. different regions are influenced by Tsunami disaster.
The tsunami risk for how reasonably providing assessment area different reoccurrence as a result, becomes current and needs what is solved to ask
Topic.
Summary of the invention
For the problems of the prior art, the present invention provides a kind of multiple current tsunami based on Monte Carlo stochastic simulation
Disaster Assessment method, this method be able to solve risk evaluation result in the prior art it is higher and can not provide its correspond to probability of happening
The problem of.
The present invention provides a kind of multiple current Tsunami disaster appraisal procedure based on Monte Carlo stochastic simulation, comprising:
S1, potential tsunami source region seismicity parameters logic tree is established using a variety of focal shock parameter estimation methods；
S2, tsunami unit source Green's function database is established using linear tsunami numerical simulation；
S3, the potential tsunami source region seismicity parameters logic tree according to foundation are raw using Monte Carlo stochastic simulation
At Stochastic earthquake event set；
S4, according to tsunami unit source Green's function database and the Stochastic earthquake event set, using random slippage mould
It is quasi- to generate tsunami wave amplitude collection；
S5, according to the tsunami wave amplitude collection, to multiple current Tsunami disaster distribution results statistics and to multiple current
The analysis of uncertainty of Tsunami disaster distribution results.
Optionally, the step S1 includes:
Using the maximum likelihood fit TGR relationship and the foundation of seismic moment conservation theorem in a variety of focal shock parameter estimation methods
The logic tree of the seismicity parameters of potential tsunami source region.
Optionally, using the magnitude parameter of TGR Relation acquisition tsunami source region, comprising:
The TGR relationship are as follows:
Wherein, M is seismic moment, MtIt is the complete Critical earthquake square of earthquake catalogue, McIt is corner seismic moment, β is TGR relationship
Slope, reflect the seismicity in region；F (M) is that seismic moment is greater than MtEarthquake incidence；
The approximation relation of seismic moment M and earthquake magnitude m is M=101.5m+C(2)；
The unit of M is ox rice, and C is constant；
Optimal parameter M is calculated with maximum likelihood functioncAnd β, maximum likelihood function are as follows:
Wherein, N is seismic moment MiGreater than Critical earthquake square MtEarthquake number；
Using the focal shock parameter estimation method of seismic moment conservation theorem, comprising:
It is indicated according to the seismic moment of geology parameter estimation are as follows: M=χ μ WLv (4)；
Wherein, χ is the earthquake coefficient of coup, and μ is rigidity modulus of shearing, and W is the underriding width of earthquake zone, and L is the length of tomography
Degree, v are the Mean Speed of plate；
On the other hand, according to TGR relationship, seismic moment M are as follows:
Wherein,
atIt is greater than M for seismic momenttSeismic events year occurrence rate, Γ is gamma function, C1For constant；
In conjunction with formula (4) and formula (5), work as Mc> > MtWhen: obtain corner seismic moment Mc:
Obtaining corner seismic moment McAfterwards, corner earthquake magnitude is inferred to according to formula (2)；
The TGR relationship and seismic moment conservation theorem use different parameters to obtain multiple corner earthquake magnitude values, combining global
Subduction zone TGR relationship establishes potential tsunami source region seismicity parameters logic tree.
Optionally, before executing step S2, the method also includes:
S2a, tsunami source region is divided into the tsunami unit source that several equal in magnitude and slippages are 1 meter；Unit source
Tomography geometric parameter obtained by historical earthquake focal mechanism solution and related geology parameter evaluation method.
Optionally, the S3 includes:
According to the tsunami source parameter in the potential tsunami source region seismicity parameters logic tree, with linear tsunami number
Value simulation calculates each tsunami source in the tsunami wave amplitude of assessment area；
Wherein, linear tsunami numerical model indicates are as follows:
In formula, η is the Free Surface displacement relative to mean sea level；For longitude；φ is latitude；R is earth radius；
H is total depth of water；P is the flux along longitude unit width；Q is the flux along latitude unit width；F is Coriolis force coefficient；G attaches most importance to
Power acceleration；
Since tsunami progression is unsatisfactory for linear relationship in offshore, the tsunami wave amplitude being calculated needs to change by Green's rule
The tsunami wave amplitude of offshore is calculated, is indicated are as follows:
Wherein AcFor the tsunami wave amplitude of offshore output point, HcFor the offshore output point depth of water, A0For the tsunami wave of offshore output point
Width, H0For the littoral output point depth of water.
