WO2020108319A1

WO2020108319A1 - Reservoir water seepage prediction method and device, computer device and storage medium

Info

Publication number: WO2020108319A1
Application number: PCT/CN2019/118595
Authority: WO
Inventors: 陈华勇
Original assignee: 深圳春沐源控股有限公司
Priority date: 2018-11-30
Filing date: 2019-11-14
Publication date: 2020-06-04
Also published as: CN109767027A

Abstract

Provided by the present invention is a reservoir water seepage prediction method, comprising: obtaining reservoir attributes of a target reservoir and expected meteorological information of the target reservoir from the current time to a target time; inputting the expected meteorological information into a preset precipitation prediction model to obtain an expected period of precipitation for the target reservoir from the current time to the target time; calculating an expected water level of the target reservoir by means of the expected period of precipitation, the reservoir attributes of the target reservoir and the current water level of the target reservoir; determining the expected water seepage amount of the target reservoir at the target time according to a relationship model for the water seepage amount, the water level and the time as well as the expected water level; and if the expected water seepage amount reaches a first water seepage amount threshold, sending an early warning message. By means of the present invention, the water seepage amount of the reservoir may be predicted quickly, and the water seepage condition of the reservoir may be known in time.

Description

Reservoir seepage amount prediction method, device, computer device and storage medium

This application requires the priority of the Chinese patent application submitted to the Chinese Patent Office on November 30, 2018, with the application number 201811456717.1 and the invention titled "Reservoir seepage prediction method and device", the entire contents of which are incorporated by reference in this application .

Technical field

The invention relates to the technical field of water conservancy engineering, in particular to a method, device, computer device and storage medium for predicting the seepage volume of a reservoir.

Background technique

Reservoir is a kind of water conservancy engineering building that blocks flood water and regulates water flow, and can be used for irrigation, power generation and flood control. Reservoir leakage (reservoir seepage) is a common problem encountered during operation and management. Reservoir leakage can cause loss of water flow, making the reservoir function unable to exert normal benefits, and endangering the safety of the dam. , Refers to the water retaining structure of the reservoir, and the dam is part of the reservoir. In the prior art, methods such as isotope, mineral detection, and weir observation seepage are often used to obtain the seepage status and predict the seepage. These methods require more time and labor, and the efficiency is not high.

Summary of the invention

In view of the above, it is necessary to provide a method, device, computer device and storage medium for predicting the seepage volume of the reservoir, which can quickly predict the seepage volume of the reservoir and help to timely understand the seepage status of the reservoir.

The invention provides a method for predicting the seepage volume of a reservoir. The method includes:

Obtain the reservoir attribute of the target reservoir and the expected meteorological information of the target reservoir from the current time to the target time;

Input the expected meteorological information into a preset precipitation prediction model to obtain the expected precipitation of the target reservoir from the current time to the target time;

Calculating the expected water level height of the target reservoir by the precipitation during the expected period, the reservoir attribute of the target reservoir and the current water level height of the target reservoir;

Determine the expected seepage volume of the target reservoir at the target time according to the relationship model between the seepage volume and the water level height and time, and the expected water level height;

If the expected seepage amount reaches the first seepage amount threshold, an early warning message is sent.

In an optional embodiment of the present invention, the method further includes:

Obtaining the relationship model between the seepage volume and the water level height and time includes:

Obtain the historical seepage volume and corresponding historical water level height of the target reservoir at historical times;

Data fitting is performed on the historical time, the historical water seepage amount and the historical water level height to obtain a relationship model between the water seepage amount and the water level height and time.

In an optional embodiment of the present invention, the relationship model between the seepage volume and the water level height and time is:

Where Q is the expected seepage volume of the target reservoir, h is the expected water level height of the target reservoir, l is the dead water level height of the target reservoir, and t is the target time, the The target time is the month.

