CN113742637B - Calculation method and device for annual average silt loss rate of reservoir, electronic equipment and storage medium - Google Patents
Calculation method and device for annual average silt loss rate of reservoir, electronic equipment and storage medium Download PDFInfo
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- 238000004364 calculation method Methods 0.000 title claims abstract description 62
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Abstract
The application discloses a calculation method and device for annual average silt loss rate of a reservoir, electronic equipment and a storage medium. The method comprises the following steps: acquiring the sedimentation data of a plurality of reservoirs in N target drainage basins, wherein the N target drainage basins are positioned in a target area; calculating the annual average silt loss rate of each reservoir according to the silt data of each reservoir; calculating the annual average loss rate of reservoirs of each target river basin by adopting a weighted average algorithm based on the loss rate of each reservoir and the reservoir capacity data corresponding to each reservoir; determining the actual total reservoir capacity of each target river basin based on the reservoir capacity data of each reservoir in each target river basin; calculating the annual average loss rate of the reservoirs in the target area by adopting a weighted average algorithm according to the annual average loss rate of the reservoirs in each target river basin and the actual total reservoir capacity of the reservoirs in each target river basin, wherein N is a positive integer; the method solves the problem of large calculation error of the direct method caused by the lack of samples and large basin difference at present.
Description
Technical Field
The invention relates to the technical field of hydraulic engineering, in particular to a calculation method and device for annual average silt loss rate of a reservoir, electronic equipment and a storage medium.
Background
Because of the high sand content of the river in China, the reservoir capacity lost by the reservoir in China is large each year, and according to the reservoir characteristics in China, a quantification method of reservoir characteristics is provided, and great theoretical guidance significance exists for reservoir evaluation and treatment work, and the dynamic reservoir rate is generally reflected by the annual average reservoir loss rate of the reservoir at present.
In the actual annual average loss rate calculation process of reservoirs, a direct method is adopted to calculate the annual average loss rate of the reservoirs at present, the annual average loss rate of a single reservoir in a certain time period is calculated according to the collected reservoir accumulation amount and the total reservoir capacity of the reservoirs, and the annual average loss rate of the reservoirs is calculated by combining reservoir capacity data and annual average loss rate data. The related technology lacks comprehensive reservoir loss data, and the number of samples in different flow domains is large, so that the annual average loss rate accuracy of reservoirs in China is not high.
Disclosure of Invention
In view of the above, the present application provides a method, an apparatus, an electronic device and a storage medium for calculating annual average loss rate of a reservoir, which are used for improving the calculation accuracy of annual average loss rate of the reservoir.
In a first aspect, an embodiment of the present application provides a method for calculating annual average loss rate of a reservoir, including: acquiring the sedimentation data of a plurality of reservoirs in N target drainage basins, wherein the N target drainage basins are positioned in a target area;
calculating the annual average silt loss rate of each reservoir according to the silt data of each reservoir;
Calculating the annual average loss rate of reservoirs of each target river basin by adopting a weighted average algorithm based on the annual average loss rate of each reservoir and the reservoir capacity data corresponding to each reservoir;
determining the actual total reservoir capacity of each target river basin based on the reservoir capacity data of each reservoir in each target river basin;
and calculating the annual average loss rate of the reservoirs in the preset time period in the target area by adopting a weighted average algorithm according to the annual average loss rate of the reservoirs in the preset time period of each target river basin and the actual total reservoir capacity of the reservoirs in each target river basin, wherein N is a positive integer.
In a second aspect, an embodiment of the present application provides a device for calculating annual average loss rate of a reservoir, including: the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring the sedimentation data of a plurality of reservoirs in N target watershed, and the N target watershed is positioned in a target area. The first calculation module is used for calculating the annual average silt loss rate of each reservoir according to the silt data of each reservoir. And the second calculation module is used for calculating the annual average loss rate of the reservoirs of each target river basin by adopting a weighted average algorithm based on the loss rate of each reservoir and the reservoir capacity data corresponding to each reservoir. And the third calculation module is used for determining the actual total reservoir capacity of the reservoirs in each target river basin based on the reservoir capacity data of each reservoir in each target river basin. And the fourth calculation module is used for calculating the annual average loss rate of the reservoirs in the target area by adopting a weighted average algorithm according to the annual average loss rate of the reservoirs in each target river basin and the actual total reservoir capacity of the reservoirs in each target river basin, wherein N is a positive integer.
In a third aspect, an embodiment of the present application provides an electronic device, including: at least one processor and a memory;
The processor is configured to execute a computer program stored in the storage device, so as to implement a method for calculating annual average loss rate of a reservoir according to any embodiment of the first aspect.
In a fourth aspect, an embodiment of the present application provides a computer storage medium storing one or more programs executable by an electronic device as described in the third aspect, to implement a method for calculating annual average loss rate of a reservoir as described in any embodiment of the first aspect.
