JP6707749B1 - Reservoir failure prediction system, reservoir failure prediction method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a system for predicting a collapse of a reservoir. SOLUTION: This is a pond failure prediction system 1 for predicting collapse of a reservoir, and a predicted water level acquisition unit 12 for acquiring predicted water level data indicating the predicted water level of the reservoir, and a measurement for acquiring measured water level data indicating the water level of the reservoir. A pond failure prediction system 1 that includes a water level acquisition unit 14 and an analysis unit 16 that predicts the infiltration of a reservoir into a bank by analyzing the difference between the predicted water level data and the measured water level data. [Selection diagram] Figure 2

Description

The present invention relates to a method of predicting a reservoir failure.

A large amount of water may infiltrate the levee body of a pond due to heavy rain, etc., and the levee body may collapse and the pond may collapse. In such a case, the water level in the reservoir is often higher than in normal times, and if the reservoir collapses in such a state, a large amount of water will flow out at once, which may cause serious damage to the downstream area. Therefore, it is important to detect the possibility that the bank of the reservoir will collapse as soon as possible, and before that, for example, to evacuate the residents in the neighboring area safely.

However, in the past, there was no effective system for predicting the collapse of a reservoir.
The present invention has been made in view of such problems.

In order to solve the above problems, one aspect of the present invention is a pond failure prediction system for predicting a failure of a reservoir, a predicted water level acquisition unit that acquires predicted water level data indicating the predicted water level of the reservoir, and the A measurement water level acquisition unit that acquires measurement water level data indicating the water level, and an analysis unit that predicts water infiltration into the bank of the reservoir by analyzing the difference between the predicted water level data and the measurement water level data, It is a reservoir failure prediction system equipped with.

Further, another aspect of the present invention is a method executed by a computer system, which comprises a step of acquiring predicted water level data indicating a predicted water level of a reservoir, and a step of acquiring measured water level data indicating a water level of the reservoir. And a step of making a prediction regarding infiltration of the reservoir to the bank by analyzing the difference between the predicted water level data and the measured water level data.

Another aspect of the present invention is a program for causing a computer system to execute the above method.

It is a figure which shows an example of a change of the predicted water level, the measured water level, and the time permeation amount of water to the bank of a reservoir. It is a figure showing an example of composition of a reservoir failure prediction system concerning one embodiment of the present invention. It is a figure which shows an example of the hardware constitutions of the reservoir failure prediction system which concerns on one Embodiment of this invention. It is a flow figure showing an example of processing in a reservoir failure prediction system concerning one embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
(Structure of reservoir failure prediction system)
Since the reservoir failure prediction system according to the present embodiment is a monitoring target, the difference between the predicted water level of the reservoir, which is predicted from precipitation, etc., and the actual water level (referred to as “measured water level” in this specification) The integrated value of the difference is calculated. Then, the integrated value is regarded as the amount of water permeating into the bank of the reservoir, and the possibility of collapse of the reservoir is predicted. Here, the “reservoir” is a pond artificially created mainly for securing agricultural water.

FIG. 1 is a diagram showing an example of changes in the predicted water level and the measured water level at each time of the reservoir, and the change in the amount of time permeation of water into the bank of the reservoir. In Fig. 1, the difference between the predicted water level and the measured water level is very small until about 10:00, but after that, the difference between the two gradually increases. In this way, when there is a difference between the predicted water level and the actual measured water level for the pond that differs from normal, the difference between the two is not a prediction error, but was caused by the water infiltrating the bank of the reservoir. You can think of it as a difference. "Time permeation amount" in Figure 1 is the permeation amount of water into the bank of the reservoir per hour, calculated based on the integrated value of the difference between the predicted water level and the measured water level at each predicted time and measurement time. is there. In this way, by calculating the difference between the predicted water level of the reservoir and the measured water level that indicates the actual reservoir water level, or the integrated value of the difference, the infiltration of water into the bank of the reservoir is calculated. It becomes possible to judge that the risk of the collapse increases as the amount increases.

The configuration of the reservoir failure prediction system according to this embodiment will be described below. FIG. 2 is a diagram showing a configuration example of the reservoir failure prediction system according to the present embodiment. As shown in FIG. 2, the reservoir failure prediction system 1 according to the present embodiment includes a predicted water level acquisition unit 12, a measured water level acquisition unit 14, and an analysis unit 16.