In an optional embodiment of the present invention, if the expected seepage amount reaches the first seepage amount threshold, sending the warning message includes:

If the expected seepage amount reaches the first seepage amount threshold, an early warning message that the cause of the leakage of the target reservoir is a dam leakage is sent.

If the expected water seepage amount does not reach the first water seepage threshold, determine whether the expected water seepage reaches the second water seepage threshold;

If yes, adjust the frequency of predicting the seepage volume of the target reservoir.

The invention also provides a device for predicting the seepage volume of a reservoir. The device includes:

An acquisition module for acquiring the reservoir attribute of the target reservoir and the expected meteorological information of the target reservoir from the current time to the target time;

An input module, configured to input the expected meteorological information into a preset precipitation prediction model to obtain the expected precipitation of the target reservoir from the current time to the target time;

A first calculation module, configured to calculate the expected water level height of the target reservoir from the expected precipitation, the reservoir attribute of the target reservoir, and the current water level height of the target reservoir;

The second calculation module is used to determine the expected seepage volume of the target reservoir at the target time according to the relationship model between the seepage volume and the water level height and time, and the expected water level height;

The early warning module is used to send an early warning message if the expected water seepage reaches the first water seepage threshold.

In an optional embodiment of the present invention, the device further includes a model acquisition module, which is used to acquire a model of the relationship between the seepage volume and the height and time of the water level;

The model acquisition module is specifically used for:

In an optional embodiment of the present invention, the early warning module is specifically used to:

In an optional embodiment of the present invention, the device further includes an adjustment module, and the adjustment module is used to:

The invention also provides a computer device. The computer device includes:

Memory, storing at least one instruction; and

The processor executes instructions stored in the memory to implement the reservoir water seepage prediction method.

The present invention also provides a computer-readable storage medium that stores at least one instruction. When the at least one instruction is executed by a processor, the method for predicting the seepage volume of a reservoir described in any embodiment is implemented.

It can be seen from the above technical solutions that the present invention obtains the target meteorological information from the current time to the target time by acquiring the reservoir properties of the target reservoir and the expected meteorological information from the current time to the target time; The expected precipitation of the target reservoir from the current time to the target time; calculating the expected water level of the target reservoir from the expected period of precipitation, the reservoir attribute of the target reservoir and the current water level height of the target reservoir Height; according to the relationship model between seepage volume and water level height and time, and the expected water level height, determine the expected seepage volume of the target reservoir at the target time; if the expected seepage volume reaches the first seepage threshold, send Early warning message. The present invention obtains the expected water level height up to the target time through the precipitation during the expected period, and obtains the expected water seepage amount based on the expected water level height, thereby realizing the expected water seepage amount of the target reservoir at the target time without manual observation or mineral detection. The purpose of quickly predicting the leakage of the reservoir is realized, and the reminder is given when the expected leakage reaches the first threshold of leakage, which is helpful for the water conservancy personnel to timely understand the leakage of the reservoir and take appropriate preventive measures.

BRIEF DESCRIPTION

FIG. 1 is a flowchart of a method for predicting a seepage volume of a reservoir according to an embodiment of the present invention;

2 is a block diagram of a device for predicting the seepage volume of a reservoir according to an embodiment of the present invention;

3 is a schematic structural diagram of a computer device of a preferred embodiment of a method for predicting the seepage volume of a reservoir according to the present invention.

detailed description

The technical solutions in the embodiments of the present invention will be described clearly and completely in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

In order to make the above objects, features and advantages of the present invention more obvious and understandable, the present invention will be further described in detail in conjunction with the accompanying drawings and specific embodiments.

As shown in FIG. 1, FIG. 1 is a flowchart of a method for predicting a reservoir seepage amount according to an embodiment of the present invention. According to different requirements, the order of the steps in the flowchart can be changed, and some steps can be omitted.

S10. Acquire the reservoir attribute of the target reservoir and the expected meteorological information of the target reservoir from the current time to the target time.

