Reservoir flood control water level dynamic control and flood recycling method and system

Abstract

The invention relates to the technical field of flood control dispatching, and discloses a reservoir flood control water level dynamic control and flood recycling method and system, and the method comprises the steps: obtaining a surface rainfall forecast value of a reservoir basin based on real-time rainwater condition data and numerical weather forecast; a hydrodynamics and hydrology coupled drainage basin runoff model is driven, and an in-reservoir flood hydrograph in a predicted period is generated; judging the flood scale and grade based on the hydrograph, and when the flood is medium and small flood, calculating the dynamic flood control storage capacity of a downstream flood control object by adopting an equivalent flood control effect algorithm taking into account the pre-discharge scheduling capability; according to the dynamic flood control storage capacity, a dynamic flood control water level control value is obtained through backstepping of a water level-storage capacity relation curve of the reservoir; and finally, generating and executing a reservoir dispatching instruction based on the control value, and storing the water level of the reservoir to not exceed the dynamic value. The problems that a fixed flood control water level method is low in water resource utilization rate and inflexible in dispatching are solved, and flood resource efficient utilization on the premise of flood control safety is achieved.

Description

Technical Field

[0001] This application relates to the field of flood control scheduling technology, and in particular to a method and system for dynamic control of reservoir flood control limit water level and flood resource utilization. Background Technology

[0002] The flood control limit level of a reservoir is the upper limit of water level at which water can be stored for beneficial purposes during the flood season. It is a key control indicator for reconciling the conflict between flood control and water use in reservoirs. Traditional reservoir operation generally adopts the fixed flood control limit level method, which strictly limits the reservoir water level to a predetermined fixed elevation during the flood season. Although this method is simple to operate, it has significant technical limitations in practical applications.

[0003] First, the fixed flood control water level method fails to fully consider the temporal variability of hydrological and meteorological conditions and forecast information. Its setting is primarily based on historical hydrological sequences and design floods, failing to respond to the spatiotemporal differences in actual rainfall and the decision-making optimization space brought about by improved forecast accuracy. This results in reservoirs still needing to maintain low water levels even when there is no risk of major floods within the forecast period, failing to effectively retain flood tails or small to medium-sized flood resources, causing the wasteful release of water resources and reducing the comprehensive utilization benefits of the reservoir.

[0004] Secondly, this method lacks sufficient scheduling flexibility, making it difficult to achieve a dynamic balance between flood control safety and efficient water resource utilization. The fixed water level control model ignores the randomness of the actual flood inflow process into the reservoir and the changes in the downstream river's discharge capacity, resulting in a rigid scheduling process. When facing small to medium-sized floods, the failure to accurately quantify the flood scale and its actual demand on flood control capacity often sacrifices potential beneficial water storage opportunities due to inherent flood control redundancy.

[0005] Furthermore, with the development of numerical weather prediction and hydrodynamic modeling technologies, precise flood forecasting and early warning have become possible. However, the traditional fixed flood control level method has failed to effectively integrate these advanced technological achievements into the scheduling decision-making process, and the value of forecast information has not been fully utilized, thus hindering the improvement of the scientific and forward-looking nature of reservoir scheduling. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, the embodiments of this application provide a method for dynamic control of reservoir flood control level and flood resource utilization to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, this application provides a method for dynamic control of reservoir flood control water level and flood resource utilization, comprising:

[0008] Based on real-time rainfall and water level data and numerical weather prediction, the areal rainfall forecast value of the reservoir basin is obtained;

[0009] Using the areal rainfall forecast as input, a watershed runoff generation and confluence model coupled with hydrodynamics and hydrology is driven to generate the inflow flood process line within the forecast period;

[0010] Based on the inflow flood process line, the flood scale level is determined. When it is determined to be a small to medium flood, the equivalent flood control effect algorithm is used to calculate the dynamic flood control capacity of the downstream flood control object.

[0011] Based on the dynamic flood control capacity, the dynamic flood limit water level control value is obtained by back-calculating the water level-capacity relationship curve of the reservoir.

[0012] Based on the dynamic flood control level, a reservoir scheduling instruction is generated and executed to raise the reservoir water level to no more than the dynamic flood control level.

[0013] To address the aforementioned problems, this application also provides a reservoir flood control level dynamic control and flood resource utilization system, the system comprising:

[0014] The areal rainfall forecast acquisition module is used to obtain the areal rainfall forecast value of the reservoir basin based on real-time rainfall and water conditions data and numerical weather forecasts.

[0015] The inflow flood hydrograph generation module is used to drive the watershed runoff generation and confluence model coupled with hydrodynamics and hydrology, using the areal rainfall forecast value as input, to generate the inflow flood hydrograph within the forecast period;

[0016] The dynamic flood control storage capacity calculation module is used to determine the flood scale level based on the inflow flood process line. When it is determined to be a small to medium flood, the equivalent flood control effect algorithm is used to calculate the dynamic flood control storage capacity of the downstream flood control object.

[0017] The dynamic flood control limit water level back-calculation module is used to back-calculate the dynamic flood control limit water level control value based on the dynamic flood control capacity and the water level-capacity relationship curve of the reservoir.

[0018] A reservoir scheduling instruction generation and execution module is used to generate and execute reservoir scheduling instructions based on the dynamic flood control level, so as to raise the reservoir water level to no more than the dynamic flood control level. Compared with the prior art, this application has the following advantages:

[0019] This invention effectively overcomes the limitations of traditional fixed flood control level methods by constructing a dynamic control system that integrates numerical weather prediction, hydrodynamic and hydrological coupling models, and equivalent flood control algorithms. Its primary technical effect is a significant improvement in the utilization efficiency of flood resources. Based on corrected areal rainfall forecasts, this method drives a high-precision watershed runoff generation and concentration model to generate the inflow flood process line within the forecast period, providing a reliable data foundation for subsequent decision-making. By accurately determining the flood scale and level, and specifically employing an equivalent flood control algorithm to calculate dynamic flood control capacity for small and medium-sized floods, this algorithm innovatively incorporates the reservoir's pre-release scheduling capacity within the forecast period. This reduces the required static flood control capacity while meeting the safe discharge requirements of downstream flood-prone areas. The dynamically calculated flood control level is higher than the fixed value, allowing the reservoir to store more floodwater that would otherwise need to be released within the safety boundary, directly converting floodwater into usable water resources and realizing flood resource utilization.

[0020] Another significant technical advantage of this invention is its comprehensive enhancement of the scientific rigor and precision of reservoir flood control scheduling, as well as its improved system decision-making efficiency. From the acquisition and correction of areal rainfall data, to the simulation of the physical mechanisms of inflow floods, to the intelligent calculation of dynamic reservoir capacity and the reverse estimation of water levels, and finally to the generation and execution of scheduling instructions, a complete, closed-loop, and highly automated technical chain is formed. This method closely integrates quantitative hydrological and hydrodynamic analysis with scheduling decisions, replacing the previous reliance on experience-based qualitative or semi-quantitative judgments. This makes the decision-making process more evidence-based and the results more accurate and reliable. Simultaneously, the systematized process design enables rapid conversion and execution from data to instructions, greatly shortening the response time of scheduling decisions and improving the overall efficiency and proactiveness of reservoirs in responding to floods. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating a method for dynamic control of reservoir flood control water level and flood resource utilization provided in an embodiment of this application.