The application has the following advantages and beneficial effects:
According to the method, the device, the electronic equipment and the storage medium for calculating the annual average loss rate of the reservoirs, which are provided by the application, the annual average loss rate of the reservoirs in each target river basin in a target area (such as the whole country) is calculated by using the inventory weighted average method, the overall characteristics of reservoir accumulation distribution in each target river basin are provided with the representativeness of the river basin, the annual average loss rate of the reservoirs in the target river basin is weighted average by combining the total reservoir capacity of the reservoirs in each target river basin, so that the annual average loss rate of the reservoirs in the target area is calculated, and the calculation precision of the annual average loss rate of the reservoirs in the target area is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings:
Fig. 1 shows an application scenario schematic diagram of a calculation method of annual average loss rate of a reservoir according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a method for calculating annual average loss rate of reservoirs according to an embodiment of the present application;
FIG. 3 is a schematic flow chart of a method for calculating annual average loss rate of a reservoir according to another embodiment of the present application;
FIG. 4 is a schematic flow chart of a method for calculating annual average loss rate of a reservoir according to another embodiment of the present application;
FIG. 5 shows a schematic flow chart of a calculation method of the annual average loss rate of the reservoir, which is provided in the embodiment of the application;
FIG. 6 shows a schematic diagram of the calculation result of the annual average loss rate of reservoirs in each river basin in China;
FIG. 7 is a block diagram showing a calculation device for annual average loss rate of reservoirs according to an embodiment of the present application;
FIG. 8 is a block diagram showing a second calculation module in a calculation device for annual average loss rate of reservoirs according to an embodiment of the present application;
FIG. 9 is a block diagram of a fourth calculation module in a calculation device for annual average loss rate of reservoirs according to an embodiment of the present application;
FIG. 10 shows a block diagram of an electronic device for performing a calculation method of the annual average loss rate of a reservoir according to an embodiment of the present application;
fig. 11 shows a storage unit for storing or carrying program codes for implementing a method for calculating a rate of annual average loss of a reservoir according to an embodiment of the present application.
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present invention, the present invention will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present invention and the descriptions thereof are for illustrating the present invention only and are not to be construed as limiting the present invention.
The following description of the embodiments of the present application will be made with reference to the accompanying drawings, in which it is evident that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The reservoir silt damage is that a large amount of river sand is deposited in a reservoir area, the reservoir capacity is damaged, the reservoir silt damage seriously affects the running efficiency of the reservoir and the stability of an ecological system, and is the country with the largest number of reservoirs in the world at present, meanwhile, the reservoir silt damage condition of China is very serious, in view of the characteristic of high sand content of the river basin of China, a quantification method is provided for reservoir silt characteristics, great theoretical guidance significance exists for reservoir silt evaluation and treatment work, and the annual average silt damage rate of the reservoir is generally used as an index of the annual average reservoir capacity loss degree of the reservoir in a certain period at present.
The applicant found that the annual average loss rate calculation of the reservoir needs to pay attention to the calculation of the current relevant reservoir loss: the number of reservoirs and the running stage are dynamically changed along with the time increment, and the reservoir samples in different flow domains have larger difference; the vast amount of reservoir fouling information lacks large-scale statistics, so that analysis can only be performed on a part of representative reservoirs for the annual average rate of the reservoirs in the river basin and the reservoirs in the whole country. In view of the reasons, the calculation accuracy of the annual average silt loss rate of the reservoirs in China is greatly influenced by the statistical samples. The calculation result lacks demonstration on a macroscopic level, and has the problem of low calculation accuracy.
Specifically, the annual average loss rate of reservoirs in China is calculated by a direct method in the related art by taking the annual average loss rate as an evaluation index, and the annual average loss rate is calculated by the following method:
According to the collected reservoir sediment volume and the reservoir total volume, calculating the annual average sediment loss rate of a single reservoir in a determined time period, wherein the specific calculation formula is as follows:
Wherein k represents the number of the whole reservoir in the statistical sample, R k is the annual average silt loss rate of the kth reservoir, deltaV k is the silt loss reservoir capacity of the kth reservoir in the statistical time, V k is the reservoir capacity of the kth reservoir, and t k is the silt statistical year of the kth reservoir.
And calculating annual average silt loss rate of reservoirs nationwide by counting the number of all the silt reservoirs in the sample, namely the silt data, wherein the calculation formula is as follows:
where c is the number of all the sedimentation reservoirs in the statistical sample.
Therefore, the embodiment of the application provides a calculation method for the annual average loss rate of reservoirs, which comprises the steps of firstly obtaining the accumulation data of a plurality of reservoirs in N target drainage basins, wherein the N target drainage basins are positioned in a target area, calculating the loss rate of each reservoir according to the accumulation data of each reservoir, calculating the annual average loss rate of each reservoir based on the loss rate of each reservoir and the corresponding reservoir capacity data of each reservoir by adopting a weighted average algorithm, determining the actual total reservoir capacity of each reservoir in each target drainage basin based on the reservoir capacity data of each reservoir in each target drainage basin, and finally calculating the annual average loss rate of the reservoirs in a preset time period in the target area by adopting the weighted average algorithm according to the annual average loss rate of each target drainage basin and the actual total reservoir capacity of each reservoir in each target drainage basin. The annual average loss rate of the reservoirs in the target area can be calculated, and the calculation accuracy of the annual average loss rate of the reservoirs in the target area is improved.
