WO2016155484A1 - 海啸预测方法以及装置、海啸预警方法以及装置 - Google Patents

海啸预测方法以及装置、海啸预警方法以及装置 Download PDF

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Publication number
WO2016155484A1
WO2016155484A1 PCT/CN2016/076283 CN2016076283W WO2016155484A1 WO 2016155484 A1 WO2016155484 A1 WO 2016155484A1 CN 2016076283 W CN2016076283 W CN 2016076283W WO 2016155484 A1 WO2016155484 A1 WO 2016155484A1
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tsunami
arrival time
grid
propagation
candidate
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English (en)
French (fr)
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苏国锋
陈涛
袁宏永
吕栋亮
黄全义
陈建国
李志鹏
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Tsinghua University
Beijing Global Safety Technology Co Ltd
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Tsinghua University
Beijing Global Safety Technology Co Ltd
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Priority to MX2017012592A priority Critical patent/MX370244B/es
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather

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  • the present invention relates to a tsunami prediction method and apparatus, a tsunami warning method and apparatus, and more particularly to a tsunami prediction method and apparatus based on tsunami propagation time.
  • Tsunami usually causes heavy casualties and huge economic losses. Therefore, accurate prediction of the arrival time of the tsunami and timely warning based on the tsunami prediction results can effectively reduce economic losses and casualties.
  • the tsunami propagation process is usually analyzed by calculating the tsunami propagation time.
  • Grid data for ocean depth is required to calculate the tsunami propagation time.
  • Non-Patent Document 1 from the viewpoint of kinematics, it is considered that the propagation of the tsunami wave follows the Huygens principle. When the tsunami wave travels, every point on the wavefront can be considered a new point source.
  • ⁇ 1 , ⁇ 2 are longitude, It is latitude and R is the radius of the earth.
  • each grid has an N ⁇ N neighborhood, and the influence range of the grid on the wavefront as a wavelet source is its N ⁇ N neighbor. area. For the grid on the N ⁇ N neighborhood of the wavelet source, if the arrival time of the wavelet source is less than the original time of the grid, the time of the grid is replaced with a small time value.
  • Non-Patent Document 2 it is considered that the tsunami wave is a shallow water wave, satisfies the shallow water wave equation, and the shallow water wave equation is solved by the finite difference method, thereby calculating the propagation time of the tsunami.
  • Non-Patent Document 1 Shokin, Yu. I., Chubarov, LB, Novikov, VA, and Sudakov, AN: Calculations of Tsunami Travel Time Charts in the Pacific Ocean-Models, Algorithms, Techniques, Results, Sci. Tsunami Hazards, 5, 85 –122,1987.
  • Non-Patent Document 2 I.V.Fine and R.E.Thomson.A wavefront orientation method for precise numerical.determination of tsunami travel time.Nat.Hazards Earth Syst.Sci., 13, 2863–2870, 2013.
  • the present invention provides a rapid tsunami prediction method.
  • the tsunami prediction method can also be executed on a general small computer.
  • a first aspect of the present invention provides a tsunami prediction method, the method comprising: a data acquisition step of acquiring spatial data of a tsunami propagation region; a propagation time calculation step of calculating an interval between adjacent meshes according to the acquired data Propagating time and storing; an arrival time calculating step, obtaining an arrival time of each mesh in the candidate mesh group according to a propagation time between the adjacent meshes, according to each network in the candidate mesh group a minimum value of the arrival time of the grid, selecting a next wavelet source from the candidate grid group, thereby calculating an arrival time of the tsunami reaching each grid in the tsunami propagation region, wherein the candidate network
  • the set of cells is a set of meshes that may be used as wavelet sources; and an output step of outputting the arrival times of the respective meshes in the tsunami propagation area.
  • the present invention also provides a second aspect, which is the tsunami prediction method according to the first aspect, wherein, in the arrival time calculation step, the wavelet source is for each wavelet source The adjacent mesh is added to the candidate mesh group. After selecting the next wavelet source, the mesh that has been selected as the next wavelet source is deleted from the candidate mesh group, and the above operation is performed until the candidate mesh is selected. There are no grids in the group.
  • the present invention also provides a third aspect, which is the tsunami prediction method according to the first or second aspect, wherein, in the arrival time calculation step, selecting arrival in the candidate mesh group The grid with the smallest time is used as the next subwave source.
  • the present invention also provides a fourth aspect, which is the tsunami prediction method according to any one of the first to third aspects, wherein the arrival time calculation step includes: an initialization step, setting for storage a two-dimensional array of arrival times of all the grids in the tsunami propagation region, and initializing, initializing the arrival times of all the meshes except the epicenter into infinity values, and selecting the epicenter as the initial wavelet source;
  • the grid group adding step inserts the adjacent grid of the wavelet source into the candidate grid group, and reads the propagation time from the wavelet source to the adjacent grid stored in the propagation time calculation step;
  • the arrival time update Step when the arrival time of the adjacent mesh is greater than the sum of the arrival time of the wavelet source and the propagation time from the wavelet source to the adjacent mesh, updating the arrival time at the adjacent mesh to the sum value
  • the next step of selecting the source of the wave source selecting the grid with the smallest arrival time as the next wavelet source in the candidate grid group;
  • the step of updating the candidate grid group deleting the selected grid
  • the present invention also provides a fifth aspect, which is the tsunami prediction method according to any one of the first or the second aspect, wherein, in the arrival time calculation step, according to all adjacent grids The minimum value of the propagation time between the minimum and the minimum arrival time in the candidate grid group is selected as the next sub-wave source.
  • the present invention also provides a sixth aspect, which is the tsunami prediction method according to any one of the first, second, and fifth modes, wherein the arrival time calculation step includes: an initialization step, setting a two-dimensional array for storing the arrival times of all the grids in the tsunami propagation region, and initializing, initializing the arrival times of all the meshes except the epicenter to infinity values, and selecting the epicenter as the initial wavelet source a minimum calculation step of calculating a minimum value of propagation time between all adjacent meshes; a step of adding a candidate mesh group, the phase of the wavelet source The neighboring grid is placed in the candidate grid group, and the propagation time from the wavelet source to the adjacent grid stored in the propagation time calculation step is read; the arrival time update step is when the arrival time of the adjacent grid is greater than When the arrival time of the wavelet source and the sum of the propagation times from the wavelet source to the adjacent grid, the arrival time at the adjacent grid is updated to the sum value; the next wavelet source selection step, according to the Selecting multiple
  • the present invention also provides a seventh mode, which is the tsunami prediction method according to the sixth aspect, wherein, in the step of selecting the next wavelet source, the selection arrival time is less than between all adjacent meshes.
  • the grid of the sum of the minimum value of the propagation time and the minimum value of the arrival time in the candidate grid group is the next sub-wave source.
  • the present invention also provides an eighth mode, which is the tsunami prediction method according to the fourth or sixth aspect, wherein, in the to-be-selected mesh group adding step, only the adjacent network of the wavelet source is A grid of the grid located in the ocean and having an arrival time greater than the arrival time of the previous wavelet source is placed in the candidate grid group.
  • the present invention also provides a ninth aspect, which is the tsunami prediction method according to the first or second aspect, wherein, in the propagation time calculation step, when the wavelet source is located on land, the slave is made The propagation time of the wavelet source to the adjacent mesh is 0, or the propagation time from the wavelet source to the adjacent mesh when the wavelet source and any of its adjacent meshes are located on land Is 0.
  • a tenth aspect of the present invention provides a tsunami warning method, comprising: the tsunami prediction method according to any one of the first to ninth aspects; and an early warning step according to the tsunami prediction method
  • the output is an early warning of an area where the arrival time is less than a predetermined threshold.
  • An eleventh aspect of the present invention provides a tsunami prediction apparatus, comprising: a data acquisition unit that acquires spatial data of a tsunami propagation area; and a propagation time calculation unit that calculates an adjacent mesh based on the acquired data Time of propagation and storage; arrival time calculation, root Obtaining an arrival time of each mesh in the candidate mesh group according to a propagation time between the adjacent meshes, according to a minimum value of the arrival time of each mesh in the candidate mesh group, Selecting a next wavelet source in the selected grid group, thereby calculating an arrival time of each grid in the tsunami propagation region where the tsunami reaches, wherein the candidate grid group is a grid that may be a wavelet source And a set of outputs that output the arrival time of each of the grids in the tsunami propagation region.