[0022] Figure 2 This is a functional block diagram of a reservoir flood control limit water level dynamic control and flood resource utilization system provided in an embodiment of this application;

[0023] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0024] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0025] This application provides a method for dynamic control of reservoir flood control levels and flood resource utilization. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data and artificial intelligence platforms.

[0026] Reference Figure 1 The diagram shown is a flowchart illustrating a method for dynamic control of reservoir flood control levels and flood resource utilization according to an embodiment of this application. In this embodiment, the method includes:

[0027] S1. Based on real-time rainfall and water level data and numerical weather forecasts, obtain the areal rainfall forecast value for the reservoir basin.

[0028] In some embodiments, obtaining the areal rainfall forecast value of the reservoir basin based on real-time rainfall and water level data and numerical weather prediction includes:

[0029] The numerical weather forecast is obtained, and rainfall data for the forecast period at each forecast point within the reservoir basin is extracted from it.

[0030] Based on the real-time rainfall and water level data, the rainfall data is corrected and assimilated in real time using the physical causal analysis method to obtain the areal rainfall forecast value of the reservoir basin.

[0031] In this embodiment, real-time rainfall and water level data are data reflecting the current hydrological and meteorological conditions, such as rainfall, river flow, and water level, collected in real time by hydrological monitoring stations, including rain gauges and water level stations; numerical weather prediction is rainfall-related forecast data for a future period of time generated based on atmospheric physical equations and numerical models.

[0032] In this embodiment of the application, the reservoir basin is the catchment area corresponding to the reservoir, that is, the entire geographical area where rainwater flows into the reservoir; the areal rainfall forecast value is the average rainfall forecast result within the reservoir basin, which can characterize the rainfall intensity level of the entire basin.

[0033] In the embodiments of this application, the forecast period is the future time interval covered by numerical weather forecasts, typically 24 to 72 hours; the rainfall data is the rainfall record for each specific forecast point within the reservoir basin during the forecast period in numerical weather forecasts; the physical causal analysis method is an analytical method that corrects the deviation of forecast data and fuses data by analyzing key factors affecting rainfall, such as topography and meteorological factors.

[0034] In this embodiment of the application, the specific implementation process of obtaining numerical weather forecasts and extracting rainfall data is as follows: First, the raw data of numerical weather forecasts is obtained through meteorological data receiving equipment such as satellite receiving terminals and meteorological department data interfaces. The raw data contains meteorological forecast information for a wide area. Geographic information filtering technology is used to lock the geographical boundary range of the reservoir basin. Then, the rainfall data of each preset forecast point in the basin is separated from the raw data using data extraction algorithms. The layout of forecast points needs to be determined based on the basin topographic features and station density uniformity to ensure coverage of the entire basin and representative data.

[0035] For example, a reservoir has a drainage area of ​​500 square kilometers and 20 forecast points are set up. The above-mentioned technical means are used to extract the hourly rainfall data of each forecast point in the next 24 hours from numerical weather prediction, forming a rainfall time series data sequence for each forecast point.

[0036] In this embodiment of the application, the specific implementation of correcting and assimilating real-time rainfall data using physical causal analysis to obtain areal rainfall forecast values ​​is as follows:

[0037] First, a data processing platform is built to synchronously input the extracted rainfall data from each forecast point and the real-time rainfall and water level data. The real-time rainfall and water level data is collected in real time by the sensors of the hydrological monitoring station and transmitted to the processing platform to ensure the timeliness of the data.

[0038] Next, using the physical causal analysis method, we first analyze the influence of topographic factors such as altitude and slope aspect, as well as meteorological factors such as wind speed and humidity on the rainfall at each forecast point. Combining the error analysis of historical rainfall data and real-time monitoring data, we determine the correction coefficient for each forecast point. The basis for determining the correction coefficient is the statistical results of the ratio of forecast rainfall to actual rainfall under the same topographic and meteorological conditions in history, to ensure that the correction coefficient conforms to the rainfall influence characteristics of the forecast point.

[0039] Then, the rainfall data of each forecast point is corrected using a correction formula. The core logic of this formula is to multiply the forecast rainfall by the corresponding correction coefficient to obtain the corrected rainfall. For example, if the forecast rainfall of a certain forecast point is 10 mm, and considering that its terrain is low hills and the real-time humidity is high, the correction coefficient is determined to be 1.1 through historical data statistics. The corrected rainfall of the forecast point is calculated to be 11 mm.

[0040] Finally, after correction, the data is assimilated using a weighted average method. The weights are assigned based on the size of the watershed area represented by each forecast point, the complexity of the terrain, and the reliability of the station data. For example, forecast points in the central area of ​​the watershed are assigned a weight of 0.08 because they have a wide coverage and high data stability, while forecast points in the peripheral areas are assigned a weight of 0.03. The areal rainfall forecast value for the reservoir watershed is obtained by multiplying the corrected rainfall of each forecast point by its corresponding weight, summing all the product results, and finally dividing by the sum of all weights.

[0041] For example, the weighted sum of the corrected rainfall from 20 forecast points is 220, with a weighted sum of 20, resulting in a calculated areal rainfall forecast of 11 mm. Throughout the process, the correction coefficients and weights are dynamically adjusted using real-time updated rainfall and water level data to ensure the accuracy and timeliness of the areal rainfall forecast. The physical causal analysis method employed fully considers the influencing factors of rainfall within the watershed, overcoming the limitations of traditional methods that rely solely on raw numerical forecast data and significantly improving forecast accuracy.

[0042] In this embodiment of the application, this step solves the problem of insufficient accuracy of rainfall forecast in specific reservoir basins by accurately extracting rainfall data and combining it with physical causal analysis for correction and assimilation. This avoids subsequent flood forecast deviations and scheduling decision errors caused by inaccurate rainfall forecasts.

[0043] S2. Using the areal rainfall forecast value as input, drive the watershed runoff generation and confluence model coupled with hydrodynamics and hydrology to generate the inflow flood process line within the forecast period.

[0044] In some embodiments, the step of using the areal rainfall forecast value as input to drive a watershed runoff generation and confluence model coupled with hydrodynamics and hydrology to generate the inflow flood hydrograph within the forecast period includes:

[0045] Based on the above areal rainfall forecast values, the watershed runoff is calculated using the unit hydrograph method to obtain the watershed net rainfall process;

[0046] Using the net rainfall process of the watershed as the upper boundary condition, and based on the digital elevation model and river cross-section data, the river confluence calculation is completed by solving the Saint-Venant equations, thereby generating the inflow flood process line within the forecast period.

[0047] In this embodiment, the watershed runoff generation and confluence model is a coupled model that integrates hydrological runoff generation calculation and hydrodynamic confluence simulation, which can completely simulate the entire process of rainfall being converted into reservoir inflow. The unit hydrograph method is a classic hydrological method that calculates the runoff process corresponding to the actual net rainfall by using a preset unit time period runoff process line generated by net rainfall per unit time period.

[0048] In this embodiment of the application, the watershed net rainfall process is the sequence of rainfall that actually participates in the formation of runoff over time after deducting rainfall losses (including evaporation, infiltration, etc.) from the surface rainfall within the watershed; the digital elevation model (DEM) is a digital model of the watershed topography constructed from discrete elevation point data, which can reflect geographical features such as topographic relief and river course.