The following describes an application environment of a calculation method of annual average loss rate of reservoirs provided by the embodiment of the application:
Referring to fig. 1, fig. 1 is a schematic diagram of an application scenario of a method for calculating an annual average loss rate of a reservoir according to an embodiment of the present application, where the method for calculating an annual average loss rate of a reservoir according to an embodiment of the present application may be applied to a system 100 for monitoring an annual average loss rate of a reservoir, and a server is taken as an electronic device in the present application as an example, and the system 100 for monitoring an annual average loss rate of a reservoir includes a server 110, a router 120 and an intelligent monitoring device 130. The server 110, the router 120 and the reservoir intelligent monitoring device 130 may be connected through the internet to form the internet of things.
The reservoir intelligent monitoring device 130 may include a plurality of reservoir intelligent monitoring devices 130, and the reservoir intelligent monitoring device 130 may be a collection device for collecting data related to annual average loss rate of the reservoir, such as a reservoir sediment volume data collection device, a reservoir total volume data collection device, and other terminal devices. Server 110 may be a server that manages reservoir intelligent monitoring device 130, such as a server for statistically gathering data, and server 110 may be a cloud server, in particular. The server 110 and the reservoir intelligent monitoring device 130 form the internet of things, and the collected information of the reservoir intelligent monitoring device 130 is obtained to perform online control monitoring and the like on the reservoir intelligent monitoring device 130, for example, the online time length and the like of the collected data of the reservoir intelligent monitoring device 130 are related information, the working state of the reservoir intelligent monitoring device 130 is controlled, and the related information of the reservoir intelligent monitoring device 130 is pushed to staff of a corresponding reservoir workstation and the like.
It should be noted that the configuration shown in fig. 1 is not limiting of the reservoir annual loss monitoring system 100, and in other embodiments, the reservoir annual loss monitoring system 100 may include fewer or more devices or components than illustrated, or may constitute some devices, or a different arrangement of components.
Embodiments of the present application will be described in detail below with reference to the accompanying drawings.
Referring to fig. 2, fig. 2 is a flow chart of a method for calculating an annual average loss rate of a reservoir according to an embodiment of the present application, and the method for calculating an annual average loss rate of a reservoir according to an embodiment of the present application is applied to a system 100 for monitoring an annual average loss rate of a reservoir, and includes:
And S10, acquiring the sedimentation materials of a plurality of reservoirs in N target watershed, wherein the N target watershed is positioned in the target area.
In the embodiment of the application, N target drainage basins are adaptively adjusted according to the selected target areas, specifically, the N target drainage basins can be classified according to the ground water collecting areas and the underground water collecting areas, and can be selected and adjusted according to the actual data use requirements of the target areas. The reservoir sediment is mainly composed of sand, and the sediment data of each reservoir can comprise water ecological parameters and the like related to the sediment loss of each country.
For example, taking China as an example, china is the country with the largest number of reservoirs in the world, and 9.8 spare seats are built in reservoirs with a reservoir capacity of more than 10 ten thousand meters 3. Meanwhile, the reservoir siltation condition of China is very severe, and the river sand is specifically taken as reservoir siltation loss characteristics of China to select reservoir data of each river basin.
As an implementation mode, the siltation data of a plurality of reservoirs in N target waterbasins are stored in a server corresponding to each waterbasin reservoir workstation in advance, the intelligent reservoir monitoring equipment continuously collects real-time data, the server obtains the real-time data and updates the siltation data, and in the embodiment of the application, each server can send a character request to obtain other server data.
And step S20, calculating the annual average silt loss rate of each reservoir according to the silt data of each reservoir.
In the embodiment of the application, the calculation time of the annual average loss rate can be automatically obtained by the time of updating the connection information of the router or the reservoir intelligent monitoring equipment. Wherein embodiments of the present application are not further limited in terms of certain practical segments. In addition, the preset time period may be preset by a hydropower station worker through the server, for example, the worker may index the sludge data of each reservoir for a certain time period in the server and calculate the sludge rate.
Whether the router or the intelligent reservoir monitoring equipment is automatically set and acquired or preset by a worker, the preset time period can be an absolute time point interval. For example, a fixed period of time (e.g., 05 months 2010) consisting of a year, a week, a month, etc. updates and transmits the time information and the sludge information to the server.
In addition, when the sludge material and the time information are transmitted between the servers, the server sends a water reservoir comprising a server identifier or a password or both, and particularly the server identifier corresponds to different watercourses.
And step S30, calculating the annual average loss rate of the reservoirs of each target river basin by adopting a weighted average algorithm based on the loss rate of each reservoir and the reservoir capacity data corresponding to each reservoir.