  • the twelfth aspect is the tsunami prediction apparatus according to the eleventh aspect, wherein the arrival time calculation unit is adjacent to the sub-wave source for each sub-wave source After adding the candidate mesh group, after selecting the next wavelet source, the mesh that has been selected as the next wavelet source is deleted from the candidate mesh group, and the above operation is performed cyclically until there is no mesh in the candidate mesh group. .
  • the present invention also provides a thirteenth aspect, the tsunami prediction apparatus according to the eleventh or twelfth aspect, wherein the arrival time calculation section selects among the candidate mesh groups The grid with the smallest arrival time is used as the next subwave source.
  • the present invention further provides a tsunami prediction apparatus according to any one of the eleventh to thirteenth aspects, wherein the arrival time calculation unit includes: an initialization unit, Setting a two-dimensional array for storing the arrival times of all the grids in the tsunami propagation region, and initializing, initializing the arrival times of all the meshes except the epicenter to infinity values, and selecting the epicenter as the initial sub-object a wave source; a candidate mesh group adding portion, placing an adjacent mesh of the wavelet source into the candidate mesh group, and reading a propagation time from the wavelet source to the adjacent mesh stored in the propagation time calculation portion
  • the arrival time update unit updates the arrival time at the adjacent mesh to when the arrival time of the adjacent mesh is greater than the arrival time of the wavelet source and the propagation time from the wavelet source to the adjacent mesh
  • the next wavelet source selecting unit selects, in the candidate mesh group, a mesh with the smallest arrival time as the next sub-wave source; the candidate mesh group update unit deletes the selected mesh group.
  • the present invention also provides a fifteenth aspect, the tsunami prediction apparatus according to any one of the eleventh or twelfth aspect, wherein the arrival time calculation section is based on all adjacent networks The minimum value of the propagation time between the cells and the minimum of the arrival time in the candidate mesh group, Select multiple meshes as the next wavelet source.
  • the present invention also provides a sixteenth aspect, the tsunami prediction apparatus according to any one of the eleventh, twelfth, and fifteenth aspects, wherein the arrival time calculation section includes : an initialization unit that sets a two-dimensional array for storing arrival times of all the meshes in the tsunami propagation region, and initializes, initializes arrival times of all meshes except the epicenter to infinity values, and selects an epicenter An initial wavelet source; a minimum value calculation unit that calculates a minimum value of the propagation time between all adjacent meshes; a candidate mesh group adding portion, the adjacent mesh of the wavelet source is placed in the candidate network In the cell group, the propagation time from the wavelet source to the adjacent mesh stored in the propagation time calculation section is read; the arrival time update section, when the arrival time of the adjacent mesh is greater than the arrival time of the wavelet source and from the wavelet source to When the sum of the propagation times of the adjacent meshes is updated, the arrival time at the adjacent mesh is updated to the sum value; the next wavelet
  • the present invention also provides a seventeenth aspect, the tsunami prediction apparatus according to the sixteenth aspect, wherein the next sub-wave source selection unit selects an arrival time less than between all adjacent grids
  • the grid of the sum of the minimum value of the propagation time and the minimum value of the arrival time in the candidate grid group is the next sub-wave source.
  • the present invention also provides an eighteenth aspect, the tsunami prediction apparatus according to the fourteenth or sixteenth aspect, wherein the candidate mesh group adding section only adjacent to the wavelet source A grid of the grid located in the ocean and having an arrival time greater than the arrival time of the previous wavelet source is placed in the candidate grid group.
  • the tsunami prediction device according to the eleventh or twelfth aspect, wherein the propagation time calculation unit makes the subwave source located on land The propagation time from the wavelet source to the adjacent mesh is 0, or the propagation from the wavelet source to the adjacent mesh when the wavelet source and any of its adjacent meshes are located on land The time is 0.
  • a twentieth aspect of the present invention provides a tsunami early warning device, comprising: the tsunami prediction device according to any one of the eleventh to nineteenth aspects; and an early warning unit according to the tsunami prediction The output of the device issues an early warning to an area where the arrival time is less than a predetermined threshold.
  • a twenty-first aspect of the present invention provides a tsunami prediction apparatus, comprising: a processor; and a memory for storing instructions executable by the processor, wherein the processor is configured to: acquire tsunami propagation The spatial data of the region; according to the acquired data, calculating the propagation time between the adjacent meshes and storing; according to the propagation time between the adjacent meshes, obtaining the meshes in the candidate mesh group Arrival time, selecting a next wavelet source from the candidate mesh group according to a minimum value of arrival times of each mesh in the candidate mesh group, thereby calculating a tsunami reaching the tsunami propagation region
  • the arrival time of each grid, wherein the candidate grid group is a set of grids that may be the wavelet source; the arrival time of each grid in the tsunami propagation region is output.
  • a twenty-second aspect of the present invention provides a tsunami prediction apparatus, comprising: an input unit for inputting spatial data of a tsunami propagation area; and a storage unit for storing a propagation time between adjacent grids; And a processor, the processor further comprising: a propagation time calculation unit that calculates a propagation time between adjacent meshes based on the input spatial data and stores the same in the storage unit; and an arrival time calculation unit according to the phase Obtaining time between neighboring grids, obtaining an arrival time of each grid in the candidate grid group, according to a minimum value of arrival times of each grid in the candidate grid group, from the candidate network Selecting a next subwave source in the cell group to calculate an arrival time of the tsunami reaching each of the tsunami propagation regions, wherein the candidate mesh group is a set of meshes that may be the wavelet source; The output unit outputs the arrival time of each of the meshes in the tsunami propagation region.
  • a twenty-third mode embodiment of the present invention provides a tsunami prediction program that causes a computer to perform operations of acquiring spatial data of a tsunami propagation region and calculating propagation between adjacent meshes based on the acquired data And storing time according to the propagation time between the adjacent grids, obtaining an arrival time of each grid in the candidate grid group, according to a minimum arrival time of each grid in the candidate grid group a value, selecting a next wavelet source from the candidate mesh group, thereby calculating an arrival time of the tsunami reaching each grid in the tsunami propagation region, where
  • the candidate mesh group is a set of meshes that may be used as wavelet sources; and the arrival time of each mesh in the tsunami propagation region is output.
  • a storage medium storing a tsunami prediction program according to a twenty-fourth aspect of the present invention the program causing a computer to perform the following operations: acquiring spatial data of a tsunami propagation area; and calculating an adjacent network according to the acquired data The propagation time between the cells is stored; according to the propagation time between the adjacent meshes, the arrival time of each mesh in the candidate mesh group is obtained, according to each mesh in the candidate mesh group a minimum value of the arrival time, selecting a next wavelet source from the candidate mesh group, thereby calculating an arrival time of the tsunami reaching each of the tsunami propagation regions, wherein the candidate mesh A group is a collection of grids that may be sourced as wavelets; the arrival time of each grid in the tsunami propagation region is output.
  • the arrival time of the tsunami reaching each grid can be quickly obtained. That is, the prediction of the tsunami can be performed quickly. Thus, it can provide a basis for timely warning.
  • the tsunami warning method and apparatus provided according to the present invention can promptly issue an early warning to an area where a tsunami may arrive.
  • people in areas that may be affected can quickly respond to disasters.
  • it can reduce casualties and economic losses.
  • the tsunami prediction method and apparatus the tsunami warning method, and the apparatus provided by the present invention have a simple structure and a small amount of calculation. Therefore, it can be applied to a general small computer. It can reduce the cost of the disaster response part.
  • FIG. 1 is a block diagram showing a main configuration of a tsunami prediction device according to a first embodiment of the present invention
  • FIG. 2 is a view showing a main flow of a tsunami prediction method according to the first embodiment of the present invention
  • FIG. 3 is a block diagram showing a main configuration of a propagation time calculation module
  • Figure 5 is a schematic diagram showing the propagation of a tsunami in a neighborhood
  • FIG. 6 is a block diagram showing a main configuration of an arrival time calculation module according to Embodiment 1;
  • FIG. 7 is a flow chart showing specific steps of calculating an arrival time according to Embodiment 1;
  • FIG. 8 is a block diagram showing a main configuration of an arrival time calculation module according to Embodiment 2;
  • Figure 10 is a diagram showing the results of predicting the Chilean tsunami propagation time on April 2, 2014 based on the present invention.
