JP2014234675A - Flow rate prediction device, flow rate prediction method, flow rate prediction program and flow rate prediction system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a flow rate prediction device, a flow rate prediction method, a flow rate prediction program and a flow rate prediction system capable of accurately predicting a flow rate of rainwater through a simple method with a reduced quantity of engineering work.SOLUTION: A flow rate prediction device comprises: a precipitation intensity acquisition section; a flow rate acquisition section; and a flow rate estimation section. The precipitation intensity acquisition section acquires precipitation intensity on a precipitation event at predetermined intervals in each of a plurality of partitioned regions partitioning an object region. The flow rate acquisition section acquires a flow rate of rainwater flowing out of the object region in synchronization with an acquisition timing of the precipitation intensity acquisition section. The flow rate estimation section estimates the flow rate of the rainwater flowing out of the object region at a future time on the basis of the precipitation intensity acquired by the precipitation intensity acquisition section and the flow rate acquired by the flow rate acquisition section.

Description

  Embodiments described herein relate generally to a flow prediction device, a flow prediction method, a flow prediction program, and a flow prediction system.

  2. Description of the Related Art Conventionally, a technique for predicting the amount of rainwater inflow into a rainwater treatment plant using the observation result of a rainfall situation by a rain radar is known (see, for example, Patent Document 1).

JP 2008-184783 A

However, the conventional rainwater inflow prediction technology does not have sufficient prediction accuracy, and enormous engineering work such as detailed modeling is required to improve the prediction accuracy.
Therefore, the problem to be solved by the present invention is that a flow rate prediction device, a flow rate prediction method, a flow rate prediction program, and a flow rate prediction that can accurately predict a rainwater flow rate by a simple method with a small amount of engineering work. Is to provide a system.

  In order to solve the above problems, a flow rate prediction apparatus according to an embodiment of the present invention includes a rainfall intensity value acquisition unit, a flow rate value acquisition unit, and a flow rate value estimation unit. The rainfall intensity value acquisition unit acquires the rainfall intensity value in the rain event for each predetermined time in advance in each of the plurality of divided areas obtained by dividing the target area. The flow value acquisition unit acquires the flow value of rainwater flowing out from the target area in synchronization with the acquisition timing by the rainfall intensity value acquisition unit. The flow rate estimation unit estimates a flow rate value at a future time of rainwater flowing out from the target region based on the rainfall intensity value acquired by the rainfall intensity value acquisition unit and the flow rate value acquired by the flow rate value acquisition unit. .

It is a figure which shows typically the whole structure of the rainwater drainage management system to which the flow volume prediction apparatus which is 1st Embodiment is applied. In the embodiment, it is a block diagram which shows the function structure of a flow volume prediction apparatus. In the same embodiment, it is the figure which represented typically the rainfall intensity value corresponding to each of the some division area which divided the object area | region, and the flow volume value of the rainwater which flows out out of the said object area | region. In the embodiment, it is a data block diagram which shows the specific example of the rain event data which a flow volume prediction apparatus takes in. In the same embodiment, it is a flowchart which shows the process of a flow volume prediction apparatus. In the same embodiment, it is the graph which showed the value of each coefficient in the kth division field (mesh k) among the coefficients memorized by the flow rate estimation part. In the same embodiment, it is the figure showing the equal arrival time curve obtained by matching the same or equivalent delay time on the two-dimensional data which the flow volume prediction apparatus produced | generated.

Hereinafter, embodiments will be described in detail with reference to the drawings.
[First Embodiment]
FIG. 1 is a diagram schematically illustrating an overall configuration of a rainwater drainage management system to which a flow rate prediction apparatus according to the first embodiment is applied. As shown in the figure, a rainwater pipe 10 (including a water collecting groove) is laid in a target area on the ground that is a target of rainwater drainage. However, the rainwater pipe 10 in the figure is represented in a simplified manner. A rainwater drainage facility 80 is provided on the drain outlet side of the rainwater pipe 10. In the rainwater drainage facility 80, a drainage pump 20 is installed with a drainage port of the rainwater pipe 10 connected thereto. Therefore, the rain that has fallen on the target area flows into or enters the rainwater pipe 10 from the ground surface and is collected in the rainwater drainage facility 80. The drainage pump 20 of the rainwater drainage facility 80 discharges the collected rainwater to, for example, a river or the sea.

  In FIG. 1, the stormwater drainage management system includes a rainfall radar 30, a signal processing device 40, a distribution device 50, a flow rate predicting device 60, and a flow rate measuring device 70.

