Method and device for determining ecological water supplement of rivers and lakes, electronic equipment and storage medium

Abstract

This invention relates to the field of river and lake ecological protection technology, and particularly to a method, device, electronic device, and storage medium for determining river and lake ecological water replenishment. The method first obtains a first flow array; then, multiple pre-simulated water replenishment flow queues are substituted into the first flow array and respectively into a flow simulation model to obtain multiple pre-simulated flow data queues; next, for each pre-simulated water replenishment flow queue, the pre-simulated flow queue and its corresponding pre-simulated flow data queue are substituted into an objective function equation, and the output of the objective function equation is used as the target state value of the pre-simulated water replenishment flow queue; finally, each pre-simulated water replenishment flow queue is adjusted based on the multiple target state values. This invention quantifies the merits of different schemes through an objective function, taking into account both the ecological flow demand and water resource input of each river section, and iteratively adjusts the water replenishment queues by combining historical best and current best schemes, gradually approaching the optimal water replenishment scheme, thus achieving efficient water resource utilization.

Description

Technical Field

[0001] This invention relates to the field of river and lake ecological protection technology, and in particular to a method, apparatus, electronic device and storage medium for determining ecological water replenishment for rivers and lakes. Background Technology

[0002] With the increasing prominence of water scarcity, river ecological protection and rational allocation of water resources have become important research directions in the field of water conservancy engineering. In the process of river ecological management, water replenishment scheduling is a key means to ensure river ecological flow and maintain the stability of the basin ecosystem. Scientific and accurate flow prediction and optimization of water replenishment plans directly determine the effectiveness of water replenishment scheduling and the efficiency of water resource utilization.

[0003] Currently, existing river water replenishment scheduling suffers from numerous limitations. Existing technologies largely rely on manual experience to determine water replenishment flow queues, lacking quantitative evaluation indicators and failing to balance the ecological flow needs of each river segment with the economic viability of water replenishment. While some schemes introduce simple evaluation parameters, they lack a comprehensive objective function to quantify the merits of the replenishment scheme. This results in either schemes failing to meet ecological flow requirements, leading to river ecosystem degradation, or excessive replenishment, causing water waste. Furthermore, adjustments to existing water replenishment flow queues are mostly unidirectional corrections, lacking iterative optimization based on historical schemes. This inefficiency makes it difficult to approximate the optimal replenishment scheme and achieve efficient water resource utilization.

[0004] In summary, existing river flow prediction and replenishment flow cohort adjustment technologies suffer from problems such as unscientific river segmentation, lack of quantitative basis for replenishment scheme optimization, and low adjustment efficiency, making it difficult to meet the actual needs of river ecological protection and rational allocation of water resources. Therefore, developing a technical solution that can balance ecological protection and efficient water resource utilization has become an urgent technical challenge to be solved. Summary of the Invention

[0005] The present invention provides a method, apparatus, electronic device and storage medium for determining ecological water replenishment for rivers and lakes, which solves the problem in the prior art that ecological water replenishment for rivers and lakes is difficult to balance ecological protection and efficient utilization of water resources.

[0006] In a first aspect, embodiments of the present invention provide a method for determining ecological water replenishment for rivers and lakes, including: Obtain the first flow array, which includes multiple first flows, each of which corresponds to a river segment. The river segments are obtained based on the segmentation of the river topology map. Multiple pre-simulated water replenishment flow queues are substituted into the flow simulation model along with the first flow array to obtain multiple pre-simulated flow data queues. Each pre-simulated flow data queue corresponds to a pre-simulated water replenishment flow queue. The pre-simulated flow data queue includes multiple second flow arrays, which represent the flow of multiple river sections at predetermined time nodes. For each pre-simulated water replenishment flow queue, the pre-simulated water replenishment flow queue and the corresponding pre-simulated flow data queue are substituted into the objective function equation, and the output of the objective function equation is used as the target state value of the pre-simulated water replenishment flow queue. The objective function equation expresses the degree to which the total water replenishment and the flow of multiple river segments meet the ecological needs in the future period. Adjust each pre-simulation water replenishment flow queue based on multiple target state values.