  • FIG. 11 is a block diagram showing a main configuration of a tsunami early warning device according to a second embodiment
  • FIG. 12 is a view showing a main flow of the tsunami warning method according to the second embodiment.
  • Figure 13 is a block diagram of the internal components of the processing device.
  • the tsunami prediction apparatus 1 of the present invention includes a data acquisition unit 101, a propagation time calculation unit 102, an arrival time calculation unit 103, and an output unit 104.
  • the tsunami prediction method of the present invention includes a data acquisition step S101, a propagation time calculation step S102, an arrival time calculation step S103, and an output step S104.
  • the data acquisition section 101 acquires spatial data of the tsunami propagation area.
  • the spatial data of the tsunami propagation area refers to the data of the longitude, latitude, and depth of the tsunami propagation area.
  • spatial data of the area where the tsunami may spread ie, the tsunami propagation area
  • Longitude ⁇ latitude Depth or elevation z.
  • This spatial data can be given as a raster file or as a text document. Among them, the unit of meridian and latitude is the decimal system, and the unit of depth or elevation is meter.
  • the z value is greater than or equal to 0, and if the grid is in the ocean, the z value is less than zero. Due to the huge amount of ocean elevation data, it has a great impact on the operation. Therefore, spatial data can be performed Simplify processing and reduce the spatial resolution of your data. By simplifying spatial data, tsunami predictions can be performed on ordinary small computers.
  • the number of rows and the number of columns of the grid data of the tsunami propagation region are respectively row and column.
  • the propagation time calculation unit 102 calculates and stores the propagation time between adjacent meshes based on the acquired data.
  • an existing method may be employed, or a calculation method described later using FIG. 2 may be employed.
  • the propagation time is the time during which the tsunami propagates between two adjacent grid points.
  • the arrival time calculation section 103 obtains the arrival times of the respective meshes in the candidate mesh group based on the propagation time between the adjacent meshes stored in step S102, according to Selecting the minimum arrival time of each grid in the grid group, selecting the next wavelet source from the candidate grid group, thereby calculating the arrival time of the tsunami reaching each grid in the tsunami propagation region.
  • the candidate mesh group is a set of meshes that may be used as a wavelet source, and the arrival time refers to the time when the tsunami reaches the mesh from the source.
  • step S103 the arrival time calculation unit 103 adds the adjacent mesh of the wavelet source to the candidate mesh group for each wavelet source, and selects the selected mesh group after selecting the next wavelet source according to the above operation.
  • the mesh that has been selected as the next sub-wave source is deleted, and the above operation is performed cyclically until there is no mesh in the candidate mesh group, thereby calculating the arrival time of the tsunami reaching each mesh in the tsunami propagation region.
  • the output unit 104 outputs the arrival time of each mesh in the tsunami propagation region.
  • the output may be output to an external storage device, an analysis device, an early warning device, a display device, a printing device, or the like.
  • the form of the output can be display, print, storage, and the like.
  • the output can be a table or a graph. For example, as shown in FIG. 10, in a geographic information system GIS, an electronic map, or the like, it is presented by a contour line of arrival time.
  • propagation time calculation step S102 executed by the propagation time calculation unit 102 will be described in detail with reference to FIGS. 3 and 4.
  • the propagation time calculation unit 102 includes a distance calculation unit 1021 and a speed calculation.
  • the step S102 further includes: step S1021, calculating a distance between adjacent grids; step S1022, calculating a propagation speed of the tsunami wave along each grid; and step S1023, according to the distance and the propagation Speed, calculating the propagation time; and step S1024, storing propagation time data between the adjacent grids.
  • the distance calculating unit 1021 can calculate the arbitrary mesh O in the tsunami propagation region to the point p 1 , p 2 in the neighborhood using the distance formula (1) between any two points on the earth. , ..., the distance ⁇ (O, p i ) between p 16 .
  • the speed calculation unit 1022 may specifically approximate the relationship between the tsunami propagation speed and the ocean depth. Determine the speed at which the tsunami wave travels on each grid.
  • step S1023 the time calculating portion 1023 calculates the propagation time between the mesh O and the mesh in the neighborhood.
  • the time calculation unit 1023 may further perform the following operations: if the elevation of the O point is greater than 0, the propagation time of the O point to the surrounding 16 points is 0; if the O and the grid in the neighborhood have an elevation greater than 0, also let the propagation time between them be 0.
  • the propagation time storage unit 1024 can store the propagation time between adjacent meshes as new basic data.
  • the grid with 4 ⁇ 4 neighborhood in the elevation data has nrow-2 rows and ncolumn-2 columns, and the propagation time of each grid point to 16 grid points in its neighborhood can be stored.
  • the arrival time calculation unit 103 includes an initialization unit 1031, a candidate mesh group addition unit 1032, an arrival time update unit 1033, a next wavelet source selection unit 1034, and a candidate network.
  • the group update unit 1035 includes an initialization unit 1031, a candidate mesh group addition unit 1032, an arrival time update unit 1033, a next wavelet source selection unit 1034, and a candidate network.
  • the group update unit 1035 includes an initialization unit 1031, a candidate mesh group addition unit 1032, an arrival time update unit 1033, a next wavelet source selection unit 1034, and a candidate network.
  • Embodiment 1 for calculating the arrival time of each grid in which the tsunami reaches the tsunami propagation region will be described with reference to FIG.
  • the step S103 includes an initializing step S1031, a candidate mesh group adding step S1032, an arrival time updating step S1033, a next wavelet source selecting step S1034, and a candidate mesh group updating step S1035.
  • the initialization section 1031 sets a two-dimensional array for storing the arrival times of all the grids in the tsunami propagation area, and initializes them.
  • the number of rows and columns of the two-dimensional array are row and column, respectively.
  • the corresponding element of the epicenter can be initialized to 0(s), and other elements are initialized to infinity values. For example, it can be set to 10 ⁇ 8(s), and the epicenter is the initial wavelet source.
  • the candidate mesh group adding unit 1032 puts the adjacent mesh of the wavelet source into the candidate mesh group list, and reads and stores it in the step S102 (transfer time) The propagation time from the wavelet source to the adjacent mesh calculated and stored by the calculation unit 102.
  • a mesh that is a wavelet source of this step and a mesh adjacent to the wavelet source, that is, the wavelet source may be read in the propagation time between adjacent meshes stored in the step S1024 ( The propagation time between 16 grids p 1 , p 2 , ..., p 16 in the 4 ⁇ 4 neighborhood of i, j).
  • the tsunami wave will not spread. That is, the tsunami only spreads in the ocean. Therefore, only the grid with the elevation z less than 0 can be placed in the candidate grid group.
  • the mesh has not been placed in the candidate mesh group by the current arrival time t 0 being greater than the arrival time min 0 of the previous wavelet source.
  • the candidate set of the mesh portion 1032 may add only the wavelet source being located adjacent mesh ocean (z ⁇ 0) and the current time is greater than the arrival time of arrival of the wave source of the sub-step t 0>
  • the grid of min 0 is placed in the candidate grid group.
  • the arrival time update unit 1033 has the original arrival time t 0 of the adjacent mesh p k greater than the arrival time min 1 of the wavelet source (i, j) and the slave wavelet source to the adjacent network.
  • next sub-wave source selection unit 1034 is waiting Select the grid with the smallest arrival time as the next subwave source in the grid group list.
  • the candidate mesh group update unit 1035 deletes the mesh that has been selected as the next wavelet source from the candidate mesh group list.
  • the steps S1032 to S1034 are repeatedly performed.
  • the tsunami prediction method by selecting a mesh having the smallest arrival time from the candidate mesh group as the next wave source, it is possible to quickly obtain the arrival of the tsunami reaching each mesh. Time can quickly predict the tsunami propagation process and provide a basis for timely warning.