  The rain radar 30 is a rain observation apparatus that observes the state of rainfall by including at least the above-mentioned target area in the observation range. Specifically, the rainfall radar 30 generates a signal indicating a rain condition by transmitting a radio wave toward the air and receiving a radio wave reflected from a raindrop or the like. The rain radar 30 supplies the generated signal to the signal processing device 40.

The signal processing device 40 receives a signal supplied by the rain radar 30 and processes the signal to process rainfall intensity value data representing the intensity of rainfall in each of a plurality of segmented regions (mesh) that segment the target region. (Rainfall intensity value data) is generated. The rainfall intensity value at a certain time is a value of the amount of rainfall obtained when the rain falling at the time continues for one hour. The unit of the rainfall intensity value is (mm / h). FIG. 1 illustrates a plurality of divided areas M obtained by dividing a target area within the observation range of the rainfall radar 30 on the ground where the rainwater pipe 10 is laid. Each divided region is a square region having an area of 62500 (250 × 250) (m ² ), for example. Note that the shape of the segmented region is not limited to a rectangle. For example, the divided area may be an area formed by a triangle, a hexagon, a circle, or the like. The signal processing device 40 supplies the rainfall intensity value data in each segment area to the distribution device 50.

  The distribution device 50 takes in the rainfall intensity value data corresponding to each of the plurality of divided regions supplied by the signal processing device 40, and converts each rainfall intensity value data into a data format for distribution to the outside. Then, the distribution device 50 supplies each rainfall intensity value data after format conversion to the flow rate prediction device 60.

The flow rate measuring device 70 is a device that is provided near the discharge port of the rainwater pipe 10 or near the discharge port, or near the water inlet of the rainwater drainage facility 80, and measures the flow rate of rainwater flowing into the rainwater drainage facility 80. The flow rate measuring device 70 supplies flow rate value data (flow rate value data) representing the flow rate to the flow rate predicting device 60. The flow rate value is the amount of water flowing per unit time (for example, 1 second). The unit of the flow value is (m ³ / s).

  The flow rate predicting device 60 uses the rainfall intensity value data supplied from the distribution device 50 and the flow rate value data supplied from the flow measuring device 70 at regular intervals (for example, 1 minute or 5 minutes) in one or more rain events. Every time). In other words, the flow rate predicting device 60 determines the rainfall intensity value data corresponding to each of a plurality of divided areas obtained by dividing the target area and the flow rate value data of rainwater flowing out from the target area at a certain level in one or more rainfall events. The data is taken in every time, and rainfall intensity value data (rainfall intensity value data set) and flow value data for a plurality of divided areas are related and stored in time series. These stored time-series data are also called rain event data. The rain event is a series of rain events from the time when it starts to rain on the surface of the target area to the time when it stops. However, if the rain-free time from when the rain has stopped once until it starts to fall again is less than a predetermined time (for example, 4 hours), the rain before and after the rain-free time is regarded as a series of rain to distinguish the rain event. do not do.

  The flow rate prediction device 60 uses the stored time series data having the rainfall intensity value data set and the flow rate value data in one or a plurality of rainfall events, and the flow rate value of rainwater from the flow rate measurement device 70 at a future time. And an estimated flow rate value is output as an estimation result. The estimated flow rate value output from the flow rate predicting device 60 is used, for example, for monitoring the operation state of the drainage pump 20 and other devices in the rainwater drainage facility 80.

Next, the structure of the flow volume prediction apparatus 60 which is 1st Embodiment is demonstrated.
FIG. 2 is a block diagram showing a functional configuration of the flow rate predicting device 60. As shown in the figure, the flow rate prediction device 60 includes a rainfall intensity value acquisition unit 61, a flow rate value acquisition unit 62, a storage unit 63, a flow rate value estimation unit 64, and a coefficient update unit 65.

  The rainfall intensity value acquisition unit 61 captures rainfall intensity value data supplied by the distribution device 50. Specifically, the rainfall intensity value acquisition unit 61 acquires rainfall intensity value data for one or a plurality of rainfall events at regular intervals in each of a plurality of divided areas (each mesh) obtained by dividing the target area. That is, the rainfall intensity value acquisition unit 61 takes in the rainfall intensity value data set in time series. The rainfall intensity value acquisition unit 61 causes the storage unit 63 to store the captured rainfall intensity value data set.

  The flow value acquisition unit 62 takes in the flow value data supplied by the flow measuring device 70. Specifically, the flow value acquisition unit 62 acquires the flow value data in synchronization with the acquisition timing by the rainfall intensity value acquisition unit 61. However, synchronizing with timing includes setting the same time. The flow value acquisition unit 62 stores the acquired flow value data in the storage unit 63.

