Parameter identification method and system for open channel integral time-delay zero model

Abstract

The invention provides a parameter identification method and system for an open channel integral time-lag zero model, and relates to the technical field of data processing, and the method comprises the steps: sequentially dividing an open channel into a plurality of sections; establishing a hydraulic model of the open channel based on the number of sections and the distance between adjacent sections; adding boundary conditions to each section; solving a steady-state solution of the hydraulic model; according to the steady-state solution, the flow fluctuation forward propagation duration and the flow fluctuation reverse propagation duration of propagation from the flow fluctuation of the channel head section to the channel tail section are solved; a first step test and a second step test are carried out with the steady-state solution as the initial condition and the section flow as the variable, the first step test is used for solving first section water level data under the channel head section flow step value, and the second step test is used for solving second section water level data under the channel tail section flow step value; fitting the first section water level data and the second section water level data respectively, and solving open channel integral time-lag zero model parameters. And the parameter identification speed and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a parameter identification method and system for an open channel integral time-delay zero model. Background Art

[0002] my country has achieved a high level of research in one-dimensional hydrodynamic models, achieving high computational efficiency. However, when using hydraulic models to experimentally calculate optimal solutions for water transmission and diversion systems, millions of hydraulic model calculations are required, and current hydraulic computational speeds are simply insufficient. Furthermore, within the scope of automated control, a more simplified model is required to facilitate the development of automatic control algorithms. The zero-integrated time-lag model simultaneously accounts for both the low-frequency and high-frequency characteristics of channel flow, effectively capturing the response of channel pool water levels to flow rate fluctuations.

[0003] The integral time-delay zero model has three key parameters: lag time, backwater area, and constant coefficient. For some very simple channels, each parameter of the integral time-delay zero model can be derived and calculated using theoretical formulas. However, in actual projects, the shapes of individual channels vary, and the flow of water is highly complex and irregular, making direct calculations using formulas extremely difficult. Furthermore, in actual projects, it is impossible to account for all operating conditions, resulting in large errors in the calculated parameters. This leads to low computational efficiency and insufficient accuracy in the real-time scheduling process.

[0004] In summary, due to the complex changes in channel shape and water flow, and the inability to obtain all operating condition data in actual projects, direct parameter identification through theoretical derivation leads to large parameter errors in the identification process and too slow calculation speed, which makes it difficult to meet the needs of real-time scheduling and efficient control, affecting the accuracy and efficiency of water resource scheduling. Summary of the Invention

[0005] In order to solve the technical problems existing in the prior art, such as the complex changes in channel shape and water flow, the inability to obtain all operating condition data in actual projects, and the large parameter errors and slow calculation speed caused by direct parameter identification through theoretical deduction in the identification process, which makes it difficult to meet the needs of real-time scheduling and efficient control, and affects the accuracy and efficiency of water resource scheduling, the present invention provides a parameter identification method and system for an open channel integral time-lag zero model.

[0006] The technical solutions provided by the embodiments of the present invention are as follows:

[0007] First aspect

[0008] An embodiment of the present invention provides a parameter identification method for an open channel integral time-delay zero model, comprising:

[0009] S1: Divide the open channel into multiple sections in sequence, and record the number of sections and the distance between adjacent sections;

[0010] S2: Establish a hydraulic model of the open channel based on the number of sections and the distance between adjacent sections;

[0011] S3: Add boundary conditions to each section, where the boundary conditions include the section flow value and the section water level value;

[0012] S4: Under the boundary conditions, solve the steady-state solution of the hydraulic model to obtain the steady-state flow value and the constant water level value of each section, wherein the steady-state flow value of each section is equal;

[0013] S5: Based on the steady-state solution, calculate the forward propagation time of the flow fluctuation from the head section to the end section, and the reverse propagation time of the flow fluctuation from the end section to the head section;

[0014] S6: With the steady-state solution as the initial condition and the cross-section flow rate as the variable, the first step test and the second step test are performed. The first step test is to obtain the water level data of the first section under the step value of the flow rate at the head section, and the second step test is to obtain the water level data of the second section under the step value of the flow rate at the end section.

[0015] S7: Fit the first section water level data and the second section water level data respectively to solve the open channel integral time-lag zero model parameters.

[0016] Second aspect

[0017] An embodiment of the present invention provides a parameter identification system for an open channel integral time-delay zero model, comprising:

[0018] processor;

[0019] A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the parameter identification method of the open channel integral time-delay zero model as described in the first aspect is implemented.

[0020] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0021] In an embodiment of the present invention, by dividing the open channel into multiple sections and constructing a hydraulic model, the steady-state solution of the hydraulic model and the flow step test are used to effectively simplify the parameter identification under complex working conditions, avoiding the excessive reliance on comprehensive working condition data in traditional methods, improving calculation efficiency, reducing a large number of experimental calculations, and being able to quickly identify key parameters to meet real-time scheduling needs. In addition, the accuracy of the parameters is improved through fitting of experimental data, significantly improving the accuracy and efficiency of water resource scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 A flow chart of a parameter identification method for an open channel integral time-delay zero model provided by an embodiment of the present invention;

[0024] Figure 2 A schematic diagram of actual numerical simulation results of a first step test and a second step test provided by an embodiment of the present invention;

[0025] Figure 3 A schematic structural diagram of a parameter identification system for an open channel integral time-delay zero model provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0027] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0028] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0029] Reference Manual Figure 1 , which shows a flow chart of a parameter identification method for an open channel integral time-delay zero model provided by an embodiment of the present invention.

[0030] An embodiment of the present invention provides a parameter identification method for an open channel integral time-delay zero model. This method can be implemented by a parameter identification device for the open channel integral time-delay zero model, which can be a terminal or a server. The process flow of the parameter identification method for the open channel integral time-delay zero model can include the following steps:

[0031] S1: Divide the open channel into multiple sections in sequence, and record the number of sections and the distance between adjacent sections.