In this embodiment, the target reservoir is the reservoir for which the seepage volume is to be predicted. The reservoir properties of the target reservoir may include but are not limited to one or more of the following: the cross-sectional area of the reservoir, the relationship curve between the water level and volume of the reservoir, and the Length, width of the crest of the reservoir, width of the bottom of the reservoir, height of the reservoir, capacity of the reservoir.

The current time is the time obtained in real time, and the target time refers to the time to be predicted. The expected meteorological information of the target reservoir from the current time to the target time is the expected meteorological information of the location of the target reservoir from the current time to the target time.

In this embodiment, the target time may be a time period (eg, a quarter, a month, a week, a day). For example, if the target reservoir's seepage volume in March is to be predicted, the target time is March; or, if the target reservoir's seepage volume is predicted half a year later, the target time is the current time plus six months.

In this embodiment, the expected weather information may include but is not limited to one or more of the following: temperature, humidity, weather, wind direction, weather duration.

S20. Input the expected meteorological information into a preset precipitation prediction model to obtain the expected precipitation of the target reservoir from the current time to the target time.

In this embodiment, the preset precipitation prediction model may be a model for predicting precipitation obtained through training. Precipitation refers to liquid or solid (after melting) water that falls from the sky to the ground without evaporation, The depth of leakage and loss accumulation on the horizontal surface.

The expected precipitation from the current time to the target time obtained by this embodiment may be the cumulative possible precipitation from the current time to the target time, that is, what is the total possible precipitation from the current time to the target time, for example, the current time It is January 1st and the expected time is February 1st, then the expected precipitation during the period can represent the monthly precipitation from January to February.

Alternatively, the expected precipitation from the current time to the target time can also be the expected actual cumulative precipitation from the current time to the target time, which means that the total possible precipitation from the current time to the target time after evaporation and loss during this period The cumulative precipitation within.

The precipitation prediction model can be obtained by the following methods:

(1) Obtain a pre-established precipitation prediction model, which is based on a neural network model;

Among them, the neural network model may be a back propagation neural network (back propagation networdk, BP neural network).

The pre-established precipitation prediction model is a functional formula containing unknown parameters.

(2) Obtain a training set for training the precipitation prediction model;

Wherein, the training set may be multiple sets of data sets containing input data corresponding to output data. For example, the reservoir attributes and the historical meteorological information of the reservoir at a certain period (such as time A to time B) are input data, and the cumulative actual precipitation of the reservoir at that time (such as time A to time B) is output data (this data can be Obtained by the actual precipitation data from the historical weather data up to the time B)/or cumulative possible precipitation (the data can be obtained by adding the precipitation during the period from the historical weather data), according to the history in different periods Meteorological data can obtain multiple sets of data sets containing input data corresponding to output data.

By training different data, the model can make different predictions. For example, when the output data in the training data is the cumulative actual precipitation, the precipitation between the current time predicted by the precipitation prediction model and the target time is the expected actual cumulative precipitation; when the output data in the training data accumulates the possible precipitation The precipitation amount predicted by the precipitation prediction model from the current time to the target time is the cumulative possible precipitation.

(3) Train the precipitation prediction model by using the training set and the neural network learning algorithm to obtain a trained precipitation prediction model.

The training process is based on the training set and the neural network model learning algorithm (for example, gradient descent algorithm) to calculate the value of the unknown parameter in the pre-established precipitation prediction model, so as to obtain the trained precipitation prediction model.

S30. Calculate the expected water level height of the target reservoir from the expected precipitation, the reservoir attribute of the target reservoir, and the current water level height of the target reservoir.

The current water level height of the target reservoir can be obtained according to real-time detection, and the current water level height of the target reservoir is the actual water level height of the target reservoir.