[0007] In one possible implementation, the flow prediction model includes multiple river segment flow models. The step of substituting multiple predicted water replenishment flow queues and the first flow array into the flow prediction model to obtain multiple predicted flow data queues includes: For each pre-simulation water replenishment flow queue, perform the following steps: The water replenishment flow is taken out sequentially from the pre-simulated water replenishment flow queue and used as the water replenishment flow for the source river section; For each river segment except the source segment, the flow of the upstream segment is extracted from the first flow array as the replenishment flow of the river segment; For each river segment, the flow rate of this river segment extracted from the first flow array and the water replenishment flow rate are substituted into the river segment flow model to obtain the simulated flow rate; Multiple simulated traffic flows are combined into a second traffic array; Add the second flow array to the pre-simulated flow data queue; If the traversal of the pre-simulated water replenishment flow queue is not completed, the second flow array is used as the first flow array, and the process jumps to the step of taking out the water replenishment flow from the pre-simulated water replenishment flow queue in sequence as the water replenishment flow of the source river section.

[0008] In one possible implementation, the flow prediction model includes multiple river segment flow models, which are constructed based on multiple sample flows, including: Multiple sample datasets are obtained. Each sample dataset includes the upstream river flow and the current river flow. Each sample dataset corresponds to a label flow of the current river flow. The time point corresponding to the label flow of the current river flow is later than the time point corresponding to the current river flow in the sample dataset. Substitute the multiple sample datasets into the first fitting equation to obtain multiple outputs of the fitting equation, where each output corresponds to a sample dataset; Based on the multiple outputs and the labeled flow rates of the river segment corresponding to the multiple sample datasets, the fitting deviation of the fitting equation is determined; If the fitting deviation is greater than the deviation threshold, then the multiple parameters of the fitting equation are adjusted according to the fitting deviation, and the process jumps to the step of substituting the multiple sample datasets into the first fitting equation to obtain the multiple outputs of the fitting equation. Otherwise, the fitted equation is used as the river segment flow model.

[0009] In one possible implementation, the first fitting equation is:

[0010] In the formula, For the first River section Traffic at specific time points The weighting coefficients for the exponent frequency. For the first River section Traffic at specific time points For the first River section Traffic at specific time points As the first coefficient, As the second coefficient, The intercept coefficient, This represents the maximum exponential number.

[0011] In one possible implementation, the objective function equation is:

[0012] In the formula, For the first The flow weight of each river section For the first River section Traffic at specific time points For the first Ecological demand flow of the river section For water replenishment flow weighting, This represents the total number of time points. The total number of river sections. The corresponding water replenishment flow queue in the pre-rehearsal Traffic at specific time points.

[0013] In one possible implementation, adjusting each pre-simulated water replenishment flow queue based on multiple target state values ​​includes: Multiple target status queues are obtained, where each target status queue corresponds to a pre-simulation water replenishment flow queue, and the target status queue includes the target status values ​​that have been adjusted in the pre-simulation water replenishment flow queue in previous iterations. For each target state value, add it to the target state queue corresponding to the pre-simulated water replenishment flow queue; For each target state queue, find the minimum value from the target state queue as the historical best value, and take the pre-simulated water replenishment flow queue corresponding to the historical best value as the historical best pre-simulated water replenishment flow queue. Find the minimum value among the multiple target state values ​​and take it as the current optimal value. Then, take the pre-simulation water replenishment flow queue corresponding to the current optimal value as the current optimal pre-simulation water replenishment flow queue. For each pre-simulated water replenishment flow queue, adjustments are made based on the historical best pre-simulated water replenishment flow queue and the current best pre-simulated water replenishment flow queue.

[0014] In one possible implementation, the adjustment of each pre-simulated water replenishment flow queue based on the historical best pre-simulated water replenishment flow queue and the current best pre-simulated water replenishment flow queue includes: For each pre-simulated water replenishment flow queue, adjustments are made based on the first formula, the historical best pre-simulated water replenishment flow queue, and the current best pre-simulated water replenishment flow queue, wherein the first formula is:

[0015] In the formula, For the first The corresponding pre-reaction water replenishment flow queue after the second adjustment Traffic at specific time points For the first The corresponding pre-reaction water replenishment flow queue after the second adjustment Traffic at specific time points The corresponding historical optimal pre-simulation water replenishment flow queue Traffic at specific time points The corresponding water replenishment flow rate in the current optimal pre-simulation queue Traffic at specific time points For the first The target state value of the pre-simulated water replenishment flow queue after the second adjustment. This is the best historical value. This is the current optimal value. The first adjustment rate coefficient, This is the second adjustment rate coefficient. This is the basic disturbance compensation amount.

