Method and system for determining flood season reservoir water level optimization scheduling index and medium

Abstract

The invention relates to a flood season reservoir water level optimization scheduling index determination method and system and a medium. The method comprises the steps of collecting reservoir riverway terrain, reservoir entering water and sand and reservoir scheduling mode data; establishing a one-dimensional non-constant flowing water and sediment mathematical model of the reservoir; selecting typical annual flood season water and sediment processes respectively representing high water and low water; according to the selected typical annual flood season water and sediment process, sediment erosion and deposition calculation under different reservoir water level conditions in the flood season is carried out, and the deposition proportion and the deposition amount calculation result of the variable backwater area are obtained; and drawing a change process chart of the sedimentation ratio of the variable backwater area and the sedimentation amount along with the water level of the flood season reservoir, and finding a critical reservoir water level which is obviously increased from the increase of the sedimentation ratio of the variable backwater area from the chart, the critical reservoir water level being an optimal scheduling index of the water level of the flood season reservoir under the principle of'allowable sediment sedimentation 'of the reservoir. The problem that in the prior art, the flood season reservoir water level optimization scheduling index is difficult to determine under the principle that sediment deposition of a reservoir can be allowed is solved.

Description

Technical Field

[0001] The present application relates to the field of water conservancy engineering technology, and more specifically, to a method, system, and medium for determining an optimal scheduling index for a reservoir water level during flood season under the principle of "allowable sedimentation" in a reservoir. Background Art

[0002] With the completion of cascade reservoirs along the main and tributary rivers of various river basins, the water storage and sediment retention functions of upstream reservoirs, as well as their soil and water conservation efforts, have often resulted in a significant reduction in sediment inflow to downstream reservoirs, significantly slowing reservoir siltation. This has provided a favorable opportunity for optimized operation of downstream reservoirs. For reservoirs designed for "storing clear water and discharging turbid water" sedimentation management, optimizing flood season operating water levels will significantly improve the reservoir's overall efficiency. However, raising flood season reservoir levels will also increase reservoir siltation, particularly in the variable backwater area. This increased siltation in the variable backwater area can lead to a number of serious problems, including a reduction in effective storage capacity, higher flood water levels at the tail end of the reservoir, increased risk of inundation at the tail end of the reservoir, and increased tailwater levels for upstream power stations. Therefore, "tolerable sedimentation" has become a key principle for reservoir optimization. When determining optimized operation indicators for flood season reservoir water levels under this principle, it is necessary to consider the impact of optimized operation on siltation in the variable backwater area. Existing technologies often consider the combined impacts of flood control, sedimentation, power generation, shipping, and ecology when determining optimal reservoir water level scheduling indicators during flood season, ultimately producing a comprehensive decision value. The purpose of sedimentation calculations is often not to proactively propose optimal reservoir water level scheduling indicators during flood season based on the principle of "allowable sedimentation," but rather to passively assess the impact of sedimentation on optimal reservoir water level scheduling indicators during flood season based on other objectives such as flood control and power generation, and then provide a conclusion of agreement or disagreement based on the results of the sedimentation impact assessment. Therefore, existing technologies suffer from the limitation of only passively assessing impacts and failing to proactively determine optimal reservoir water level scheduling indicators. Summary of the Invention

[0003] The purpose of the embodiments of the present application is to overcome the shortcomings of the existing technology and provide a method, system and medium for determining the optimal scheduling index of the reservoir water level during the flood season, which can solve the problem that the existing technology cannot solve the problem of difficulty in determining the optimal scheduling index of the reservoir water level during the flood season under the principle of "permissible siltation".

[0004] To achieve the above objectives, this application provides the following technical solutions:

[0005] In a first aspect, an embodiment of the present application provides a method for determining an optimal scheduling index for a reservoir water level during a flood season, comprising the following steps:

[0006] Step 1: Collect data on reservoir river topography, incoming water and sediment, and reservoir operation methods;

[0007] Step 2: Establish a one-dimensional unsteady flow-water and sediment mathematical model of the reservoir;

[0008] Step 3: Select the typical flood season and sedimentation process representing the flood season and the dry season respectively;

[0009] Step 4: Based on the water and sediment process during the flood season of a typical year, a one-dimensional non-steady flow and sediment mathematical model of the reservoir is used to calculate the sediment scouring and deposition under different reservoir water levels during the flood season, and the calculation results of the sedimentation proportion and sedimentation amount in the variable backwater area are obtained;

[0010] Step 5: Draw a graph showing how the proportion of sedimentation in the variable backwater area and the amount of sedimentation change with the reservoir water level during the flood season, and find the critical reservoir water level at which the growth rate of the proportion of sedimentation in the variable backwater area begins to increase significantly. This critical reservoir water level is the optimized scheduling index for the reservoir water level during the flood season under the principle of "allowable sedimentation".