[0049] In this embodiment, the river cross-section data are geometric parameters such as water depth, river width, and flow area at different cross-sections of the river obtained through field measurements; the Saint-Venant equations are a set of classical equations describing the flow motion in the river, including the continuity equation reflecting the conservation of flow mass and the momentum equation reflecting the conservation of energy; the river confluence calculation uses a hydrodynamic model to simulate the process of runoff formed by net rainfall evolving from upstream to downstream in the river channel and finally reaching the reservoir inlet cross-section; the inflow flood hydrograph is a curve showing the change of flow rate at the reservoir inlet cross-section over time, which can intuitively reflect key characteristics such as the flood peak size and flood duration within the forecast period.

[0050] In this embodiment of the application, the specific implementation of calculating the net rainfall process of the watershed using the unit hydrograph method based on the areal rainfall forecast is as follows:

[0051] First, determine the calculation period, which is usually consistent with the time resolution of the areal rainfall forecast (e.g., 1 hour) to ensure data time sequence matching.

[0052] Next, the rainfall loss in the watershed is analyzed. This loss needs to be determined in combination with the soil type in the watershed (such as loam and sand) and the soil moisture in the previous period (such as drought and wet). For example, if the soil in a certain watershed is loam and it was wet in the previous period, the hourly rainfall loss is set to 2 mm. This value is based on the statistical analysis of historical rainfall-runoff observation data, which can ensure that the loss calculation is consistent with the actual hydrological characteristics of the watershed.

[0053] Then, the net rainfall of the watershed for each time period is calculated. The calculation logic is to subtract the rainfall loss of the corresponding time period from the areal rainfall forecast value. For example, taking the areal rainfall forecast value of 11 mm / h obtained in S1, subtracting the rainfall loss of 2 mm / h, we get the net rainfall of the watershed of 9 mm / h for that time period. The net rainfall of each time period within the forecast period is calculated in sequence according to this logic to form a continuous net rainfall process in the watershed (e.g., the net rainfall of each time period fluctuates between 7-10 mm within the 24-hour forecast period).

[0054] Finally, the unit hydrograph method is used to calculate the runoff. First, a unit hydrograph applicable to the basin is derived based on the historical flood data of the basin (such as the 1-hour runoff process line generated by 1 hour of net rainfall, with a peak flow of 30 cubic meters per second). Then, the net rainfall of each time period is multiplied by the runoff coefficient of the corresponding time period of the unit hydrograph, and the actual runoff of each time period is obtained by summing them up, thus completing the runoff generation calculation of the basin.

[0055] In this embodiment of the application, this step solves the problem of traditional single hydrological models ignoring the physical mechanism of water flow and having low confluence accuracy by using a watershed runoff generation and confluence model that couples hydrodynamics and hydrology. The generated inflow flood process line can accurately reflect the actual characteristics of the flood within the forecast period, providing accurate data support for subsequent judgment of flood scale and level and calculation of dynamic flood control capacity.

[0056] In some embodiments, the step of using the net rainfall process of the watershed as the upper boundary condition, and based on the digital elevation model and river cross-section data, completing the river confluence calculation by solving the Saint-Venant equations to generate the inflow flood hydrograph for the forecast period includes:

[0057] Based on the digital elevation model and the river cross-section data, the finite volume method is used to divide the river into grids in order to construct a river hydrodynamic model.

[0058] The net rainfall process in the watershed is used as the upstream boundary input condition of the river hydrodynamic model, and the real-time monitored river flow data is used as the initial hydrological condition of the river hydrodynamic model.

[0059] Based on the river hydrodynamic model, the upstream boundary input conditions and the initial hydrological conditions, the flow evolution of the entire river channel is simulated by solving the Saint-Venant equations to obtain the flow process data at the reservoir inlet section.

[0060] Based on the flow process data, an inflow flood process curve for the forecast period is generated.

[0061] In some embodiments, the Saint-Venant equations include a mass conservation equation describing the continuity of water flow and a momentum conservation equation describing energy conversion. By solving the Saint-Venant equations simultaneously, the hydrodynamic transformation from the net rainfall process in the watershed to the flow process at the reservoir inlet section can be realized.

[0062] In this embodiment, the finite volume method is a numerical calculation method that divides the computational domain into multiple discrete control volumes (grids) and performs numerical solutions for each control volume based on conservation laws. It is suitable for simulating fluid dynamics problems such as river flow motion. River grid division is the process of dividing the river region into several regular or irregular computational units using the finite volume method. Each unit contains clear geometric boundaries and hydrological parameters, providing a computational basis for the hydrodynamic model.

[0063] In this embodiment, the river hydrodynamic model is a mathematical model constructed based on river topographic data and hydrodynamic principles, which can simulate the movement state of water flow in the river (such as flow velocity, flow rate, and water level changes). The upstream boundary input conditions are the initial driving data on the upstream side provided for the river hydrodynamic model, which are used to reflect the upstream water inflow situation. In this application, they are the lateral inflow data after the watershed net rainfall process is converted.

[0064] In this application embodiment, the initial hydrological conditions are the initial flow state data when the river hydrodynamic model is started, which are used to determine the starting benchmark for model calculation. In this application, it is the real-time monitored river flow data. The whole river flow evolution simulation is to simulate the entire process of water flow from generation to movement to the reservoir inlet section from the upstream to the downstream of the river through the river hydrodynamic model, covering the spatiotemporal changes of water flow velocity and flow rate.

[0065] In this embodiment, the flow process data is a collection of flow values ​​at different times at the reservoir inlet section, forming a flow sequence that changes over time and reflects the dynamic characteristics of the inflow. The mass conservation equation is a component of the Saint-Venant equations, describing the law that the mass of the water flow remains constant during the movement, and reflecting the relationship between the cross-sectional area and the flow rate change.

[0066] In this embodiment, the momentum conservation equation is a component of the Saint-Venant equations, which describes the balance between the change in momentum and external forces such as gravity and friction during water flow, and reflects the relationship between flow rate, water level, and resistance. The hydrodynamic conversion is the process of converting the net rainfall process (hydrological data) of the watershed into the flow process at the reservoir inflow section (hydrodynamic data) by solving the Saint-Venant equations, thereby simulating the physical mechanism from rainfall to flood inflow.

[0067] In this embodiment of the application, the specific implementation of constructing a river hydrodynamic model by dividing the river channel into grids using the finite volume method based on the digital elevation model and river cross-section data is as follows:

[0068] First, the basic data is preprocessed. The digital elevation model (30-meter resolution) obtained from S2 is imported into the Geographic Information System (GIS). The river centerline and basin boundary are extracted using terrain analysis tools to determine the scope of the river simulation (e.g., from the confluence of upstream tributaries to the reservoir inlet section, a total length of 50 kilometers). At the same time, the river cross-section data (100 cross-sections in total, one cross-section every 500 meters) is organized, including parameters such as the river width (e.g., 30 meters in the upstream section, 50 meters in the midstream section, and 80 meters in the downstream section), water depth (average 1.5 meters in the upstream section, 2.5 meters in the midstream section, and 3 meters in the downstream section), and water flow area (45 square meters in the upstream section, 125 square meters in the midstream section, and 240 square meters in the downstream section), and a cross-section attribute database is established.

[0069] Next, the finite volume method was used to divide the simulation area into 167 control volumes (grids) along the river channel, with the river centerline as the reference. Each grid is approximately 300 meters long, and the lateral boundaries of the grids are based on the contour lines of the riverbanks to ensure that the grids cover the entire river cross-section. The geometric parameters of each cross-section (such as the water flow area and river width) were assigned to the corresponding grid. At the same time, the Manning roughness of each grid was set according to the vegetation cover in the river channel (such as herbaceous cover in the upstream and shrub cover in the downstream) (0.03 in the upstream, 0.035 in the midstream, and 0.04 in the downstream), and the water flow exchange rules between grids were defined. Finally, the physical structure of the river hydrodynamic model was completed. This model can accurately reflect the influence of river topographic differences on water flow and provides a reliable computational framework for subsequent water flow evolution simulation.