[0016] Secondly, embodiments of the present invention provide a river and lake ecological water replenishment determination device, used to implement the river and lake ecological water replenishment determination method as described in the first aspect or any possible implementation thereof, the river and lake ecological water replenishment determination device comprising: The river segment status acquisition module is used to acquire the first flow array, which includes multiple first flows, each of which corresponds to a river segment. The river segments are obtained based on the segmentation of the river topology map. The river section flow prediction module is used to substitute multiple prediction water replenishment flow queues and the first flow array into the flow prediction model to obtain multiple prediction flow data queues. Each prediction flow data queue corresponds to a prediction water replenishment flow queue. The prediction flow data queue includes multiple second flow arrays, and the second flow arrays include flow characteristics of multiple river sections at predetermined time nodes. The target state determination module is used to, for each pre-simulated water replenishment flow queue, substitute the pre-simulated water replenishment flow queue and the corresponding pre-simulated flow data queue into the objective function equation, and use the output of the objective function equation as the target state value of the pre-simulated water replenishment flow queue. The objective function equation expresses the degree to which the total water replenishment and the flow of multiple river segments meet the ecological needs in the future period. as well as, The water replenishment adjustment module is used to adjust the water replenishment flow rate of each pre-simulation queue based on multiple target status values.

[0017] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor executes the computer program to implement the steps of the method as described in the first aspect or any possible implementation of the first aspect.

[0018] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any possible implementation thereof.

[0019] The beneficial effects of the embodiments of the present invention compared with the prior art are as follows: This invention discloses a method for determining ecological water replenishment for rivers and lakes. First, a first flow array is obtained, comprising multiple first flow rates, each corresponding to a river segment obtained based on a river topology map. Then, multiple pre-simulated water replenishment flow queues are substituted into a flow simulation model along with the first flow arrays to obtain multiple pre-simulated flow data queues. Each pre-simulated flow data queue corresponds to a pre-simulated water replenishment flow queue, and each pre-simulated flow data queue includes multiple second flow arrays, each representing the flow rate of multiple river segments at a predetermined time node. Next, for each pre-simulated water replenishment flow queue, the pre-simulated flow queue and its corresponding pre-simulated flow data queue are substituted into an objective function equation. The output of the objective function equation is used as the target state value of the pre-simulated water replenishment flow queue, where the objective function equation expresses the degree to which the total water replenishment and the flow rates of multiple river segments meet ecological needs in the future. Finally, each pre-simulated water replenishment flow queue is adjusted based on the multiple target state values.

[0020] This invention quantifies the merits of different schemes through an objective function, takes into account the ecological flow demand and water resource input of each river section, and iteratively adjusts the water replenishment queue by combining historical and current best schemes, gradually approaching the optimal water replenishment scheme and achieving efficient utilization of water resources.

[0021] This invention clarifies the weight of ecologically sensitive river sections, prioritizes ensuring that ecological flow meets standards, and controls the total water replenishment volume through the weight of water replenishment flow, thereby achieving coordinated development of ecological protection and rational allocation of water resources. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of the method for determining ecological water replenishment for rivers and lakes provided in the embodiments of the present invention; Figure 2 This is a schematic diagram of the pre-traffic data queue construction process provided by an embodiment of the present invention; Figure 3 This is a functional block diagram of the river and lake ecological water replenishment determination device provided in the embodiments of the present invention; Figure 4 This is a functional block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0024] In the following description, specific details such as particular system structures and techniques are set forth for illustrative purposes and not for limitation, so as to provide a thorough understanding of embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0025] To make the objectives, technical solutions, and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

[0026] The embodiments of the present invention will be described in detail below. This example is implemented based on the technical solution of the present invention, and provides detailed implementation methods and specific operation processes. However, the protection scope of the present invention is not limited to the following embodiments.

[0027] Figure 1 A flowchart illustrating the method for determining ecological water replenishment for rivers and lakes provided in this embodiment of the invention.

[0028] like Figure 1 As shown, a flowchart illustrating the implementation of the river and lake ecological water replenishment determination method provided by the embodiments of the present invention is presented below in detail: In step 101, a first flow array is obtained, wherein the first flow array includes multiple first flows, each first flow corresponds to a river segment, and the river segment is obtained based on the segmentation of the river topology map.

[0029] In step 102, multiple pre-simulated water replenishment flow queues are substituted into the flow simulation model along with the first flow array to obtain multiple pre-simulated flow data queues. Each pre-simulated flow data queue corresponds to a pre-simulated water replenishment flow queue. The pre-simulated flow data queue includes multiple second flow arrays, which represent the flow of multiple river sections at predetermined time nodes.

