JP2014235121A - Simulated rainfall data generation device, generation method and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a simulated rainfall data generation device capable of investigating so as to grasp a situation where an event easily occurs due to rainfall such as flood, a generation method, and a program.SOLUTION: The simulated rainfall data generation device includes an information acquisition unit and a rainfall amount calculation unit. The information acquisition unit acquires feature amount in a rainfall state. The rainfall amount calculation unit calculates a value showing time course of the rainfall amount in a plurality of locations by using information acquired by the information acquisition unit.

Description

  Embodiments described herein relate generally to a simulated rainfall data generation device, a generation method, and a program.

  Currently, the Ministry of Land, Infrastructure, Transport and Tourism and the Japan Meteorological Agency are preparing rain radars and observing rainfall conditions using the radars. These radar information is now indispensable information such as river level prediction, prediction of inflow into sewers, etc., and provision of current rainfall information in weather forecasts in daily life. (For example, refer to Patent Document 1).

  In recent years, a lot of local heavy rain (guerrilla heavy rain) has occurred due to the effects of global warming and heat island phenomenon, which has caused many damage such as inundation in cities and flooding of rivers. Then, as a measure against such frequent guerrilla heavy rain, the development of X-band MP (Multi Parameter) radar has been promoted nationwide since FY2009. Note that X-band MP radar integrates the functions of Doppler radar and dual-polarization radar, and estimates the particle size distribution of raindrops and accurate rainfall intensity from reflection factors, Doppler velocities, and polarization parameters. It is a lator that can. The Japan Meteorological Agency also distributes radar rainfall information by radar and nowcast, and distribution of precipitation intensity prediction information by rainfall nowcast.

  Under such circumstances, it is very important to conduct analysis such as runoff analysis and inundation analysis in the city, to grasp the inundation situation in the city, and to use it for countermeasures. In conducting runoff analysis and inundation analysis, commercially available software called runoff analysis software is often used. Typical examples of outflow analysis software include InfoWorks, MOUSE, XP-SWMM, and the like. Rainfall data is necessary as one of the input data in such an analysis, and such an analysis is often performed based on past actual rainfall event data.

JP-A-10-170660

  However, since the way it rains varies depending on the rain event, for example, when investigating the circumstances under which inundation is likely to occur in a certain area, whether it depends on the amount of rain or the time of rainfall There is a problem that it is difficult to identify the cause such as whether it is a thing.

  The problem to be solved by the present invention is to provide a simulated rainfall data generation device, a generation method, and a program capable of investigating under what circumstances an event caused by rainfall such as inundation is likely to occur. is there.

  The simulated rainfall data generation apparatus of the embodiment has an information acquisition unit and a rainfall amount calculation unit. The information acquisition unit acquires the feature amount of the rainfall situation. The rainfall amount calculation unit calculates a value indicating the elapsed time of the rainfall amount at a plurality of points using the information acquired by the information acquisition unit.

It is a schematic block diagram which shows the structure of the simulated rainfall data generation apparatus 10 of embodiment. It is a figure which shows the example of the area | region which produces the simulated rain data in the same embodiment. It is a graph showing the example of the time change of the rainfall intensity in the embodiment. It is a figure which shows the example of the time density function in the same embodiment. It is a figure which shows the example of the simulated rainfall amount distribution which the mesh rain amount calculation part 15 in the embodiment calculates. It is a figure which shows the example of a format of the simulated rainfall data which the mesh rainfall calculation part 15 in the embodiment produces | generates. It is a flowchart explaining operation | movement of the simulated rainfall data generation apparatus 10 in the same embodiment. It is a figure which shows the utilization example of the simulated rainfall data in the embodiment.