[0032] Among them, the section refers to dividing the open channel into multiple parts at certain intervals, and the cross-section of each part is regarded as a "section". Each section represents a section of the channel water flow, and its position is set according to the spacing between adjacent sections. By calculating hydraulic parameters such as flow and water level at each section, the changes in water flow in the open channel can be simulated in detail. By dividing the open channel into multiple sections, the characteristics of water flow at different locations can be captured in detail, providing a clear foundation for the subsequent establishment of a hydraulic model. This can more accurately simulate the spatial distribution of water flow and avoid simplification errors that may occur in the overall model. At the same time, dividing the sections helps to better control the hydraulic parameters of each section, thereby improving the accuracy and flexibility of the model and being able to adapt to complex working conditions.

[0033] S2: Establish a hydraulic model of the open channel based on the number of sections and the distance between adjacent sections.

[0034] Hydraulic models are mathematical models used to describe and predict the behavior of water in open channels, rivers, or other water bodies. They simulate the temporal and spatial variations of flow parameters such as water level, velocity, and flow rate by considering fundamental laws of water flow, such as the continuity equation and the momentum equation. In open channels, hydraulic models typically include factors such as water depth, velocity, and flow rate, as well as channel shape and slope, to predict the stability and changing trends of water flow.

[0035] It's important to note that by dividing an open channel into multiple sections and establishing a hydraulic model based on the number of sections and the distances between adjacent sections, the goal is to accurately simulate and calculate the flow conditions at each section. This process allows for the description of the dynamic changes in water level, velocity, and flow rate at different locations within the open channel, providing a precise calculation basis for subsequent flow fluctuation propagation and parameter identification, ensuring the accuracy and operability of the model.

[0036] S3: Add boundary conditions to each section.

[0037] Among them, the boundary conditions include section flow value and section water level value.

[0038] It's important to note that boundary conditions are set for each section to ensure that the hydraulic model accurately reflects actual water flow conditions. Specifically, the cross-sectional flow rate determines the water flow rate at each section, while the cross-sectional water level determines the water level at that section. These boundary conditions serve as input parameters for the model, helping to define the initial state and flow characteristics of the water flow. This allows the hydraulic model to accurately predict changes in water flow at each section during simulation and provides the necessary reference for subsequent parameter identification.

[0039] S4: Under the boundary conditions, solve the steady-state solution of the hydraulic model to obtain the steady-state flow value and constant water level value of each section.

[0040] Among them, the steady-state flow values of each section are equal.

[0041] It is important to note that, based on the established boundary conditions, the open channel hydraulic model is solved until the system reaches a steady state. At this point, the flow rate at each section no longer varies over time and remains consistent, meaning the steady-state flow rate values are equal. At the same time, a constant water level value is obtained for each section. This step is crucial in providing a stable and repeatable hydraulic foundation, laying a solid foundation for subsequent flow perturbation experiments and model parameter fitting, ensuring the representativeness and accuracy of the identification results.

[0042] In a possible implementation, S4 is specifically:

[0043] The steady-state solution is obtained by the Pressimann algorithm.

[0044] The Pressimann algorithm is a commonly used implicit difference method for solving partial differential equations in one- or two-dimensional flow problems. It is particularly well-suited for hydraulic models describing fluid flow. It discretizes time and space, transforming the continuous flow equations into a discrete system of linear equations. Compared to explicit methods, the Pressimann algorithm offers superior numerical stability and can effectively handle complex boundary conditions and large time steps. The Pressimann algorithm's process for obtaining a steady-state solution involves discretizing the hydraulic equations into difference equations and then iteratively calculating the flow and water level at each section within each time step using an implicit difference method. Under steady-state conditions, the system is assumed to have reached equilibrium, meaning that the flow and water level values no longer vary with time. Therefore, the calculated cross-sectional flow and water level values are continuously solved and adjusted until the system converges and a steady-state solution is reached. This process ensures accurate calculation of the steady-state flow and water level at each section, even in complex flow environments.

[0045] S5: Based on the steady-state solution, calculate the forward propagation time of the flow fluctuation from the head section to the end section, and the reverse propagation time of the flow fluctuation from the end section to the head section.

[0046] The forward propagation time of flow fluctuations is the time it takes for flow fluctuations to propagate from the headwater section to the endwater section. The reverse propagation time is the time it takes for flow fluctuations to propagate from the endwater section to the headwater section. The endwater section refers to the set N value. If N is 2, the endwater section is the second section. If N is 3, the endwater section is the third section.

[0047] It is important to note that by analyzing the steady-state solution, the time it takes for a flow disturbance to propagate from one section to another is calculated without changing the system structure. This is used to quantify the propagation characteristics of water flow in the channel. The forward propagation time represents the time it takes for flow fluctuations to propagate from upstream to downstream, while the reverse propagation time describes the time it takes for downstream disturbances to feed back upstream. These two propagation times reflect the dynamic characteristics of the water flow response and are key to the subsequent calculation of the integral time-lag zero model parameters, helping to improve the model's ability to describe unsteady processes.

[0048] In a possible implementation, the forward propagation duration of the traffic fluctuation is calculated as follows:

[0049]

[0050] Among them, τ d Indicates the forward propagation time of traffic fluctuation, L i represents the distance between the i-th section and the i+1-th section, i=1,2,…,N-1, N represents the maximum number of sections, u i represents the cross-sectional flow velocity of the i-th section, c i represents the still water propagation velocity of flow fluctuation at the i-th section, g represents the acceleration of gravity, and A i represents the cross-sectional water area at the i-th section, B i represents the water surface width at the i-th section, that is, the section width.