[0030] In some embodiments, the flow prediction model includes multiple river segment flow models, and the step of substituting multiple prediction water replenishment flow queues and the first flow array into the flow prediction model to obtain multiple prediction flow data queues includes: For each pre-simulation water replenishment flow queue, perform the following steps: The water replenishment flow is taken out sequentially from the pre-simulated water replenishment flow queue and used as the water replenishment flow for the source river section; For each river segment except the source segment, the flow of the upstream segment is extracted from the first flow array as the replenishment flow of the river segment; For each river segment, the flow rate of this river segment extracted from the first flow array and the water replenishment flow rate are substituted into the river segment flow model to obtain the simulated flow rate; Multiple simulated traffic flows are combined into a second traffic array; Add the second flow array to the pre-simulated flow data queue; If the traversal of the pre-simulated water replenishment flow queue is not completed, the second flow array is used as the first flow array, and the process jumps to the step of taking out the water replenishment flow from the pre-simulated water replenishment flow queue in sequence as the water replenishment flow of the source river section.

[0031] In some implementations, the flow prediction model includes multiple river segment flow models, which are constructed based on multiple sample flows, including: Multiple sample datasets are obtained. Each sample dataset includes the upstream river flow and the current river flow. Each sample dataset corresponds to a label flow of the current river flow. The time point corresponding to the label flow of the current river flow is later than the time point corresponding to the current river flow in the sample dataset. Substitute the multiple sample datasets into the first fitting equation to obtain multiple outputs of the fitting equation, where each output corresponds to a sample dataset; Based on the multiple outputs and the labeled flow rates of the river segment corresponding to the multiple sample datasets, the fitting deviation of the fitting equation is determined; If the fitting deviation is greater than the deviation threshold, then the multiple parameters of the fitting equation are adjusted according to the fitting deviation, and the process jumps to the step of substituting the multiple sample datasets into the first fitting equation to obtain the multiple outputs of the fitting equation. Otherwise, the fitted equation is used as the river segment flow model.

[0032] In some implementations, the first fitting equation is:

[0033] In the formula, For the first River section Traffic at specific time points The weighting coefficients for the exponent frequency. For the first River section Traffic at specific time points For the first River section Traffic at specific time points As the first coefficient, As the second coefficient, The intercept coefficient, This represents the maximum exponential number.

[0034] For example, the river topology map needs to fully cover the distribution of the main stream and tributaries of the target river and the location of hydrological nodes. The segmentation process needs to take into account factors such as river morphology, watershed boundaries, and distribution of hydrological monitoring stations to ensure that the hydrological characteristics of each river segment are relatively uniform and that the connection relationship between river segments is consistent with the actual river topology, so that each first flow can accurately represent the initial flow state of the corresponding river segment.

[0035] Assuming the target river is the main stream and two major tributaries of a certain basin, based on the river topology map and the distribution of hydrological monitoring sections, it is divided into 5 river segments: the upstream segment of the main stream, the middle segment of the main stream, the downstream segment of the main stream, tributary A segment, and tributary B segment. The corresponding first flow array is [Q1, Q2, Q3, Q4, Q5], where Q1 to Q5 correspond to the initial real-time flow (unit: m³ / s) of the above 5 river segments, respectively. The flow data can be obtained by processing the real-time data collected by the hydrological monitoring stations in the basin.

[0036] This invention substitutes multiple pre-simulated water replenishment flow queues and a first flow array into a flow simulation model to obtain multiple pre-simulated flow data queues. Each pre-simulated water replenishment flow queue corresponds to a pre-simulated water replenishment scheme, and the queue contains water replenishment flow values ​​at multiple time points. The interval between time points can be set according to actual simulation requirements (e.g., 1 hour, 1 day). Each pre-simulated flow data queue corresponds to a pre-simulated water replenishment flow queue, and the pre-simulated flow data queue includes multiple second flow arrays. The second flow arrays represent the flow of multiple river sections at predetermined time points, that is, each second flow array corresponds to a time point, and the elements in the array correspond one-to-one with the first flow array, respectively representing the pre-simulated flow of each river section at that time point, thereby achieving accurate simulation of the flow change trend of each river section under different water replenishment schemes.