In the embodiment of the application, the silt loss rate of each reservoir and the reservoir capacity data corresponding to each reservoir are counted by a server and corresponding associated information is carried out. The information association can be manually and manually carried out by a worker through a server, or can be automatically associated with corresponding stock capacity data according to a server identification, and the server comprises a monitoring node which can be set to be judged by an intelligent algorithm or manually judged. For example, regression analysis can be performed according to historical data to determine the annual average loss rate value domain range of the reservoir.
And S40, determining the actual total reservoir capacity of the reservoirs in each target river basin based on the reservoir capacity data of each reservoir in each target river basin.
In the embodiment of the application, the server calculates the reservoir capacity data of reservoirs with different target watershed and gathers the actual total reservoir capacity of the reservoirs.
And S50, calculating the annual average loss rate of the reservoirs in a preset time period in the target area by adopting a weighted average algorithm according to the annual average loss rate of the reservoirs in each target river basin and the actual total reservoir capacity of the reservoirs in each target river basin, wherein N is a positive integer.
According to the reservoir annual average loss rate calculation method provided by the application, the reservoir annual average loss rate of each target river basin in a target area (such as the whole country) is calculated by using the inventory weighted average method, the calculation result has the river basin representativeness, the reservoir annual average loss rate of each target river basin is weighted and averaged by combining the reservoir total capacity of each target river basin, so that the reservoir annual average loss rate in the target area is calculated, and the calculation precision of the reservoir annual average loss rate in the target area is improved.
In one embodiment, the fouling material comprises: each target basin identification, after step S10, the method further comprises: and classifying the sedimentation data of the reservoirs based on the identification of each target river basin to obtain the sedimentation data of each reservoir in each target river basin.
In this embodiment, the identification process is performed on a plurality of reservoirs in different domains in the server, and the reservoirs identified corresponding to each server in step S20 in the embodiment are summarized to the corresponding domains for performing the secondary identification process, specifically, the identification process includes setting a first character set and a second character set, the server processes each domain according to the first character set, and marks different reservoirs with different second character sets according to serial numbers on the basis of the first character set, specifically, the first character set and the second character set include symbols such as numbers and letters.
As a preferable aspect of the above embodiment, the above sludge includes: calculating the sediment loss rate of each reservoir according to the sediment data of each reservoir, wherein the sediment loss reservoir capacity and the total reservoir capacity are counted internally, and the sediment loss rate calculating method comprises the following steps:
The silt loss rate of each reservoir is calculated by adopting the following formula:
Wherein R ij is the annual average loss rate of the jth reservoir in the ith target flow area, i is the target flow area to which the reservoir belongs, j is the serial number of the jth reservoir in the target flow area, deltaV ij is the loss reservoir capacity of the jth reservoir in the ith target flow area, V ij is the total reservoir capacity of the jth reservoir in the ith target flow area, t ij is the accumulation statistical time of the jth reservoir in the ith flow area, and i is smaller than or equal to N.
Referring to fig. 3, fig. 3 is a flowchart of another calculation method of annual average loss rate of a reservoir according to an embodiment of the present application, which is applied to the annual average loss rate monitoring system 100 of a reservoir, and step S30: calculating the annual average loss rate of reservoirs of each target river basin by adopting a weighted average algorithm based on the loss rate of each reservoir and the reservoir capacity data corresponding to each reservoir, comprising:
S302: determining the total reservoir capacity of each target river basin based on the total reservoir capacity of each reservoir;
S304: determining the sediment loss storage capacity of each target river basin based on the annual average sediment loss rate of each reservoir and the total storage capacity of each reservoir;
S306: dividing the reservoir loss storage capacity of each target river basin by the total reservoir capacity of the corresponding target river basin to obtain the annual reservoir loss rate of the target river basin.
As a preference of the above embodiment, step S306 is as follows: dividing the reservoir loss storage capacity of each target river basin by the total reservoir capacity of the corresponding target river basin to obtain the annual reservoir loss rate of the target river basin, wherein the method comprises the following steps:
the annual average loss rate of reservoirs of each target river basin is calculated by adopting the following formula:
Wherein R i is the annual average loss rate of reservoirs in the ith target river basin, m is the total number of investigation reservoirs in the ith target river basin, j is the serial number of the reservoirs in the target river basin, wherein j is a positive integer, The total reservoir capacity of the ith target river basin,And (5) the sediment storage capacity of the ith target drainage basin.
Referring to fig. 4, fig. 4 is a flowchart of another calculation method of annual average loss rate of a reservoir according to an embodiment of the present application, which is applied to the annual average loss rate monitoring system 100, and the step S50 is as follows: according to the annual average loss rate of reservoirs of each target river basin and the actual total reservoir capacity of the reservoirs of each target river basin, calculating the annual average loss rate of reservoirs in a preset time period in the target region by adopting a weighted average algorithm, wherein the method comprises the following steps:
S502: determining the sediment loss storage capacity in the target area based on the annual sediment loss rate of the reservoirs of each target river basin and the actual total storage capacity of the reservoirs of each target river basin;
s504: determining the actual total reservoir capacity of the reservoirs in the target area based on the actual total reservoir capacity of the reservoirs in each target river basin;
s506: and dividing the sediment loss reservoir capacity in the target area by the actual total reservoir capacity of the reservoirs in the target area to determine the annual average sediment loss rate of the reservoirs in the target area for a preset period of time.