[0070] In this embodiment of the application, the specific implementation of using the watershed net rainfall process as the upstream boundary input condition and the real-time monitored river flow data as the initial hydrological condition is as follows:

[0071] The first step is to convert the net rainfall process of the watershed. The net rainfall process of the watershed obtained from S2 is used (e.g., the net rainfall in each period is between 7-10 mm within the 24-hour forecast period). Based on the watershed area (500 square kilometers) and soil infiltration characteristics, the net rainfall is converted into lateral inflow intensity using the runoff coefficient method. For example, if the net rainfall is 9 mm in a certain period, the runoff coefficient is taken as 0.8, and the lateral inflow intensity is calculated to be 0.002 cubic meters per second per square meter. The data is then organized into an upstream boundary data file that the model can recognize by time series. This file contains the lateral inflow values ​​at each calculation time (time step set to 10 minutes) to ensure that the upstream water inflow data is completely matched with the net rainfall process.

[0072] The second step is to acquire and set the initial hydrological conditions. Real-time flow data is obtained from the river monitoring station 5 kilometers upstream of the reservoir. For example, if the measured flow at the simulation start time (the start time of the forecast period) is 50 cubic meters per second, this flow value is assigned as the initial condition to all grids of the river hydrodynamic model to ensure that the initial state of the model is consistent with the actual water flow in the river and to avoid distortion of subsequent simulation results due to deviations in the initial conditions. At the same time, the rationality of the initial flow data is verified by comparing it with the flow data at the same water level in the same period of history. After confirming that there are no abnormalities in the data (such as no sudden increase or decrease), the boundary and initial conditions are set.

[0073] In this embodiment, the Saint-Venant equations are solved based on a river hydrodynamic model and boundary and initial conditions to simulate the evolution of the entire river flow and obtain inflow cross-section data. The specific implementation is as follows:

[0074] The first step is to determine the numerical solution method. The Preissmann implicit difference scheme is used to discretize the Saint-Venant equations. This scheme can effectively handle different states of river flow, such as slow flow and rapid flow, by approximating the time and space derivatives with differences. It also has good numerical stability (convergence error controlled within 0.01) and is suitable for simulating the evolution of long-distance flow in the entire river channel.

[0075] The second step involves simultaneously solving the mass conservation equation and the momentum conservation equation. The core logic of the mass conservation equation is that the change in the cross-sectional area of ​​a grid cell over time is equal to the difference between the upstream inflow and downstream outflow of that cell, plus the lateral inflow (net rainfall conversion data from the upstream boundary). For example, at a certain moment, the upstream inflow of a grid cell is 60 cubic meters per second, the downstream outflow is 58 cubic meters per second, and the lateral inflow is 3 cubic meters per second. Therefore, the increase in the cross-sectional area of ​​that grid cell over time corresponds to the area change of 5 cubic meters per second. The core logic of the momentum conservation equation is that the change in the flow rate of a grid cell over time is balanced by the change in the kinetic energy of the water in that cell (related to the square of the flow rate and the cross-sectional area), the effect of gravity (related to the water level difference), and the frictional resistance (related to the Manning roughness and the square of the flow rate). For example, when water flows from a high water level to a low water level upstream, gravity promotes the increase in flow rate, while frictional resistance inhibits the increase in flow rate. The equation uses numerical calculation to balance the forces and obtain the flow rate value at that moment.

[0076] The third step involves performing a full-channel flow evolution simulation. After inputting the boundary and initial conditions into the model, the total calculation time (24 hours, consistent with the forecast period) and time step (10 minutes, with a total of 144 calculation steps) are set, and the model is started for iterative calculation. Within each time step, the model solves the Saint-Venant equations for all grid cells in sequence, updates the parameters such as flow rate, water level, and flow area of ​​each grid, and uses the calculation results of the downstream grid as the input for the next time step of the upstream adjacent grid, realizing the segmented evolution of the flow from upstream to downstream. During the simulation, the flow data of key sections (such as the midstream control section and the section 1 kilometer before the reservoir) are monitored in real time and compared with the historical flood simulation results to ensure that the simulation trend is reasonable (e.g., the flood peak propagation speed conforms to the actual hydraulic characteristics of the river channel, about 0.5 meters per second).

[0077] The fourth step is to extract the inflow process data at the reservoir inlet section. When the water flow reaches the reservoir inlet section (the downstream end grid of the model), the flow value at each time step is recorded to form a flow sequence within the 24-hour forecast period (e.g., 52 cubic meters per second in the 1st hour, 85 cubic meters per second in the 6th hour, 480 cubic meters per second in the 12th hour, 210 cubic meters per second in the 18th hour, and 60 cubic meters per second in the 24th hour). This sequence is the flow process data at the reservoir inlet section, providing a direct basis for the subsequent generation of the inflow flood process line.

[0078] In this embodiment of the application, the specific implementation of generating the inflow flood hydrograph within the forecast period based on the flow process data is as follows:

[0079] First, the flow process data at the inlet section is preprocessed to remove outliers (such as instantaneous negative flow or sudden increases or decreases in flow due to calculation errors, which are replaced by the average flow at adjacent times) to ensure data continuity and rationality.

[0080] Next, a coordinate system for the process line is set up, with time as the horizontal axis (unit: hours, range 0-24 hours) and flow rate as the vertical axis (unit: cubic meters / second, range 0-500 cubic meters / second); then the preprocessed flow rate data is mapped one by one into the coordinate system in chronological order to form discrete flow rate-time data points;

[0081] Finally, linear interpolation is used to connect the data points to form a smooth inflow flood process line. The process line needs to clearly mark key features such as peak flow (e.g., 480 cubic meters per second), peak occurrence time (e.g., 12 hours), flood rise time (e.g., 3 hours), and receding time (e.g., 21 hours) to complete the generation of the inflow flood process line within the forecast period. This process line can intuitively reflect the dynamic change pattern of the flood and meet the needs of subsequent steps to determine the flood scale.

[0082] In this embodiment of the application, this step constructs an accurate river hydrodynamic model using the finite volume method and combines it with the Saint-Venant equations to simulate the evolution of the entire river flow. This solves the problem of low simulation accuracy caused by the traditional confluence calculation ignoring differences in river topography and simplifying the physical mechanism of water flow. The generated inflow flood process line can truly reflect the key characteristics of the flood, such as the flood peak and duration, and provides high-precision data support for subsequent flood level judgment and dynamic flood control capacity calculation.

[0083] S3. Based on the inflow flood process line, determine the flood scale level. When it is determined to be a small to medium flood, use the equivalent flood control effect algorithm to calculate the dynamic flood control capacity of the downstream flood control object.

[0084] In some embodiments, the step of determining the flood scale level based on the inflow flood hydrograph, and when determined to be a small to medium flood, using an equivalent flood control algorithm to calculate the dynamic flood control capacity of the downstream flood control object, includes:

[0085] The peak flow of the inflow flood process curve is compared with the preset flood level classification standard to determine the flood scale level;

[0086] When the flood scale level is determined to be a small to medium flood, the dynamic flood control capacity is calculated using the inflow flood process line as input and the equivalent flood control effect algorithm. The calculation process of the equivalent flood control effect algorithm has taken into account the reservoir's pre-discharge scheduling capacity within the forecast period to ensure that the calculation results meet the safe discharge requirements of downstream flood control targets.