[0037] In some implementations, the flow prediction model includes multiple river segment flow models, each corresponding to an independent river segment flow model. The river segment flow model can predict flow changes at subsequent time points based on the upstream input flow and its own initial flow. Multiple predicted water replenishment flow queues are substituted into the flow prediction model along with the first flow array to obtain multiple predicted flow data queues, specifically including: like Figure 2 As shown, for each pre-simulation water replenishment flow queue, the following steps are performed: The first step is to sequentially extract the water replenishment flow from the pre-simulated water replenishment flow queue 201 as the water replenishment flow for the source river section. The source river section refers to the upstream section in the river topology map that has no other tributary sections. It is usually the starting section of the main stream or the starting section of a major tributary. The water replenishment flow of the source river section directly affects the flow distribution of the entire basin, so it needs to be determined first and substituted into the pre-simulated water replenishment flow.

[0038] The second step involves extracting the upstream flow rate from the first flow array for each river segment, excluding the source segment, as the replenishment flow rate for that segment. The determination of the upstream segment is based on the connectivity of the river topology map; that is, the upstream segment of a given river segment is the segment directly flowing into that segment. If a river segment has multiple upstream flowing segments, the sum of the flows of all upstream segments is taken as the upstream input flow rate (i.e., the replenishment flow rate) for that segment, ensuring the rationality of flow transfer.

[0039] The third step involves substituting the flow rate of this river segment extracted from the first flow array 202 and the replenishment flow rate into the river segment flow model 203 to obtain the simulated flow rate 204. The flow rate of this river segment is the initial flow rate at the current time point, and the replenishment flow rate is the input flow rate of this river segment (the simulated replenishment flow rate for the source river segment and the upstream river segment flow rate for non-source river segments). Both are used as inputs to the river segment flow model 203, and the simulated flow rate 204 for the next time point of this river segment is calculated through the model.

[0040] The fourth step is to construct a second flow array 205 from multiple simulated flows. The simulated flow of each river segment corresponds to one element in the second flow array 205. The order of the elements is consistent with that of the first flow array 202 to ensure that the correspondence between each element and the river segment is not deviated. Thus, the simulated flow status of all river segments at this time point can be completely represented by the second flow array 205.

[0041] The fifth step is to add the second flow array 205 to the pre-simulated flow data queue. The pre-simulated flow data queue stores each second flow array 205 in chronological order of time nodes, forming a complete flow change sequence, which facilitates subsequent analysis of the flow distribution characteristics of each river segment at different time nodes.

[0042] Step 6: If the traversal of the pre-simulated water replenishment flow queue 201 is not completed, then the second flow array 205 is used as the first flow array 202, and the process jumps to the step of sequentially retrieving the water replenishment flow from the pre-simulated water replenishment flow queue 201 as the water replenishment flow for the source river section. That is, through iterative looping, the pre-simulated flow of the previous time node is used as the initial flow of the next time node, and the pre-simulated water replenishment flow is continuously substituted until all water replenishment flows in the pre-simulated water replenishment flow queue have been traversed, ultimately forming a complete pre-simulated flow data queue, realizing the simulation of river flow changes throughout the entire pre-simulation period.

[0043] The flow prediction model includes multiple river segment flow models, which are constructed based on multiple sample flows to accurately fit the flow variation patterns of the river segments and ensure the accuracy of the prediction results. The specific construction process includes: The first step is to acquire multiple sample datasets. Each sample dataset includes upstream river flow and local river flow, with each dataset corresponding to a labeled flow for that local river segment. The time point corresponding to the labeled flow is later than the time point corresponding to the local river flow in the sample dataset. The acquisition of sample datasets must be based on long-term hydrological monitoring data, covering different seasons and hydrological conditions (such as flood season and dry season) to ensure sample diversity and representativeness. The time interval must be consistent with the simulation requirements. The time difference between the labeled flow and the local river flow in the sample dataset must be equal to the prediction step size of the simulation model (e.g., if the prediction step size is 1 day, then the time point of the labeled flow is 1 day later than the time point in the sample dataset), ensuring that the labeled flow accurately represents the prediction result corresponding to the sample input.

[0044] The second step involves substituting the multiple sample datasets into the first fitting equation to obtain multiple outputs of the fitting equation, where each output corresponds to one sample dataset. The first fitting equation is a pre-defined nonlinear fitting equation that characterizes the correlation between upstream river flow, historical flow of the current river segment, and future flow of the current river segment. Substituting the upstream river flow and current river segment flow from the sample dataset yields the output value of the equation, which is a preliminary prediction of the labeled flow of the current river segment.