  The storage unit 63 sequentially associates and stores the rainfall intensity value data set supplied by the rainfall intensity value acquisition unit 61 and the flow rate value data supplied by the flow rate value acquisition unit 62. That is, the storage unit 63 correlates the rainfall intensity value data corresponding to each of the plurality of segmented regions, which is captured at regular intervals in one or a plurality of rainfall events, and the flow rate value data of rainwater flowing out from the target region. And memorize them in time series. The storage unit 63 is realized by, for example, a magnetic hard disk device or a semiconductor storage device.

  The flow value estimation unit 64 is based on the rainfall intensity value data set and the time series data of the flow value data (that is, past rainfall event data) in one or a plurality of rainfall events stored in the storage unit 63. Estimate the flow rate of rainwater flowing out from the future time. Specifically, the flow value estimation unit 64 reads the rainfall intensity value data set and the time series data of the flow value data from one or more rain events from the storage unit 63. Then, the flow value estimation unit 64 executes a multiple regression analysis process based on the read time-series data, thereby calculating a coefficient (regression) of a prediction formula (flow estimation formula) of the flow value with respect to the rainfall intensity value in a plurality of divided regions. (Coefficients) are calculated and stored in a storage unit incorporating these coefficients. Here, the coefficient includes an intercept and an error. The flow rate estimation unit 64 estimates a flow rate value (estimated flow rate value) at a future time by executing a calculation process of a prediction formula to which the stored coefficient is applied. The flow rate estimation unit 64 outputs the calculated estimated flow rate data (estimated flow rate data).

  The coefficient update unit 65 updates the coefficient stored in the storage unit of the flow value estimation unit 64 at a predetermined timing with the coefficient calculated by the flow value estimation unit 64. For example, every time the flow rate estimation unit 64 calculates a coefficient, the coefficient update unit 65 rewrites (updates) the coefficient stored in the storage unit with the calculated coefficient. Alternatively, the coefficient updating unit 65 updates after a certain time (for example, several hours or days) after the update. Alternatively, the coefficient updating unit 65 updates after a predetermined date and time has elapsed according to the time measurement result of the built-in clock.

Next, the rain event data captured by the flow rate prediction device 60 will be described.
FIG. 3 is a diagram schematically showing the rainfall intensity value corresponding to each of a plurality of divided areas obtained by dividing the target area and the flow value of rainwater flowing out from the target area. The figure, at a certain time, (the n, 2 or more integer) n number obtained by dividing the target area rainfall intensity value corresponding to the segmented region of the r _1, r _2, · · ·, and r _n, the target area Represents the flow rate value Q of rainwater flowing out from the water. The flow rate predicting device 60 captures and stores the rain event data shown in the figure at regular intervals in one or a plurality of rain events.

FIG. 4 is a data configuration diagram illustrating a specific example of the rain event data captured by the flow rate prediction device 60. According to the figure, the flow rate predicting device 60 indicates that the rain intensity value data set _{(r 1, r 2, ···} , r n) a and flow rate value Q, is taken every minute.

  Next, the multiple regression analysis process executed by the flow rate estimation unit 64 in the flow rate prediction device 60 will be described. In the multiple regression analysis process, if the number of segmented areas (mesh) is n, and the target time range is the time from the current time to m (the unit is minutes), n × (m + 1) A large number of data is required. For example, in order to execute the multiple regression analysis process using the rain event data from the current time to 20 minutes before the target area divided into 20 divided areas, 20 × (20 + 1) = 420 or more I need data.

The flow value estimation unit 64 reads the rain event data from the time (t−m) to the time t stored in the storage unit 64 and executes the multiple regression analysis process, thereby expressing the following equation (1). A coefficient a _{i, j} , intercept a ₀ , and error ε in the regression equation are calculated. In Expression (1), r _i (t−j) is a rainfall intensity value corresponding to the i-th mesh at time (t−j). However, (i = 1, 2,..., N) and (j = 0, 1, 2,..., M). Q (hat) (t + 1) is an estimated flow rate value at time (t + 1). Note that “(hat)” is “^” added to the upper part of the character “Q” immediately before it.

The flow rate estimation unit 64 uses the calculated coefficient a _{i, j} , intercept a ₀ , and error ε as a regression equation based on the equation (1), and sets the rainfall intensity value data set from time (tm) to time t. By substituting and calculating, an estimated flow rate value Q (hat) (t + 1) from the target region at time (t + 1) is obtained.