The predicted water level acquisition unit 12 acquires predicted water level data indicating the predicted water level of the reservoir. The predicted water level can be predicted in consideration of the weather (for example, precipitation amount) at the time of and before the prediction time, the amount of water flowing into the reservoir from the surroundings, and the like. As an example, the predicted water level acquisition unit 12 can acquire the predicted water level data from an external computer system (apparatus) such as the water level prediction system of Japanese Patent No. 5654147. Note that the predicted water level may be a predicted water level that does not allow water to permeate the levee body (without considering penetration into the levee body), or may be derived from past data or empirical values, for example. The predicted water level may be based on the condition that the average amount of water that has been infiltrated into the bank is generated.

Further, the predicted water level data and the measured water level data acquired by the measured water level acquisition unit 14 described later are data representing the predicted water level and the measured water level at each time of a predetermined time interval. Measured water level data may be acquired in near real-time conditions (although some delay may be tolerated). The predicted time of the predicted water level and the measured time of the measured water level are preferably approximately the same time. The term “substantially the same time” means that the identities are not required until they completely match.

The measured water level acquisition unit 14 acquires measured water level data indicating the actual water level of the reservoir. In the present embodiment, as an example, a water level measuring instrument is installed in the pond because it is a monitoring target, and the measurement water level obtaining unit 14 obtains measurement water level data from the water level measuring instrument via a network or a recording medium.

The analysis unit 16 analyzes the difference between the predicted water level data and the measured water level data to predict the infiltration of water into the bank of the reservoir. For example, the analysis unit 16 predicts the amount of water permeating into the bank of the reservoir based on the integrated value of the difference between the predicted water level data and the measured water level data. That is, assuming that the permeation amount (permeation amount per time) of the reservoir at the time t=LV(t), the predicted water level=LV(t)pre, and the measured water level=LV(t)meas,

Is expressed as Therefore, the amount of water permeated into the bank of the reservoir between time T1 and time Tn is

Is expressed as In the example of FIG. 1, the permeation amount is represented by weight (ton:t), but the unit of the above formulas (1) and (2) is the water level (meter:m, etc.). The above formula is an example, and the difference and the integrated value of the difference may be calculated as the weight or the volume. Since the shape of the reservoir is usually known, the amount of water (cubic meter: m ³ ) is calculated from the bottom area (square meter: m ² ) × water level (m). For example, in the above formulas (1) and (2), assuming that the bottom area of the reservoir is B(m ² ), the permeation amount X(t) at time t and between time T1 and time Tn are as follows: Can be described as a calculation formula of the permeation amount (total amount) X (m ³ ) in the above.

Further, in these equations, the amount of water may be expressed in other units, where water 1 m ³ =1000 L (liter)=1 t.
The analysis unit 16 also determines the risk of collapse of the reservoir based on the difference between the predicted water level data and the measured water level data or the integrated value of the difference.

For example, the analysis unit 16 may determine that the reservoir breaks down (probability is high) when the difference between the predicted water level data and the measured water level data exceeds a predetermined threshold Vth1. As shown in Fig. 1, when the amount of water that permeates the bank of the pond increases due to heavy rainfall, the difference between the predicted water level and the measured water level widens. If there is no infiltration into the bank (or even if the infiltration amount is small), there is usually a prediction error between the two, but if the difference between the two becomes large to some extent, It is considered that the difference is caused by the increase in the amount of water permeating into the bank body. Further, how much the difference becomes (when the permeation amount becomes) and the risk of failure is increased can be determined from, for example, an empirical rule. Let Vth1 be the threshold value for determining that there is a risk of breakage,

It can be judged that there is a danger of a collapse at the time t.
Similarly, when the integrated value of the difference between the predicted water level and the measured water level becomes large to some extent, it can be determined that the risk of collapse is increasing. Let Vth2 be the threshold that is judged to be in danger of breaking,

It can be determined that there is a risk of collapse at time Tn. Note that these calculation formulas may also be expressed in the amount of water (m ³ ) or another unit as in the formulas (3) and (4). The same applies to the threshold values Vth1 and Vth2.

As to how to set the thresholds Vth1 and Vth2, for example, in a normal condition (a situation in which it can be assumed that water does not permeate the bank of the reservoir, or when the permeation amount is small (no precipitation or In the case where it is within a predetermined range)), the range of the prediction error (or the range of the integrated value of the prediction error) between the two is calculated based on the measured water level and the predicted water level of the reservoir, and the error range (or A limit value that deviates from the range of the integrated value of the prediction error) may be set as the threshold value. Further, for example, an average value or a maximum value (or a value larger than these) of both errors (or erroneous integrated values) during normal times may be set as the threshold value. Then, when a difference exceeding this threshold value is detected, it may be determined that the reservoir breaks down (there is a high possibility).