  • Embodiment 2 in which the arrival time of each grid of the tsunami reaching the tsunami propagation region is calculated will be described with reference to FIGS. 8 and 9.
  • next wavelet source selecting unit 1034 in the first embodiment is replaced by the next wavelet source selecting unit 1034', and may further include a minimum value calculating unit 1030, and other configurations and Example 1 is the same.
  • the step S103 includes the next sub-wave source selection step S1034' to replace the next sub-wave source selection step S1034 in the embodiment 1, and may further include a minimum value calculation step S1030, and other steps and the embodiment 1 the same.
  • the minimum value calculation portion 1030 calculates the minimum value ⁇ t min of the propagation time between all adjacent meshes, and outputs it to the next wavelet source selection portion 1034'.
  • the minimum value calculation step S1030 is located after the initialization step S1031, however, the minimum value calculation step S1030 may also be located before the step S1031.
  • the minimum value of the propagation time between all adjacent grids may be calculated by other modules and stored, and in the next wavelet source selection step S1034', the next wavelet source selection section 1034' directly utilizes the minimum value ⁇ t min . That is, the step S103 may not include the minimum value calculation step 1030, which may be omitted. That is, the arrival time calculation unit 103 of the present invention may not include the minimum value calculation step 1030, and the minimum value calculation step 1030 may be omitted.
  • next step S1034 wavelet source select ' the next step wavelet source select unit 1034' according to the arrival time of a minimum value t min of the minimum propagation time ⁇ t min between all adjacent mesh and the mesh to be selected in the group, Select multiple meshes as the next wavelet source.
  • the next wavelet source selecting section 1034' selects the minimum value ⁇ t min of the propagation time less than the propagation time between all the adjacent meshes and the arrival time in the candidate mesh group.
  • the grid of the sum of the minimum values t min is the next subwave source. That is, for any mesh p k in the candidate mesh group (1 ⁇ k ⁇ n, where n is the length of the list), if the arrival time at the grid p k Then select the grid as the next wavelet source.
  • the steps S1032 to S1033, S1034', and S1035 are repeatedly executed.
  • Embodiment 2 by selecting a batch of mesh having a smaller arrival time from the candidate mesh group as the next wave source, in addition to the same effect as Embodiment 1, there is convergence. Quick advantage. That is, the calculation speed can be further increased. At the same time, the introduction of cumulative errors is avoided.
  • the invention can be implemented by a tsunami warning device and a tsunami warning method.
  • the tsunami early warning device 2 includes an early warning unit 105 in addition to the tsunami prediction device 1 of the first embodiment.
  • the tsunami warning method according to the second embodiment further includes an early warning step S105 in addition to the tsunami prediction method of the first embodiment.
  • the early warning unit 105 issues an early warning to the area where the arrival time is less than the predetermined threshold value based on the output result of the output step S104 of the tsunami prediction method (the output result of the output unit 104).
  • a contour line may be drawn according to the arrival time, an early warning line may be generated according to a predetermined threshold value, and an early warning may be issued to an area in which the contour line is located in the warning line.
  • the second embodiment it is possible to issue an early warning to the area where the tsunami may arrive, so that people in the affected area can respond to the disaster in time, thereby reducing casualties and economic losses.
  • FIG. 13 is a block diagram of internal components of a processing device, which can Is a workstation, for example, the processing device comprises a bus 409, the connection structure on the bus is as follows: the processing device comprises a processor 405, the processor 405 is a very large-scale integrated circuit, is the computing core of a computer And control core. Its function is mainly to explain computer instructions and to process data in computer software.
  • Processor 405 primarily includes an arithmetic unit and cache 406 and a bus that implements the data, control, and status of the connections between them.
  • the processing device further includes a memory, and the memory in the computer can be divided into a main memory (memory) according to the use, for example, a ROM (Read Only Memory image) 403, a RAM (Random Access Memory) 404, and an auxiliary device.
  • the memory has a memory space for program code for performing any of the method steps described above.
  • the storage space for the program code may include various program codes for implementing the various steps in the above methods, respectively.
  • the program code can be read from or written to one or more computer program products.
  • These computer program products include program code carriers such as a hard disk, a compact disk (CD), a memory card, or a floppy disk. Such computer program products are typically portable or fixed storage units.
  • the storage unit may have a storage section, a storage space, and the like arranged similarly to the memory in the terminal described above.
  • the program code for performing any of the above method steps can also be downloaded over the network.
  • the program code can be compressed, for example, in an appropriate form.
  • a storage unit includes computer readable code, ie, code that can be read by a processor, such as, when run by a search engine program on a server, causing the server to perform various steps in the methods described above.
  • the processing device includes at least one input device 401 for interaction between the user and the processing device, and the input device 401 can be a keyboard, a mouse, an image capturing component, a gravity sensor, a sound receiving component, a touch screen, etc.; Including at least one output device 408, the output device 408 can be a speaker, a buzzer, a flash, an image projection unit, a vibration output component, a screen or a touch screen, etc.; the processing device can also include a communication interface for data communication in a wired or wireless manner. 407.

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Abstract

一种海啸预测方法以及装置、海啸预警方法以及装置。该海啸预测方法包括：数据获取步骤（S101），获取海啸传播区域的空间数据；传播时间计算步骤（S102），根据所获取的数据，计算出相邻网格之间的传播时间并存储；到达时间计算步骤（S103），根据相邻网格之间的传播时间，获得待选网格组中的各网格的到达时间，根据待选网格组中的各网格的到达时间的最小值，从待选网格组中选择下一步子波源，从而计算出海啸到达海啸传播区域中的每个网格的到达时间，其中，待选网格组是可能作为子波源的网格的集合；以及输出步骤（S104），输出海啸传播区域中的各网格的到达时间。从而能够进行快速的海啸预测、预警。

Description

海啸预测方法以及装置、海啸预警方法以及装置 技术领域
本发明涉及海啸预测方法以及装置、海啸预警方法以及装置，尤其涉及基于海啸传播时间的海啸预测方法以及装置。
背景技术
海啸通常会造成惨重的人员伤亡和巨大的经济损失。因此，对海啸的到达时间进行准确的预测，并基于海啸预测结果进行及时的预警，可以有效地降低经济损失和人员伤亡。
当前，通常，通过计算海啸传播时间来分析海啸的传播过程。计算海啸传播时间时需要用到海洋深度的网格数据。
在非专利文献1中，从运动学的角度进行了考虑，认为海啸波的传播遵循惠更斯原理。当海啸波行进时，波前上的每一点都可视为新的点波源。
海啸波在大洋中的传播速度近似为
Figure PCTCN2016076283-appb-000001
地球上任两点
Figure PCTCN2016076283-appb-000002
Figure PCTCN2016076283-appb-000003
间的距离公式为：
Figure PCTCN2016076283-appb-000004
其中θ1，θ2是经度，
Figure PCTCN2016076283-appb-000005
是纬度，R是地球半径。
设O是子波源，A是O邻域上的网格，那么O到格点A的传播时间为
Figure PCTCN2016076283-appb-000006
从而可以计算出子波源到其邻域任意网格上的传播时间。
由于海洋深度数据为矩形网格形式，在这种数据格式下，每个网格都有一个N×N邻域，假定波前上的网格作为子波源的影响范围是它的N×N邻域。对于子波源N×N邻域上的网格，如果经子波源的到达的时间小于该网格原来的时间，那么用小的时间值替代该网格的时间。
在非专利文献2中，认为海啸波是浅水波，满足浅水波方程，通过有限差分方法求解浅水波方程，由此计算出了海啸的传播时间。
非专利文献1：Shokin,Yu.I.,Chubarov,L.B.,Novikov,V.A.,and Sudakov,A.N.:Calculations of Tsunami Travel Time Charts in the PacificOcean–Models,Algorithms,Techniques,Results,Sci.TsunamiHazards,5,85–122,1987.
非专利文献2：I.V.Fine and R.E.Thomson.A wavefront orientation method for precise numerical.determination of tsunami travel time.Nat.Hazards Earth Syst.Sci.,13,2863–2870,2013.