In this embodiment, after obtaining the actual reservoir height of the target reservoir, the reservoir attribute of the target reservoir, and the expected period of precipitation of the target reservoir, the cross-sectional area of the reservoir (including Height cross-sectional area) to determine the current water level height cross-sectional area, and then based on the expected period of precipitation and the current water level height cross-sectional area, calculate how much new water volume can be obtained according to the expected period of precipitation, and finally find the reservoir properties The included water level and volume relationship curve determines how much the newly added water volume can make the water level reach, that is, the expected water level height of the target reservoir.

The expected water level height obtained through this embodiment is the expected water level height of the target reservoir at the target time.

S40: Determine the expected seepage volume of the target reservoir at the target time according to the relationship model between the seepage volume and the water level height and time, and the expected water level height.

In this embodiment, the relationship model between the seepage volume and the water level height and time may also be a model established in advance.

Further, the relationship model between the seepage volume and the water level height and time can also be obtained by the following method:

(1) Obtain the historical seepage volume and corresponding historical water level height of the target reservoir at historical time;

(2) Perform data fitting on the historical time, the historical seepage amount and the historical water level height to obtain a relationship model between the seepage amount and the water level height and time.

The historical seepage amount may be the monthly seepage amount in the past 5 years or 10 years, and the corresponding water level height in the past 5 years or 10 years each month; The amount of water seepage and the corresponding water level height per day/week in the past 2 years.

The data fitting of historical time, historical seepage and historical water level height can be: drawing a rectangular coordinate system through a graphics drawing program to obtain multiple discrete data in a planar rectangular coordinate system, for example, the rectangular coordinate system takes time as the horizontal axis 3. The water level height is the vertical axis. According to a number of discrete data (different water level heights at different times) in the rectangular coordinate system, the first function relationship between water level height and time is established by fitting; The second functional relationship is based on the first functional relationship and the second functional relationship to establish a third functional relationship between water level height, time, and seepage volume. The third functional relationship is a relationship model between seepage volume, water level height, and time.

The relationship model between the seepage volume and the height and time of the water level obtained by this embodiment is obtained through the method of historical data through mathematical statistics, and has a certain accuracy.

Preferably, if the seepage volume and the corresponding water level height are obtained using the month as a time unit to perform data fitting, the obtained relationship model between the seepage volume and the water level height and time may be:

Where, in formula (1), Q is the expected seepage volume of the target reservoir, h is the expected water level of the target reservoir, l is the dead water level of the target reservoir, and t is the The target time, which is the month.

Among them, the target dead water level refers to the lowest water level that allows the target reservoir water level to decrease under normal operating conditions. Generally, the reservoir can not be lower than the dead water level during normal operation. The dead water level of different reservoirs is different. Therefore, the value of l can be set in advance according to the actual situation.

S50: If the expected seepage amount reaches the first seepage amount threshold, send an early warning message.

Wherein, the first water seepage threshold may be preset according to actual needs, and the first water seepage threshold is used to determine whether the expected water seepage of the target reservoir is excessive. When the expected seepage volume reaches the first seepage threshold, it indicates that the target reservoir may have more expected seepage. When the expected seepage volume does not reach the first seepage threshold, it indicates that the target reservoir is within a reasonable range. Hazard and impact on the reservoir.

In the embodiment of the present invention, an early warning message can be sent to the water conservancy engineer's mobile phone, computer, or other communication equipment to remind the water conservancy engineer to take preventive measures (such as enhanced protection) according to the situation of excessive water seepage that may occur.

Further, in another embodiment of the present invention, if the expected seepage amount reaches the first seepage amount threshold, sending the warning message includes:

In this embodiment, when the expected seepage amount reaches the first seepage amount threshold, providing the hydraulic engineering personnel with more valuable early-warning information is conducive to improving the efficiency of the water engineering personnel in handling the problem.