[0087] In some embodiments, the calculation process of the equivalent flood control algorithm has taken into account the reservoir's pre-release scheduling capacity within the forecast period to ensure that the calculation results meet the safe discharge requirements of downstream flood control targets, including:

[0088] Based on the inflow flood process line and the safe discharge requirements of the downstream flood control targets, determine the total flood control capacity required within the forecast period;

[0089] Based on the reservoir's discharge capacity and forecast period, calculate the reservoir's pre-discharge scheduling capacity that can be used for pre-discharge before the arrival of a flood.

[0090] The dynamic flood control capacity is obtained by subtracting the capacity corresponding to the pre-discharge scheduling capacity from the total flood control capacity.

[0091] In this embodiment of the application, the peak flow is the maximum flow value that appears in the process line of the flood entering the reservoir, which can intuitively reflect the intensity of the flood; the preset flood level classification standard is based on the reservoir design flood control standard, the characteristics of the basin flood and the bearing capacity of the downstream flood control objects, and is a flow threshold rule used to distinguish different flood scales.

[0092] In this embodiment, the equivalent flood control algorithm is an algorithm that considers the reservoir's pre-discharge scheduling capacity and calculates the dynamic flood control capacity required to meet downstream flood control safety. The core is to offset part of the flood control capacity demand through pre-discharge capacity. The downstream flood control objects are areas or facilities downstream of the reservoir that are threatened by floods, including towns, farmland, bridges, etc., and their safety needs to be guaranteed through reservoir scheduling.

[0093] In this embodiment, dynamic flood control capacity is the reservoir flood control capacity that is dynamically adjusted according to the flood scale and pre-discharge capacity. Unlike traditional fixed flood control capacity, it can achieve a balance between flood control and beneficial use. Pre-discharge scheduling capacity is the water discharge capacity that the reservoir can free up by opening gates or releasing water from units before the arrival of a flood. It depends on the performance of the reservoir's discharge facilities and the forecast period.

[0094] In this embodiment, the safe discharge requirement is the maximum river discharge that the downstream flood control target can withstand. Exceeding this discharge will cause flood disasters downstream, which is a key constraint on reservoir scheduling. The total flood control capacity is the minimum flood control capacity required to intercept inflow floods and ensure that the discharge flow does not exceed the downstream safe discharge, without considering the impact of pre-discharge scheduling.

[0095] In this embodiment of the application, the specific implementation of comparing the peak flow of the inflow flood hydrograph with the preset flood level classification standard to determine the flood scale level is as follows:

[0096] First, the peak flow of the inflow flood process line is extracted. Using the inflow flood process line generated earlier (24-hour forecast period, peak flow of 480 cubic meters per second), the maximum flow value is identified and extracted from the process line data through the data reading module to ensure the accuracy of the extraction results (such as eliminating misjudgments caused by data fluctuations through multiple verifications).

[0097] Next, the pre-defined flood level classification standard is determined. This standard needs to be formulated in conjunction with the historical flood data of the basin where the reservoir is located (such as flood statistics of the past 30 years) and the flood control standards of downstream flood control objects (such as the urban flood control standard of once in 20 years). For example, it is set that: flood peak flow of less than or equal to 500 cubic meters per second is a small to medium flood, greater than 500 cubic meters per second but less than or equal to 1,000 cubic meters per second is a large flood, and greater than 1,000 cubic meters per second is an extremely large flood. This threshold has been verified by the water conservancy engineering design specifications and meets the downstream flood control safety requirements.

[0098] Finally, a level comparison was performed. The extracted peak flow of 480 cubic meters per second was compared with the threshold in the preset standard. Since 480 cubic meters per second is less than or equal to 500 cubic meters per second, the scale of this flood was determined to be a small to medium flood, which provides a basis for the subsequent calculation of dynamic flood control capacity using the equivalent flood control effect algorithm.

[0099] In this embodiment of the application, the specific implementation of determining the total flood control capacity required within the forecast period based on the inflow flood hydrograph and the safe discharge requirements of downstream flood control targets is as follows:

[0100] First, the safe discharge requirements for downstream flood control targets are clarified. Based on the flood control engineering conditions of downstream towns and farmland (such as the height of dikes and the flood discharge capacity of the river), the safe discharge is determined to be 300 cubic meters per second through hydraulic calculations. This value is verified by on-site surveys and hydraulic models to ensure that there is no flood risk in the downstream area under this discharge.

[0101] Next, obtain the complete flow sequence of the inflow flood process line, that is, the hourly inflow data of the reservoir within the 24-hour forecast period (such as 52 cubic meters per second in the 1st hour, 85 cubic meters per second in the 6th hour, 480 cubic meters per second in the 12th hour, 210 cubic meters per second in the 18th hour, 60 cubic meters per second in the 24th hour, etc.).

[0102] Then, the excess floodwater volume for each time period is calculated. The core logic is as follows: when the inflow to the reservoir exceeds the safe discharge capacity during a certain time period, the excess portion needs to be intercepted by the flood control capacity. The excess water volume is equal to the difference between the inflow to the reservoir and the safe discharge capacity during that time period multiplied by the time period length (1 hour, converted to 3600 seconds). When the inflow to the reservoir is less than or equal to the safe discharge capacity, there is no excess water volume, and no interception is required. For example, in the 12th hour, the inflow to the reservoir is 480 cubic meters per second, and the safe discharge capacity is 300 cubic meters per second. The excess water volume for this time period is (480-300)×3600=648000 cubic meters. In the 6th hour, the inflow to the reservoir is 85 cubic meters per second, which is less than 300 cubic meters per second, so the excess water volume is 0.

[0103] Finally, by summing up the excess water volume for all periods, the total flood control capacity required within the forecast period is obtained. The calculated summation result is: With a capacity of cubic meters, this reservoir can ensure that the discharge flow at all times does not exceed the downstream safe discharge capacity.

[0104] In this embodiment of the application, the specific implementation of calculating the pre-release scheduling capacity based on the reservoir's discharge capacity and the forecast period is as follows:

[0105] First, the discharge capacity of the reservoir is determined. Based on the design parameters of the reservoir's flood discharge facilities (such as gates and spillway tunnels) (such as gate size, opening height, and cross-sectional area of ​​the spillway tunnel), the maximum discharge capacity of the reservoir is calculated to be 200 cubic meters per second using hydraulic formulas. This value is the discharge capacity when the gates are fully open. After on-site testing and verification, it is found to be consistent with the actual operating performance of the facilities.

[0106] Next, the duration of the forecast period is clarified. The forecast period set earlier is 24 hours, meaning that the reservoir has 24 hours of pre-discharge time before the flood arrives.

[0107] Then, the pre-release scheduling capacity is calculated. The core logic is that the pre-release scheduling capacity equals the reservoir's discharge capacity multiplied by the forecast period (converted to seconds). The formula can be expressed as: the reservoir capacity corresponding to the pre-release scheduling capacity equals the discharge flow rate per unit time multiplied by the pre-release time. During the calculation, it is necessary to ensure that the units are consistent (flow rate in cubic meters per second, time in seconds). Substituting the numerical values, the pre-release scheduling capacity is: The cubic meter figure represents the maximum storage capacity that the reservoir can free up through pre-release within the forecast period, providing data for subsequent calculations of dynamic flood control capacity.