[0045] The third step is to determine the fitting bias of the fitted equation based on the multiple outputs and the corresponding labeled flow rates of the river segment in the multiple sample datasets. The fitting bias is used to measure the prediction accuracy of the fitted equation and can be calculated using indicators such as mean squared error and mean absolute error. Specifically, the fitting bias is calculated by subtracting the fitted output of each sample dataset from the corresponding labeled flow rate of the river segment, and then performing statistical analysis on all differences to obtain the overall fitting bias. The smaller the fitting bias, the higher the prediction accuracy of the fitted equation.

[0046] Fourth, if the fitting deviation is greater than the deviation threshold, adjust multiple parameters of the fitting equation according to the fitting deviation, and then proceed to the step of substituting the multiple sample datasets into the first fitting equation to obtain multiple outputs of the fitting equation. The deviation threshold is set according to the accuracy requirements of the actual application scenario, combined with factors such as the ecological flow requirements of the river section and the accuracy of hydrological monitoring; parameter adjustment needs to be based on the changing trend of the fitting deviation, gradually optimizing parameters such as weight coefficients, coefficients, and intercepts in the equation until the fitting deviation drops below the deviation threshold, ensuring that the fitting equation can accurately fit the changing patterns of the sample data.

[0047] Fifth, otherwise, use the fitted equation as the river segment flow model. When the fitting deviation is less than or equal to the deviation threshold, it indicates that the fitted equation can accurately characterize the flow variation pattern of the river segment, and can be used as the flow model for the river segment in subsequent flow prediction calculations.

[0048] In some implementations, the first fitting equation is:

[0049] In the formula, For the first River section Traffic at specific time points, i.e., pre-render traffic; The weighting coefficients for the exponent degree are used to adjust the degree of influence of different exponent terms on the simulated flow. The higher the exponent degree, the smaller the weighting coefficients are usually to ensure the stability of the equation. For the first River section Traffic at a given time node, i.e., the first The flow rate of the upstream section of the river at the adjacent previous time point; For the first River section Traffic at a given time node, i.e., the first Historical flow of the river section; The first coefficient is used to adjust the weight of the influence of the upstream river flow on the current river flow in this river section; The second coefficient is used to adjust the weight of the influence of historical flow on current flow in this river section; These are the intercept coefficients, used to correct systematic errors in the equations; The maximum exponent is usually set according to the complexity of the flow variation in the river section, and is generally taken as 2-5. For complex river sections, the value can be appropriately increased to ensure that the equation can fit the nonlinear variation law of the flow.

[0050] For example, suppose a certain river section is the middle reaches of the main stream ( =2), maximum exponential number =2, and the values ​​of each parameter are: w1=0.7, w2=0.02, C1=0.3, C2=0.6, C0=2; Time point, upstream river section ( =1) flow Flow rate of this river section =70m³ / s, substituting this into the first fitting equation, we can obtain: =0.7×(0.3×80+0.6×70)¹ + 0.02×(0.3×80+0.6×70)² + 2, and finally summed, we get: =75.32 m³ / s, this result is the river section at Traffic flow at specific time points.

[0051] In step 103, for each pre-simulated water replenishment flow queue, the pre-simulated water replenishment flow queue and the corresponding pre-simulated flow data queue are substituted into the objective function equation, and the output of the objective function equation is used as the target state value of the pre-simulated water replenishment flow queue. The objective function equation expresses the degree to which the total water replenishment and the flow of multiple river segments meet the ecological needs in the future period.

[0052] In some implementations, the objective function equation is:

[0053] In the formula, For the first The flow weight of each river section For the first River section Traffic at specific time points For the first Ecological demand flow of the river section For water replenishment flow weighting, This represents the total number of time points. The total number of river sections. The corresponding water replenishment flow queue in the pre-rehearsal Traffic at specific time points.

[0054] For example, for each pre-simulated water replenishment flow queue, the pre-simulated water replenishment flow queue and the corresponding pre-simulated flow data queue are substituted into the objective function equation, and the output of the objective function equation is used as the target state value of the pre-simulated water replenishment flow queue. The objective function equation expresses the degree to which the total water replenishment volume and the flow of multiple river sections meet the ecological needs in the future period. Its core function is to quantify the advantages and disadvantages of different pre-simulated water replenishment schemes, take into account the economic efficiency of water replenishment volume and the compliance rate of ecological flow, and provide a quantitative basis for the subsequent adjustment of the water replenishment flow queue.