[0051] The still water propagation velocity of flow fluctuations refers to the propagation velocity of flow fluctuations in still water in open channel flow.

[0052] The calculation method for the reverse propagation time of traffic fluctuations is as follows:

[0053]

[0054] Among them, τ u Indicates the reverse propagation time of traffic fluctuations.

[0055] It should be noted that the propagation time of flow fluctuations is divided into two parts: forward propagation and reverse propagation. The forward propagation time is calculated based on the distance between adjacent sections, the cross-sectional flow velocity, and the still-water propagation velocity of the flow fluctuation. The still-water propagation velocity is related to the acceleration of gravity, the water flow area, and the cross-sectional width. The reverse propagation time is calculated based on the difference between the flow velocity and the still-water propagation velocity. The calculation of these two propagation times reflects the propagation characteristics of flow fluctuations in the water flow and affects the accuracy of water flow control and simulation. Accurately considering the propagation characteristics of flow fluctuations between different sections, taking into account both the influence of flow velocity on propagation time and the still-water propagation velocity, can more comprehensively describe the transmission process of flow fluctuations, thereby improving the accuracy and response speed of water flow control models. By distinguishing between forward and reverse propagation times, dynamic changes in actual water flows can be better simulated.

[0056] S6: Take the steady-state solution as the initial condition and the cross-sectional flow rate as the variable to perform the first step test and the second step test.

[0057] Among them, the first step test is to solve the water level data of the first section under the step value of the flow rate of the head section, and the second step test is to solve the water level data of the second section under the step value of the flow rate of the end section.

[0058] It should be noted that by introducing a flow step perturbation under steady-state conditions, conducting tests at the head and end of the canal, and observing and recording the water level response data at the corresponding sections, this step test effectively stimulates the dynamic characteristics of the system, thereby capturing the response of the water level to flow changes. This provides key experimental data for the subsequent establishment of an integral time-lag zero model, helping to accurately reflect the time-lag characteristics of the channel hydraulic response.

[0059] In a possible implementation manner, the test duration of the first step test is a first preset multiple of the flow fluctuation forward propagation duration, and the test duration of the second step test is a second preset multiple of the flow fluctuation reverse propagation duration.

[0060] It should be noted that by flexibly adjusting the first and second preset multiples, the test duration can be optimized based on actual conditions to more accurately simulate the propagation of flow fluctuations in the water flow. By adjusting the multiples, the test duration can be flexibly controlled based on different water flow conditions, experimental requirements, and model accuracy requirements, thereby improving experimental efficiency and the reliability of the results.

[0061] It should be noted that those skilled in the art can set the first preset multiple and the second preset multiple according to actual needs, and the present invention is not limited thereto. Optionally, both the first preset multiple and the second preset multiple can be set to 5.

[0062] In a possible implementation, S6 specifically includes:

[0063] S601: Setting a step flow rate at the head section, and determining a water level change rate at the head section and a water level change rate at the end section, wherein the step flow rate at the head section is greater than an initial flow rate at the head section corresponding to a steady-state solution.

[0064] Optionally, the head section step flow rate can be specifically set to 1.1 times the head section initial flow rate.

[0065] The calculation formula for the water level change rate at the head section is:

[0066]

[0067] in, It represents the change of flow rate at the head section in the first step test. A represents the change in flow rate at the end of the channel in the first step test. u Indicates the free water surface area of the current section under initial conditions.

[0068] The calculation formula for the water level change rate at the end of the channel section is:

[0069]

[0070] Among them, A d Indicates the backwater area of the current section under initial conditions.

[0071] S602: Based on the duration of the first step test and the speed of change of the water level at the head section, the first section water level data of each section under the step flow at the head section is determined to complete the first step test.

[0072] S603: Setting a step flow rate at the end section of the channel, and determining the water level change speeds at the head section and the end section of the channel, wherein the step flow rate at the end section of the channel is less than the initial flow rate at the end section of the channel corresponding to the steady-state solution.

[0073] Optionally, the step flow rate at the channel end section can be specifically set to 0.9 times the initial flow rate at the channel end.

[0074] The calculation formula for the water level change rate at the head section is:

[0075]

[0076] in, It represents the change of flow rate at the head section in the second step test. It represents the change in flow rate at the end section of the channel in the second step test.

[0077] The calculation formula for the water level change rate at the end of the channel section is:

[0078]

[0079] S604: Based on the test duration of the second step test and the water level change rate of the channel end section, the second section water level data of each section under the step flow of the channel head section is determined to complete the second step test.

[0080] Specifically, by precisely controlling and calculating the flow changes at the head and end sections of the canal, the impact of water flow fluctuations on the water level can be systematically simulated. First, by setting a step flow at the head section, the speed of change of the water level at the head of the canal is effectively amplified, making it easier to capture and analyze the initial impact of flow fluctuations on the water level. By calculating the speed of change of the water level at the head and end sections (taking into account the free water surface area and the backwater area, respectively), the response of the water level to flow changes can be accurately quantified. Then, by combining the duration of the first step test and the second step test, the dynamic change data of the water level at each section are further clarified. This phased test design allows the forward and reverse propagation of flow fluctuations to be verified separately, thereby providing a more comprehensive and accurate analysis of water flow control under different water flow conditions. By setting the step flow and calculating the water level change speed, this scheme can accurately capture the propagation characteristics of water flow fluctuations between different sections, improve the simulation accuracy, and flexibly adjust the experimental conditions to meet the needs of different actual projects.

[0081] S7: Fit the first section water level data and the second section water level data respectively to solve the open channel integral time-lag zero model parameters.