发明内容
然而，由于用于预测海啸的基础数据非常庞大、而且目前用于计算海啸的到达时间的方法比较复杂，运算量非常大，因此需要很长的计算时间。从而，虽然可以用于海啸的事后分析，但是很难在海上发生地震之后马上用于进行海啸的预测。另外，难以在普通的小型计算机上进行海啸预测。也就是说，无法满足应对灾害的有关部门快速地预测海啸的传播并及时发布预警信息的需求。另外，灾害应对相关部门需要配备大型的、专用的计算设备，要求投入较大的成本。
因此，本发明提供一种快速的海啸预测方法。该海啸预测方法还能够在普通的小型计算机上执行。
本发明的第一方式提供了一种海啸预测方法，该方法包括：数据获取步骤，获取海啸传播区域的空间数据；传播时间计算步骤，根据所获取的数据，计算出相邻网格之间的传播时间并存储；到达时间计算步骤，根据所述相邻网格之间的传播时间，获得待选网格组中的各网格的到达时间，根据所述待选网格组中的各网格的到达时间的最小值，从所述待选网格组中选择下一步子波源，从而计算出海啸到达所述海啸传播区域中的每个网格的到达时间，其中，所述待选网格组是可能作为子波源的网格的集合；以及输出步骤，输出所述海啸传播区域中的各网格的所述到达时间。
本发明还提供了第二方式，该第二方式是如第一方式所述的海啸预测方法，其中，在所述到达时间计算步骤中，针对每个子波源，将该子波源 的相邻网格加入待选网格组中，在选择下一步子波源之后，从待选网格组中删除已经被选为下一步子波源的网格，循环执行上述操作直到待选网格组中没有网格。
本发明还提供了第三方式，该第三方式是如第一或第二方式所述的海啸预测方法，其中，在所述到达时间计算步骤中，在所述待选网格组中选择到达时间最小的网格作为下一步子波源。
本发明还提供了第四方式，该第四方式是如第一至第三方式中的任一方式所述的海啸预测方法，其中，所述到达时间计算步骤包括：初始化步骤，设置用于存储所述海啸传播区域中的所有网格的到达时间的二维数组，并进行初始化，将除了震中以外的所有网格的到达时间初始化为无穷大的值，且选择震中为初始的子波源；待选网格组添加步骤，将子波源的相邻网格放入所述待选网格组中，读入在传播时间计算步骤中存储的从子波源到相邻网格的传播时间；到达时间更新步骤，当相邻网格的到达时间大于子波源的到达时间和从子波源到该相邻网格的传播时间的和值时，将该相邻网格处的到达时间更新为所述和值；下一步子波源选取步骤，在所述待选网格组中选择到达时间最小的网格作为下一步子波源；待选网格组更新步骤，从待选网格组中删除已经被选为下一步子波源的网格；当待选网格组的个数为1以上时，重复执行所述待选网格组添加步骤、到达时间更新步骤、下一步子波源选取步骤、待选网格组更新步骤。
本发明还提供了第五方式，该第五方式是如第一或第二方式中的任一方式所述的海啸预测方法，其中，在所述到达时间计算步骤中，根据所有相邻网格之间的传播时间的最小值和待选网格组中的到达时间的最小值，选择多个网格作为下一步子波源。
本发明还提供了第六方式，该第六方式是如第一、第二、第五方式中的任一方式所述的海啸预测方法，其中，所述到达时间计算步骤包括：初始化步骤，设置用于存储所述海啸传播区域中的所有网格的到达时间的二维数组，并进行初始化，将除了震中以外的所有网格的到达时间初始化为无穷大的值，且选择震中为初始的子波源；最小值计算步骤，计算所有相邻网格之间的传播时间的最小值；待选网格组添加步骤，将该子波源的相 邻网格放入所述待选网格组中，读入在传播时间计算步骤中存储的从子波源到相邻网格的传播时间；到达时间更新步骤，当相邻网格的到达时间大于子波源的到达时间和从子波源到该相邻网格的传播时间的和值时，将该相邻网格处的到达时间更新为所述和值；下一步子波源选取步骤，根据所述所有相邻网格之间的传播时间的最小值和待选网格组中的到达时间的最小值，选择多个网格作为下一步子波源；待选网格组更新步骤，从待选网格组中删除已经被选为下一步子波源的网格；当待选网格组的个数为1以上时，重复执行所述待选网格组添加步骤、到达时间更新步骤、下一步子波源选取步骤、待选网格组更新步骤。
本发明还提供了第七方式，该第七方式是如第六方式所述的海啸预测方法，其中，在所述下一步子波源选取步骤中，选择到达时间小于所有相邻网格之间的传播时间的最小值和待选网格组中的到达时间的最小值的和值的网格为下一步子波源。
本发明还提供了第八方式，该第八方式是如第四或第六方式所述的海啸预测方法，其中，在所述待选网格组添加步骤中，仅将子波源的相邻网格之中位于海洋且到达时间大于上一步子波源的到达时间的网格放入待选网格组中。
本发明还提供了第九方式，该第九方式是如第一或第二方式所述的海啸预测方法，其中，在所述传播时间计算步骤中，当所述子波源位于陆地时，使从该子波源到相邻网格的传播时间均为0，或者，当所述子波源及其相邻网格中的任意一个位于陆地时，使从该子波源到该相邻网格的传播时间为0。
本发明的第十方式提供了一种海啸预警方法，其特征在于，包括：第一方式至第九方式中的任一项所述的海啸预测方法；以及预警步骤，根据所述海啸预测方法的输出结果，对到达时间小于预定的阈值的区域发出预警。
本发明的第十一方式提供了一种海啸预测装置，其特征在于，包括：数据获取部，获取海啸传播区域的空间数据；传播时间计算部，根据所获取的数据，计算出相邻网格之间的传播时间并存储；到达时间计算部，根 据所述相邻网格之间的传播时间，获得待选网格组中的各网格的到达时间，根据所述待选网格组中的各网格的到达时间的最小值，从所述待选网格组中选择下一步子波源，从而计算出海啸到达所述海啸传播区域中的每个网格的到达时间，其中，所述待选网格组是可能作为子波源的网格的集合；以及输出部，输出所述海啸传播区域中的各网格的所述到达时间。
本发明还提供了第十二方式，该第十二方式是如第十一方式所述的海啸预测装置，其中，所述到达时间计算部针对每个子波源，将该子波源的相邻网格加入待选网格组中，在选择下一步子波源之后，从待选网格组中删除已经被选为下一步子波源的网格，循环执行上述操作直到待选网格组中没有网格。
本发明还提供了第十三方式，该第十三方式是如第十一或第十二方式所述的海啸预测装置，其中，所述到达时间计算部在所述待选网格组中选择到达时间最小的网格作为下一步子波源。
本发明还提供了第十四方式，该第十四方式是如第十一至第十三方式中的任一方式所述的海啸预测装置，其中，所述到达时间计算部包括：初始化部，设置用于存储所述海啸传播区域中的所有网格的到达时间的二维数组，并进行初始化，将除了震中以外的所有网格的到达时间初始化为无穷大的值，且选择震中为初始的子波源；待选网格组添加部，将子波源的相邻网格放入所述待选网格组中，读入在传播时间计算部中存储的从子波源到相邻网格的传播时间；到达时间更新部，当相邻网格的到达时间大于子波源的到达时间和从子波源到该相邻网格的传播时间的和值时，将该相邻网格处的到达时间更新为所述和值；下一步子波源选取部，在所述待选网格组中选择到达时间最小的网格作为下一步子波源；待选网格组更新部，从待选网格组中删除已经被选为下一步子波源的网格；当待选网格组的个数为1以上时，使所述待选网格组添加部、到达时间更新部、下一步子波源选取部、待选网格组更新部重复动作。
本发明还提供了第十五方式，该第十五方式是如第十一或第十二方式中的任一方式所述的海啸预测装置，其中，所述到达时间计算部根据所有相邻网格之间的传播时间的最小值和待选网格组中的到达时间的最小值， 选择多个网格作为下一步子波源。