  Hereinafter, the simulated rainfall data generation device 10 of the embodiment will be described with reference to the drawings. FIG. 1 is a schematic block diagram illustrating a configuration of a simulated rainfall data generation device 10 according to the embodiment. The simulated rainfall data generation apparatus 10 according to the present embodiment includes an information acquisition unit 11, a step number calculation unit 12, a total hourly rainfall calculation unit 13, a time density distribution calculation unit 14, and a mesh rainfall calculation unit 15. The number-of-steps calculation unit 12, the total hourly rainfall calculation unit 13, the time density distribution calculation unit 14, and the mesh rainfall calculation unit 15 constitute a rainfall calculation unit 16.

  The information acquisition unit 11 acquires a feature amount of a rain condition, information indicating a region in which simulated rain data is created, and a time interval Tint (for example, 5 minutes, 10 minutes, etc.) for creating simulated rain data. The information acquisition unit 11 may acquire information input by the user using an input device such as a keyboard, or may be acquired by reading an electronic file specified by the user including such information. Also good. In the present embodiment, the area for creating simulated rain data is divided into a plurality of meshes, and the number of meshes in each of the X direction and the Y direction is used as information indicating the area for creating simulated rain data.

Specific examples of the characteristic amount of the rainfall situation include total rainfall R, rainfall duration T, rainfall peak time Tp, start point mesh, end point mesh, standard deviation σ _X in X direction, standard deviation σ _Y in Y direction, X direction And the case where the correlation coefficient ρ in the Y direction is used will be described. That is, the information acquisition unit 11 adds the total rainfall R, the rainfall duration T, the rainfall peak time T _p , the start point mesh, the end point mesh, X, in addition to the information indicating the area for creating the pseudo-rainfall data and the time interval Tint. The standard deviation σ _{X in} the direction, the standard deviation σ _{Y in} the Y direction, and the correlation coefficient ρ in the X direction and the Y direction are acquired.

The total rainfall R is the total amount of rainfall that occurs in the simulated rainfall event, and its unit is [mm]. The total rainfall R can be said to be an average value for all meshes of the rainfall [mm] through the simulated rainfall event in each mesh. The rain duration time T is the time from the start to the end of the rain in the simulated rain event. Rainfall peak time T _p is the simulated rainfall event, the time at which the rainfall reaches a peak. Rainfall peak time T _p is a time in the rainfall duration T.

The start point mesh is a mesh (Xs, Ys) that becomes the center of the rain region at the rain start time of the simulated rain event. The end point mesh is a mesh (Xe, Ye) that becomes the center of the rain region at the rain end time of the simulated rain event. The standard deviation σ _X in the X direction is a value representing the spread in the X direction (longitude direction) of the rain region in the simulated rain event, and is the standard deviation in the X direction of the probability density function of rainfall. The standard deviation σ _Y in the Y direction is a value representing the spread of the rain area in the Y direction (latitude direction) in the simulated rain event, and is the standard deviation in the Y direction of the probability density function of rainfall. The correlation coefficient ρ adjusts the directionality of the rain area spread in the simulated rainfall event, and is set to a value in the range from −1 to 1.

Of these feature amounts, total rainfall R, rainfall duration T, rainfall peak time T _p is information representing the time course of time the total rainfall representing the rainfall of the entire area for calculating the amount of rainfall. Further, the start point mesh (Xs, Ys) and the end point mesh (Xe, Ye) are information indicating the moving direction of rainfall. Further, the standard deviation σ _{X in} the X direction, the standard deviation σ _{Y in} the Y direction, and the correlation coefficient ρ in the X direction and the Y direction are information representing the extent of the rainfall area.

The step number calculation unit 12 calculates the time step number l for creating simulated rainfall data by dividing the rainfall duration T acquired by the information acquisition unit 11 by the time interval Tint. Time The total rainfall calculating unit 13, total rainfall R information acquisition unit 11 has acquired, with the rainfall duration T, rainfall peak time T _p, number calculating section 12 is the number of time steps l fraction calculation step Calculate the total rainfall (unit: [mm]). A method for calculating the total rainfall during each time step will be described later.