Since the expected seepage volume is calculated by the expected water level height, it shows that there is a certain correlation between the seepage volume and the water level height, and there is a positive correlation between the seepage volume of the target reservoir and the water level height. The positive correlation between the seepage volume of the target reservoir and the water level height means that when the water level height increases, the seepage volume increases, and when the water level height decreases, the seepage volume decreases. For example, if the seepage volume model of the target reservoir is formula (1), when the time is consistent, if the expected water level height h increases, the expected seepage volume Q of the target reservoir increases.

The causes of reservoir leakage are mainly divided into dam body leakage, dam foundation leakage, and dam shoulder leakage. When the water level changes, the amount of water contacting the dam body directly changes, and at this time, the amount of water leakage changes. The quantity change is related to the height of the water level. It is determined that the seepage mainly occurs in the dam body, that is, the cause of the reservoir leakage is the cause of the dam body. Therefore, the warning message that the cause of the leakage of the target reservoir is the dam body leakage can be sent.

Further, since the dam body is usually protected by the panel anti-leakage system, an early warning message for processing the panel anti-leakage system can also be sent.

Further, in another embodiment of the present invention, the method further includes:

In this embodiment, adjusting the frequency of predicting the seepage volume of the target reservoir specifically increases the frequency of predicting the seepage volume of the target reservoir, that is, shortens the detection time of the target seepage volume. For example, it was originally to predict the seepage volume of the target reservoir every 6 months. If the expected seepage volume is greater than the second seepage threshold and less than the first seepage threshold, it will be adjusted to the expected seepage of the target reservoir every 3 months. Forecast.

The second water seepage threshold may be set according to actual needs, and the second water seepage threshold is less than the first water seepage threshold.

Optionally, the second seepage threshold may be a preset multiple of the current seepage (the multiple may be determined according to actual needs), and the second seepage threshold may be used to determine whether the expected seepage is much larger than the current seepage. If so, it indicates that the target reservoir may have the risk of excessive seepage. Adjusting the frequency of the target reservoir's seepage volume prediction is helpful to find out whether the target reservoir's seepage volume exceeds the first seepage volume threshold for early warning.

In this embodiment, by predicting the seepage volume and then adjusting the frequency of predicting the seepage volume of the target reservoir, a perfect reservoir seepage warning mechanism can be established to improve the stability and safety of the reservoir during operation.

The method for predicting the seepage amount of a reservoir provided by the present invention obtains the said meteorological information of the target reservoir from the current time to the target time by entering the expected meteorological information from the current time to the target time; The expected precipitation of the target reservoir from the current time to the target time; calculating the expected water level of the target reservoir from the expected period of precipitation, the reservoir attribute of the target reservoir and the current water level height of the target reservoir Height; according to the relationship model between seepage volume and water level height and time, and the expected water level height, determine the expected seepage volume of the target reservoir at the target time; if the expected seepage volume reaches the first seepage threshold, send Early warning message. The present invention obtains the expected water level height up to the target time through the precipitation during the expected period, and obtains the expected water seepage amount based on the expected water level height, so as to obtain the expected water seepage amount of the target reservoir at the target time without manual observation or mineral detection. The purpose of quickly predicting the leakage of the reservoir is realized, and the reminder is given when the expected leakage reaches the first threshold of leakage, which is helpful for the water conservancy personnel to timely understand the leakage of the reservoir and take appropriate preventive measures.

As shown in FIG. 2, FIG. 2 is a functional block diagram of a device for predicting a seepage volume of a reservoir according to an embodiment of the present invention. The reservoir water seepage prediction device includes an acquisition module 210, an input module 220, a first calculation module 230, a second calculation module 240, and an early warning module 250. The module referred to in the present invention refers to a series of computer program segments that can be executed by a processor of a computer device (such as a server) and can perform a fixed function, and are stored in a memory of the computer device. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

The obtaining module 210 is used to obtain the reservoir attribute of the target reservoir and the expected meteorological information of the target reservoir from the current time to the target time.