[0082] In a possible embodiment, the open channel integral time-delay zero model parameters include the free water surface area A of the head section. u , backwater area of the channel end section A d , the first constant coefficient b related to the change in flow rate and water level at the head section u1 , the second constant coefficient b related to the change in flow at the end section of the channel and the change in water level at the head section u2 , the third constant coefficient b related to the change in flow at the head section and the change in water level at the end section d1 and the fourth constant coefficient b related to the change in flow rate and water level at the end of the channel section d2 .

[0083] It should be noted that the open channel integral time-delay zero model parameters accurately describe the time-delay characteristics of water flow between different sections by combining the water level and flow changes at the head and end sections. u ) and the backwater area of the channel end section (A d ) reflects the distribution of fluid in each section, and each constant coefficient (b u1 、b u2 、bd1 、b d2 ) quantifies the impact of flow changes on water level. These coefficients relate flow and water level changes at the head and end of the channel, respectively. They accurately capture the response characteristics of water flow, provide a more detailed dynamic description for the model, and optimize water flow simulation and control strategies.

[0084] In a possible implementation, S7 specifically includes:

[0085] S701: Obtain the first section water level data of the first preset time length and the second section water level data of the second preset time length, wherein the first preset time length is the third preset multiple of the forward propagation time length of the flow fluctuation, and the second preset time length is the fourth preset multiple of the reverse propagation time length of the flow fluctuation, wherein the third preset multiple is smaller than the first preset multiple, and the fourth preset multiple is smaller than the second preset multiple.

[0086] Optionally, the third preset multiple and the fourth preset multiple can both be set to 2.

[0087] S702: Fitting the acquired first section water level data and second section water level data respectively according to their respective sections to obtain a fitting equation.

[0088] The fitting equation is specifically:

[0089]

[0090]

[0091] Among them, k1 and b1 represent the water level record values at the head section in the first step test. The slope and bias of the correlation, k2 and b2, represent the water level records at the end of the channel in the first step test. The related slope and bias, k3 and b3, represent the water level records at the head section in the second step test. The slope and bias of the correlation, k4 and b4, represent the water level records at the end of the channel in the second step test. Related slope and bias.

[0092] S703: Solve the fitting equation to obtain the free water surface area of the channel head section and the backwater area of the channel end section.

[0093] S704: Establishing an equation for the instantaneous change of the water level at the head section and an equation for the instantaneous change of the water level at the end section in the first step test and the second step test, respectively.

[0094] The instantaneous change equations of the water level at the head section and the end section are as follows:

[0095]

[0096] in, The instantaneous change value of the water level at the head section in the equation of the instantaneous change of the water level at the head section in the first step test is represented by The instantaneous change value of the water level at the end of the channel in the equation of the instantaneous change of the water level at the end of the channel in the first step test is represented by The instantaneous change value of the water level at the head section in the equation of the instantaneous change of the water level at the head section in the second step test is represented by The instantaneous change value of the water level at the end of the channel in the instantaneous change equation of the water level at the end of the channel in the second step test is represented by and They represent the time t and t-τ in the first step test respectively. d The change in flow rate at the head section at the moment, and They represent the time t and t-τ in the first step test respectively. u The change in flow rate at the end of the channel at time and They represent the time t and t-τ in the second step test respectively. d The change in flow rate at the head section at the moment, and They represent the time t and t-τ in the second step test respectively. u The change in flow rate at the end section of the channel at the time.

[0097] S705: Calculate the instantaneous change value of the water level at the head section and the instantaneous change value of the water level at the end section in the first step test and the second step test respectively based on the fitting equation.

[0098] S706: Substitute the calculated instantaneous change values of the water level at the head section and the instantaneous change values of the water level at the end section into the corresponding instantaneous change equation of the water level at the head section and the instantaneous change equation of the water level at the end section to obtain the first constant coefficient, the second constant coefficient, the third constant coefficient and the fourth constant coefficient.

[0099] The specific solution process of S705 and S706 is:

[0100] The calculation methods for the instantaneous change of water level at the head section and the end section in the first step test are as follows:

[0101] In the first step test, the instantaneous change of flow rate at section 1 is Instantaneous change of flow rate at section N According to the fitted linear equation, calculate the water level value at the instant of the step Subtract the water level value before the step from the water level value at the instant of the step to obtain the water level change at the instant of the step in section 1 of the first step test. Right now Therefore, according to the formula Obtain parameter b u1 .

[0102] Similarly, the water level of section N passes through τ d After that, a transient response will be generated due to the sudden increase of inflow flow. At this time, the instantaneous change of flow at section 1 is Instantaneous change of flow rate at section N However, due to the flattening effect of flow during propagation, the response time of the water level at section N will be delayed. Therefore, when selecting the instantaneous water level height after the step at section N, it is necessary to calculate the τ d Add 0.5τ to the time to correct the propagation delay. The water level value corresponding to the corrected time in the fitting straight line equation This is the instantaneous water level height after the step at section N that we are concerned about. The instantaneous water level change of section N in test 1 can be obtained by subtracting the water level value before the step from the water level value at the instantaneous step. Right now According to the formula The parameter b can be calculated d1 .

[0103] In the second step test, the instantaneous change of flow rate at section 1 is Instantaneous change of flow rate at section N According to the fitted linear equation, calculate the water level at the instant of the step The water level change at the instant of the step is obtained by subtracting the water level value before the step from the water level value at the instant of the step. Right now According to the formula Obtain parameter b d2 .

[0104] Similarly, the water level of section 1 after time τ u After that, a transient response will be generated due to the sudden decrease in outflow flow. At this time, the instantaneous change in flow at section 1 is Instantaneous change of flow rate at section N However, due to the flattening effect of flow during propagation, the response time of the water level at Section 1 will be delayed. Therefore, when selecting the instantaneous water level height after the step at Section 1, it is necessary to use τ in the fitting linear equation. u Add 0.5τ to the time to correct the propagation delay. The water level value corresponding to the corrected time in the fitting straight line equation is the instantaneous water level height after the step at section 1 that we are concerned about. Subtract the water level value before the step from the water level value at the instant of the step to obtain the water level change at the instant of the step in section 1 of the second step test. Right now According to the formula The parameter b can be calculated u2 .