Optionally, the S3 includes:
Using Monte Carlo stochastic simulation based on the logic tree established in S1, generated at random within the scope of tsunami source region more
Cover the seismic events collection in the following certain period of time；
The seismic events that each independent seismic events is concentrated random distribution in tsunami source region, and each sea
Earthquake magnitude-frequency relation of seismic events in howl source region meets wherein one in TGR logic tree.
Optionally, the S4 includes:
For each of Stochastic earthquake event set seismic events, using earthquake magnitude-, rupture range formula is determining and delimits
Unit source needed for calculating tsunami wave amplitude；Earthquake magnitude-rupture range empirical equation indicates are as follows:
mw=4.868+1.392log10(L) (13)；
mw=4.441+0.846log10(A) (14)；
M in formulawFor magnitude, L is rupture length, and A is Strain energy, selectes the earthquake according to rupture length and area
Event calculates required tsunami unit source；
The seismic events are generated at random every using the earthquake random breakage analogue technique based on von Karman function
Rupture slippage on a unit source；Each event is calculated in the maximum tsunami wave of assessment area in conjunction with tsunami unit source database
Width is to generate maximum tsunami wave amplitude event set.
Optionally, the S5 includes:
For some seismic events collection, it is assumed that there is NtA seismic sea wave source region contributes the tsunami risk of bank point,
In n-th potential complications tsunami source region influence the outcross probability P of coastal waters bank site h tsunami wave amplitude Tn(H >=h), then site h
Tsunami wave amplitude T must outcross probability indicate are as follows:
Output point is released by (15) formula and reaches specified tsunami wave amplitude HhReturn period ThAre as follows:
For a certain specific Disaster Assessment output point O, can be transferred through in specific return period T, N number of earthquake catalogue
(16) formula calculates the maximum tsunami wave amplitude h on the aspecti, then the maximum tsunami wave amplitude for output point O in return period T are as follows:
In addition, by maximum amplitude h caused by different earthquake catalogueiClassified statistic obtain different focal shock parameters pair
As a result influence degree.
In order to achieve the above objectives, the present invention also provides a kind of multiple current Tsunami disaster based on Monte Carlo stochastic simulation
Device is assessed, including memory, processor, bus and stores the computer journey that can be run on a memory and on a processor
Sequence, the processor are realized when executing described program such as the step of above method any one.
In order to achieve the above objectives, a kind of computer storage medium, is stored thereon with computer program, and described program is processed
It realizes when device executes such as the step of above method any one.
The device have the advantages that as follows:
The first, due to existing earthquake catalogue curtailment (longest was only more than 100 years), sample number is less, simple
It will cause the corner earthquake magnitude (m in Fig. 4 therein using historical earthquake data fitting TGR relationshipc, main function is to TGR relationship
High earthquake magnitude part is modified, and greater than the return period of the seismic events of this earthquake magnitude, exponentially form is increased rapidly in TGR relationship) partially
It is low, and then underestimate the risk of tsunami.Seismic moment superposition principle is combined to establish the potential tsunami source region TGR logic of relations in the present invention
Tree, the law can pass through the Seismic annual occurrence rate of a period of time and regional structure parameter (underriding rate, the earthquake coupling of subduction zone
Close the factor, modulus of shearing etc.) calculate the corner earthquake magnitude in TGR relationship, corner earthquake magnitude is thus given in logic tree
A variety of possibility, so that assessment result is more accurate.
The second, the certainty that any perfect evaluation system should all have uncertainty analysis system, however apply at present
Tsunami methods of risk assessment is can not provide result probabilistic.Monte carlo algorithm (Meng Teka is utilized in the present invention
Lip river stochastic simulation), simulate the seismic events of magnanimity.The position of each seismic events, earthquake magnitude or even rupture process are totally full
It is all random on the basis of the certain rule of foot.This just provides enough samples for analysis of uncertainty, also can will not really
It is qualitative to be fused in assessment result.