Next, operation | movement of the flow volume prediction apparatus 60 which is 1st Embodiment is demonstrated.
FIG. 5 is a flowchart showing the process of the flow rate prediction device 60.
In step S1, the flow rate predicting device 60 stands by until a rainfall event is started (step S1: NO). Specifically, the flow rate predicting device 60 determines whether or not a non-rainy time has passed a predetermined time (for example, 4 hours) or more. When the rainless time has elapsed for a predetermined time or more and the rain starts, the flow rate prediction device 60 determines that the rain event has started. When the flow rate prediction device 60 determines that a rain event has started (step S1: YES), the process proceeds to step S2.

  In step S <b> 2, the rainfall intensity value acquisition unit 61 takes in the rainfall intensity value data set supplied by the distribution device 50 and stores the rainfall intensity value data set in the storage unit 64. The flow value acquisition unit 62 captures the flow value data supplied from the flow measurement device 70 in synchronization with the acquisition timing by the rainfall intensity value acquisition unit 61, and associates the flow value data with the rainfall intensity value data set. To be stored in the storage unit 64.

  Next, in step S <b> 3, the flow rate prediction device 60 determines whether or not to end the rain event data capture. For example, the flow rate predicting device 60 determines whether or not the rain event data has been acquired in one or a plurality of rain events in which the amount of rainfall exceeds a certain amount of rainfall. If the flow rate predicting device 60 determines not to finish capturing the rain event data (step S3: NO), it returns to the process of step S1. On the other hand, when it determines with the flow volume prediction apparatus 60 complete | finishing taking in of rain event data (step S3: YES), it moves to the process of step S4.

  In step S <b> 4, the flow value estimation unit 64 reads the rainfall intensity value data set and the time series data of the flow value data from one or more rain events from the storage unit 63. Next, the flow value estimation unit 64 calculates the coefficient of the prediction formula of the flow value with respect to the rainfall intensity value in the plurality of divided regions by executing the multiple regression analysis process based on the read time series data, and these coefficients Is stored in a built-in storage unit.

  Next, in step S <b> 5, the flow rate estimation unit 64 calculates an estimated flow rate value at a future time by executing a prediction formula calculation process using the stored coefficient. Next, the flow value estimation unit 64 outputs estimated flow value data that is data of the calculated estimated flow value.

  Next, in step S <b> 6, the coefficient update unit 65 determines whether or not to update the coefficient stored in the flow value estimation unit 64 with the coefficient calculated by the flow value estimation unit 64. For example, the coefficient updating unit 65 determines to update the flow rate estimation unit 64 whenever the flow rate estimation unit 64 calculates the coefficient. Alternatively, the coefficient updating unit 65 determines whether a certain time has elapsed since the previous update. However, if it has not been updated yet, it is determined that it will always be updated. Alternatively, the coefficient updating unit 65 determines whether or not a predetermined date and time (for example, 0:00 am on June 1) has been reached using a built-in clock. If the coefficient update unit 65 determines to update (step S6: YES), the coefficient update unit 65 proceeds to the process of step S7. If determined not to update (step S6: NO), the coefficient update unit 65 returns to the process of step S1.

  In step S7, the coefficient updating unit 65 updates the coefficient stored in the flow value estimation unit 64 with the coefficient calculated by the flow value estimation unit 64 in the process of step S5. Next, the flow rate prediction device 60 returns to the process of step S1.

Next, the acquisition method of the equal arrival time curve in the target region by the flow rate prediction device 60 will be described.
FIG. 6 is a graph showing the value of each coefficient in the kth segmented area (mesh k) among the coefficients stored in the flow rate estimation unit 64. In the figure, the horizontal axis represents the coefficient in the mesh k, and the vertical axis represents the coefficient value. Note that 0 ≦ l (el) ≦ m. As shown in the figure, among the coefficients a _{k, 0} to the coefficients a _{k, m} in the mesh k, the coefficient a _{k, l} is the maximum coefficient value. Therefore, it can be said that there is a delay time of time l (el) between the time point when the rainfall intensity value corresponding to the mesh k is acquired and the time point when the rainwater flows from the target region.

  The flow rate predicting device 60 detects the coefficient having the maximum coefficient value for each of the divided areas in the target area, and acquires the delay time from the detected coefficient. Then, the flow rate predicting device 60 generates two-dimensional data in which the delay times in all the divided areas of the target area are associated with the divided areas, and by associating the same or equivalent delay times with each other in the two-dimensional data, Get equal arrival time.

FIG. 7 is a diagram showing an equal arrival time curve obtained by associating the same or equivalent delay times on the two-dimensional data generated by the flow rate prediction device 60. In the figure, the equal arrival time is represented by a line so as to be visually easy to see, but the equal arrival time may be represented by, for example, color-coding the mesh or changing the length in the three-dimensional direction.
By obtaining the equal arrival time, it is possible to visually grasp the flow characteristics in the target region.