The time density distribution calculation unit 14 includes the start point mesh (Xs, Ys), the end point mesh (Xe, Ye) acquired by the information acquisition unit 11, the standard deviation σ _{X in} the X direction, the standard deviation σ _Y in the Y direction, and the correlation coefficient. Using ρ, a time density function corresponding to the time step number l calculated by the step number calculation unit 12 is calculated. The time density function is a probability density function of rainfall at each time step. A method of calculating the time probability density function by the time density distribution calculating unit 14 will be described later. The mesh rainfall calculation unit 15 calculates the time density distribution calculation unit 14 so that the average of the rainfalls of all the meshes in the time step becomes the total hourly rainfall R _i calculated by the total hourly rainfall calculation unit 13. Using the value of each mesh of the time density function, the rainfall amount (unit: [mm]) of each mesh at the time step is calculated and used as simulated rainfall data.

  FIG. 2 is a diagram illustrating an example of an area in which simulated rainfall data is created. In the example shown in FIG. 2, the area for creating simulated rainfall data is divided into n meshes in the X direction and m meshes in the Y direction, that is, n × m meshes. Each mesh is expressed using the lower right coordinates, for example, the third mesh in the X direction and the second mesh in the Y direction, such as (3, 2). As described above, the information acquisition unit 11 acquires the number of meshes in each of the X direction and the Y direction, that is, n and m in the example of FIG. 2, as information indicating a region in which simulated rainfall data is created.

FIG. 3 is a graph showing an example of temporal change in rainfall intensity. In FIG. 3, the horizontal axis represents time, the vertical axis represents rainfall intensity [mm / h], and the time T represents the end time of the simulated rain event when the start time of the simulated rain event is “0”. Time T _p is the time when the total rainfall for the hour is the maximum. With reference to the graph of FIG. 3, the calculation method of the time total rainfall of each time step by the time total rainfall calculation part 13 is demonstrated below. Since the start time of the simulated rain event is “0”, the end time of the simulated rain event is the rain duration time T. Rainfall peak time T _p is the time at which rainfall intensity is maximum.

When the graph of FIG. 3 is integrated, the total rainfall R is obtained. That is, since the area of the graph of FIG. 3 is R, if the rainfall intensity at time T _p is I _tp , then R = T × I _tp / 2. When this is modified, I _tp = 2R / T. Further, when the rainfall intensity at the i-th time step T _i is I _i , when T _i <T _p , I _i : T _i = I _tp : T _p , and when T _i ≧ T _p , I _i : (T−T _i ) = I _tp : (T−T _p ). Further, the total amount of rainfall R _i = I _i × Tint. Using the equations (1) and (2) obtained from these, the hourly total rainfall calculation unit 13 calculates the hourly total rainfall R _i at each time step T _i .

FIG. 4 is a diagram illustrating an example of a time density function. In FIG. 4, the horizontal axis is the X axis, and the vertical axis is the Y axis. Further, the mesh m _s is a start point mesh, and the mesh _me is an end point mesh. Vector Dr from the starting point mesh m _s to the end point mesh m _e is the moving direction of the rain zone. Time density distribution calculating unit 14, the start point mesh m _s and the end point mesh m a line segment connecting the _e, aliquoted at time step number l, the center point m _1, m 2 of the rain zone at each time _step, ... The coordinates (X ₁ , Y ₁ ), (X ₂ , Y ₂ ),. The time density distribution calculation unit 14 calculates a time density function of the i-th time step using the following equation (3).

In Expression (3), f (X _j , Y _k , i) is a value representing the density of the mesh (X _j , Y _k ) at the i-th time step. σ _X , σ _Y , and ρ are the standard deviation σ _X , standard deviation σ _Y , and correlation density ρ acquired by the information acquisition unit 11, respectively. π is the pi, and e is the base of the natural logarithm (also called the Napier number). (X _i , Y _i ) are the coordinates of the center point of the rain area at the i-th time step.