[0105] Specifically, first, by obtaining the water level data at the head and end of the channel in different time periods and fitting them, the corresponding fitting equations are obtained. These equations quantify the relationship between flow changes and water level changes, providing a basis for subsequent water level change calculations. Then, using these fitting equations, combined with the instantaneous changes in flow, the instantaneous water level change equations at the head and end of the channel are established. By considering the water level response caused by flow changes and its propagation time lag effect, the delay factor of flow propagation is corrected, making the model more accurate. Finally, by calculating and substituting into the water level change equation, the key coefficients affecting water level changes are solved, completing the model parameter solution process. This method can effectively simulate the instantaneous response of water flow fluctuations to water level, and accurately reflect the relationship between water level changes and flow changes, providing more accurate model support for water flow control and scheduling.

[0106] In a possible implementation manner, after S706, the method further includes:

[0107] S707: Update the open channel integral time-lag zero model parameters under preset conditions, wherein the preset conditions are that the offset of the steady-state flow value of the section is greater than a first preset offset or the offset of the constant water level value of the section of the same section is greater than a second preset offset.

[0108] It should be noted that those skilled in the art can set the first preset offset and the second preset offset according to actual needs, and the present invention is not limited thereto. Optionally, the first preset offset can be set to 15%, and the second preset offset can be set to 5%.

[0109] It is important to note that updating the open channel integral zero-delay model parameters under pre-set conditions ensures that the model can adapt to changing flow conditions during actual operation. The offset requirement in the pre-set conditions ensures that the model parameters are adjusted to maintain simulation accuracy when there are significant changes in the steady-state flow or water level at the section.

[0110] In a possible implementation manner, after S7, the method further includes:

[0111] The open channel integral time-lag zero model parameters are substituted into the open channel integral time-lag zero model to complete the construction of the open channel integral time-lag zero model, wherein the open channel integral time-lag zero model includes a first open channel integral time-lag zero model related to the forward propagation time of flow fluctuations and a second open channel integral time-lag zero model related to the reverse propagation time of flow fluctuations.

[0112] The first open channel integral time-delay zero model is specifically:

[0113]

[0114] in, It represents the change of water level at the head section relative to the initial time in the first open channel integral time-lag model. It represents the change of water level at the end section of the channel relative to the initial time in the first open channel integral time-lag model.

[0115] The second open channel integral time-delay model is specifically:

[0116]

[0117] in, represents the change in water level at the head section relative to the initial moment in the second open channel integral time-lag model, It represents the change of water level at the end section of the channel relative to the initial time in the second open channel integral time-lag model.

[0118] It should be noted that by bringing the parameters of the open channel integral time-delay zero model into the model, two time-delay zero models related to the forward and reverse propagation time of flow fluctuations were constructed. The first open channel integral time-delay zero model describes the relationship between the water level change at the head and end sections and the flow change, which involves the time lag of the forward propagation of flow fluctuations. The second open channel integral time-delay zero model takes into account the impact of the reverse propagation delay of flow fluctuations on water level changes. By defining the water level change equations at the head and end sections respectively, and introducing corrections for flow changes and time lags, the model can more accurately simulate the complex relationship between water flow changes and water level responses.

[0119] By incorporating the parameters of the open channel integral time-delay zero model into the model, a time-delay model with forward and reverse propagation durations was constructed, accurately reflecting the time-delay effect of flow fluctuations on water level changes. The forward and reverse propagation of flow fluctuations were processed separately, improving the model's ability to capture the dynamic processes of water flow. By separately processing water level changes at the head and end sections of the channel, the response time difference of the water flow can be better simulated, especially in complex hydraulic systems. The spatiotemporal evolution of water level changes can be more accurately described, thereby improving the model's adaptability and accuracy. This phased, time-delay adjustment strategy helps to more accurately predict water level changes in practical applications, especially in situations where flow fluctuations are large, ensuring the reliability and practicality of the simulation results.

[0120] Specifically, by dividing the open channel into multiple sections and establishing a hydraulic model, starting with a steady-state solution, the integral time-lag zero model parameters are systematically identified by combining forward and reverse flow disturbance propagation times and step test data. This process not only avoids reliance on full-scale measured data but also significantly improves computational efficiency and parameter accuracy, making it suitable for rapid modeling and intelligent regulation in complex hydraulic environments, meeting the needs of real-time scheduling and automated control.

[0121] In practical application, the parameter identification process for the open channel integral time-delay zero model is as follows: First, a hydraulic model is established for the target open channel. Given fixed flow boundaries at Section 1 and fixed water level boundaries at Section N, the traditional Pressimann method is used to solve the channel hydraulic model until a steady-state solution is obtained. Then, the delay time required for flow fluctuations at Section 1 to propagate to Section N and the delay time required for flow fluctuations at Section N to propagate to Section 1 under the channel's current steady-state conditions is calculated through integration. Two flow step numerical simulation experiments are then conducted. Experiment 1 involves a step change in flow at Section 1 while maintaining the flow at Section N. Water level data are then collected at Sections 1 and N, and the time-varying water level curves for Sections 1 and N are plotted. Experiment 2 involves a step change in flow at Section N while maintaining the flow at Section 1. Water level data are then collected at Sections 1 and N, and the time-varying water level curves for Sections 1 and N are plotted. Curve fitting is then performed using the data from Experiments 1 and 2 after twice the delay time. The backwater area of Section 1 and Section N is calculated based on the slope of the fitted linear equation. The instantaneous water level change at the step is calculated based on the linear equation. According to the formula:

[0122]

[0123] Calculate the constant coefficient, then output the resulting return area of Section 1, the return area of Section N, and the constant coefficient to complete parameter identification. If operating conditions change, update the fixed flow boundary of Section 1, change the initial flow value, and set the fixed water level boundary of Section N, while keeping the water level unchanged. Alternatively, set the fixed flow boundary of Section 1, keep the flow value unchanged, and update the fixed water level boundary of Section N, while changing the initial water level. Return to rebuild the hydraulic model and repeat parameter identification.