  The flow rate prediction apparatus according to the first embodiment includes a rainfall intensity value acquisition unit that acquires, in advance, a rainfall intensity value in a rain event every predetermined time in each of a plurality of divided areas obtained by dividing the target area. In addition, the flow rate prediction apparatus includes a flow value acquisition unit that acquires the flow value of rainwater flowing out from the target region in synchronization with the acquisition timing of the rainfall intensity value acquisition unit. In addition, the flow rate predicting apparatus estimates a flow rate value at a future time of rainwater flowing out from the target area based on the rainfall intensity value acquired by the rainfall intensity value acquiring unit and the flow rate value acquired by the flow rate acquiring unit. A value estimation unit is provided.

  The flow rate predicting apparatus according to the first embodiment estimates the flow rate of rainwater from the target region at a future time based on the rainfall intensity value and the flow rate value in the target region measured at regular intervals for the rain event. Therefore, according to the flow volume prediction apparatus which is 1st Embodiment, the rainwater flow volume can be estimated with the simple method which restrained the engineering work amount small.

  In addition, the flow rate estimation unit in the flow prediction device according to the first embodiment performs a multiple regression analysis process on the basis of the acquired rainfall intensity value and the flow rate value, and thereby the flow rate for the rainfall intensity value in the plurality of segmented regions. A coefficient of a value prediction formula is calculated, and a flow rate value at a future time is estimated by calculating a prediction formula to which these coefficients are applied.

  Thereby, according to the flow volume prediction apparatus which is 1st Embodiment, the rainwater flow volume can be accurately estimated by the simple method which restrained the engineering work amount small.

  In addition, the flow rate prediction apparatus according to the first embodiment includes a coefficient update unit that updates a coefficient calculated by the flow value estimation unit at a predetermined timing. The update timing may be controlled so as to always keep the coefficient which is the latest calculation result, or may be controlled to be updated when determined in advance.

  Thereby, the flow volume prediction apparatus which is 1st Embodiment can predict a rainwater flow volume accurately by using a suitable coefficient.

[Second Embodiment]
The rainfall intensity value acquisition unit 61 in the first embodiment stores the rainfall intensity value of the rainfall intensity value data captured from the distribution device 50 in the storage unit 63 as it is. That is, in the first embodiment, since the rainfall intensity value data for each divided region generated by the signal processing device 40 based on the signal generated by the rain radar 30 is used as it is, it is caused by noise or signal attenuation due to terrain change. The effect on rainfall intensity was not considered. The second embodiment is an example in which the rainfall intensity value acquisition unit normalizes the acquired rainfall intensity value data in association with a plurality of ranges divided according to the rainfall intensity.

  As the functional configuration diagram of the flow rate prediction apparatus according to the second embodiment, FIG. 2 showing the functional configuration of the flow rate prediction apparatus 60 according to the first embodiment is used. In the second embodiment, parts that are different from the first embodiment will be described, and descriptions of common parts will be omitted.

  The rainfall intensity value acquisition unit 61 in the second embodiment takes in the rainfall intensity value data supplied by the distribution device 50 as in the first embodiment. Then, the rainfall intensity value acquisition unit 61 normalizes the acquired rainfall intensity value data in correspondence with a plurality of ranges divided according to the rainfall intensity.

  Specifically, the rainfall intensity value acquisition unit 61 stores range data indicating a plurality of ranges in advance in a built-in storage unit. As an example when the rainfall intensity value is 200 (mm / h) or less, the storage unit of the rainfall intensity value acquisition unit 61 is, for example, 0 (mm / h), greater than 0 (mm / h), and 1 (mm / h). h) or less, greater than 1 (mm / h), 5 (mm / h) or less, greater than 5 (mm / h), less than 10 (mm / h), greater than 10 (mm / h), 20 (mm / h) Hereinafter, greater than 20 (mm / h) and not greater than 50 (mm / h), greater than 50 (mm / h) and not greater than 100 (mm / h), and greater than 100 (mm / h) and not greater than 200 (mm / h) Is stored in advance.

  The rainfall intensity value acquisition unit 61 normalizes the captured rainfall intensity value data by converting it into the median value of the corresponding range according to the range in the stored range data. That is, the rainfall intensity value acquisition unit 61 converts the captured rainfall intensity value data as shown in Table 1 below.