[0011] In step 1, the reservoir river topography that needs to be collected refers to the measured large sections of the main and tributary rivers in the reservoir area, the water and sediment data entering the reservoir are recent data to reflect the current reality, and the reservoir scheduling mode data are the reservoir scheduling modes during the flood season, water storage period, and drawdown period.

[0012] In step 2, after establishing a one-dimensional non-steady flow-water-sediment mathematical model of the reservoir, the model is verified using measured data to ensure the calculation accuracy of the model.

[0013] In step 3, the specific duration of the flood season is first determined based on the reservoir scheduling method collected in step 1, and then the water and sediment processes of typical flood seasons representing high and low water levels are selected from the reservoir water and sediment data collected in step 1.

[0014] In step 4, the siltation ratio of the variable backwater area refers to the ratio of the siltation amount of the variable backwater area to the siltation amount of the entire reservoir area.

[0015] In the second aspect, an embodiment of the present application provides a system for determining an optimal scheduling index for a reservoir water level during a flood season, the system comprising: a memory and a processor, the memory comprising a program for a method for determining an optimal scheduling index for a reservoir water level during a flood season, and the program for a method for determining an optimal scheduling index for a reservoir water level during a flood season, when executed by the processor, implements the steps of the method for determining an optimal scheduling index for a reservoir water level during a flood season as described above.

[0016] In a third aspect, an embodiment of the present application provides a computer-readable storage medium storing program code. When the program code is executed by a processor, the steps of the method for determining the optimal scheduling index of the flood season reservoir water level are implemented as described above.

[0017] Compared with the prior art, the present invention has the following beneficial effects:

[0018] A method for determining the optimal scheduling index of the reservoir water level during the flood season under the principle of "allowable siltation" of the reservoir can be obtained, which is helpful to determine the optimal scheduling index of the reservoir water level during the flood season under the principle of "allowable siltation" of the reservoir, and provides technical support for scientific scheduling of the reservoir. The method of the present invention is applicable to the problem of determining the optimal scheduling index of the reservoir water level during the flood season under the principle of "allowable siltation" of various large reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A flow chart of the method of this application;

[0021] Figure 2 This is a graph showing the percentage of siltation in the backwater area and the amount of siltation in July according to the embodiment of this application. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present application will be described below in conjunction with the accompanying drawings. It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0023] The terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0024] The terms "first," "second," etc. are only used to distinguish one entity or operation from another entity or operation, and are not to be understood as indicating or implying relative importance, nor are they to be understood as requiring or implying any actual relationship or order between these entities or operations.

[0025] See also Figure 1 The embodiment of the present application provides a method for determining an optimal scheduling index for a reservoir water level during a flood season, comprising the following steps:

[0026] Step 1: Collect data on reservoir river topography, incoming water and sediment, and reservoir operation methods;

[0027] Step 2: Establish a one-dimensional unsteady flow-water and sediment mathematical model of the reservoir;

[0028] Step 3: Select the typical flood season and sedimentation process representing the flood season and the dry season respectively;

[0029] Step 4: Based on the water and sediment process during the flood season of a typical year, a one-dimensional non-steady flow and sediment mathematical model of the reservoir is used to calculate the sediment scouring and deposition under different reservoir water levels during the flood season, and the calculation results of the sedimentation proportion and sedimentation amount in the variable backwater area are obtained;

[0030] Step 5: Draw a graph showing how the proportion of sedimentation in the variable backwater area and the amount of sedimentation change with the reservoir water level during the flood season, and find the critical reservoir water level at which the growth rate of the proportion of sedimentation in the variable backwater area begins to increase significantly. This critical reservoir water level is the optimized scheduling index for the reservoir water level during the flood season under the principle of "allowable sedimentation".

[0031] In step 1, the reservoir river topography that needs to be collected refers to the measured large sections of the main and tributary rivers in the reservoir area, the water and sediment data entering the reservoir are recent data to reflect the current reality, and the reservoir scheduling mode data are the reservoir scheduling modes during the flood season, water storage period, and drawdown period.

[0032] In step 2, after establishing a one-dimensional non-steady flow-water-sediment mathematical model of the reservoir, the model is verified using measured data to ensure the calculation accuracy of the model.

[0033] In step 3, the specific duration of the flood season is first determined based on the reservoir scheduling method collected in step 1, and then the water and sediment processes of typical flood seasons representing high and low water levels are selected from the reservoir water and sediment data collected in step 1.