[0055] In some implementations, the objective function equation is:

[0056] In the formula, For the first The flow weight of each river section is set according to the ecological importance of the river section. Ecologically sensitive river sections (such as fish spawning sections and river sections where rare aquatic organisms are located) have a larger weight value, while ordinary river sections have a smaller weight value, to ensure the principle of ecological priority. For the first River section Traffic at a given time point, i.e., the corresponding value in the pre-simulation traffic data queue; For the first The ecological demand flow of a river section, which is the minimum flow required to maintain the stability of the ecosystem in that river section, is determined based on factors such as the ecological function and the needs of aquatic organisms in that river section. The water replenishment flow weight is used to adjust the impact of the total water replenishment on the target state value, reflecting the economy of water replenishment. The larger the weight value, the more significant the impact of water replenishment. It needs to be set in conjunction with the total water resource constraints. This represents the total number of time nodes, i.e., the number of time nodes included in the entire rehearsal period. This represents the total number of river segments, i.e., the total number of river segments after segmentation based on the river topology map; For the pre-rehearsal water replenishment flow queue corresponding to The flow rate at a given time point represents the total water replenishment at that time point. The smaller the target state value, the better the scheme corresponding to the simulated water replenishment flow queue, which can both meet the ecological flow requirements of each river section and control the total water replenishment, thus achieving efficient utilization of water resources.

[0057] For example, suppose a certain watershed has a total of 3 river sections ( =3), the rehearsal period includes 5 time nodes ( =5), the flow weights of each river segment are respectively , , Water replenishment flow weight The ecological demand flow for each river section is as follows: , , The flow rates at each time point in a certain pre-simulation water replenishment flow queue are: , , , , In the corresponding pre-simulated flow data queue, the flow of each river segment at each time node is known. Substitute it into the objective function equation, calculate the term value and total water replenishment term value of each river segment at each time node, and then sum them to obtain the target state value. If the calculated target state value is 8.6, then this value is the quantitative evaluation result of the pre-simulated water replenishment flow queue.

[0058] In step 104, each pre-simulation water replenishment flow queue is adjusted based on multiple target state values.

[0059] In some implementations, adjusting each pre-simulated water replenishment flow queue based on multiple target state values ​​includes: Multiple target status queues are obtained, where each target status queue corresponds to a pre-simulation water replenishment flow queue, and the target status queue includes the target status values ​​that have been adjusted in the pre-simulation water replenishment flow queue in previous iterations. For each target state value, add it to the target state queue corresponding to the pre-simulated water replenishment flow queue; For each target state queue, find the minimum value from the target state queue as the historical best value, and take the pre-simulated water replenishment flow queue corresponding to the historical best value as the historical best pre-simulated water replenishment flow queue. Find the minimum value among the multiple target state values ​​and take it as the current optimal value. Then, take the pre-simulation water replenishment flow queue corresponding to the current optimal value as the current optimal pre-simulation water replenishment flow queue. For each pre-simulated water replenishment flow queue, adjustments are made based on the historical best pre-simulated water replenishment flow queue and the current best pre-simulated water replenishment flow queue.

[0060] In some implementations, the adjustment of each pre-simulated water replenishment flow queue based on the historical best pre-simulated water replenishment flow queue and the current best pre-simulated water replenishment flow queue includes: For each pre-simulated water replenishment flow queue, adjustments are made based on the first formula, the historical best pre-simulated water replenishment flow queue, and the current best pre-simulated water replenishment flow queue, wherein the first formula is:

[0061] In the formula, For the first The corresponding pre-reaction water replenishment flow queue after the second adjustment Traffic at specific time points For the first The corresponding pre-reaction water replenishment flow queue after the second adjustment Traffic at specific time points The corresponding historical optimal pre-simulation water replenishment flow queue Traffic at specific time points The corresponding water replenishment flow rate in the current optimal pre-simulation queue Traffic at specific time points For the first The target state value of the pre-simulated water replenishment flow queue after the second adjustment. This is the best historical value. This is the current optimal value. The first adjustment rate coefficient, This is the second adjustment rate coefficient. This is the basic disturbance compensation amount.