In Figure 4, the i-th area density is equal to or higher than the predetermined value in the time density function at time step, are surrounded by a broken line D _i. The area surrounded by the broken line Ds is an area having a density equal to or higher than a predetermined value in the time density function at the start of the simulated rain event. Further, the area surrounded by the broken line De is an area having a density equal to or higher than a predetermined value in the time density function at the end of the simulated rain event. Thus, the time density function at each time step is the same time density function translated in accordance with the movement of the central point of the rain region.

FIG. 5 is a diagram illustrating an example of simulated rainfall distribution calculated by the mesh rainfall calculation unit 15. The X-axis, Y-axis, mesh m _s , mesh _me , vector Dr, rain zone center points m ₁ , m ₂ ,... Are the same as in FIG. The mesh rainfall calculation unit 15 adds the density f () of each mesh at the time step i calculated by the time density distribution calculation unit 14 to the total time rainfall R _i at each time step i calculated by the total time rainfall calculation unit 13. By multiplying X _j , Y _k , i) and the number of meshes n × m, simulated rainfall r (X _j , Y _k , i) at each time step and each mesh is calculated.

In FIG. 5, a region surrounded by a broken line Rd _i is a region where the rainfall amount is a predetermined value or more in the simulated rainfall amount distribution in the i-th time step. Incidentally, the region surrounded by a broken line Rd _s is simulated rainfall in the distribution of the simulated rainfall at the start of the simulated rainfall event is a region higher than a predetermined value. Also, the region surrounded by a broken line Rd _e is simulated rainfall in the distribution of the simulated rainfall at the end of the simulated rainfall event is a region higher than a predetermined value. As described with reference to FIG. 4, the time density function is the same time density function translated in accordance with the movement of the central point of the rain region. the amount of distribution, according to the magnitude of the time total rainfall R _i, the size of the area changes.

  FIG. 6 is a diagram illustrating a format example of simulated rainfall data generated by the mesh rainfall calculation unit 15. In the example shown in FIG. 6, the simulated rainfall data is a table having a row for each time step and a column for each mesh. Each cell stores a corresponding time step and a simulated rainfall r of the mesh. For example, the value of the simulated rainfall r (1, 1, 1) of the mesh (1, 1) at the time step i = 1 is stored in the cells in the first column and the second row.

FIG. 7 is a flowchart for explaining the operation of the simulated rainfall data generation apparatus 10. First, the information acquisition unit 11 acquires information indicating a feature amount of a rainfall situation, a time interval Tint, and an area for creating simulated rainfall data (S1). Next, the step number calculation unit 12 obtains the necessary number of time steps from the rain duration time T and the time interval Tint (S2). Next, the hourly total rainfall calculation unit 13 obtains the hourly total rainfall R _i in each time step from the time transition of the rainfall based on the total rainfall R, the rainfall duration T, and the rainfall peak time T _p. (S3).

Next, the following steps S5 to S7 are repeated for each time step (S4). In step S5, the time density distribution calculation unit 14 obtains the center (X _i , Y _i ) of the rain region at the time step from the start point mesh (X _s , Y _s ) and the end point mesh (X _e , Y _e ). . In the next step S6, the time density distribution calculation unit 14 calculates a time density function in the time step using the center obtained in step S5. In the next step S7, the mesh rainfall calculation unit 15 calculates the simulated rainfall of each mesh using the time density function calculated in step S6 and the total time rainfall calculated in step S3.

  If these steps S5 to S7 are repeated for all time steps, the process proceeds to step S9 (S8). In step S9, the mesh rainfall calculation unit 15 collects the simulated rainfall calculated in step S7 as time series data, generates and outputs simulated rainfall data, and ends the process.