Third, during tsunami numerical simulation, tsunami initial displacement field model is usually the bullet that is proposed by Okada
Property dislocation FAULT MODEL calculate.The slippage of the model interrupting layer determines the sea level relief volume of initial fields, logarithm mould
Quasi- result is affected.However, people are usual in the slippage of computed tomography in current tsunami risk assessment application
It assumes that it is uniformly distributed, and is calculated according to earthquake magnitude empirical equation.With the development of earthquake finite fault inversion technique, people
Find that the slippage of actual seismic rupture is unevenly distributed, and the influence to region tsunami numerical simulation result is very big.
Present invention application tsunami unit source Green's function database makes to calculate maximum tsunami wave amplitude, this method caused by each seismic events
Tsunami wave amplitude caused by the seismic events of magnanimity random breakage process must be simulated to be possibly realized, can both increase the accurate of result
Property, while random breakage process can also be assessed to the uncertainty of result.
It is higher and result pair can not be provided to solve tsunami assessment result in the prior art using method of the invention as a result,
A variety of uncertainties are fused in final assessment result by the problem of answering probability of happening, increase the confidence level of result, simultaneously
Operational efficiency is improved, policymaker is facilitated targetedly to make prevent and reduce natural disasters deployment and physical construction planning.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention without any creative labor, may be used also for those of ordinary skill in the art
To obtain other attached drawings according to these attached drawings.
Fig. 1 is the schematic diagram for the tsunami risk that Manila trench " the worst " scene assesses marginal basins area；
Fig. 2 a and Fig. 2 b are respectively method flow schematic diagram provided in an embodiment of the present invention；
Fig. 3 is Manila trench historical earthquake distribution；
Fig. 4 is Manila trench TGR relation schematic diagram；
Fig. 5 is Manila trench TGR parameter logistics tree；
Fig. 6 is that Manila trench tsunami unit source divides schematic diagram；
Fig. 7 is the maximum tsunami wave amplitude distribution schematic diagram for the marginal basins regional return period being 200 years；
Fig. 8 is the maximum tsunami wave amplitude distribution schematic diagram for the marginal basins regional return period being 500 years；
Fig. 9 is the maximum tsunami wave amplitude distribution schematic diagram for the marginal basins regional return period being 2000；
Figure 10 (a) to Figure 10 (d) is respectively that the schematic diagram of marginal basins urban tsunami wave height curve (is followed successively by height
Hero, Ku Limaao, Hong Kong and Wenchang).
Specific embodiment
In order to preferably explain the present invention, in order to understand, with reference to the accompanying drawing, by specific embodiment, this is sent out
It is bright to be used to assess marginal basins tsunami risk.
In the following description, multiple and different aspects of the invention will be described, however, for common skill in the art
For art personnel, the present invention can be implemented just with some or all structures or process of the invention.In order to explain
Definition for, specific number, configuration and sequence are elaborated, however, it will be apparent that these specific details the case where
Under the present invention also can be implemented.It in other cases, will no longer for some well-known features in order not to obscure the present invention
It is described in detail.
As shown in Figure 2 a and 2 b, Fig. 2 a and Fig. 2 b respectively illustrate one embodiment of the invention offer based on Monte Carlo
The flow chart of the multiple current Tsunami disaster appraisal procedure of stochastic simulation, the method for the present embodiment include the following steps:
S1, potential tsunami source region seismicity parameters logic tree is established using a variety of focal shock parameter estimation methods.
It for example, can be Manila sea according to geological structure theory, the main subduction zone of marginal basins in the present embodiment
Ditch, while being also the main potential tsunami source in the region.Historical earthquake in regional scope is as shown in figure 3, can in the present embodiment
Using the TGR relationship in the maximum likelihood fit region, the TGR relationship are as follows:
Wherein, M is seismic moment, MtIt is the complete Critical earthquake square of earthquake catalogue, McIt is corner seismic moment, β is TGR relationship
Slope, reflect the seismicity in region；
The approximation relation of seismic moment M and earthquake magnitude m is M=101.5m+C(2)；
The unit of M is ox rice, and C is constant.
Optimal parameter M is calculated with maximum likelihood methodcAnd β, maximum likelihood function are as follows:
The TGR parameter in the region is found out using maximum likelihood method, wherein β=0.45, corner earthquake magnitude mcValue be 7.5, it is bent
Line is as shown in Figure 4.Corner earthquake magnitude in the relationship is significantly lower than the average value of global subduction zone, mainly due to earthquake catalogue mistake
Caused by short, it is therefore desirable to be modified by other methods.