As a preference of the above embodiment, step S506 is described above: dividing the sediment loss reservoir capacity in the target area by the actual total reservoir capacity of the reservoirs in the target area to determine the annual average sediment loss rate of the reservoirs in the target area for a preset time period, wherein the method comprises the following steps:
the annual average loss rate of the reservoir in the preset time period in the target area is calculated by adopting the following formula:
wherein R represents the annual average loss rate of reservoirs in a preset time period in the target area, V i' represents the total reservoir capacity of the actual reservoirs contained in the target river basin i, Is the actual total reservoir capacity of the reservoir in the target area,/>Is the silt storage capacity in the target area.
For example, the time period is set to be annual, domestic is taken as a target area, please refer to fig. 5, fig. 5 is a schematic flow chart of a calculation method of annual average rate of loss of a water reservoir in an embodiment of the application, and in combination with the steps of the embodiment, S1, firstly, the data reservoir capacity V ij, the reservoir loss reservoir capacity DeltaV ij and the reservoir accumulation statistical time Deltat are obtained according to an obtaining module, and S2, the annual average rate of loss of a single reservoir in a river basin is calculated through a first calculating moduleThe annual average loss rate of the reservoir in the whole country can be calculated, S3, the total annual average loss rate/>, of the river basin i is calculated through a second calculation moduleS4, calculating the actual total reservoir capacity V i' of the river basin i through a third calculation module, and S5, calculating the annual average silt loss rate of the reservoir nationwide through a fourth calculation module
According to the method, the device, the electronic equipment and the storage medium for calculating the annual average loss rate of the reservoirs, the annual average loss rate is taken as a preset time period, the domestic reservoirs are taken as calculation targets of the annual average loss rate of the reservoirs, the accumulation data of a plurality of reservoirs in the domestic target river basin are firstly obtained, the annual average loss rate of each reservoir is calculated according to the reservoir capacity data of each reservoir, the annual average loss rate of each target river basin is calculated by adopting a weighted average algorithm based on the annual average loss rate of each reservoir and the reservoir capacity data corresponding to each reservoir, the actual total reservoir capacity of each target river basin is determined based on the reservoir capacity data of each reservoir in each target river basin, and finally the annual average loss rate of the domestic reservoirs is calculated by adopting a weighted average algorithm according to the reservoir annual average loss rate of each target river basin and the reservoir actual total reservoir capacity of each target river basin.
Referring to fig. 6, fig. 6 is a schematic diagram of a calculation result of annual average loss rate of reservoirs in each drainage basin in China, in which reference 1 is a value of annual average loss rate of reservoirs calculated by a direct method mentioned in the related art, reference 2 is a value of annual average loss rate of reservoirs obtained by a calculation method of annual average loss rate of reservoirs provided by the application, and the annual average loss rate of each drainage basin is calculated according to the national seven-large-drainage-basin 6702 reservoir sediment data, wherein the annual average loss rate of reservoirs calculated by the direct method is 0.49%, and the calculation result by the weighted average method is 0.41%, so that the calculation accuracy of the annual average loss rate of reservoirs can be improved, and the method has wide application prospects.
Referring to fig. 7, a computing device 700 for annual average loss rate of a reservoir according to an embodiment of the present application is applied to a system 100 for monitoring annual average loss rate of a reservoir, and the device includes:
An obtaining module 710, configured to obtain sludge of a plurality of reservoirs in N target drainage basins, where the N target drainage basins are located in a target area;
the first calculating module 720 is configured to calculate a loss rate of each reservoir according to the reservoir capacity data of each reservoir;
a second calculation module 730, configured to calculate a reservoir annual average loss rate of each target river basin by using a weighted average algorithm based on the loss rate of each reservoir and the reservoir capacity data corresponding to each reservoir;
a third calculation module 740, configured to determine an actual total reservoir capacity of each target drainage basin based on the reservoir capacity data of each reservoir in each target drainage basin;
And a fourth calculation module 750, configured to calculate the annual average loss rate of the reservoir in the preset time period in the target area by using a weighted average algorithm according to the annual average loss rate of the reservoir in each target river basin and the actual total reservoir capacity of the reservoir in each target river basin, where N is a positive integer.
Referring to fig. 8, fig. 8 is a block diagram of a second calculation module in a calculation device for annual average loss rate of a reservoir according to an embodiment of the present application, where the second calculation module 730 includes:
A first confirmation module 731 for determining a total reservoir capacity for each target basin based on the total reservoir capacity for each reservoir;
A second confirmation module 732 for determining a loss storage capacity of each target basin based on the loss rate of each reservoir and the total storage capacity of each reservoir;
The second sub-calculation module 733 is configured to divide the reservoir capacity of each target river basin by the total reservoir capacity of the corresponding target river basin to obtain the annual reservoir average reservoir loss rate of the target river basin.