  FIG. 8 is a diagram illustrating an example of use of simulated rainfall data. FIG. 8 shows an example used in the outflow analysis software. In analysis such as runoff analysis and inundation analysis in a city, the runoff analysis apparatus 20 realized by a computer executing commercially available software called runoff analysis software is often used. The runoff analysis device 20 includes ground surface data d1 indicating the ground surface height, land use status, etc., the length of the pipe, the pipe diameter, the gradient, the pipe bottom height, the laying position, etc. The pipe / facility data d2 indicating information such as the installation location of the pumping station equipment and the number of pumps, and the rainfall data d3 indicating the state of rainfall in the target basin are used as input data. Then, calculations are performed using various models that represent the outflow phenomenon on the ground surface and the downflow phenomenon in the pipeline. As a result, the outflow amount, the inflow amount, the water level in the pipeline, the overflow amount, the occurrence of inundation, etc. The simulation result r1 can be obtained.

  When such a simulation is performed, data of actual rainfall events in the past are often used as the rain data. However, since the method of raining is different for each rainfall event, for example, in order to investigate under what circumstances inundation in a certain area is likely to occur, whether it is due to rainfall or depending on the rainfall time It was difficult to identify factors such as whether it was a thing.

  Therefore, if the simulated rainfall data d3 expressing the characteristics of the rainfall with such a unified index can be used, for example, even if the rainfall is the same, the standard deviation of the rain region is changed, that is, the locality is increased, Perform simulations such as whether the inundation situation changes depending on whether it falls within the range, or change the movement method of the rain by changing the start point mesh and the end point mesh even if the rainfall amount and the extent of the rain area are the same As a result, a simulation result r1 can be obtained, such as whether the inflow situation to the rainwater pumping station changes. Then, referring to the simulation results that take into account the features of rainfall, we identify geographically and civilally weak points, which can be used for studying the installation policy of pipes and facilities, and in actual rainfall, It is thought that it can be used to estimate the location of inundation considering the amount.

  As described above, in the simulated rain data generation apparatus, the setting of feature values and the procedure for creating simulated rain data using the feature values have been described. However, these are only examples and do not depart from the contents. You may change suitably etc. in the range.

  For example, as shown in FIG. 3, the total hourly rainfall calculation unit 13 increases the rainfall intensity over time from the rain start time to the rain peak time in proportion to the time, and the rain peak time ends. It is assumed that the rainfall will decrease in proportion to the time until the time. However, it is also possible to add a time during which the rain peak continues as a feature amount and change the rainfall intensity into a trapezoidal shape so that the rain peak continues for that time. Alternatively, a plurality of rainfall peak times and the rainfall intensity at those times may be added as feature quantities to create a simulated rainfall event in which there are multiple rainfall peak times within one rainfall event. . Moreover, it is also possible to perform simulated rainfall data in which a plurality of such temporal changes in rainfall intensity are superimposed and synthesized.

In the above-described embodiment, the region for creating simulated rainfall data is represented by the number of meshes in each of the X direction and the Y direction. However, the present invention is not limited to this. For example, each X coordinate may be expressed using information indicating a Y coordinate range, or each Y coordinate may be expressed using information indicating a X coordinate range.
In the aforementioned embodiment, the center of the rain zone at each time step, the line segment connecting the starting point mesh m _s and the end point mesh m _e, but the equally spaced points on at time step number l, and the equal amount You may make it the mesh containing a point.

In the embodiment described above, the mesh rainfall calculation unit 15 uses the rainfall [mm] as the simulated rainfall, but simulates the rainfall (rain intensity) per unit time by dividing the rainfall by the time interval Tint. It is good also as rainfall.
In the above-described embodiment, the total rainfall R has been described as an average value for all meshes of the rainfall [mm] through the simulated rainfall event in each mesh. However, the total rainfall R is a total value for all meshes. There may be.
Further, in the above-described embodiment, the information acquisition unit 11 may not acquire a part of the characteristic amount of the rainfall situation described above by setting a predetermined value.