[0034] In step 4, the siltation ratio of the variable backwater area refers to the ratio of the siltation amount of the variable backwater area to the siltation amount of the entire reservoir area.

[0035] Example 1:

[0036] Data will be collected on the measured large-scale topography of the BHT Reservoir's main and tributary rivers by the end of 2023, water and sediment inflows from 2020 to 2023, and reservoir operation methods. Based on the latest optimized operation methods, the BHT Reservoir's normal water level, flood control limit level, and dead water level are 825m, 785m, and 765m, respectively. The reservoir level should generally fall to the flood control limit level by the end of June. The flood control limit level will be 785m in July, the flood season. In early July, the reservoir level will be controlled to fluctuate within 787.5m. The reservoir level will gradually fluctuate in mid-to-late July. Starting on August 1st, water will be gradually stored at the previous operating level. In mid-to-late August, water will be gradually stored to the normal storage level of 825m. The BHT Reservoir's diversion tunnel overflowed in 2014, and sluice gates began to be closed in 2021. The upstream WDD Reservoir began sluice gate storage in 2020.

[0037] A one-dimensional non-steady flow and sediment mathematical model of the main and tributary rivers of the BHT reservoir was established, and the model was verified using the measured water level and flow data and sediment scouring and deposition data of the reservoir area from 2022 to 2023. The verification calculation results of water level, flow, sedimentation, and sediment discharge ratio were in good agreement with the measured values, indicating that the constructed model can be used to carry out calculation research on sedimentation problems in the optimal scheduling of the BHT reservoir.

[0038] The BHT Reservoir has a relatively short storage lifespan. Therefore, from the water and sediment inflow data for 2020-2023, the water and sediment processes in July of 2020, 2022, and 2023 were selected as representative water and sediment processes for flood season calculations at the BHT Reservoir. 2020 was used as a representative year of high water flow, while 2022 and 2023 were used as representative years of low water flow. Table 1 shows the water and sediment characteristic values ​​for July at the WDD station at the tail of the BHT Reservoir, and Table 2 shows the sediment inflows into the BHT Reservoir in July, including interval sediment loads. The water inflows to the BHT Reservoir primarily come from the WDD station.

[0039] Table 1 Water and sediment characteristic values ​​at WDD station

[0040] time <![CDATA[Water volume (100 million m 3 )]]> Sand volume (10,000 tons) <![CDATA[Maximum peak flood discharge (m 3 / s)]]> <![CDATA[Maximum sediment concentration (kg / m 3 )]]> July 2020 192 82 12400 0.083 July 2022 139 31 7600 0.049 July 2023 107 23 5850 0.114

[0041] Table 2 Sediment inflow into BHT Reservoir in July (including interval sediment inflow)

[0042]

[0043]

[0044] Based on the water and sediment processes during the flood season of a typical year, a one-dimensional non-steady flow and sediment mathematical model of the reservoir was used to calculate sediment scour and deposition under different reservoir water levels during the flood season, and the sediment accumulation percentage and amount in the variable backwater area were calculated. The proposed calculation scheme combines the following conditions: the inlet boundary is the measured water and sediment processes entering the reservoir in July 2020, 2022, and 2023, respectively. The water level in front of the BHT reservoir remains unchanged every day in July throughout the flood season, and the water levels in front of the dam are 765m, 770m, 775m, 780m, 785m, 787.5m, 790m, 795m, 800m, 805m, 810m, 815m, 820m, and 825m respectively.

[0045] Draw the calculation results of the proportion of sedimentation in the backwater area of ​​BHT reservoir and the amount of sedimentation as the reservoir water level changes during flood season, see Figure 2 .from Figure 2 As can be seen, in July during the flood season, when the reservoir water level was below 805m, both the percentage and amount of siltation in the variable backwater area were very low. After the reservoir water level rose above 805m, the growth rate of the percentage of siltation in the variable backwater area began to accelerate significantly. Furthermore, due to the significant decrease in sediment inflow after reservoir construction and the relatively short calculation period, the amount of siltation in the variable backwater area remained relatively small. When the reservoir water level was below 805m, the percentage of siltation in the variable backwater area in July 2020 and 2023 was very similar, around 3%, and the percentage in July 2022 was around 6%. This characteristic of low water levels and high sediment content is the main reason for the relatively high percentage of siltation in the variable backwater area in July 2022. It can be seen that in July during the flood season, the reservoir water level of 805m is the critical water level at which the proportion of siltation in the variable backwater area begins to increase rapidly. Therefore, the critical reservoir water level of 805m can be preliminarily regarded as the flood season reservoir water level optimization scheduling indicator under the principle of "permissible siltation" of the BHT reservoir. In the process of carrying out flood season optimization scheduling, in order to reduce siltation in the reservoir area, especially in the variable backwater area, it is recommended that the reservoir operation and management unit and the scheduling unit decide whether the BHT reservoir water level can exceed 805m during the flood season based on the amount of water and sediment entering the reservoir.