[0124] Reference Manual Figure 2 , which shows a schematic diagram of real numerical simulation results of a first step test and a second step test provided by an embodiment of the present invention.

[0125] Figure 2 Test 1 is the first-step test, and Test 2 is the second-step test.

[0126] For example, the method of the present invention is further explained by taking the 36#~37# regulating gates of the middle line of the South-to-North Water Diversion Project as an example. The entire pure channel between the 36#~37# regulating gates of the middle line of the South-to-North Water Diversion Project was intercepted, and a numerical experiment of the hydraulic model (using the Pressimann four-point implicit difference format) was carried out. For the entire pure channel between the 36#~37# regulating gates of the middle line of the South-to-North Water Diversion Project, it is assumed that the channel is divided into N sections, and the section numbers are 1, 2, ..., N from upstream to downstream, and the distances between adjacent sections are L1, L2, ..., Ln-1 , establish the hydraulic model, given the fixed flow boundary of section 1, and set the flow value as Q0=117.5164m 3 / s, let the water level be Z0, given the fixed water level boundary of section N, let the water level be Z N , the traditional Pressimann method is used to solve the channel hydraulic model until a steady state is obtained, that is, the flow rate of all sections Q1=Q2=…=Q N =Q0=117.5164m 3 / s, at this time, under the fixed boundary value, the water level values of all sections Z1, Z2, ...Z N The water level of section 1 is Z1=93.345m, and the water level of section N is Z N =92.958m.

[0127] Step 1: Calculate the propagation time τ required for the flow fluctuation at section 1 to propagate to section N under the current steady-state conditions of the channel by integration d By integrating the channel under the current steady-state conditions, the propagation time τ required for the flow fluctuation of section N to propagate to section 1 is calculated. u τ d is the time delay of flow from the head to the end of the channel, τ u It is the time delay of flow from the end of the channel to the head of the channel.

[0128] Step 2: Taking the current steady-state water level and flow rate of the channel as the initial conditions and setting the initial time t = 0, two flow step numerical simulation tests are carried out.

[0129] Test 1: At t = 0, the boundary flow of section 1 is set to 1.1Q0 = 129.268m 3 / s, other conditions remain unchanged (the flow change of section 1 is The flow change of section N is ) Continue to call the hydraulic model to simulate backward to t=5τ d , collect the water level change process of section 1 during the simulation of numerical experiment 1 The water level change process of section N during the simulation of numerical experiment 1

[0130] Test 2: At t = 0, the boundary flow rate of section N is set to 0.9Q0 = 105.765m 3 / s, other conditions remain unchanged, (the flow change of section 1 is The flow change of section N is Continue to call the hydraulic model to simulate backward to t=5τ u , collect the water level change process of section 1 during the simulation of numerical experiment 2 The water level change process of section N during the simulation of numerical experiment 1

[0131] Step 3:

[0132] 1) The numerical simulation results of Experiment 1 and Experiment 2 are as follows Figure 2 As shown. and The water level record value, with the corresponding time as the independent variable and the water level height as the dependent variable, plot the water level change curves at Section 1 and Section N over time in Experiment 1 and Experiment 2 respectively. Fitting the water level in these four curves to the approximately stable rising stage over time can be obtained

[0133] Four straight line equations, among which You can find the parameters

[0134] 2) In test 1, the water level at section 1 increases instantaneously due to the sudden increase in flow, and the water level at section N will increase at t = τ d In the experiment 2, the water level of section N increases instantaneously due to the sudden decrease of flow. The water level of section 1 will increase instantaneously at t=τ u The relationship between the instantaneous increase in water level and the instantaneous change in flow is as follows:

[0135]

[0136] Where, are the instantaneous water level changes of section 1 and section N in test 1, are the instantaneous water level changes of section 1 and section N in test 2, respectively, and b d1 , b d2 , b u1 , b u2 is a constant coefficient, and is the instantaneous change in flow rate at section 1 in test 1, and is the instantaneous change in flow rate at section N in test 1, and is the instantaneous change in flow rate at section 1 in test 2, and is the instantaneous change in flow rate at section N in test 2.

[0137] 3) In test 1, the instantaneous change in flow rate at section 1 is Instantaneous change of flow rate at section N According to the fitted linear equation, calculate the water level value at the instant of the step Subtract the water level value before the step from the water level value at the instant of the step to obtain the water level change at the instant of the step in section 1 of test 1. Right now According to the above formula, Obtain parameters

[0138] Similarly, the water level of section N passes through τ d After that, a transient response will be generated due to the sudden increase of inflow flow. At this time, the instantaneous change of flow at section 1 is Instantaneous change of flow rate at section N However, due to the flattening effect of flow during propagation, the response time of the water level at section N will be delayed. Therefore, when selecting the instantaneous water level height after the step at section N, it is necessary to calculate the water level at τ d Add 800s to the time to correct the propagation delay. The water level value corresponding to the corrected time in the fitting straight line equation The instantaneous water level height after the step at section N of interest is obtained by subtracting the water level value before the step from the water level value at the instantaneous step to obtain the instantaneous water level change at section N in test 1. Right now According to the above formula, Parameters can be found