本发明还提供了第十六方式，该第十六方式是如第十一、第十二、第十五方式中的任一方式所述的海啸预测装置，其中，所述到达时间计算部包括：初始化部，设置用于存储所述海啸传播区域中的所有网格的到达时间的二维数组，并进行初始化，将除了震中以外的所有网格的到达时间初始化为无穷大的值，且选择震中为初始的子波源；最小值计算部，计算所有相邻网格之间的传播时间的最小值；待选网格组添加部，将该子波源的相邻网格放入所述待选网格组中，读入在传播时间计算部中存储的从子波源到相邻网格的传播时间；到达时间更新部，当相邻网格的到达时间大于子波源的到达时间和从子波源到该相邻网格的传播时间的和值时，将该相邻网格处的到达时间更新为所述和值；下一步子波源选取部，根据所述所有相邻网格之间的传播时间的最小值和待选网格组中的到达时间的最小值，选择多个网格作为下一步子波源；待选网格组更新部，从待选网格组中删除已经被选为下一步子波源的网格；当待选网格组的个数为1以上时，使所述待选网格组添加部、到达时间更新部、下一步子波源选取部、待选网格组更新部重复动作。
本发明还提供了第十七方式，该第十七方式是如第十六方式所述的海啸预测装置，其中，所述下一步子波源选取部选择到达时间小于所有相邻网格之间的传播时间的最小值和待选网格组中的到达时间的最小值的和值的网格为下一步子波源。
本发明还提供了第十八方式，该第十八方式是如第十四或第十六方式所述的海啸预测装置，其中，所述待选网格组添加部仅将子波源的相邻网格之中位于海洋且到达时间大于上一步子波源的到达时间的网格放入待选网格组中。
本发明还提供了第十九方式，该第十九方式是如第十一或第十二方式所述的海啸预测装置，其中，所述传播时间计算部在所述子波源位于陆地时，使从该子波源到相邻网格的传播时间均为0，或者，在所述子波源及其相邻网格中的任意一个位于陆地时，使从该子波源到该相邻网格的传播时间为0。
本发明的第二十方式提供一种海啸预警装置，其特征在于，包括：第十一方式至第十九方式中的任一项所述的海啸预测装置；以及预警部，根据所述海啸预测装置的输出结果，对到达时间小于预定的阈值的区域发出预警。
本发明的第二十一方式提供一种海啸预测装置，其特征在于，包括：处理器；以及用于存储处理器可执行的指令的存储器，其中，所述处理器被配置为：获取海啸传播区域的空间数据；根据所获取的数据，计算出相邻网格之间的传播时间并存储；根据所述相邻网格之间的传播时间，获得待选网格组中的各网格的到达时间，根据所述待选网格组中的各网格的到达时间的最小值，从所述待选网格组中选择下一步子波源，从而计算出海啸到达所述海啸传播区域中的每个网格的到达时间，其中，所述待选网格组是可能作为子波源的网格的集合；输出所述海啸传播区域中的各网格的所述到达时间。
本发明的第二十二方式提供一种海啸预测装置，其特征在于，包括：输入部，用于输入海啸传播区域的空间数据；存储部，用于存储相邻网格之间的传播时间；以及处理器，所述处理器还包括：传播时间计算部，根据所输入的空间数据，计算出相邻网格之间的传播时间并存储到存储部中；到达时间计算部，根据所述相邻网格之间的传播时间，获得待选网格组中的各网格的到达时间，根据所述待选网格组中的各网格的到达时间的最小值，从所述待选网格组中选择下一步子波源，从而计算出海啸到达所述海啸传播区域中的每个网格的到达时间，其中，所述待选网格组是可能作为子波源的网格的集合；以及输出部，输出所述海啸传播区域中的各网格的所述到达时间。
本发明的第二十三方式实施方式提供一种海啸预测程序，所述程序使得计算机执行如下操作：获取海啸传播区域的空间数据；根据所获取的数据，计算出相邻网格之间的传播时间并存储；根据所述相邻网格之间的传播时间，获得待选网格组中的各网格的到达时间，根据所述待选网格组中的各网格的到达时间的最小值，从所述待选网格组中选择下一步子波源，从而计算出海啸到达所述海啸传播区域中的每个网格的到达时间，其中， 所述待选网格组是可能作为子波源的网格的集合；输出所述海啸传播区域中的各网格的所述到达时间。
本发明的第二十四方式实施方式所提供的存储有海啸预测程序的存储介质，所述程序使得计算机执行如下操作：获取海啸传播区域的空间数据；根据所获取的数据，计算出相邻网格之间的传播时间并存储；根据所述相邻网格之间的传播时间，获得待选网格组中的各网格的到达时间，根据所述待选网格组中的各网格的到达时间的最小值，从所述待选网格组中选择下一步子波源，从而计算出海啸到达所述海啸传播区域中的每个网格的到达时间，其中，所述待选网格组是可能作为子波源的网格的集合；输出所述海啸传播区域中的各网格的所述到达时间。
根据本发明所提供的海啸预测方法和装置，能够快速地获得海啸到达每个网格的到达时间。即，能够快速地进行海啸的预测。从而，能够为及时的预警提供基础。
根据本发明所提供的海啸预警方法和装置，能够对海啸可能到达的区域及时地发出预警。从而，使得可能受灾的区域的人们能够迅速应对灾害。并且，能够减少人员伤亡和经济损失。
另外，本发明所提供的海啸预测方法以及装置、海啸预警方法以及装置结构简单，运算量小。从而，能够在普通的小型计算机上应用。能够降低灾害应对部分的成本。
附图说明
图1是示出本发明的第一实施方式所涉及的海啸预测装置的主要构成的框图；
图2是示出本发明的第一实施方式所涉及的海啸预测方法的主要流程的图；
图3是示出传播时间计算模块的主要构成的框图；
图4是示出计算相邻网格之间的传播时间的具体步骤的流程图；
图5是示出海啸在邻域内传播的示意图；
图6示出实施例1所涉及的到达时间计算模块的主要构成的框图；
图7是示出实施例1所涉及的计算到达时间的具体步骤的流程图；
图8是示出实施例2所涉及的到达时间计算模块的主要构成的框图；
图9是示出实施例2所涉及的计算到达时间的具体步骤的流程图；
图10是示出基于本发明预测2014年4月2号的智利海啸传播时间的结果的图；
图11是示出第二实施方式所涉及的海啸预警装置的主要构成的框图；
图12是示出第二实施方式所涉及的海啸预警方法的主要流程的图；
图13是处理装置的内部组件的方框图。
具体实施方式
以下，参照附图对本发明的具体实施方式进行详细说明。
<第一实施方式>
首先，参照图1和图2，说明本发明的第一实施方式所涉及的海啸预测装置的构成和海啸预测方法的主要流程。
如图1所示，本发明的海啸预测装置1包括：数据获取部101、传播时间计算部102、到达时间计算部103、输出部104。
如图2所示，本发明的海啸预测方法包括：数据获取步骤S101、传播时间计算步骤S102、到达时间计算步骤S103、输出步骤S104。
在数据获取步骤S101中，数据获取部101获取海啸传播区域的空间数据。
具体来说，海啸传播区域的空间数据是指海啸传播区域的经度、纬度、深度的数据。
在海啸的预测中，需要海啸可能传播的区域(即，海啸传播区域)的空间数据
Figure PCTCN2016076283-appb-000007
经度θ，纬度
Figure PCTCN2016076283-appb-000008
深度或高程z。该空间数据可以以栅格文件或文本文档给出。其中，经、纬度的单位为十进制度，深度或高程的单位为米。
若网格位于陆地，则z值大于等于0，若网格在海洋，则z值小于0。由于海洋高程数据量巨大，对运算影响很大。因此，可以对空间数据进行 简化处理，降低数据的空间分辨率。通过对空间数据进行简化，能够在普通的小型计算机执行海啸预测。
本发明中，假设海啸传播区域的网格数据的行数、列数分别为row，column。
接着，在传播时间计算步骤S102中，传播时间计算部102根据所获取的数据，计算出相邻网格之间的传播时间并存储。关于传播时间的具体计算方法，可以采用已有的方法，也可以采用利用图2后述的计算方法。
在本发明中，传播时间为海啸在相邻的两个网格点之间传播的时间。
接下来，在到达时间计算步骤S103中，到达时间计算部103根据在步骤S102中存储的相邻网格之间的传播时间，获得待选网格组中的各网格的到达时间，根据待选网格组中的各网格的到达时间的最小值，从待选网格组中选择下一步子波源，从而计算出海啸到达所述海啸传播区域中的每个网格的到达时间。
在本发明中，待选网格组是可能作为子波源的网格的集合，到达时间是指海啸从震源到达该网格的时间。