Using the focal shock parameter estimation method of seismic moment conservation theorem, it may include:
It may be expressed as: M=χ μ WLv (4) according to the seismic moment of geology parameter estimation；
Wherein χ is the earthquake coefficient of coup, and according to previous studies, the geology coefficient of coup in the region is between 0.1-0.3；μ
For rigidity modulus of shearing, value 3.0-4.9Gpa；W is the underriding width of earthquake zone, value 98km；L is the length of tomography, is taken
Value is 1100km；V is the Mean Speed of plate, value 90mm/yr；
On the other hand, according to TGR relationship, seismic moment M be can be evaluated whether are as follows:
Wherein,
atIt is greater than M for seismic momenttSeismic events year occurrence rate, Γ is gamma function, C1For constant；
In conjunction with formula (4) and formula (5), work as Mc> > MtWhen:
Corner seismic moment M can be obtainedc:
Obtaining corner seismic moment McAfterwards, corner earthquake magnitude is inferred to according to formula (2).It is available to bring different parameters into
Modified four corner earthquake magnitudes value 7.9,8.1,8.2 and 8.4, β value can select the TGR fitting result 0.45 in Manila region and complete
The average result 0.66 of ball subduction zone.Thus Manila trench TGR logic of relations tree (as shown in Figure 5) is established.
S2, tsunami unit source Green's function database is established using linear tsunami numerical simulation.
For example, before executing S2, it is 1 meter that tsunami source region can be divided into several equal in magnitude and slippages
Tsunami unit source；The tomography geometric parameter in unit source passes through historical earthquake focal mechanism solution and related geology parameter evaluation method
It obtains.
For example, dividing Manila region in conjunction with geologic parameter existing near Manila trench and history focal mechanism solution
Tsunami unit source (as shown in Figure 6), each a length of 100km in unit source, width 50km, slippage be 1 meter.The tomography in unit source
Geometric parameter can be obtained by historical earthquake focal mechanism solution and relevant geologic parameter evaluation method.
Based on tsunami source parameter (obtaining in step S1) above, the tsunami numerical model in marginal basins region is established,
Terrain resolution is 2 points, chooses 355 output points in bank, is commenting with each tsunami source of linear tsunami numerical simulation calculation
The tsunami wave amplitude in region is estimated, wherein linear tsunami numerical model can indicate are as follows:
In formula, η is the Free Surface displacement relative to mean sea level；For longitude；φ is latitude；R is earth radius；
H is total depth of water；P is the flux along longitude unit width；Q is the flux along latitude unit width；F is Coriolis force coefficient；G attaches most importance to
Power acceleration.
Since tsunami progression is unsatisfactory for linear relationship in offshore, the tsunami wave amplitude being calculated needs to change by Green's rule
The tsunami wave amplitude for calculating offshore, may be expressed as:
Wherein AcFor the tsunami wave amplitude of offshore output point, HcFor the offshore output point depth of water, A0For the tsunami wave of offshore output point
Width, H0For the littoral output point depth of water.
S3, the potential tsunami source region seismicity parameters logic tree according to foundation are raw using Monte Carlo stochastic simulation
At Stochastic earthquake event set.
Using Monte Carlo stochastic simulation (Monte carlo algorithm) based on the logic tree established in S1, in tsunami source region model
Enclose the seismic events collection in the following certain period of time of interior random generation mostly set.Symbiosis is at earthquake catalogue 100, each earthquake catalogue
Time is 100,000 year, amounts to seismic events 166096, largest magnitude 9.05.
S4, according to tsunami unit source Green's function database and the Stochastic earthquake event set, using random slippage mould
It is quasi- to generate tsunami wave amplitude collection.
For each of Stochastic earthquake event set generated in step S3 seismic events, using earthquake magnitude-rupture model
Unit source needed for enclosing formula determination and delimiting calculating tsunami wave amplitude.Earthquake magnitude-rupture range empirical equation may be expressed as:
mw=4.868+1.392log10(L) (13)
mw=4.441+0.846log10(A) (14)
M in formulawFor magnitude, L is rupture length, and A is Strain energy, can determine choosing according to rupture length and area
Determine the tsunami unit source needed for seismic events calculate.