[0139] 4) In test 2, the instantaneous change in flow rate at section 1 is Instantaneous change of flow rate at section N According to the fitted linear equation, calculate the water level at the instant of the step The water level change at the instant of the step is obtained by subtracting the water level value before the step from the water level value at the instant of the step. Right now According to the above formula, Obtain parameters

[0140] Similarly, the water level of section 1 after time τ u After that, a transient response will be generated due to the sudden decrease in outflow flow. At this time, the instantaneous change in flow at section 1 is Instantaneous change of flow rate at section N However, due to the flattening effect of flow during propagation, the response time of the water level at Section 1 will be delayed. Therefore, when selecting the instantaneous water level height after the step at Section 1, it is necessary to uAdd 800s to the time to correct the propagation delay. The water level value corresponding to the corrected time in the fitting linear equation is the instantaneous water level height after the step at section 1 of interest. Subtract the water level value before the step from the water level value at the instant of the step to obtain the water level change at the instant of the step in section 1 of test 2. Right now According to the above formula, Parameters can be found

[0141] Step 3: According to the above steps, the parameter τ is obtained d , τ u , A u , A d , b d1 , b d2 , b u1 , b u2 , the integral time-delay zero model of test 1 under this working condition is as follows:

[0142]

[0143] Where, is the water level change of section 1 relative to the initial moment, is the water level change of section N relative to the initial moment, t is the simulation time, τ d The propagation time required for the flow fluctuation at section 1 to propagate to section N.

[0144] According to the above steps, the parameter τ is obtained u , A u , A d , b d1 , b d2 , b u1 , b u2 , the integral time-delay zero model of test 2 under this working condition is as follows:

[0145]

[0146] Where, is the water level change of section 1 relative to the initial moment, is the water level change of section N relative to the initial moment, t is the simulation time, τ u The propagation time required for the flow fluctuation at section N to propagate to section 1.

[0147] According to the above linear equation with time as the independent variable and water level change height as the dependent variable, the change in water level height of Section 1 and Section N at any time under this working condition can be predicted, and the water level height of Section 1 and Section N at any time can be calculated.

[0148] In practical applications, the parameter identification process for the open channel integral time-delay zero model accurately determines the dynamic response characteristics of the flow by dividing the open channel into multiple sections and combining step tests with experimental data fitting. This method takes into account the propagation delay of water flow fluctuations and improves the model's prediction accuracy for water level changes through forward and backward propagation calculations. Its advantages include improved accuracy of the hydraulic model, flexible adaptation to different operating conditions, and precise capture of the relationship between flow and water level changes.

[0149] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0150] In an embodiment of the present invention, by dividing the open channel into multiple sections and constructing a hydraulic model, the steady-state solution of the hydraulic model and the flow step test are used to effectively simplify the parameter identification under complex working conditions, avoiding the excessive reliance on comprehensive working condition data in traditional methods, improving calculation efficiency, reducing a large number of experimental calculations, and being able to quickly identify key parameters to meet real-time scheduling needs. In addition, the accuracy of the parameters is improved through fitting of experimental data, significantly improving the accuracy and efficiency of water resource scheduling.

[0151] Reference Manual Figure 3 , which shows a structural schematic diagram of a parameter identification system for an open channel integral time-delay zero model provided by the present invention.

[0152] The present invention further provides a parameter identification system 20 for an open channel integral time-delay zero model, which is applied to the above-mentioned parameter identification method for the open channel integral time-delay zero model, comprising:

[0153] Processor 201.

[0154] The memory 202 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 201 , the parameter identification method of the open channel integral time-delay zero model in the method embodiment is implemented.

[0155] The parameter identification system 20 of the open channel integral time-delay zero model provided by the present invention can execute the above-mentioned parameter identification method of the open channel integral time-delay zero model and achieve the same or similar technical effects. To avoid repetition, the present invention will not elaborate on them.

[0156] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0157] In an embodiment of the present invention, by dividing the open channel into multiple sections and constructing a hydraulic model, the steady-state solution of the hydraulic model and the flow step test are used to effectively simplify the parameter identification under complex working conditions, avoiding the excessive reliance on comprehensive working condition data in traditional methods, improving calculation efficiency, reducing a large number of experimental calculations, and being able to quickly identify key parameters to meet real-time scheduling needs. In addition, the accuracy of the parameters is improved through fitting of experimental data, significantly improving the accuracy and efficiency of water resource scheduling.

[0158] It should be understood that the processor in the embodiments of the present invention may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0159] It should also be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DR RAM).

[0160] The above embodiments can be implemented in whole or in part through software, hardware (such as circuits), firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired method (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, or magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0161] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0162] In this disclosure, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of a, b, or c" can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0163] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0164] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0165] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0166] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of the device or unit, which can be electrical, mechanical or other forms.

[0167] The units described as separate components may or may not be physically separate, and the components shown as units 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 these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0168] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0169] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0170] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

[0171] There are a few points to note:

[0172] (1) The drawings of the embodiments of the present invention only relate to the structures related to the embodiments of the present invention. Other structures may refer to conventional designs.

[0173] (2) For the sake of clarity, the thickness of layers or regions in the drawings used to describe the embodiments of the present invention are exaggerated or reduced, that is, these drawings are not drawn to scale. It is understood that when an element such as a layer, film, region, or substrate is referred to as being "on" or "under" another element, the element may be "directly" "on" or "under" the other element or intervening elements may be present.

[0174] (3) In the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other to form new embodiments.