  The rainfall intensity value acquisition unit 61 in the second embodiment normalizes the acquired rainfall intensity value data in correspondence with a plurality of ranges divided according to the rainfall intensity, so that the rainfall before normalization can be achieved with a simple configuration. The error contained in the intensity value data can be absorbed, and the rainwater flow rate can be predicted accurately.

[Third Embodiment]
The third embodiment is an example in which the rainfall intensity value acquisition unit normalizes the acquired rainfall intensity value data corresponding to a plurality of ranges divided according to the rainfall intensity, and is a modification of the second embodiment. It is.

  As the functional configuration diagram of the flow rate prediction apparatus according to the third embodiment, FIG. 2 showing the functional configuration of the flow rate prediction apparatus 60 according to the first embodiment is used. In the third embodiment, a configuration that is different from the second embodiment will be described, and a description of a configuration that is common to the first embodiment and the second embodiment will be omitted.

  As in the first embodiment, the rainfall intensity value acquisition unit 61 in the third embodiment captures the rainfall intensity value data set supplied by the distribution device 50 in time series. Then, the rainfall intensity value acquisition unit 61 normalizes the acquired rainfall intensity value data set in association with a plurality of ranges divided according to the rainfall intensity.

  Specifically, the rainfall intensity value acquisition unit 61 stores range data indicating a plurality of ranges in advance in a built-in storage unit, as in the second embodiment. The contents of the range data here are the same examples as in the second embodiment.

  The rainfall intensity value acquisition unit 61 does not convert the rainfall intensity value data having the maximum rainfall intensity value in the captured rainfall intensity value data set, and converts other rainfall intensity value data into the range in the stored range data. Accordingly, normalization is performed by converting to the median of the corresponding range. For example, when the rainfall intensity value data set includes 40 (mm / h) of rainfall intensity value data as the maximum value, the rainfall intensity value acquisition unit 61 selects the captured rainfall intensity value data set as shown in Table 2 below. Convert as follows.

  The rainfall intensity value acquisition unit 61 according to the third embodiment associates the acquired rainfall intensity value data set with a plurality of ranges divided according to the rainfall intensity, except for the rainfall intensity value data having the maximum rainfall intensity value. By normalizing, the error contained in the rainfall intensity value data before normalization can be absorbed with a simple configuration, and the rainwater flow rate can be predicted accurately.

[Fourth Embodiment]
The fourth embodiment is an example in which the rainfall intensity value acquisition unit normalizes the acquired rainfall intensity value data in association with a plurality of ranges divided according to the rainfall intensity, and is a modification of the third embodiment. It is.

  As the functional configuration diagram of the flow rate prediction apparatus according to the fourth embodiment, FIG. 2 showing the functional configuration of the flow rate prediction apparatus 60 according to the first embodiment is used. In the fourth embodiment, the configuration different from the third embodiment will be described, and the description of the configuration common to the first to third embodiments will be omitted.

  The rainfall intensity value acquisition unit 61 in the fourth embodiment takes in the rainfall intensity value data set supplied by the distribution device 50 in time series, as in the first embodiment. Then, the rainfall intensity value acquisition unit 61 normalizes the acquired rainfall intensity value data set in association with a plurality of ranges divided according to the rainfall intensity.

  Specifically, the rainfall intensity value acquisition unit 61 stores range data indicating a plurality of ranges in advance in a built-in storage unit, as in the second embodiment. The contents of the range data here are the same examples as in the second embodiment.

  The rainfall intensity value acquisition unit 61 does not convert the rainfall intensity value data (maximum rainfall intensity value data) having the maximum rainfall intensity value in the captured rainfall intensity value data set. Then, the rainfall intensity value acquisition unit 61 makes other rainfall intensity value data constant in each range up to the minimum range based on the ratio of the maximum rainfall intensity value in the range including the maximum rainfall intensity value data. Normalize by converting to a value corresponding to the rate of increase or decrease at a rate of. For example, when the rainfall intensity value data set includes the rainfall intensity value data of 75 (mm / h) as the maximum value, the rainfall intensity value acquisition unit 61 sets the captured rainfall intensity value data set as the following Table 3. Convert as follows.

  The rainfall intensity value acquisition unit 61 according to the fourth embodiment associates the acquired rainfall intensity value data set with a plurality of ranges divided according to the rainfall intensity, except for the rainfall intensity value data having the maximum rainfall intensity value. By normalizing, the error contained in the rainfall intensity value data before normalization can be absorbed with a simple configuration, and the rainwater flow rate can be predicted accurately.

[Fifth Embodiment]
The fifth embodiment is an example in which the flow value estimation unit calculates a coefficient in a prediction formula for each of a plurality of ranges divided according to rainfall intensity, and calculates the prediction formula for each range.