  According to the simulated rainfall data generation device of at least one embodiment described above, the time lapse of the rainfall amount at a plurality of points using the information acquisition unit that acquires the feature amount of the rainfall situation and the information acquired by the acquisition unit By having a rainfall amount calculation unit that calculates a value indicating, simulated rainfall data necessary for urban runoff analysis, urban inundation analysis, and the like can be created. Therefore, it is possible to investigate under what circumstances an event caused by rainfall, such as inundation, is likely to occur, or to identify a location that is weak in terms of geography or civil engineering.

  Further, a program for realizing the function of the simulated rainfall data generation device 10 in FIG. 1 is recorded on a computer-readable recording medium, and the program recorded on the recording medium is read into a computer system and executed. The simulated rainfall data generation device 10 may be realized. Here, the “computer system” includes an OS and hardware such as peripheral devices.

Further, the “computer system” includes a homepage providing environment (or display environment) if a WWW system is used.
The “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM and a CD-ROM, and a hard disk incorporated in a computer system. Furthermore, the “computer-readable recording medium” dynamically holds a program for a short time like a communication line when transmitting a program via a network such as the Internet or a communication line such as a telephone line. In this case, a volatile memory in a computer system serving as a server or a client in that case, and a program that holds a program for a certain period of time are also included. The program may be a program for realizing a part of the functions described above, and may be a program capable of realizing the functions described above in combination with a program already recorded in a computer system.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

[Embodiment 1]
Embodiment 1 includes an information acquisition unit that acquires a feature value of a rainfall situation, and a rainfall amount calculation unit that calculates a value indicating the elapsed time of the rainfall amount at a plurality of points using the information acquired by the information acquisition unit. This is a simulated rainfall data generation device.

[Embodiment 2]
Embodiment 2 is the simulated rainfall data generation apparatus according to Embodiment 1, wherein the feature amount of the rain condition is information indicating the time elapsed of the total rainfall amount representing the rainfall amount of the whole of the plurality of points, and the movement direction of the rain This is a simulated rainfall data generation device including at least one of the information indicating the spread of the rainfall area.

[Embodiment 3]
Embodiment 3 is the simulated rainfall data generation apparatus according to Embodiment 2, wherein the information indicating the time lapse of the time total rainfall includes a rainfall duration T indicating the duration of rainfall, and a rainfall amount of the rainfall duration time. Of the total amount of rainfall, and the rainfall peak time, which is the time at which the total amount of rainfall is maximum, of the total rainfall amount.

[Embodiment 4]
Embodiment 4 is the simulated rainfall data generation apparatus according to Embodiment 2, wherein the information indicating the moving direction of the rain includes coordinates indicating the center of the rain area at the start of rain and the center of the rain area at the end of the rain. Coordinates to represent.

[Embodiment 5]
Embodiment 5 is the simulated rainfall data generation apparatus according to Embodiment 2, wherein the information representing the extent of the rain region includes information representing the extent of the first direction, information representing the extent of the second direction, Information indicating the correlation between the first direction and the second direction.

DESCRIPTION OF SYMBOLS 10 ... Simulated rainfall data generation apparatus 11 ... Information acquisition part 12 ... Step number calculation part 13 ... Total time rainfall calculation part 14 ... Time density distribution calculation part 15 ... Mesh rainfall calculation part 16 ... Rainfall calculation part

Claims (3)

An information acquisition unit for acquiring the characteristic amount of the rainfall situation;
Using the information acquired by the information acquisition unit, a rainfall calculation unit that calculates a value indicating the elapsed time of rainfall at a plurality of points;
A simulated rainfall data generation device. A method for generating simulated rainfall data in a simulated rainfall data generating device,
A first process in which the simulated rainfall data generation device acquires a feature value of a rainfall situation;
A second step in which the simulated rainfall data generation device calculates a value indicating a time lapse of rainfall at a plurality of points using the characteristic amount of the rainfall situation;
A method for generating simulated rainfall data. Computer
An information acquisition unit that acquires feature values of rainfall conditions;
A program for functioning as a rainfall amount calculation unit that calculates a value indicating a lapse of time of rainfall amounts at a plurality of points using information acquired by the information acquisition unit.

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