Further, a plurality of thresholds may be set for the difference between the predicted water level data and the measured water level data or an integrated value of the differences, and the risk of reservoir failure may be determined in stages. For example, if the difference between the predicted water level data and the measured water level data or the integrated value of the differences exceeds the first threshold value, it is determined that there is a possibility that the reservoir will be destroyed (the possibility of failure to neighboring residents). If the difference or the integrated value of the differences exceeds the second threshold value, which is a value larger than the first threshold value, it is determined that there is a high possibility that the reservoir will collapse (neighborhood). If the difference or the accumulated value of the differences exceeds the third threshold, which is even larger, such as notifying the residents of evacuation preparation), it is determined that there is a high possibility that the reservoir will be destroyed (instruct neighboring residents to evacuate). Etc.). Further, based on such a stepwise judgment, the notification to the manager or the neighboring residents may be carried out via e-mail or web page.

In addition, the analysis unit 16 may be configured to predict inundation damage when the reservoir breaks, based on the measured water level data. The prediction of inundation damage when a reservoir breaks is based on the amount of water that flows out when the reservoir breaks. The following two can be considered as this amount of water.
(A) Inundation volume of the reservoir at the time of the collapse (b) Inundation volume of the reservoir at the time of the collapse + Infiltration amount of water that has penetrated into the dam body of the reservoir by the time of the collapse Here, (a) Inundation volume of the reservoir at Tn at the time of the collapse W can be represented by the following formula by the measured water level LV(t)meas and the bottom area B of the reservoir.

In addition, (b) the amount of water inundated by the reservoir + the amount of infiltration into the bank at the time of failure Tn can be expressed by the following formula.

More specifically, for example, the predicted water level data and the measured water level data at the predicted time and the measured time at the predetermined time interval are acquired by the predicted water level acquisition unit 12 and the measured water level acquisition unit 14, and the acquired data are stored in the reservoir. The data is sequentially stored in a storage area such as a hard disk of the failure prediction system 1. The analysis unit 16 calculates the difference or the integrated value of the differences between the stored data each time the data is acquired and compares it with each threshold value to determine the risk of collapse of the reservoir. In addition, it is also possible to use the measured water level data (and the infiltration amount data) to predict the inundation damage at the time of reservoir failure using a simulator program or the like.

The configuration of the pond failure prediction system 1 described above is merely an example, and the present invention is not limited to this.
(Hardware configuration)
The configuration of the pond failure prediction system 1 described above can be realized by the same hardware configuration as a general computer device. FIG. 3 is a diagram illustrating an example of a hardware configuration of the reservoir failure prediction system 1. As an example, the computer device 20 shown in FIG. 3 includes a processor 21, a RAM (Random Access Memory) 22, a ROM (Read Only Memory) 23, a built-in hard disk device 24, an external hard disk device, a CD, a DVD. , A removable memory 25 such as a USB memory, a memory stick, or an SD card, and an input/output user interface 26 (keyboard, mouse, touch panel, speaker, microphone, lamp, etc.) for the user to exchange data with the computer device 20, A wired/wireless communication interface 27 capable of communicating with other computer devices and a display 28 are provided. The functions of the reservoir failure prediction system 1 according to the present embodiment are described above, for example, in that the processor 21 reads a program previously stored in the hard disk device 24, the ROM 23, the removable memory 25, or the like into a memory such as the RAM 22 and performs processing. It can be realized by executing the program while appropriately reading the data from the hard disk device 24, the ROM 23, the removable memory 25, and the like.

The reservoir failure prediction system 1 may be configured as a single computer device or may be configured by a plurality of computer devices. In the latter case, the functions of the above-described storage pond failure prediction system 1 are distributedly realized by a plurality of computer devices, and each computer device has the same or similar configuration as the computer device 20 shown in FIG. May be provided.

The hardware configuration shown in FIG. 3 is merely an example, and the present invention is not limited to this.
(Processing flow)
FIG. 4 is a flowchart showing an example of processing in the reservoir failure prediction system according to the present embodiment.