Above-mentioned seismic events are given birth at random each using the earthquake random breakage analogue technique based on von Karman function
Rupture slippage on unit source.Each event is calculated in the maximum tsunami wave amplitude of assessment area in conjunction with tsunami unit source database
To generate maximum tsunami wave amplitude event set.
S5, according to the tsunami wave amplitude collection, to multiple current Tsunami disaster distribution results statistics and to multiple current
The analysis of uncertainty of Tsunami disaster distribution results.
For example, for some seismic events collection, it is assumed that there is NtA seismic sea wave source region has tribute to the tsunami risk of bank point
It offers, wherein n-th of potential complications tsunami source region influences the outcross probability P of coastal waters bank site h tsunami wave amplitude Tn(H >=h), then
Site h tsunami wave amplitude T must outcross probability indicate are as follows:
Output point can be released by (15) formula and reach specified tsunami wave amplitude HhReturn period ThAre as follows:
For a certain specific Disaster Assessment output point O, can be transferred through in specific return period T, N number of earthquake catalogue
(16) formula calculates the maximum tsunami wave amplitude h on the aspecti, then the maximum tsunami wave amplitude for output point O in return period T are as follows:
Maximum tsunami wave amplitude distribution in 200 years, 500 years and 2000 in marginal basins region is calculated according to above-mentioned formula
As shown in Fig. 7, Fig. 8 or Fig. 9, statistics obtains Kaohsiung, Ku Limaao, the tsunami maximum amplitude curve in Hong Kong and the city of Wenchang four
As shown in Figure 10, Figure 10 (a) to Figure 10 (d) is respectively the schematic diagram of marginal basins urban tsunami wave height curve, such as according to
Secondary is Kaohsiung, Ku Limaao, the tsunami wave height curve in Hong Kong and Wenchang city.
The potential tsunami source region TGR logic of relations is established in conjunction with seismic moment superposition principle in the present invention in the present embodiment
Tree, the law can pass through the Seismic annual occurrence rate of a period of time and regional structure parameter (underriding rate, the earthquake coupling of subduction zone
Close the factor, modulus of shearing etc.) calculate the corner earthquake magnitude in TGR relationship, corner earthquake magnitude is thus given in logic tree
A variety of possibility, so that assessment result is more accurate.Using Monte carlo algorithm, the seismic events of magnanimity are simulated.Each earthquake
The position of event, earthquake magnitude or even rupture process are all random on the basis of totally meeting certain rule.This is just not true
Qualitative analysis provides enough samples, and also uncertainty can be fused in assessment result.Using tsunami unit source Green's letter
Library is counted to calculate maximum tsunami wave amplitude caused by each seismic events, this method makes the ground for simulating magnanimity random breakage process
Tsunami wave amplitude caused by shake event is possibly realized, and can both increase the accuracy of result, while can also assess random breakage
Uncertainty of the process to result.
Marginal basins area multiple current tsunami risk and urban are given using method of the invention as a result,
Tsunami amplitude curve.
According to another aspect of an embodiment of the present invention, the present invention also provides a kind of based on the more of Monte Carlo stochastic simulation
Return period Tsunami disaster assesses device, the device include: memory, processor, bus and storage on a memory and can be by
The computer program that processor executes, the processor execute the method for realizing above-mentioned Fig. 2 a and Fig. 2 b when described program.For example,
Potential tsunami source region seismicity parameters logic tree is established using a variety of focal shock parameter estimation methods；For example, answering
With in a variety of focal shock parameter estimation methods maximum likelihood fit TGR relationship and seismic moment conservation theorem establish potential tsunami source
The logic tree of the seismicity parameters in area.
Tsunami unit source Green's function database is established using linear tsunami numerical simulation；
According to the potential tsunami source region seismicity parameters logic tree of foundation, using Monte Carlo stochastic simulation generate with
Machine seismic events collection；
According to tsunami unit source Green's function database and the Stochastic earthquake event set, simulates and give birth to using random slippage
At tsunami wave amplitude collection；
According to the tsunami wave amplitude collection, to multiple current Tsunami disaster distribution results statistics and to multiple current tsunami
The analysis of uncertainty of disaster distribution results.