Referring to fig. 9, fig. 9 is a block diagram of a fourth calculation module in a calculation device for annual average loss rate of a reservoir according to an embodiment of the present application, where the fourth calculation module 750 includes:
A first obtaining module 751, configured to determine a loss storage capacity in the target area based on the annual average loss rate of the reservoirs in each target river basin and the actual total storage capacity of the reservoirs in each target river basin;
a second obtaining module 752, configured to determine an actual total reservoir capacity of the reservoir in the target area based on the actual total reservoir capacities of the reservoirs of the respective target river basin;
And the third sub-calculation module 753 is used for dividing the reservoir loss storage capacity in the target area by the actual total reservoir capacity of the reservoirs in the target area to determine the annual average reservoir loss rate of the reservoirs in the preset time period in the target area.
It should be noted that, in the present application, the device embodiment corresponds to the foregoing method embodiment, and specific principles in the device embodiment may refer to the content in the foregoing method embodiment, which is not described herein again.
Referring to fig. 10, based on the embodiment of the present application, an electronic device 200 is further provided, which includes a method for calculating the annual average loss rate of the reservoir, where the electronic device 200 may be a smart phone, a tablet computer, a computer or a portable computer.
The electronic device 200 also includes a processor 202 and a memory 204. The storage 204 stores therein a program capable of executing the contents of the foregoing embodiments, and the processor 202 can execute the program stored in the storage 204.
Processor 202 may include one or more cores for processing data and a message matrix unit, among other things. The processor 202 utilizes various interfaces and lines to connect various portions of the overall electronic device 200, perform various functions of the electronic device 200, and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 204, and invoking data stored in the memory 204. Alternatively, the processor 202 may be implemented in at least one hardware form of digital signal Processing (DIGITAL SIGNAL Processing, DSP), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA), editable logic array (Programmable Logic Array, PLA). The processor 202 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modulation decoder, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for being responsible for rendering and drawing of display content; the modem is used to handle wireless communications. It will be appreciated that the above described modulation decoder may not be integrated into the processor and may be implemented solely by a single communication chip.
The storage 204 may include random access Memory (Random Access Memory, RAM) or Read-Only Memory (RAM). The storage 204 may be used to store instructions, programs, code sets, or instruction sets. The memory 204 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for implementing at least one function (e.g., instructions for a user to obtain a random number), instructions for implementing various method embodiments described below, and the like. The stored data area may also store data (e.g., random numbers) created by the terminal in use, and so on.
The electronic device 200 may further include a network module and a screen, where the network module is configured to receive and transmit electromagnetic waves, and implement mutual conversion between the electromagnetic waves and the electrical signals, so as to communicate with a communication network or other devices, such as an audio playing device. The network module may include various existing circuit elements for performing these functions, such as an antenna, a radio frequency transceiver, a digital signal processor, an encryption/decryption chip, a Subscriber Identity Module (SIM) card, memory, and the like. The network module may communicate with various networks such as the internet, intranets, wireless networks, or with other devices via wireless networks. The wireless network may include a cellular telephone network, a wireless local area network, or a metropolitan area network. The screen may display interface content and perform data interaction.
Referring to fig. 11, a block diagram of a computer readable storage medium according to an embodiment of the present application is shown. The computer readable medium 900 has stored therein program code which is callable by a processor to perform the method described in the method embodiments described above.
The computer readable storage medium may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. Optionally, the computer readable storage medium comprises a non-volatile computer readable medium (non-transitory computer-readable storage medium). The computer readable storage medium has storage space for program code to perform any of the method steps described above. The program code can be read from or written to one or more computer program products. The program code may be compressed, for example, in a suitable form.
Embodiments of the present application also provide a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the method for calculating the annual average loss rate of the reservoir described in the above various alternative implementations.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will be appreciated by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not drive the essence of the corresponding technical solutions to depart from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims (8)
1. The method for calculating the annual average loss rate of the reservoir is characterized by comprising the following steps:
Acquiring the sedimentation data of a plurality of reservoirs in N target drainage basins, wherein the N target drainage basins are positioned in a target area;
calculating the annual average silt loss rate of each reservoir according to the silt data of each reservoir;
Calculating the annual average loss rate of reservoirs of each target river basin by adopting a weighted average algorithm based on the annual average loss rate of each reservoir and the reservoir capacity data corresponding to each reservoir;
determining the actual total reservoir capacity of each target river basin based on the reservoir capacity data of each reservoir in each target river basin;
Calculating the annual average loss rate of the reservoirs in the target area by adopting a weighted average algorithm according to the annual average loss rate of the reservoirs in each target river basin and the actual total reservoir capacity of the reservoirs in each target river basin, wherein the method comprises the following steps: determining annual average silt loss storage capacity in a target area based on the annual average silt loss rate of the reservoirs of each target river basin and the actual total storage capacity of the reservoirs of each target river basin; determining the actual total reservoir capacity of the reservoirs in the target area based on the actual total reservoir capacity of the reservoirs in each target river basin; dividing the annual average loss storage capacity in the target area by the actual total storage capacity of the reservoirs in the target area to determine the annual average loss rate of the reservoirs in the target area, wherein the annual average loss rate comprises the following steps:
The annual average loss rate of the reservoir in the target area is calculated by adopting the following formula:
Wherein R represents the annual average loss rate of reservoirs in the target area, V i' represents the total reservoir capacity of the actual reservoirs contained in the target river basin i, Is the actual total reservoir capacity of the reservoir in the target area,/>The method is characterized in that the storage capacity is lost for annual average silt in a target area, wherein N is a positive integer.