[0046] An embodiment of the present application provides a system for determining an optimal scheduling index for a reservoir water level during a flood season. The system includes: a memory and a processor. The memory includes a program for a method for determining an optimal scheduling index for a reservoir water level during a flood season. When the program for the method for determining an optimal scheduling index for a reservoir water level during a flood season is executed by the processor, the steps of the method for determining an optimal scheduling index for a reservoir water level during a flood season as described above are implemented.

[0047] An embodiment of the present application provides a computer-readable storage medium storing program code. When the program code is executed by a processor, the steps of the method for determining the optimal scheduling index of the flood season reservoir water level are implemented as described above.

[0048] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0049] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0050] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0051] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0052] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0053] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0054] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0055] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for determining reservoir water level optimization scheduling indicators during flood season, characterized in that: The following steps are involved: Step 1: Collect data on reservoir river topography, incoming water and sediment, and reservoir operation methods; Step 2: Establish a one-dimensional unsteady flow-water and sediment mathematical model of the reservoir; Step 3: Select the typical flood season and sedimentation process representing the flood season and the dry season respectively; Step 4: Based on the water and sediment process during the flood season of a typical year, a one-dimensional non-steady flow and sediment mathematical model of the reservoir is used to calculate the sediment scouring and deposition under different reservoir water levels during the flood season, and the calculation results of the sedimentation proportion and sedimentation amount in the variable backwater area are obtained; Step 5: Draw a graph showing how the proportion and amount of sedimentation in the variable backwater area changes with the reservoir water level during the flood season. From the graph, find the critical reservoir water level at which the growth rate of the proportion of sedimentation in the variable backwater area begins to increase significantly. This critical reservoir water level is the optimal scheduling indicator for the reservoir water level during the flood season under the principle of "allowable sedimentation." 2. The method for determining the optimal scheduling index of reservoir water level during flood season according to claim 1, characterized in that: In step 1, the reservoir river topography that needs to be collected refers to the measured large sections of the main and tributary rivers in the reservoir area, the water and sediment data entering the reservoir are recent data to reflect the current reality, and the reservoir scheduling mode data are the reservoir scheduling modes during the flood season, water storage period, and drawdown period.

3. The method for determining the optimal scheduling index of reservoir water level during flood season according to claim 1, characterized in that: In step 2, after establishing a one-dimensional non-steady flow-water-sediment mathematical model of the reservoir, the model is verified using measured data to ensure the calculation accuracy of the model.

4. The method for determining the optimal scheduling index of reservoir water level during flood season according to claim 1, characterized in that: In step 3, the specific duration of the flood season is first determined based on the reservoir scheduling method collected in step 1, and then the water and sediment processes of typical flood seasons representing high and low water levels are selected from the reservoir water and sediment data collected in step 1.

5. The method for determining the optimal scheduling index of reservoir water level during flood season according to claim 1, characterized in that: In step 4, the siltation ratio of the variable backwater area refers to the ratio of the siltation amount of the variable backwater area to the siltation amount of the entire reservoir area.

6. A system for determining reservoir water level optimization scheduling indicators during flood season, characterized in that: The system includes: a memory and a processor, wherein the memory includes a program for determining a method for optimizing the scheduling index of a reservoir water level during a flood season, and when the program is executed by the processor, the following steps are implemented: Step 1, collecting data on reservoir river topography, inflow water and sediment, and reservoir scheduling methods; Step 2: Establish a one-dimensional unsteady flow-water and sediment mathematical model of the reservoir; Step 3: Select the typical flood season and sedimentation process representing the flood season and the dry season respectively; Step 4: Based on the water and sediment process during the flood season of a typical year, a one-dimensional non-steady flow and sediment mathematical model of the reservoir is used to calculate the sediment scouring and deposition under different reservoir water levels during the flood season, and the calculation results of the sedimentation proportion and sedimentation amount in the variable backwater area are obtained; Step 5: Draw a graph showing how the proportion and amount of sedimentation in the variable backwater area changes with the reservoir water level during the flood season. From the graph, find the critical reservoir water level at which the growth rate of the proportion of sedimentation in the variable backwater area begins to increase significantly. This critical reservoir water level is the optimal scheduling indicator for the reservoir water level during the flood season under the principle of "allowable sedimentation." 7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores program code, and when the program code is executed by a processor, the steps of the method for determining the flood season reservoir water level optimization scheduling index as described in any one of claims 1 to 5 are implemented.

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