[0108] In this embodiment of the application, the dynamic flood control capacity is obtained by deducting the capacity corresponding to the pre-discharge scheduling capacity from the total flood control capacity as follows:

[0109] First, let's clarify the values ​​for the total flood control capacity and the pre-discharge scheduling capacity. Referring to the calculation results above, the total flood control capacity is... cubic meters, the reservoir capacity corresponding to the pre-discharge scheduling capacity is cubic meters, ensuring that the units of the two parameters are consistent (both are cubic meters) and the calculation basis is the same (both are based on a 24-hour forecast period).

[0110] Next, deduction calculations are performed. The core logic is that the dynamic flood control capacity equals the total flood control capacity minus the capacity corresponding to the pre-release scheduling. The capacity freed up by pre-release scheduling can replace part of the function of the total flood control capacity, reducing the actual flood control capacity that needs to be reserved, while not affecting downstream flood control safety. Substituting the numerical values, the dynamic flood control capacity is... cubic meter;

[0111] Finally, the calculation results were validated for reasonableness, and compared with the existing beneficial storage capacity of the reservoir (e.g., the normal beneficial storage capacity of the reservoir is...). (cubic meters), confirming dynamic flood control capacity. The volume of water is within the total reservoir capacity, and the reserved capacity for beneficial use can meet the needs of water supply and power generation, achieving a balance between flood control and beneficial use, and completing the calculation of dynamic flood control capacity.

[0112] In this embodiment of the application, this step solves the problem of water resource waste caused by traditional fixed flood control capacity by accurately judging the flood level and using the equivalent flood control effect algorithm to calculate the dynamic flood control capacity. Under the premise of ensuring downstream flood control safety, it reduces the reserved amount of flood control capacity and provides storage space for flood resource utilization.

[0113] S4. Based on the dynamic flood control capacity, the dynamic flood limit water level control value is obtained by back-calculating the water level-capacity relationship curve of the reservoir.

[0114] In some embodiments, the step of obtaining the dynamic flood control limit water level control value by back-calculating the water level-capacity relationship curve of the reservoir based on the dynamic flood control capacity includes:

[0115] Obtain the initial flood control limit water level and its corresponding initial reservoir capacity, and add the initial reservoir capacity to the dynamic flood control reservoir capacity to obtain the upper limit reservoir capacity that can be controlled.

[0116] The dynamic flood control level is obtained by querying the water level-capacity relationship curve of the reservoir based on the upper limit reservoir capacity.

[0117] In this embodiment, the initial flood limit water level is the benchmark flood limit water level set by the reservoir during the regular flood season. It is the initial water level reference value for reservoir scheduling and is usually determined according to the basin flood control standards and reservoir design requirements. The initial storage capacity is the actual storage capacity of the reservoir corresponding to the initial flood limit water level, that is, the volume of water stored in the reservoir when the reservoir water level is at the initial flood limit water level. The upper limit storage capacity that can be controlled is the maximum storage capacity that the reservoir can reach during dynamic scheduling. It is obtained by adding the initial storage capacity and the dynamic flood control storage capacity and is the core basis for subsequent reverse-driven dynamic flood limit water level.

[0118] In this embodiment, the water level-storage capacity relationship curve is a curve drawn through field measurements and hydrological calculations. It is used to characterize the one-to-one correspondence between the reservoir water level and the corresponding storage capacity. The curve shows a monotonically increasing trend, reflecting the correlation between water level changes and storage capacity changes. The dynamic flood control limit water level control value is the flood control limit water level after dynamic flood control storage capacity adjustment. It is the highest control water level that the reservoir can reach under the current flood conditions and is used to guide the actual operation of the reservoir.

[0119] In this embodiment of the application, the specific implementation of obtaining the initial flood control limit water level and its corresponding initial reservoir capacity, and calculating the upper limit reservoir capacity that can be controlled is as follows:

[0120] First, the initial flood control limit water level is obtained. Based on the flood control plan and historical scheduling experience of the basin where the reservoir is located, and in conjunction with the reservoir design documents (such as the reservoir preliminary design report), the initial flood control limit water level of this reservoir is determined to be 120.0 meters. This value has been approved by the water conservancy department and meets the overall flood control requirements of the basin.

[0121] Next, the initial reservoir capacity was obtained by querying the reservoir's water level-capacity relationship curve (this curve was drawn from topographic survey data during the reservoir's construction phase and has been verified and corrected using years of actual operational data, ensuring its accuracy meets scheduling requirements). The initial reservoir capacity corresponding to the initial flood control limit water level of 120.0 meters was then determined. cubic meters, ensuring that the correspondence between the initial reservoir capacity and the initial flood control limit water level is accurate;

[0122] Then, refer to the dynamic flood control capacity calculated in S3. cubic meters. The upper limit of the allowable storage capacity is calculated by adding the initial storage capacity to the dynamic flood control capacity. The calculation logic is that the upper limit of the storage capacity equals the sum of the initial storage capacity and the dynamic flood control capacity. Substituting the values, we can obtain: The cubic meter is used to calculate the upper limit of the reservoir capacity that can be controlled. This capacity value is a key parameter for determining the dynamic flood control limit water level.

[0123] In this embodiment, the core implementation process of obtaining the dynamic flood control limit water level value by querying the water level-reservoir capacity relationship curve based on the upper limit reservoir capacity is as follows: First, prepare the water level-reservoir capacity relationship curve of the reservoir. The horizontal axis of this curve is the reservoir water level (unit: meters, range 110.0 meters - 130.0 meters), and the vertical axis is the corresponding reservoir capacity (unit: cubic meters, range 110.0 meters - 130.0 meters). Each data point on the curve comes from on-site measurements (such as using a depth sounder to measure the underwater topography of the reservoir at different water levels and calculate the corresponding reservoir capacity), and the reservoir capacity values ​​corresponding to key water levels (such as dead water level, normal storage water level, and initial flood limit water level) are marked to ensure the accuracy and usability of the curve.

[0124] Next, locate the upper limit storage capacity on the curve, and calculate the upper limit storage capacity that can be controlled. Find the corresponding point on the vertical axis (storage capacity axis) for cubic meters. This point needs to be precisely matched. If the upper limit storage capacity lies between two known data points on the curve (e.g., the storage capacity corresponding to 120.5 meters on the curve), then... Cubic meters, 121.0 meters corresponds to the reservoir capacity. cubic meter, If the volume is between the two (cubic meters), then linear interpolation is used to calculate the corresponding water level. The calculation logic of linear interpolation is as follows: first calculate the difference between the upper limit reservoir capacity and the lower reservoir capacity, then calculate the reservoir capacity difference corresponding to the two known water levels, then calculate the interpolation ratio, and finally add the lower water level to the product of the interpolation ratio and the water level difference to obtain the dynamic flood control limit water level control value of approximately 120.75 meters.

[0125] Finally, the calculation results were verified by substituting 120.75 meters into the water level-storage capacity relationship curve to look up the corresponding reservoir capacity, confirming that the reservoir capacity obtained from the lookup matches the upper limit of the allowable control capacity. The cubic meter error is within 0.1%, ensuring the accuracy and reliability of the dynamic flood control water level control value, which can be used to guide subsequent reservoir scheduling operations.

[0126] In this embodiment of the application, this step reverses the dynamic flood control limit water level control value through the water level-storage capacity relationship curve, which solves the problem that the traditional fixed flood control limit water level cannot be flexibly adjusted according to the actual flood situation, realizes the dynamic optimization of the flood control limit water level, and while ensuring flood control safety, reserves more beneficial storage capacity for the reservoir and improves the efficiency of flood resource utilization.