2. The method for calculating the annual average loss rate of a reservoir according to claim 1, wherein said accumulation data comprises: each target basin identification, the method further comprising:
And classifying the sedimentation data of the reservoirs based on the identification of each target river basin to obtain the sedimentation data of each reservoir in each target river basin.
3. The method for calculating the annual average loss rate of a reservoir according to claim 2, wherein said accumulation data comprises: calculating the annual average loss rate of each reservoir according to the accumulation data of each reservoir, wherein the annual average loss rate comprises the following steps:
The annual average silt loss rate of each reservoir is calculated by adopting the following formula:
Wherein R ij is the annual average loss rate of the jth reservoir in the ith target flow area, i is the target flow area to which the reservoir belongs, j is the serial number of the jth reservoir in the target flow area, deltaV ij is the loss reservoir capacity of the jth reservoir in the ith target flow area, V ij is the total reservoir capacity of the jth reservoir in the ith target flow area, t ij is the accumulation statistical time of the jth reservoir in the ith flow area, and the unit is year, and i is less than or equal to N.
4. The method for calculating the annual average loss rate of reservoirs according to claim 3, wherein the calculating the annual average loss rate of reservoirs of each target river basin based on the annual average loss rate of each reservoir and the reservoir capacity data corresponding to each reservoir by using a weighted average algorithm comprises:
determining the total reservoir capacity of each target river basin based on the total reservoir capacity of each reservoir;
determining the annual average silt loss reservoir capacity of each target river basin based on the annual average silt loss rate of each reservoir and the total reservoir capacity of each reservoir;
dividing the annual average loss reservoir capacity of each target river basin by the total reservoir capacity of the corresponding target river basin to obtain the annual average loss rate of the reservoirs of the target river basin.
5. The method for calculating the annual average loss rate of reservoirs according to claim 4, wherein dividing the loss storage capacity of each target river basin by the total storage capacity of the reservoirs of the corresponding target river basin to obtain the annual average loss rate of reservoirs of the target river basin comprises:
the annual average loss rate of reservoirs of each target river basin is calculated by adopting the following formula:
Wherein R i is the annual average loss rate of reservoirs in the ith target river basin, m is the total number of investigation reservoirs in the ith target river basin, j is the serial number of the reservoirs in the target river basin, wherein j is a positive integer, The total reservoir capacity of the ith target river basin,The storage capacity is lost for the annual average of the ith target river basin.
6. A computing device for annual average loss rate of reservoirs, comprising:
The system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring the sedimentation data of a plurality of reservoirs in N target watershed, wherein the N target watershed is positioned in a target area;
the first calculation module is used for calculating the annual average silt loss rate of each reservoir according to the silt data of each reservoir;
the second calculation module is used for calculating the annual average loss rate of the reservoirs of each target river basin by adopting a weighted average algorithm based on the annual average loss rate of each reservoir and the reservoir capacity data corresponding to each reservoir;
the third calculation module is used for determining the actual total reservoir capacity of the reservoirs in each target drainage basin based on the reservoir capacity data of each reservoir in each target drainage basin;
The fourth calculation module is configured to calculate, according to the annual average loss rate of reservoirs in each target river basin and the actual total reservoir capacity of the reservoirs in each target river basin, the annual average loss rate of reservoirs in the target area by using a weighted average algorithm, where the fourth calculation module includes: determining annual average silt loss storage capacity in a target area based on the annual average silt loss rate of the reservoirs of each target river basin and the actual total storage capacity of the reservoirs of each target river basin; determining the actual total reservoir capacity of the reservoirs in the target area based on the actual total reservoir capacity of the reservoirs in each target river basin; dividing the annual average loss storage capacity in the target area by the actual total storage capacity of the reservoirs in the target area to determine the annual average loss rate of the reservoirs in the target area, wherein the annual average loss rate comprises the following steps:
The annual average loss rate of the reservoir in the target area is calculated by adopting the following formula:
Wherein R represents the annual average loss rate of reservoirs in the target area, V i' represents the total reservoir capacity of the actual reservoirs contained in the target river basin i, Is the actual total reservoir capacity of the reservoir in the target area,/>The method is characterized in that the storage capacity is lost for annual average silt in a target area, wherein N is a positive integer.
7. An electronic device, comprising:
One or more processors;
A reservoir;
One or more programs, wherein the one or more programs are stored in the storage configured to be executed by the one or more processors, the one or more programs configured to perform the method of calculating the annual average loss rate of a reservoir of any of claims 1-5.