  The functional configuration diagram of the flow rate predicting apparatus according to the fifth embodiment uses FIG. 2 showing the functional configuration of the flow rate predicting apparatus 60 according to the first embodiment. In the fifth embodiment, portions that are different from the first embodiment will be described, and descriptions of common portions will be omitted.

  The flow value estimation unit 64 reads the rainfall intensity value data set and the time series data of the flow value data from the storage unit 63 in one or a plurality of rain events in association with each of a plurality of ranges divided according to the rainfall intensity. . As an example when the rainfall intensity value is 200 (mm / h) or less, the range is, for example, 0 (mm / h), greater than 0 (mm / h) and 1 (mm / h) or less, 1 (mm / h) h) greater than 5 (mm / h) and greater than 5 (mm / h) greater than 10 (mm / h) and greater than 10 (mm / h) and not greater than 20 (mm / h) and 20 (mm / h) It is larger than 50 (mm / h), larger than 50 (mm / h) and smaller than 100 (mm / h), and larger than 100 (mm / h) and smaller than or equal to 200 (mm / h).

  Then, for each range, the flow value estimation unit 64 calculates the coefficient of the prediction formula of the flow value with respect to the rainfall intensity values in the plurality of divided regions by executing the multiple regression analysis process based on the read time series data. These coefficients are stored. The coefficient includes an intercept and an error. For each range, the flow rate estimation unit 64 estimates a flow rate value at a future time by calculating a prediction formula to which the stored coefficient is applied. The flow value estimation unit 64 outputs estimated flow value data of the calculated estimated flow value. That is, the flow rate estimation unit 64 calculates a coefficient in a prediction formula for each of a plurality of ranges divided according to rainfall intensity, and estimates a flow rate value at a future time for each range by calculating a prediction formula for each range. To do.

  As a result, when the degree of rainwater flow from the target area changes depending on the degree of rainfall in the target area, in other words, even when the coefficient of the prediction formula changes according to the degree of rain, the prediction of the rainwater flow rate is accurate. It can be carried out.

[Sixth Embodiment]
In a plurality of divided areas obtained by dividing the target area, it takes time to contribute to the flow rate from the target area as the divided area is farther from the place where the rainwater drainage facility 80 is installed. Therefore, the sixth embodiment is an example in which the flow value estimation unit also calculates a coefficient for the rain intensity value in the segmented region farther from the outflow point in the target region as the elapsed time in the rain event is longer. In other words, when the elapsed time in the rain event is short, the flow value estimation unit in the sixth embodiment calculates a coefficient for the rain intensity value in the segmented area close to the outflow location in the target area. The coefficient to be calculated is increased so as to widen the segment area from the location side.

  As the functional configuration diagram of the flow rate prediction apparatus according to the sixth embodiment, FIG. 2 showing the functional configuration of the flow rate prediction apparatus 60 according to the first embodiment is used. In the sixth embodiment, portions that are different from the first embodiment will be described, and descriptions of common portions will be omitted.

  The flow rate estimation unit 64 reads the rainfall intensity value data set and the time series data of the flow rate value data from one or more rainfall events from the storage unit 63. Then, when calculating the coefficient, the flow rate estimation unit 64 also calculates a coefficient for the rainfall intensity value in the segmented area farther from the outflow location in the target area as the elapsed time in the rain event is longer.

  Thereby, the load of coefficient calculation can be reduced and the processing time can be shortened without reducing the prediction accuracy of the rainwater flow rate.

  In addition, at least one configuration in the rainfall intensity value acquisition unit, the flow value acquisition unit, the storage unit, the flow value estimation unit, and the coefficient update unit in the flow rate prediction device according to each embodiment is separated as a device and used as a flow rate prediction system. It may be configured.

  Moreover, you may make it implement | achieve a part of function of the flow volume prediction apparatus 60 which is embodiment mentioned above with a computer. In this case, a flow rate prediction program for realizing the function is recorded on a computer-readable recording medium, the flow rate prediction program recorded on the recording medium is read by the computer system, and the computer system executes the program. It may be realized. This computer system includes an operating system (OS) and hardware of peripheral devices. The computer-readable recording medium is a portable recording medium such as a flexible disk, a magneto-optical disk, an optical disk, or a memory card, and a storage device such as a magnetic hard disk or a solid state drive provided in the computer system. Furthermore, a computer-readable recording medium dynamically holds a program for a short time, such as a computer network such as the Internet, and a communication line when transmitting a program via a telephone line or a cellular phone network. In addition, a server that holds a program for a certain period of time, such as a volatile memory inside a computer system serving as a server device or client in that case, may be included. Further, the above flow rate prediction program may be for realizing a part of the above-described functions, and further, realizing the above-described functions by a combination with a program already recorded in the computer system. May be.