[0127] S5. Based on the dynamic flood limit water level control value, generate and execute a reservoir scheduling instruction to raise the reservoir water level to no more than the dynamic flood limit water level control value.

[0128] In some embodiments, generating and executing reservoir scheduling instructions based on the dynamic flood control level to raise the reservoir water level to no more than the dynamic flood control level includes:

[0129] The dynamic flood control level is set as the upper limit control target for reservoir operation;

[0130] Based on the upper limit control target, gate and unit scheduling instructions are generated and executed to control the reservoir water level within the range not exceeding the dynamic flood limit water level control value.

[0131] In this embodiment, the reservoir scheduling instruction is a set of instructions that guide the operation of reservoir gates and the operation of generating units. It is used to adjust the inflow and outflow balance of the reservoir and achieve the water level control target. The upper limit control target is the highest water level limit set during the reservoir scheduling process. In this application, it is the dynamic flood limit water level control value, which is used to constrain the reservoir water level from exceeding the limit to ensure flood control safety.

[0132] In this embodiment, the gate scheduling command is an operation command for facilities such as reservoir flood discharge gates and water conveyance gates, including parameters such as gate opening height and opening duration, used to adjust the reservoir outflow; the unit scheduling command is an operation command for equipment such as reservoir generator units and pumping units, including parameters such as unit start-up and shutdown status and output, used to coordinate power generation demand with water level control objectives.

[0133] In this embodiment of the application, the specific implementation of setting the dynamic flood control limit water level control value as the upper limit control target for reservoir scheduling is as follows:

[0134] First, obtain the dynamic flood control water level control value obtained by reverse calculation in S4. Referring to the calculation result above, this value is 120.75 meters.

[0135] Next, the value is entered into the reservoir dispatch control system, setting 120.75 meters as the upper limit control target for the current forecast period, and setting a water level warning threshold (e.g., 120.65 meters, triggering an warning when the water level approaches this value to remind dispatchers to pay attention). At the same time, the system automatically links to the reservoir's real-time water level monitoring data (collected through water level sensors deployed on the reservoir dam, with a data update frequency of 10 minutes / time), forming a dynamic comparison interface of "real-time water level - upper limit target". This facilitates dispatchers in monitoring water level changes in real time, ensuring that the upper limit control target is effectively implemented in the dispatch system and providing a clear constraint basis for the generation of subsequent instructions.

[0136] In this embodiment of the application, the core implementation process of this step is to generate and execute gate and unit scheduling instructions based on the upper limit control target, as detailed below:

[0137] The first step is to acquire real-time dispatch data, including the reservoir's real-time water level (e.g., the current water level is 119.80 meters), real-time inflow (referencing the corresponding time period data from the inflow flood process line in S2, e.g., the current inflow is 150 cubic meters per second), the current status of the gates (e.g., all three floodgates are fully closed, both generator units are operating at rated output, with a single unit output corresponding to an outflow of 50 cubic meters per second and a total power generation outflow of 100 cubic meters per second), and the real-time flow of the downstream river (monitored by the downstream hydrological station, currently 80 cubic meters per second, below the safe discharge of 300 cubic meters per second).

[0138] The second step is to calculate the water level control requirements. Based on the difference (0.95 meters) between the upper limit control target of 120.75 meters and the current water level of 119.80 meters, and combined with the reservoir water level-capacity relationship curve, the required increase in water storage is calculated. At the same time, based on the difference between the real-time inflow and the current outflow, the natural water storage rate is calculated to determine the time required to reach the upper limit water level without adjusting the outflow. It is necessary to appropriately reduce the outflow to accelerate the water storage speed, while ensuring that the downstream flow does not exceed the safe discharge capacity.

[0139] The third step involves generating gate and generator unit scheduling instructions. Based on the above calculations, regarding generator unit scheduling: maintain the operation of two generator units without adjusting their output (total outflow of 100 cubic meters per second) to avoid power supply disruptions due to unit shutdowns; regarding gate scheduling: since the current outflow is less than the inflow and the downstream flow is far below the safe discharge capacity, there is no need to open the floodgates. Keep the gates fully closed and gradually raise the water level through natural water storage. If the real-time water level subsequently approaches the warning threshold of 120.65 meters (e.g., if the water level reaches 120.60 meters), a gate fine-tuning instruction will be generated, such as opening floodgate No. 1 to 5% opening (hydraulic calculations show that this opening corresponds to an outflow of 15 cubic meters per second), increasing the total outflow to 115 cubic meters per second, slowing down the water storage rate, and preventing the water level from exceeding the upper limit target.

[0140] The fourth step involves executing dispatch instructions. The dispatch system sends gate and generator dispatch instructions to the field control units (gate control unit and generator control unit) via industrial Ethernet. After receiving the instructions, the field units automatically drive the actuators (gate hoists and generator speed governors) to perform the operations and provide real-time feedback on the operational status (such as gate opening degree reaching 5% and generator output remaining stable) to the dispatch system. Dispatchers track the execution of instructions in real time through the system monitoring interface. If an abnormality occurs in the execution of instructions (such as gate jamming), the system automatically alarms and generates emergency instructions (such as closing other gates or adjusting generator output) to ensure that the water level is always controlled within the range of 120.75 meters, ultimately achieving the goal of storing the reservoir water level to near but not exceeding the dynamic flood control limit.

[0141] In this embodiment of the application, this step achieves dynamic control of the reservoir water level by accurately generating and executing gate and unit scheduling instructions. This solves the problems of low water level control accuracy and delayed response in traditional scheduling. Under the premise of ensuring that the water level does not exceed the dynamic flood limit level, the reservoir maximizes the use of flood resources for water storage, improves the benefits of the reservoir, and at the same time ensures the flood control safety of the downstream area.

[0142] like Figure 2 The diagram shown is a functional block diagram of a reservoir flood control limit water level dynamic control and flood resource utilization system provided in an embodiment of this application.

[0143] The reservoir flood control limit water level dynamic control and flood resource utilization system 100 described in this application can be installed in an electronic device. Depending on the functions implemented, the reservoir flood control limit water level dynamic control and flood resource utilization system 100 may include an areal rainfall forecast acquisition module 101, an inflow flood process line generation module 102, a dynamic flood control capacity calculation module 103, a dynamic flood control limit water level reverse calculation module 104, and a reservoir scheduling instruction generation and execution module 105. The modules described in this application can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0144] In this embodiment, the functions of each module / unit are as follows:

[0145] The areal rainfall forecast acquisition module 101 is used to acquire the areal rainfall forecast value of the reservoir basin based on real-time rainfall and water conditions data and numerical weather forecasts.

[0146] The inflow flood process line generation module 102 is used to drive the watershed runoff generation and confluence model coupled with hydrodynamics and hydrology, with the areal rainfall forecast value as input, to generate the inflow flood process line within the forecast period.

[0147] The dynamic flood control storage capacity calculation module 103 is used to determine the flood scale level based on the inflow flood process line. When it is determined to be a small to medium flood, the equivalent flood control effect algorithm is used to calculate the dynamic flood control storage capacity of the downstream flood control object.

[0148] The dynamic flood control limit water level back-calculation module 104 is used to back-calculate the dynamic flood control limit water level control value based on the dynamic flood control capacity and the water level-capacity relationship curve of the reservoir.