8. A computer readable storage medium having program code stored therein, the program code being executable by a processor to perform the method of calculating the annual average loss rate of a reservoir as claimed in any one of claims 1 to 5.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100563757B1 (en) * | 2006-01-23 | 2006-03-24 | 김은주 | Methods to measure pondage |
| CN108320095A (en) * | 2018-01-31 | 2018-07-24 | 黄河水利委员会黄河水利科学研究院 | A kind of reservoir sedimentation methods of risk assessment |
| CN111027226A (en) * | 2019-12-25 | 2020-04-17 | 中国电建集团中南勘测设计研究院有限公司 | Pumped storage power station water-sand numerical simulation calculation method |
| CN111723995A (en) * | 2020-06-24 | 2020-09-29 | 中国长江三峡集团有限公司 | Optimized scheduling method for sediment in flood season of reservoir under combined scheduling of cascade reservoirs |
| CN111967157A (en) * | 2020-08-14 | 2020-11-20 | 中国水利水电科学研究院 | Reservoir group water and sand optimization scheduling method and system considering staged multi-objective function |
| CN112287436A (en) * | 2020-10-16 | 2021-01-29 | 黄河勘测规划设计研究院有限公司 | Method and system for designing sediment section and effective storage capacity of reservoir of sandy river |
| CN112287528A (en) * | 2020-10-16 | 2021-01-29 | 黄河勘测规划设计研究院有限公司 | Flood control high water level determination method for sandy river reservoir based on high beach trough |
| CN112418491A (en) * | 2020-11-06 | 2021-02-26 | 黄河勘测规划设计研究院有限公司 | Dynamic configuration method for residual sediment storage capacity of reservoir |
| CN112561213A (en) * | 2021-02-23 | 2021-03-26 | 浙江贵仁信息科技股份有限公司 | Reservoir flood control scheduling method, system, equipment and medium based on improved POA |
-
2021
- 2021-08-16 CN CN202110937105.XA patent/CN113742637B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100563757B1 (en) * | 2006-01-23 | 2006-03-24 | 김은주 | Methods to measure pondage |
| CN108320095A (en) * | 2018-01-31 | 2018-07-24 | 黄河水利委员会黄河水利科学研究院 | A kind of reservoir sedimentation methods of risk assessment |
| CN111027226A (en) * | 2019-12-25 | 2020-04-17 | 中国电建集团中南勘测设计研究院有限公司 | Pumped storage power station water-sand numerical simulation calculation method |
| CN111723995A (en) * | 2020-06-24 | 2020-09-29 | 中国长江三峡集团有限公司 | Optimized scheduling method for sediment in flood season of reservoir under combined scheduling of cascade reservoirs |
| CN111967157A (en) * | 2020-08-14 | 2020-11-20 | 中国水利水电科学研究院 | Reservoir group water and sand optimization scheduling method and system considering staged multi-objective function |
| CN112287436A (en) * | 2020-10-16 | 2021-01-29 | 黄河勘测规划设计研究院有限公司 | Method and system for designing sediment section and effective storage capacity of reservoir of sandy river |
| CN112287528A (en) * | 2020-10-16 | 2021-01-29 | 黄河勘测规划设计研究院有限公司 | Flood control high water level determination method for sandy river reservoir based on high beach trough |
| CN112418491A (en) * | 2020-11-06 | 2021-02-26 | 黄河勘测规划设计研究院有限公司 | Dynamic configuration method for residual sediment storage capacity of reservoir |
| CN112561213A (en) * | 2021-02-23 | 2021-03-26 | 浙江贵仁信息科技股份有限公司 | Reservoir flood control scheduling method, system, equipment and medium based on improved POA |
Non-Patent Citations (9)
| Title |
|---|
| An analysis of the factors affecting the annual average sedimentation loss rates of reservoirs;Jiangguo Chen 等;《E-proceedings of the 38th IAHR World Congress》;20191206;3098-3102 * |
| Strategied for managing reservoir sedimentation;Zhaoyin Wang 等;《International Journal of Sediment Research》;20091231(第4期);369-284 * |
| 喜马拉雅山区一座水库的使用期限;S.K.马宗德, 刘敏;水利水电快报;20011214(第23期);5-6 * |
| 基于组合赋权-理想点法的梯级水库蓄水研究;归力佳;顾圣平;林乐曼;咸京;李江林;;人民黄河;20180510(第05期);50-54 * |
| 水库年平均淤损率影响因素分析;陈建国 等;《泥沙研究》;20190806;第44卷(第4期);1-5 * |
| 水库泥沙淤积量计算方法探讨;赵定平;汤小云;何海涛;;科技资讯;20081213(第35期);241-242 * |
| 水库淤积物密实变化对冲淤计算与库容影响的研究;王育杰 等;《泥沙研究》;20200529;第45卷(第3期);46-52 * |
| 清江隔河岩水库泥沙计算分析;吴虹娟, 杨国录, 余明辉;人民长江;20000820(第08期);27-28 * |
| 碧口水库泥沙淤积规律及控制;何录合;西北电力技术;20000830(第04期);49-51 * |
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