[0175] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A parameter identification method for an open channel integral time-delay zero model, characterized in that: include: S1: Divide the open channel into multiple sections in sequence, and record the number of sections and the distance between adjacent sections; S2: establishing a hydraulic model of the open channel based on the number of sections and the distance between adjacent sections; S3: adding boundary conditions to each of the sections, wherein the boundary conditions include a section flow value and a section water level value; S4: Under the boundary conditions, solving the steady-state solution of the hydraulic model to obtain the steady-state flow value and the constant water level value of each section, wherein the steady-state flow value of each section is equal; S5: According to the steady-state solution, solve the forward propagation time of the flow fluctuation from the head section to the end section, and the reverse propagation time of the flow fluctuation from the end section to the head section; S6: using the steady-state solution as the initial condition and the cross-section flow rate as the variable, performing a first step test and a second step test, wherein the first step test is to obtain the first cross-section water level data under the step value of the flow rate at the head of the channel, and the second step test is to obtain the second cross-section water level data under the step value of the flow rate at the end of the channel; S7: Fitting the first section water level data and the second section water level data respectively to solve the open channel integral time-lag zero model parameters.

2. The parameter identification method according to claim 1, characterized in that: The S4 is specifically: The steady-state solution is obtained by the Pressimann algorithm.

3. The parameter identification method of the open channel integral time-delay zero model according to claim 1 is characterized in that: The forward propagation time of the traffic fluctuation is calculated as follows: Among them, τ d Indicates the forward propagation time of traffic fluctuation, L i represents the distance between the i-th section and the i+1-th section, i=1,2,…,N-1, N represents the maximum number of sections, u i represents the cross-sectional flow velocity of the i-th section, c i represents the still water propagation velocity of flow fluctuation at the i-th section, g represents the acceleration of gravity, and A i represents the cross-sectional water area at the i-th section, B i represents the water surface width at the i-th section, i.e., the section width; The calculation method of the reverse propagation time of the traffic fluctuation is specifically as follows: Among them, τ u Indicates the reverse propagation time of traffic fluctuations.

4. The parameter identification method of the open channel integral time-delay zero model according to claim 1, characterized in that: The test duration of the first step test is a first preset multiple of the forward propagation time of the flow fluctuation, and the test duration of the second step test is a second preset multiple of the reverse propagation time of the flow fluctuation.

5. The parameter identification method of the open channel integral time-delay zero model according to claim 1 is characterized in that: The S6 specifically includes: S601: Setting a head section step flow rate, determining a water level change rate at the head section and a water level change rate at the end section, wherein the head section step flow rate is greater than the head section initial flow rate corresponding to the steady-state solution; S602: Determine the first section water level data of each section under the step flow at the headwater section based on the test duration of the first step test and the water level change rate at the headwater section, thereby completing the first step test; S603: Setting a step flow rate at the end section of the channel, and determining a water level change rate at the head section and a water level change rate at the end section of the channel, wherein the step flow rate at the end section of the channel is less than an initial flow rate at the end section of the channel corresponding to the steady-state solution; S604: Based on the duration of the second step test and the water level change rate of the channel end section, the second section water level data of each section under the step flow of the channel head section is determined to complete the second step test.

6. The parameter identification method of the open channel integral time-delay zero model according to claim 1, characterized in that: The open channel integral time-delay zero model parameters include the free water surface area A of the head section u , backwater area of the channel end section A d , the first constant coefficient b related to the change in flow rate and water level at the head section u1 , the second constant coefficient b related to the change in flow at the end section of the channel and the change in water level at the head section u2 , the third constant coefficient b related to the change in flow at the head section and the change in water level at the end section d1 and the fourth constant coefficient b related to the change in flow rate and water level at the end of the channel section d2 .

7. The parameter identification method of the open channel integral time-delay zero model according to claim 4, characterized in that: The S7 specifically includes: S701: Acquire water level data of a first section for a first preset duration and water level data of a second section for a second preset duration, wherein the first preset duration is a third preset multiple of the forward propagation duration of the flow fluctuation, and the second preset duration is a fourth preset multiple of the reverse propagation duration of the flow fluctuation, wherein the third preset multiple is smaller than the first preset multiple, and the fourth preset multiple is smaller than the second preset multiple; S702: Fitting the acquired first section water level data and second section water level data according to their respective sections to obtain a fitting equation; S703: Solving the fitting equation to obtain the free water surface area of the channel head section and the backwater area of the channel end section; S704: establishing an equation for the instantaneous change of the water level at the head section and an equation for the instantaneous change of the water level at the end section in the first step test and the second step test, respectively; S705: Calculating the instantaneous change value of the water level at the head section and the instantaneous change value of the water level at the end section in the first step test and the second step test respectively based on the fitting equation; S706: Substitute the calculated instantaneous change values of the water level at the head section and the instantaneous change values of the water level at the end section into the corresponding instantaneous change equation of the water level at the head section and the instantaneous change equation of the water level at the end section to obtain the first constant coefficient, the second constant coefficient, the third constant coefficient and the fourth constant coefficient.

8. The parameter identification method of the open channel integral time-delay zero model according to claim 7, characterized in that: After S706, the method further includes: S707: Update the open channel integral time-lag zero model parameters under preset conditions, wherein the preset conditions are that the offset of the steady-state flow value of the section is greater than a first preset offset or the offset of the constant water level value of the section of the same section is greater than a second preset offset.

9. The parameter identification method of the open channel integral time-delay zero model according to claim 1, characterized in that: After S7, the method further includes: The open channel integral time-lag zero model parameters are substituted into the open channel integral time-lag zero model to complete the construction of the open channel integral time-lag zero model, wherein the open channel integral time-lag zero model includes a first open channel integral time-lag zero model related to the forward propagation time length of the flow fluctuation and a second open channel integral time-lag zero model related to the reverse propagation time length of the flow fluctuation.

10. A parameter identification system for an open channel integral time-delay zero model, characterized in that: include: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the parameter identification method of the open channel integral time-delay zero model according to any one of claims 1 to 9 is implemented.

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