In addition, the embodiment of the present invention also provides a kind of computer storage medium, it is stored thereon with computer program, the journey
It realizes when sequence is executed by processor such as the step of above method any one.
It should be clear that the invention is not limited to specific configuration described above and shown in figure and processing.
For brevity, it is omitted here the detailed description to known method.In the above-described embodiments, several tools have been described and illustrated
The step of body, is as example.But method process of the invention is not limited to described and illustrated specific steps, this field
Technical staff can make various changes, modification and addition after understanding spirit of the invention, or suitable between changing the step
Sequence.
It should also be noted that, the exemplary embodiment referred in the present invention, is retouched based on a series of step or device
State certain methods or system.But the present invention is not limited to the sequence of above-mentioned steps, that is to say, that can be according in embodiment
The sequence referred to executes step, may also be distinct from that the sequence in embodiment or several steps are performed simultaneously.
Finally, it should be noted that above-described embodiments are merely to illustrate the technical scheme, rather than to it
Limitation；Although the present invention is described in detail referring to the foregoing embodiments, those skilled in the art should understand that:
It can still modify to technical solution documented by previous embodiment, or to part of or all technical features into
Row equivalent replacement；And these modifications or substitutions, it does not separate the essence of the corresponding technical solution various embodiments of the present invention technical side
The range of case.
Claims (10)
1. a kind of multiple current Tsunami disaster appraisal procedure based on Monte Carlo stochastic simulation, which is characterized in that the method
For assessing the tsunami risk of marginal basins, which comprises
S1, potential tsunami source region seismicity parameters logic tree is established using a variety of focal shock parameter estimation methods；Specifically, lead to
The regional structure parameter of Seismic annual occurrence rate and global subduction zone after a period of time, establishes potential tsunami source region seismicity
Parameter logistics tree；The main region of potential tsunami source region is Manila trench；
S2, tsunami unit source Green's function database is established using linear tsunami numerical simulation；
S3, the potential tsunami source region seismicity parameters logic tree according to foundation, using Monte Carlo stochastic simulation generate with
Machine seismic events collection；Wherein position, earthquake magnitude and the rupture process of each seismic events are random in Stochastic earthquake event set；
S4, according to tsunami unit source Green's function database and the Stochastic earthquake event set, simulate and give birth to using random slippage
At tsunami wave amplitude collection；Wherein, rupture slippage of each seismic events on each unit source is random；
S5, according to the tsunami wave amplitude collection, to multiple current Tsunami disaster distribution results statistics and to multiple current tsunami
The analysis of uncertainty of disaster distribution results.
2. the method according to claim 1, wherein the step S1 includes:
Using in a variety of focal shock parameter estimation methods maximum likelihood fit TGR relationship and seismic moment conservation theorem establish it is potential
The logic tree of the seismicity parameters of tsunami source region.
3. according to the method described in claim 2, it is characterized in that,
Using the magnitude parameter of TGR Relation acquisition tsunami source region, comprising:
The TGR relationship are as follows:
Wherein, M is seismic moment, MtIt is the complete Critical earthquake square of earthquake catalogue, McIt is corner seismic moment, β is the oblique of TGR relationship
Rate reflects the seismicity in region；F (M) is that seismic moment is greater than MtEarthquake incidence；
The approximation relation of seismic moment M and earthquake magnitude m is M=101.5m+C(2)；
The unit of M is ox rice, and C is constant；
Optimal parameter M is calculated with maximum likelihood functioncAnd β, maximum likelihood function are as follows:
Wherein, NeFor seismic moment MiGreater than Critical earthquake square MtEarthquake number；
Using the focal shock parameter estimation method of seismic moment conservation theorem, comprising:
It is indicated according to the seismic moment of geology parameter estimation are as follows: M=χ μ WLv (4)；
Wherein, χ is the earthquake coefficient of coup, and μ is rigidity modulus of shearing, and W is the underriding width of earthquake zone, and L is the length of tomography, v
For the Mean Speed of plate；
On the other hand, according to TGR relationship, seismic moment M are as follows:
Wherein,
atIt is greater than M for seismic momenttSeismic events year occurrence rate, Γ is gamma function, C1For constant；
In conjunction with formula (4) and formula (5), work as Mc> > MtWhen: obtain corner seismic moment Mc:
Obtaining corner seismic moment McAfterwards, corner earthquake magnitude is inferred to according to formula (2)；
The TGR relationship and seismic moment conservation theorem use different parameters to obtain multiple corner earthquake magnitude values, and combining global dives
Band TGR relationship, establishes potential tsunami source region seismicity parameters logic tree.