[0149] The reservoir scheduling instruction generation and execution module 105 is used to generate and execute reservoir scheduling instructions based on the dynamic flood limit water level control value, so as to raise the reservoir water level to no more than the dynamic flood limit water level control value.

[0150] In the embodiments provided in this application, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0151] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0152] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0153] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from the spirit or essential characteristics of this application.

[0154] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0155] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this application without departing from the spirit and scope of the technical solutions of this application.

Claims

1. A method for dynamic control of reservoir flood control water level and flood resource utilization, characterized in that, The method includes: Based on real-time rainfall and water level data and numerical weather prediction, the areal rainfall forecast value of the reservoir basin is obtained; Using the areal rainfall forecast as input, a watershed runoff generation and confluence model coupled with hydrodynamics and hydrology is driven to generate the inflow flood process line within the forecast period; Based on the inflow flood process line, the flood scale level is determined. When it is determined to be a small to medium flood, the equivalent flood control effect algorithm is used to calculate the dynamic flood control capacity of the downstream flood control object. Based on the dynamic flood control capacity, the dynamic flood limit water level control value is obtained by back-calculating the water level-capacity relationship curve of the reservoir. Based on the dynamic flood control level, a reservoir scheduling instruction is generated and executed to raise the reservoir water level to no more than the dynamic flood control level.

2. The method for dynamic control of reservoir flood control water level and flood resource utilization as described in claim 1, characterized in that, The process of obtaining areal rainfall forecasts for the reservoir basin based on real-time rainfall and water level data and numerical weather prediction includes: The numerical weather forecast is obtained, and rainfall data for the forecast period at each forecast point within the reservoir basin is extracted from it. Based on the real-time rainfall and water level data, the rainfall data is corrected and assimilated in real time using the physical causal analysis method to obtain the areal rainfall forecast value of the reservoir basin.

3. The method for dynamic control of reservoir flood control water level and flood resource utilization as described in claim 1, characterized in that, The process of using the areal rainfall forecast as input to drive a watershed runoff generation and concentration model coupled with hydrodynamics and hydrology to generate the inflow flood hydrograph within the forecast period includes: Based on the above areal rainfall forecast values, the watershed runoff is calculated using the unit hydrograph method to obtain the watershed net rainfall process; Using the net rainfall process of the basin as the upper boundary condition, and based on the digital elevation model and river cross-section data, the river confluence calculation is completed by solving the Saint-Venant equations, thereby generating the inflow flood process line within the forecast period.

4. The method for dynamic control of reservoir flood control water level and flood resource utilization as described in claim 3, characterized in that, The process of using the net rainfall process of the watershed as the upper boundary condition, and based on the digital elevation model and river cross-section data, completes the river confluence calculation by solving the Saint-Venant equations, thereby generating the inflow flood hydrograph for the forecast period, including: Based on the digital elevation model and the river cross-section data, the finite volume method is used to divide the river into grids in order to construct a river hydrodynamic model. The net rainfall process in the watershed is used as the upstream boundary input condition of the river hydrodynamic model, and the real-time monitored river flow data is used as the initial hydrological condition of the river hydrodynamic model. Based on the river hydrodynamic model, the upstream boundary input conditions, and the initial hydrological conditions, the flow evolution of the entire river channel is simulated by solving the Saint-Venant equations to obtain the flow process data at the reservoir inlet section. Based on the flow process data, an inflow flood process curve for the forecast period is generated.

5. The method for dynamic control of reservoir flood control water level and flood resource utilization as described in claim 4, characterized in that, The Saint-Venant equations include the mass conservation equation describing the continuity of water flow and the momentum conservation equation describing energy conversion. By solving the Saint-Venant equations simultaneously, the hydrodynamic transformation from the net rainfall process in the watershed to the flow process at the reservoir inlet section can be realized.

6. The method for dynamic control of reservoir flood control water level and flood resource utilization as described in claim 1, characterized in that, The process of determining the flood scale level based on the inflow flood hydrograph, and when determined to be a small to medium flood, employing an equivalent flood control algorithm to calculate the dynamic flood control capacity of the downstream flood control target, includes: The peak flow of the inflow flood process curve is compared with the preset flood level classification standard to determine the flood scale level; When the flood scale level is determined to be a small to medium flood, the dynamic flood control capacity is calculated using the inflow flood process line as input and the equivalent flood control effect algorithm. The calculation process of the equivalent flood control effect algorithm has taken into account the reservoir's pre-discharge scheduling capacity within the forecast period to ensure that the calculation results meet the safe discharge requirements of downstream flood control targets.

7. The method for dynamic control of reservoir flood control water level and flood resource utilization as described in claim 6, characterized in that, The calculation process of the equivalent flood control algorithm has taken into account the reservoir's pre-release scheduling capacity within the forecast period to ensure that the calculation results meet the safe discharge requirements of downstream flood control targets, including: Based on the inflow flood process line and the safe discharge requirements of the downstream flood control targets, determine the total flood control capacity required within the forecast period; Based on the reservoir's discharge capacity and forecast period, calculate the reservoir's pre-discharge scheduling capacity that can be used for pre-discharge before the arrival of a flood. The dynamic flood control capacity is obtained by subtracting the capacity corresponding to the pre-discharge scheduling capacity from the total flood control capacity.

8. The method for dynamic control of reservoir flood control water level and flood resource utilization as described in claim 1, characterized in that, The process of obtaining the dynamic flood control limit water level control value by back-calculating the water level-capacity relationship curve of the reservoir based on the dynamic flood control capacity includes: Obtain the initial flood control limit water level and its corresponding initial reservoir capacity, and add the initial reservoir capacity to the dynamic flood control reservoir capacity to obtain the upper limit reservoir capacity that can be controlled. The dynamic flood control level is obtained by querying the water level-capacity relationship curve of the reservoir based on the upper limit reservoir capacity.

9. The method for dynamic control of reservoir flood control water level and flood resource utilization as described in claim 1, characterized in that, The step of generating and executing reservoir scheduling instructions based on the dynamic flood control level to raise the reservoir water level to no more than the dynamic flood control level includes: The dynamic flood control level is set as the upper limit control target for reservoir operation; Based on the upper limit control target, gate and unit scheduling instructions are generated and executed to control the reservoir water level within the range not exceeding the dynamic flood limit water level control value.

10. A reservoir flood control limit water level dynamic control and flood resource utilization system, used to implement the reservoir flood control limit water level dynamic control and flood resource utilization method according to any one of claims 1-9, characterized in that, The system includes: The areal rainfall forecast acquisition module is used to obtain the areal rainfall forecast value of the reservoir basin based on real-time rainfall and water conditions data and numerical weather forecasts. The inflow flood hydrograph generation module is used to drive the watershed runoff generation and confluence model coupled with hydrodynamics and hydrology, using the areal rainfall forecast value as input, to generate the inflow flood hydrograph within the forecast period; The dynamic flood control storage capacity calculation module is used to determine the flood scale level based on the inflow flood process line. When it is determined to be a small to medium flood, the equivalent flood control effect algorithm is used to calculate the dynamic flood control storage capacity of the downstream flood control object. The dynamic flood control limit water level back-calculation module is used to back-calculate the dynamic flood control limit water level control value based on the dynamic flood control capacity and the water level-capacity relationship curve of the reservoir. The reservoir scheduling instruction generation and execution module is used to generate and execute reservoir scheduling instructions based on the dynamic flood limit water level control value, so as to raise the reservoir water level to no more than the dynamic flood limit water level control value.

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