The current time is the time obtained in real time, and the target time refers to the time to be predicted. The expected meteorological information of the target reservoir from the current time to the target time is the expected meteorological information of the location of the target reservoir from the current time to the target time. In this embodiment, the target time may be a time period (eg, a quarter, a month, a week, a day). For example, if the target reservoir's seepage volume in March is to be predicted, the target time is March; or, if the target reservoir's seepage volume is predicted half a year later, the target time is the current time plus six months.

The input module 220 is configured to input the expected meteorological information into a preset precipitation prediction model to obtain the expected precipitation of the target reservoir from the current time to the target time.

In this embodiment, the preset precipitation prediction model may be a model obtained by training to predict the precipitation of the reservoir. The precipitation refers to the liquid or solid (after melting) water that has landed from the sky to the ground, without The depth of evaporation, leakage, and loss accumulation on the horizontal surface.

The precipitation prediction model can be obtained through the following model building module (not marked in the drawings), which is used to:

(1) Obtain a pre-established precipitation prediction model, and the precipitation prediction model is based on a neural network model;

(2) Obtain a training set for training the precipitation prediction model;

The first calculation module 230 is configured to calculate the expected water level height of the target reservoir based on the expected precipitation, the reservoir attribute of the target reservoir, and the current water level height of the target reservoir.

The second calculation module 240 is used to determine the expected seepage amount of the target reservoir at the target time according to the relationship model between the seepage amount and the water level height and time, and the expected water level height.

Further, the model of the relationship between the seepage volume and the height and time of the water level can also be acquired through a model acquisition module (not shown in the drawings). The model acquisition module is used to:

Obtain the historical seepage volume and corresponding historical water level height of the target reservoir at historical times; and

Data fitting is performed on the historical time, the historical seepage volume and the historical water level height to obtain a relationship model between the seepage volume and the water level height and time.

Preferably, if the seepage volume and the corresponding water level height are obtained by using the month as the time unit for data fitting, the obtained relationship model between the seepage volume and the water level height and time is:

The early warning module 250 sends an early warning message if the expected water seepage reaches the first water seepage threshold.

Further, in another embodiment of the present invention, the early warning module is specifically used for:

In this embodiment, when the expected seepage amount reaches the first seepage amount threshold, providing the water conservancy engineer with more valuable early warning information is conducive to improving the efficiency of the water engineer in handling the problem.

The causes of reservoir leakage are mainly divided into dam body leakage, dam foundation leakage, and dam shoulder leakage. When the water level changes, the amount of water contacting the dam body directly changes, and at this time, the amount of water leakage changes. The change in quantity is related to the height of the water level. It can be determined that the seepage mainly occurs in the dam, that is, the cause of the reservoir leakage is the cause of the dam. Therefore, the warning message that the cause of the leakage of the target reservoir is the dam leakage can be sent.

Further, in another embodiment of the present invention, the device further includes an adjustment module (not shown in the drawings), the adjustment module is used for:

The reservoir seepage amount prediction device provided by the present invention obtains the reservoir attribute of the target reservoir and the expected meteorological information of the target reservoir from the current time to the target time through an acquisition module; the input module inputs the expected meteorological information to a preset precipitation prediction model To obtain the expected precipitation of the target reservoir from the current time to the target time; the first calculation module passes the expected precipitation, the reservoir attribute of the target reservoir and the current water level of the target reservoir Calculate the expected water level height of the target reservoir; the second calculation module determines the expected water seepage amount of the target reservoir at the target time according to the relationship model between the seepage amount and the water level height and time, and the expected water level height; the early warning module If the expected seepage amount reaches the first seepage amount threshold, an early warning message is sent. The present invention obtains the expected water level height up to the target time through the precipitation during the expected period, and obtains the expected water seepage amount based on the expected water level height, thereby realizing the expected water seepage amount of the target reservoir at the target time without manual observation or mineral detection. The purpose of quickly predicting the leakage of the reservoir is realized, and the reminder is given when the expected leakage reaches the first threshold of leakage, which is helpful for the water conservancy personnel to timely understand the leakage of the reservoir and take appropriate preventive measures.