4. according to the method described in claim 3, it is characterized in that, before executing step S2, the method also includes:
S2a, tsunami source region is divided into the tsunami unit source that several equal in magnitude and slippages are 1 meter；Break in unit source
Layer geometric parameter is obtained by historical earthquake focal mechanism solution and related geology parameter evaluation method.
5. according to the method described in claim 3, it is characterized in that, the S3 includes:
According to the tsunami source parameter in the potential tsunami source region seismicity parameters logic tree, with linear tsunami Numerical-Mode
It is quasi- to calculate each tsunami source in the tsunami wave amplitude of assessment area；
Wherein, linear tsunami numerical model indicates are as follows:
In formula, η is the Free Surface displacement relative to mean sea level；For longitude；φ is latitude；R is earth radius；H is total
The depth of water；P is the flux along longitude unit width；Q is the flux along latitude unit width；F is Coriolis force coefficient；G adds for gravity
Speed；
Since tsunami progression is unsatisfactory for linear relationship in offshore, the tsunami wave amplitude being calculated needs to be converted to by Green's rule
The tsunami wave amplitude of offshore indicates are as follows:
Wherein AcFor the tsunami wave amplitude of offshore output point, HcFor the offshore output point depth of water, A0For the tsunami wave amplitude of offshore output point, H0
For the littoral output point depth of water.
6. according to the method described in claim 5, it is characterized in that, the S3 includes:
Using Monte Carlo stochastic simulation based on the logic tree established in S1, more sets are generated at random not within the scope of tsunami source region
Carry out the seismic events collection in certain period of time；
The seismic events that each independent seismic events is concentrated random distribution in tsunami source region, and each tsunami source
Earthquake magnitude-frequency relation of seismic events in area meets wherein one in TGR logic tree.
7. according to the method described in claim 6, it is characterized in that, the S4 includes:
For each of Stochastic earthquake event set seismic events, using earthquake magnitude-, rupture range formula is determining and delimits calculating
Unit source needed for tsunami wave amplitude；Earthquake magnitude-rupture range empirical equation indicates are as follows:
mw=4.868+1.392log10(L) (13)；
mw=4.441+0.846log10(A) (14)；
M in formulawFor magnitude, L is rupture length, and A is Strain energy, selectes the seismic events according to rupture length and area
Tsunami unit source needed for calculating；
The seismic events are generated at random in each list using the earthquake random breakage analogue technique based on von Karman function
Rupture slippage on the source of position；Each event is calculated in conjunction with tsunami unit source database to use in the maximum tsunami wave amplitude of assessment area
To generate maximum tsunami wave amplitude event set.
8. the method according to the description of claim 7 is characterized in that the S5 includes:
For some seismic events collection, it is assumed that there is NtA seismic sea wave source region contributes the tsunami risk of bank point, wherein n-th
A potential complications tsunami source region influences the outcross probability P of coastal waters bank site h tsunami wave amplitude Tn(H >=h), then site h tsunami
Wave amplitude T must outcross probability indicate are as follows:
Output point is released by (15) formula and reaches specified tsunami wave amplitude HhReturn period ThAre as follows:
For a certain specific Disaster Assessment output point O, (16) formula can be transferred through in specific return period T, N number of earthquake catalogue
Calculate the maximum tsunami wave amplitude h on the aspecti, then the maximum tsunami wave amplitude for output point O in return period T are as follows:
In addition, by maximum amplitude h caused by different earthquake catalogueiClassified statistic obtain different focal shock parameters to result
Influence degree.
9. a kind of multiple current Tsunami disaster based on Monte Carlo stochastic simulation assesses device, which is characterized in that including storage
Device, processor, bus and storage on a memory and the computer program that can run on a processor, the processor execution
It realizes when described program such as the step of claim 1-8 any one.
10. a kind of computer storage medium, is stored thereon with computer program, it is characterised in that: described program is held by processor
It realizes when row such as the step of claim 1-8 any one.
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