在S103步骤中，到达时间计算部103针对每个子波源，将该子波源的相邻网格加入待选网格组中，在根据上述的操作选择下一步子波源之后，从待选网格组中删除已经被选为下一步子波源的网格，循环执行上述操作直到待选网格组中没有网格，从而计算出海啸到达所述海啸传播区域中的每个网格的到达时间。
最后，在输出步骤S104中，输出部104输出海啸传播区域中的各网格的到达时间。所述输出可以输出给外部的存储装置、分析装置、预警装置、显示装置、打印装置等。输出的形式可以是显示、打印、存储等。输出的结果可以是表格，也可以是图形。例如，如图10所示，在地理信息系统GIS、电子地图等中，通过到达时间的等高线来展现。
<计算传播时间>
以下，参照图3和图4，对传播时间计算部102执行的上述传播时间计算步骤S102进行详细说明。
如图3所示，传播时间计算部102包括：距离计算部1021、速度计算 部1022、时间计算部1023、传播时间存储部1024。
如图4所示，S102步骤还包括：S1021步骤，计算相邻网格之间的距离；S1022步骤，计算海啸波沿每个网格的传播速度；S1023步骤，根据所述距离和所述传播速度，计算出所述传播时间；S1024步骤，存储所述相邻网格之间的传播时间数据。
具体来说，在S1021步骤中，距离计算部1021可以利用地球上的任意两点之间的距离公式(1)计算出海啸传播区域内的任意网格O到其邻域内点p1,p2,...,p16之间的距离ρ(O,pi)。
在S1022步骤中，速度计算部1022具体可以根据海啸传播速度与海洋深度的近似关系式
Figure PCTCN2016076283-appb-000009
确定海啸波在每个网格上的传播速度。
在S1023步骤中，时间计算部1023计算网格O到邻域内的网格之间的传播时间。
如图5所示，在矩形网格中，存在4×4邻域的网格。记O点所在网格上的速度为v，点pi(1≤i≤16)所在网格的速度为vi。则O与pi之间的传播时间为
Figure PCTCN2016076283-appb-000010
在S1023步骤中，时间计算部1023还可以进行如下操作：如果O点的高程大于0，令O点到周围16个点的传播时间均为0；如果O与邻域内的网格有一个高程大于0，也令它们之间的传播时间为0。
在S1024步骤中，传播时间存储部1024可以将相邻网格之间的传播时间存储起来，作为新的基础数据。高程数据中具有4×4邻域的网格共有nrow-2行、ncolumn-2列，可以将每个网格点到其邻域内16个网格点的传播时间都存储起来。
<计算到达时间>
以下，对到达时间计算部103所执行的到达时间计算步骤S103进行详细说明。
实施例1
如图6所示，到达时间计算部103包括：初始化部1031、待选网格组添加部1032、到达时间更新部1033、下一步子波源选取部1034、待选网 格组更新部1035。
以下，结合图7来说明计算海啸到达海啸传播区域的每个网格的到达时间的实施例1。
如图7所示，S103步骤包括：初始化步骤S1031、待选网格组添加步骤S1032、到达时间更新步骤S1033、下一步子波源选取步骤S1034、待选网格组更新步骤S1035。
在初始化步骤S1031中，初始化部1031设置用于存储海啸传播区域中的所有网格的到达时间的二维数组，并对其进行初始化。该二维数组的行数、列数分别为row和column。可以将震中对应的元素初始化为0(s)，其他元素都初始化为无穷大的值，例如可以设定为10^8(s)，震中为初始的子波源。
在待选网格组添加步骤S1032中，待选网格组添加部1032将子波源的相邻网格放入待选网格组list中，并读入在S102步骤中计算并存储(传播时间计算部102所计算并存储)的从子波源到相邻网格的传播时间。
具体来说，可以读入在S1024步骤中存储的相邻网格之间的传播时间之中、作为这一步的子波源的网格和与该子波源相邻的网格、即该子波源(i,j)的4×4邻域内的16个网格p1,p2,...,p16之间的传播时间。
另外，如果碰到陆地，海啸波将不会接着传播。即，海啸仅在于海洋中传播。因此，可以仅将高程z小于0的网格放入待选网格组中。
并且，在本发明中，例如，通过目前的到达时间t0大于上一步子波源的到达时间min0来判断该网格还未被放入过待选网格组中。
因此，在S1032步骤中，待选网格组添加部1032可以仅将子波源的相邻网格之中位于海洋(z＜0)且目前的到达时间大于上一步子波源的到达时间t0＞min0的网格放入待选网格组中。
在到达时间更新步骤S1033中，到达时间更新部1033在相邻网格pk的原有的到达时间t0大于子波源(i,j)的到达时间min1和从子波源到该相邻网格pk的传播时间Δtk的和值、即min1+Δtk＜t0时，将该相邻网格处的到达时间更新为所述和值，即t1＝min1+Δtk。
在下一步子波源选取步骤S1034中，下一步子波源选取部1034在待 选网格组list中选择到达时间最小的网格作为下一步子波源。
在待选网格组更新步骤S1035中，待选网格组更新部1035从待选网格组list中删除已经被选为下一步子波源的网格。
若待选网格组list的个数为1以上，则重复执行S1032～S1034步骤。
根据第一实施方式的实施例1所涉及的海啸预测方法，通过从待选网格组中选择到达时间最小的一个网格作为下一步的波源，能够快速地获得海啸到达每个网格的到达时间，能够迅速地预测海啸的传播过程，能够为及时的预警提供基础。
实施例2
以下，参照图8和图9来说明计算海啸到达海啸传播区域的每个网格的到达时间的实施例2。
如图8所示，在实施例2中，由下一步子波源选取部1034’来替换实施例1中的下一步子波源选取部1034，且还可以包括最小值计算部1030，其他的构成与实施例1相同。
如图9所示，在S103步骤包括下一步子波源选取步骤S1034’来替换实施例1中的下一步子波源选取步骤S1034，且还可以包括最小值计算步骤S1030，其他的步骤与实施例1相同。
在最小值计算步骤S1030中，最小值计算部1030计算所有相邻网格之间的传播时间的最小值Δtmin，将其输出给下一步子波源选取部1034’。
在图9中，该最小值计算步骤S1030位于初始化步骤S1031之后，然而，该最小值计算步骤S1030也可以位于步骤S1031之前。
另外，还可以通过其他模块计算所有相邻网格之间的传播时间的最小值并存储，而在下一步子波源选取步骤S1034’中，下一步子波源选取部1034’直接利用该最小值Δtmin。也就是说，S103步骤可以不包含最小值计算步骤1030，该最小值计算步骤1030可以省略。即，本发明的到达时间计算部103可以不包含最小值计算步骤1030，最小值计算步骤1030可以省略。
在下一步子波源选取步骤S1034’中，下一步子波源选取部1034’根据所有相邻网格之间的传播时间的最小值Δtmin和待选网格组中的到达时间的 最小值tmin，选择多个网格作为下一步子波源。
具体来说，在步骤S1034’中，下一步子波源选取部1034’选择到达时间小于所述所有相邻网格之间的传播时间的最小值Δtmin和待选网格组中的到达时间的最小值tmin的和值的网格为下一步子波源。即，对于待选网格组中的任意网格pk(1≤k≤n，其中，n为list的长度)，如果网格pk处的到达时间
Figure PCTCN2016076283-appb-000011
则将该网格选择为下一步子波源。
而在实施例2中，若待选网格组list的个数为1以上，则重复执行S1032～S1033、S1034’、S1035步骤。
根据实施例2所涉及的海啸预测方法，通过从待选网格组中选择到达时间较小的一批网格作为下一步的波源，除了与实施例1相同的效果之外，还具有收敛更快的优点。即，能够进一步提高运算速度。同时，避免了引入累计误差。
<第二实施方式>
本发明可以通过海啸预警装置和海啸预警方法来实现。