As shown in FIG. 3, it is a schematic structural diagram of a computer device for implementing a preferred embodiment of a method for predicting reservoir seepage. The computer device includes at least one sending device 31, at least one memory 32, at least one processor 33, at least one receiving device 34, and at least one communication bus. Wherein, the communication bus is used to implement connection communication between these components.

The computer device is a device that can automatically perform numerical calculation and/or information processing according to a preset or stored instruction, and its hardware includes but is not limited to a microprocessor, an application specific integrated circuit (Application Specific Integrated Circuit, ASIC) , Programmable gate array (Field-Programmable Gate Array, FPGA), digital processor (Digital Signal Processor, DSP), embedded equipment, etc. The computer device may also include network equipment and/or user equipment. The network equipment includes but is not limited to a single network server, a server group composed of multiple network servers, or a cloud composed of a large number of hosts or network servers based on cloud computing (Cloud Computing), where cloud computing is distributed computing One is a super virtual computer composed of a group of loosely coupled computers.

The computer device may be, but not limited to, any electronic product that can interact with a user through a keyboard, a touchpad, or a voice control device, such as a tablet computer, a smart phone, or a personal digital assistant (Personal Digital Assistant, PDA), smart wearable devices, camera equipment, monitoring equipment and other terminals.

The network where the computer device is located includes, but is not limited to, the Internet, wide area network, metropolitan area network, local area network, virtual private network (Virtual Private Network, VPN), etc.

Wherein, the receiving device 34 and the sending device 31 may be a wired sending port, or may be a wireless device, for example, including an antenna device, for performing data communication with other devices.

The memory 32 is used to store program codes. The memory 32 may be a circuit with a storage function in an integrated circuit that does not have a physical form, such as a FIFO (First In First Out). Alternatively, the memory 32 may also be a physical memory, such as a memory stick, TF card (Trans-flash Card), smart media card (smart media card), secure digital card (secure digital card), flash memory card (flash card) and other storage devices, etc.

The processor 33 may include one or more microprocessors and digital processors. The processor 33 can call the program code stored in the memory 32 to perform related functions. For example, each unit described in FIG. 3 is a program code stored in the memory 32 and executed by the processor 33 to implement a method for predicting the amount of water seepage from a reservoir. The processor 33 is also called a central processing unit (CPU, Central Processing Unit), which is a very large-scale integrated circuit, a computing core (Core) and a control core (Control Unit).

In the several embodiments provided by the present invention, it should be understood that the disclosed system, device, and method may be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the module is only a division of logical functions, and there may be other divisions in actual implementation.

The modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical units, that is, they may be located in one place or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware, or in the form of hardware plus software function modules.

It will be apparent to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-limiting, the scope of the present invention is defined by the appended claims rather than the above description, and is therefore intended to fall within the claims All changes within the meaning and scope of the equivalent requirements are included in the present invention. Any reference signs in the claims should not be considered as limiting the claims involved. In addition, it is clear that the word "include" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the system claims can also be implemented by one unit or device through software or hardware. The second-class words are used to denote names and do not denote any particular order.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be Modifications or equivalent replacements are made without departing from the spirit and scope of the technical solutions of the present invention.

Claims

A method for predicting reservoir seepage, characterized in that the method includes:

Obtain the reservoir attribute of the target reservoir and the expected meteorological information of the target reservoir from the current time to the target time;

Input the expected meteorological information into a preset precipitation prediction model to obtain the expected precipitation of the target reservoir from the current time to the target time;

Calculating the expected water level height of the target reservoir by the precipitation during the expected period, the reservoir attribute of the target reservoir and the current water level height of the target reservoir;

Determine the expected seepage volume of the target reservoir at the target time according to the relationship model between the seepage volume and the water level height and time, and the expected water level height;