  As described above in detail, according to the flow rate prediction device in each embodiment, rainwater from the target region at a future time based on the rainfall intensity value and the flow rate value measured at regular intervals for a rain event in the target region. By having the flow rate estimation unit for estimating the flow rate, the rainwater flow rate can be predicted with high accuracy by a simple method with a small amount of engineering work.

  As mentioned above, although some embodiment of this invention was described, these embodiment is shown as an example and is not intending limiting the range of 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.

  DESCRIPTION OF SYMBOLS 10 ... Rainwater pipe, 20 ... Drain pump, 30 ... Rainfall radar, 40 ... Signal processing device, 50 ... Distribution device, 60 ... Flow rate prediction device, 61 ... Rainfall intensity value acquisition unit, 62 ... Flow rate value acquisition unit, 63 ... Storage unit 64 ... flow rate estimation unit, 65 ... coefficient updating unit, 70 ... flow rate measuring device, 80 ... rain drainage facility

Claims (9)

In each of a plurality of divided areas that divide the target area, a rainfall intensity value acquisition unit that acquires a rainfall intensity value in a rain event every predetermined time in advance,
A flow value acquisition unit that acquires a flow value of rainwater flowing out of the target area in synchronization with an acquisition timing by the rainfall intensity value acquisition unit;
Based on the rainfall intensity value acquired by the rainfall intensity value acquisition unit and the flow rate value acquired by the flow rate acquisition unit, a flow value estimation unit that estimates a flow value at a future time of rainwater flowing out from the target area;
A flow rate prediction apparatus comprising: The flow value estimation unit calculates a coefficient of a prediction formula of a flow value with respect to a rainfall intensity value in the plurality of divided areas by executing a multiple regression analysis process, and calculates the prediction formula to which the coefficient is applied. Estimating a flow value at the future time;
The flow rate prediction apparatus according to claim 1. The rainfall intensity value acquisition unit normalizes the acquired rainfall intensity value corresponding to a plurality of ranges divided according to the rainfall intensity,
The flow rate prediction apparatus according to claim 1 or 2. The flow rate estimation unit calculates a coefficient in the prediction formula for each of a plurality of ranges divided according to rainfall intensity, and calculates the prediction formula for each range.
The flow volume prediction apparatus in any one of Claim 2 or Claim 3. The flow rate estimation unit also calculates a coefficient for a rain intensity value in a segmented area away from an outflow location in the target area, as the elapsed time in the rain event is longer.
The flow volume prediction apparatus as described in any one of Claims 2-4. A coefficient updating unit that updates the coefficient calculated by the flow rate estimation unit at a predetermined timing;
The flow rate prediction apparatus according to claim 2, further comprising: A rainfall intensity value acquisition step in which a rainfall intensity value acquisition unit acquires a rainfall intensity value in a rain event in advance every predetermined time in each of a plurality of divided areas into which the target area has been divided,
A flow value acquisition unit acquires a flow value of rainwater flowing out of the target area in synchronization with an acquisition timing in the rainfall intensity value acquisition step, and
Based on the rainfall intensity value acquired in the rainfall intensity value acquisition step and the flow rate value acquired in the flow value acquisition step, the flow value estimation unit calculates a flow value at a future time of rainwater flowing out from the target area. A flow value estimation step to be estimated;
A flow rate prediction method comprising: Computer
In each of a plurality of divided areas that divide the target area, a rainfall intensity value acquisition unit that acquires a rainfall intensity value in a rain event every predetermined time in advance,
A flow value acquisition unit that acquires a flow value of rainwater flowing out of the target area in synchronization with an acquisition timing by the rainfall intensity value acquisition unit;
Based on the rainfall intensity value acquired by the rainfall intensity value acquisition unit and the flow rate value acquired by the flow rate acquisition unit, a flow value estimation unit that estimates a flow value at a future time of rainwater flowing out from the target area;
Flow prediction program to function as. In each of a plurality of divided areas into which the target area is divided, a rainfall intensity value acquisition device that acquires a rainfall intensity value in a rain event every predetermined time in advance,
A flow value acquisition device that acquires the flow value of rainwater flowing out of the target area in synchronization with the acquisition timing by the rainfall intensity value acquisition device;
A flow value estimation device that estimates a flow value at a future time of rainwater flowing out from the target area, based on a rainfall intensity value acquired by the rainfall intensity value acquisition device and a flow value acquired by the flow value acquisition device;
A flow rate prediction system comprising:

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