如图11所示，第二实施方式所涉及的海啸预警装置2除了第一实施方式的海啸预测装置1之外还包括预警部105。
第二实施方式所涉及的海啸预警方法除了第一实施方式的海啸预测方法之外还包括预警步骤S105。
在预警步骤105中，预警部105根据海啸预测方法的输出步骤S104的输出结果(输出部104的输出结果)，对到达时间小于预定的阈值的区域发出预警。
例如，如图10所示的那样，可以根据到达时间的大小绘制出等高线，根据预定的阈值生成预警线，对等高线位于预警线内的区域发出预警。
根据第二实施方式，能够对海啸可能到达的区域及时地发出预警，使得受灾区域的人们能够及时应对灾害，从而减少人员伤亡和经济损失。
本发明的各个部件实施例可以以硬件实现，或者以在一个或者多个处理器上运行的软件模块实现，或者以它们的组合实现。本领域的技术人员应当理解，如图13所示，为一个处理装置的内部组件的方框图，它可以 是工作站，例如，该处理装置包括一个总线409，总线上连接各组成结构如下所述：该处理装置包括一个处理器405，处理器405是一块超大规模的集成电路，是一台计算机的运算核心和控制核心。它的功能主要是解释计算机指令以及处理计算机软件中的数据。处理器405主要包括运算器和高速缓冲存储器406及实现它们之间联系的数据、控制及状态的总线。
处理装置还包括存储器，计算机中的存储器按用途可分为主存储器(内存)，例如，ROM(Read Only Memory image，只读存储器)403、RAM(Random Access Memory，随机存取存储器)404和辅助存储器(外存)402。存储器具有用于执行上述方法中的任何方法步骤的程序代码的存储空间。例如，用于程序代码的存储空间可以包括分别用于实现上面的方法中的各种步骤的各个程序代码。这些程序代码可以从一个或者多个计算机程序产品中读出或者写入到这一个或者多个计算机程序产品中。这些计算机程序产品包括诸如硬盘，光盘(CD)、存储卡或者软盘之类的程序代码载体。这样的计算机程序产品通常为便携式或者固定存储单元。该存储单元可以具有与前面所述的终端中的存储器类似布置的存储段、存储空间等。用于执行上述方法中的任何方法步骤的程序代码也可以通过网络进行下载。程序代码可以例如以适当形式进行压缩。通常，存储单元包括计算机可读代码，即可以由诸如之类的处理器读取的代码，这些代码当由服务器上运行搜索引擎程序时，导致该服务器执行上面所描述的方法中的各个步骤。
进一步地，该处理装置包括至少一个输入装置401用于用户与处理装置之间的相互作用，输入装置401可以为键盘、鼠标、图像捕捉元件，重力传感器，声音接收元件，触摸屏等；处理装置还包括至少一个输出装置408，输出装置408可以是喇叭，蜂鸣器，闪光灯，图像投影单元，振动输出元件，屏幕或触摸屏等；处理设备还可以包括一个以有线或无线方式进行数据通信的通信接口407。
在此处所提供的说明书中，说明了大量具体细节。然而，能够理解，本发明的实施例可以在没有这些具体细节的情况下被实践。在一些实例中，并未详细示出公知的方法、结构和技术，以便不模糊对本说明书的理解。
应该注意的是上述实施例对本发明进行说明而不是对本发明进行限制，并且本领域技术人员在不脱离所附权利要求的范围的情况下可设计出替换实施例。单词“包含”不排除存在未列在权利要求中的元件或步骤。位于元件之前的单词“一”或“一个”不排除存在多个这样的元件。本发明可以借助于包括有若干不同元件的硬件以及借助于适当编程的计算机来实现。在列举了若干装置的单元权利要求中，这些装置中的若干个可以是通过同一个硬件项来具体体现。单词第一、第二、以及第三等的使用不表示任何顺序。可将这些单词解释为名称。
此外，还应当注意，本说明书中使用的语言主要是为了可读性和教导的目的而选择的，而不是为了解释或者限定本发明的主题而选择的。因此，在不偏离所附权利要求书的范围和精神的情况下，对于本技术领域的普通技术人员来说许多修改和变更都是显而易见的。对于本发明的范围，对本发明所做的公开是说明性的，而非限制性的，本发明的范围由所附权利要求书限定。
上述实施例只为说明本发明的技术构思及特点，其目的是让熟悉该技术领域的技术人员能够了解本发明的内容并据以实施，并不能以此来限制本发明的保护范围。凡根据本发明精神实质所作出的等同变换或修饰，都应涵盖在本发明的保护范围之内。
虽然结合附图描述了本发明的实施方式，但是本领域技术人员可以在不脱离本发明的精神和范围的情况下做出各种修改和变形，这样的修改和变形均落入由所述权利要求所限定的范围之内。

Claims (10)

  1. 一种海啸预测方法，其特征在于，包括：
    数据获取步骤，获取海啸传播区域的空间数据；
    传播时间计算步骤，根据所获取的数据，计算出相邻网格之间的传播时间并存储；
    到达时间计算步骤，根据所述相邻网格之间的传播时间，获得待选网格组中的各网格的到达时间，根据所述待选网格组中的各网格的到达时间的最小值，从所述待选网格组中选择下一步子波源，从而计算出海啸到达所述海啸传播区域中的每个网格的到达时间，其中，所述待选网格组是可能作为子波源的网格的集合；以及
    输出步骤，输出所述海啸传播区域中的各网格的所述到达时间。
  2. 如权利要求1所述的海啸预测方法，其特征在于，
    在所述到达时间计算步骤中，针对每个子波源，将该子波源的相邻网格加入待选网格组中，在选择下一步子波源之后，从待选网格组中删除已经被选为下一步子波源的网格，循环执行上述操作直到待选网格组中没有网格。
  3. 如权利要求2所述的海啸预测方法，其特征在于，
    在所述到达时间计算步骤中，在所述待选网格组中选择到达时间最小的网格作为下一步子波源。
  4. 如权利要求2所述的海啸预测方法，其特征在于，
    在所述到达时间计算步骤中，根据所有相邻网格之间的传播时间的最小值和待选网格组中的到达时间的最小值，选择多个网格作为下一步子波源。
  5. 一种海啸预警方法，其特征在于，包括：
    权利要求1至4中的任一项所述的海啸预测方法；以及
    预警步骤，根据所述海啸预测方法的输出结果，对到达时间小于预定的阈值的区域发出预警。
  6. 一种海啸预测装置，其特征在于，包括：
    数据获取部，获取海啸传播区域的空间数据；
    传播时间计算部，根据所获取的数据，计算出相邻网格之间的传播时间并存储；
    到达时间计算部，根据所述相邻网格之间的传播时间，获得待选网格组中的各网格的到达时间，根据所述待选网格组中的各网格的到达时间的最小值，从所述待选网格组中选择下一步子波源，从而计算出海啸到达所述海啸传播区域中的每个网格的到达时间，其中，所述待选网格组是可能作为子波源的网格的集合；以及
    输出部，输出所述海啸传播区域中的各网格的所述到达时间。
  7. 如权利要求6所述的海啸预测装置，其特征在于，
    所述到达时间计算部针对每个子波源，将该子波源的相邻网格加入待选网格组中，在选择下一步子波源之后，从待选网格组中删除已经被选为下一步子波源的网格，循环执行上述操作直到待选网格组中没有网格。
  8. 如权利要求7所述的海啸预测装置，其特征在于，
    所述到达时间计算部在所述待选网格组中选择到达时间最小的网格作为下一步子波源。
  9. 如权利要求7所述的海啸预测装置，其特征在于，
    所述到达时间计算部根据所有相邻网格之间的传播时间的最小值和待选网格组中的到达时间的最小值，选择多个网格作为下一步子波源。
  10. 一种海啸预警装置，其特征在于，包括：
    权利要求6至9中的任一项所述的海啸预测装置；以及
    预警部，根据所述海啸预测装置的输出结果，对到达时间小于预定的阈值的区域发出预警。
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