If the expected seepage amount reaches the first seepage amount threshold, an early warning message is sent.
The method for predicting the seepage volume of a reservoir according to claim 1, wherein the method further comprises:

Obtaining the relationship model between the seepage volume and the water level height and time includes:

Obtain the historical seepage volume and corresponding historical water level height of the target reservoir at historical times;

Data fitting is performed on the historical time, the historical water seepage amount and the historical water level height to obtain a relationship model between the water seepage amount and the water level height and time.
The method for predicting the seepage volume of a reservoir according to claim 1, wherein the relationship model between the seepage volume and the water level height and time is:

Where Q is the expected seepage volume of the target reservoir, h is the expected water level height of the target reservoir, l is the dead water level height of the target reservoir, and t is the target time, the The target time is the month.
The method for predicting the seepage volume of a reservoir according to any one of claims 1 to 3, characterized in that, if the expected seepage volume reaches the first seepage volume threshold, sending the warning message includes:

If the expected seepage amount reaches the first seepage amount threshold, an early warning message that the cause of the leakage of the target reservoir is a dam leakage is sent.
The method for predicting the seepage volume of a reservoir according to any one of claims 1 to 3, wherein the method further comprises:

If the expected water seepage amount does not reach the first water seepage threshold, determine whether the expected water seepage reaches the second water seepage threshold;

If yes, adjust the frequency of predicting the seepage volume of the target reservoir.
A device for predicting the seepage volume of a reservoir, characterized in that the device comprises:

An acquisition module for acquiring the reservoir attribute of the target reservoir and the expected meteorological information of the target reservoir from the current time to the target time;

An input module, configured to input the expected meteorological information into a preset precipitation prediction model to obtain the expected precipitation of the target reservoir from the current time to the target time;

A first calculation module, configured to calculate the expected water level height of the target reservoir from the expected precipitation, the reservoir attribute of the target reservoir, and the current water level height of the target reservoir;

The second calculation module is used to determine the expected seepage volume of the target reservoir at the target time according to the relationship model between the seepage volume and the water level height and time, and the expected water level height;

The early warning module is used to send an early warning message if the expected water seepage reaches the first water seepage threshold.
The apparatus for predicting the seepage volume of a reservoir according to claim 6, wherein the apparatus further comprises a model acquisition module for acquiring a relationship model between the seepage volume and the water level height and time;

The model acquisition module is specifically used for:

Obtain the historical seepage volume and corresponding historical water level height of the target reservoir at historical times;

Data fitting is performed on the historical time, the historical water seepage amount and the historical water level height to obtain a relationship model between the water seepage amount and the water level height and time.
The device for predicting the seepage volume of a reservoir according to claim 6, wherein the relationship model between the seepage volume and the water level height and time is:

Where Q is the expected seepage volume of the target reservoir, h is the expected water level height of the target reservoir, l is the dead water level height of the target reservoir, and t is the target time, the The target time is the month.
The device for predicting the seepage volume of a reservoir according to any one of claims 6 to 8, wherein the early warning module is specifically used for:

If the expected seepage amount reaches the first seepage amount threshold, an early warning message that the cause of the leakage of the target reservoir is a dam leakage is sent.
The device for predicting the seepage volume of a reservoir according to any one of claims 6 to 8, wherein the device further comprises an adjustment module, and the adjustment module is used for:

If the expected water seepage amount does not reach the first water seepage threshold, determine whether the expected water seepage reaches the second water seepage threshold;

If yes, adjust the frequency of predicting the seepage volume of the target reservoir.
A computer device, characterized in that the computer device comprises:

Memory, storing at least one instruction; and

The processor executes the instructions stored in the memory to implement the method for predicting the seepage volume of the reservoir according to any one of claims 1 to 5.
A computer-readable storage medium, wherein at least one instruction is stored in the computer-readable storage medium, and the at least one instruction is executed by a processor in a server to implement any one of claims 1 to 5. The reservoir water seepage prediction method.