In step S102, the predicted water level acquisition unit 12 acquires predicted water level data. In addition, in step S104, the measured water level acquisition unit 14 acquires measured water level data. The following is assumed for the predicted water level data and the measured water level data. That is, the predicted water level and the measured water level are predicted and measured at each time of a predetermined time interval, the predicted time and the measured time of these data are approximately the same time, and the predicted water level data and the measured water level data are almost real-time. It is desirable to be acquired in a state close to. The processes of steps S102 and S104 can be processed in parallel. The acquired predicted water level data and measured water level data may be stored in a storage area such as a hard disk of the reservoir failure prediction system.

In step S106, the analysis unit 16 analyzes the difference between the predicted water level data acquired in steps S102 and S104 or the integrated value of the difference. For example, the analysis unit 16 predicts the amount of infiltration into the bank of the reservoir based on the integrated value of the difference between the predicted water level data and the measured water level data. Further, for example, when the difference between the predicted water level data and the measured water level data or the integrated value of the differences exceeds a predetermined threshold value, the analysis unit 16 determines that there is a high possibility of reservoir failure. This step may be executed, for example, every time the predicted water level data and the measured water level data are acquired in steps S102 and S104. Alternatively, the process of this step may be executed when a predetermined number of predicted water level data and measured water level data are acquired.

In step S108, the analysis unit 16 predicts inundation damage when the reservoir breaks, based on the integrated value of the difference between the predicted water level data and the measured water level data. Note that this step may be executed every time the predicted water level data and the measured water level data are acquired in steps S102 and S104, or when a predetermined number of predicted water level data and measured water level data are acquired. The processing of this step may be executed.

The above process can be repeated a plurality of times until the prediction process is completed.
Up to this point, one embodiment of the present invention has been described, but it goes without saying that the present invention is not limited to the above embodiment and may be implemented in various different forms within the scope of the technical idea thereof.

Moreover, the scope of the present invention is not limited to the exemplary embodiments shown and described, but also includes all embodiments providing equivalent effects to those intended by the present invention. Furthermore, the scope of the invention is not limited to the combination of inventive features defined by each claim, but can be defined by any desired combination of specific features of each disclosed feature. ..

1 Reservoir failure prediction system 12 Predicted water level acquisition unit 14 Measured water level acquisition unit 16 Analysis unit 20 Computer device 21 Processor 22 RAM
23 ROM
24 hard disk device 25 removable memory 26 input/output user interface 27 communication interface 28 display

Claims (6)

A pond failure prediction system for predicting the failure of a pond,
A predicted water level acquisition unit that acquires predicted water level data indicating the predicted water level of the reservoir,
A measurement water level acquisition unit that acquires measurement water level data indicating the water level of the reservoir,
By analyzing the difference between the predicted water level data and the measured water level data, an analysis unit that predicts the infiltration of water into the bank of the reservoir,
Equipped with
The reservoir failure prediction system , wherein the analysis unit predicts the amount of water permeating into the bank of the reservoir based on the integrated value of the difference between the predicted water level data and the measured water level data . A pond failure prediction system for predicting the failure of a pond,
A predicted water level acquisition unit that acquires predicted water level data indicating the predicted water level of the reservoir,
A measurement water level acquisition unit that acquires measurement water level data indicating the water level of the reservoir,
By analyzing the difference between the predicted water level data and the measured water level data, an analysis unit that predicts the infiltration of water into the bank of the reservoir,
Equipped with
A reservoir failure prediction system , wherein the analysis unit predicts inundation damage at the time of reservoir failure based on the measured water level data . The storage pond failure prediction system according to claim 1 or 2, wherein the analysis unit determines a risk of failure of the storage pond based on a difference between the predicted water level data and the measured water level data or an integrated value of the difference. .. A method performed by a computer system, comprising:
Acquiring the predicted water level data indicating the predicted water level of the reservoir, and
Obtaining measured water level data indicating the water level of the reservoir,
Analyzing the difference between the predicted water level data and the measured water level data to make a prediction regarding water infiltration into the bank of the reservoir,
Equipped with
The step of predicting the infiltration of water into the bank of the reservoir, based on the integrated value of the difference between the predicted water level data and the measured water level data, to predict the amount of water infiltration into the bank of the reservoir, Reservoir failure prediction method. A method performed by a computer system, comprising:
Acquiring the predicted water level data indicating the predicted water level of the reservoir, and
Obtaining measured water level data indicating the water level of the reservoir,
Analyzing the difference between the predicted water level data and the measured water level data to make a prediction regarding water infiltration into the bank of the reservoir,
Equipped with
The method of predicting inundation of a reservoir according to the step of predicting the infiltration of water into the bank of the reservoir based on the measured water level data . A program for causing a computer system to execute the method according to claim 4 or 5.

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