[0062] For example, step 104 adjusts each pre-simulated water replenishment flow queue according to multiple target state values. The core purpose is to optimize the pre-simulated water replenishment scheme so that the target state value corresponding to the adjusted pre-simulated water replenishment flow queue is smaller. That is, it takes into account both ecological flow compliance and water replenishment economy, gradually approaching the optimal water replenishment scheme and ensuring the rational allocation of water resources.

[0063] In some implementations, adjusting each pre-simulation water replenishment flow queue based on multiple target state values ​​specifically includes: The first step is to obtain multiple target state queues, each corresponding to a pre-emptive water replenishment flow queue. Each target state queue includes the target state values ​​from each adjustment of the pre-emptive water replenishment flow queue. After multiple adjustments, each pre-emptive water replenishment flow queue will generate multiple target state values. These values ​​are stored in chronological order of adjustment to form the target state queue. This queue allows for clear tracking of the optimization process of each pre-emptive water replenishment flow queue and understanding the changing trends of its target state values.

[0064] The second step is to add each target state value to the target state queue corresponding to the pre-simulated water replenishment flow queue. Each time the pre-simulated water replenishment flow queue is adjusted, its new target state value is calculated and added to the end of the corresponding target state queue to ensure that the queue can be updated in real time and completely record the optimization trajectory of the scheme.

[0065] The third step involves finding the minimum value for each target state queue, which is then used as the historical optimal value. The corresponding pre-simulated water replenishment flow queue is then designated as the historical optimal pre-simulated water replenishment flow queue. The historical optimal value represents the best performance of the pre-simulated water replenishment flow queue in all adjustments, and the corresponding pre-simulated water replenishment flow queue is the optimal historical version of the scheme, serving as a reference benchmark for subsequent adjustments to prevent regression in the optimization process.

[0066] The fourth step involves finding the minimum value among multiple target state values, which is then taken as the current optimal value. The corresponding pre-simulated water replenishment flow queue is then designated as the current optimal pre-simulated water replenishment flow queue. The current optimal value represents the best quantified result of all pre-simulated water replenishment flow queues after this adjustment, and the corresponding pre-simulated water replenishment flow queue is the optimal version among all current schemes. This serves as a global reference benchmark, guiding all pre-simulated water replenishment flow queues to adjust towards a better direction.

[0067] The fifth step involves adjusting each pre-optimal water replenishment flow queue based on both the historical best and the current best pre-optimal flow queue. By combining the queue's own historical best and the global best, the flow rates at each time point are corrected. This process retains the reasonable aspects of the optimization process while also leveraging the advantages of the global best solution, ensuring that the adjusted solution is more rational and optimal.

[0068] In some implementations, for each pre-simulated water replenishment flow queue, adjustments are made based on the historical best pre-simulated water replenishment flow queue and the current best pre-simulated water replenishment flow queue, specifically including: For each pre-simulated water replenishment flow queue, adjustments are made based on the first formula, the historical best pre-simulated water replenishment flow queue, and the current best pre-simulated water replenishment flow queue, wherein the first formula is:

[0069] In the formula, For the first The corresponding pre-reaction water replenishment flow queue after the second adjustment Traffic at a given time point, i.e., the adjusted target traffic; For the first The corresponding pre-reaction water replenishment flow queue after the second adjustment The flow rate at a given time point, i.e., the initial flow rate before adjustment; The corresponding historical optimal pre-simulation water replenishment flow queue Traffic at a given time point, i.e., the traffic at the corresponding time point of its own historical best solution; The corresponding water replenishment flow rate in the current optimal pre-simulation queue Traffic at a given time point, i.e., the traffic at the corresponding time point of the current global optimal solution; For the first The target state value of the pre-adjustment water replenishment flow queue, i.e. the quantitative evaluation result before the adjustment; This is the historical best value, that is, the target state value of its own historical best solution; This is the current optimal value, i.e., the target state value of the current optimal solution globally; The first adjustment rate coefficient is used to adjust the influence of the historical best solution on the adjustment process. Its value range is usually 0.1-0.5. The larger the value, the more significant the influence of the historical best solution. This is the second adjustment rate coefficient, used to adjust the degree of influence of the current optimal solution on the adjustment process. Its value range is usually 0.1-0.5. The larger the value, the more significant the influence of the current optimal solution. This is the basic disturbance compensation amount, used to avoid getting trapped in local optima and to ensure the rationality of the water replenishment flow. The value is set according to the actual water replenishment scenario, and is usually a small positive number (such as 1-5 m³ / s).

[0070] For example, suppose a pre-simulation water replenishment flow queue is performing the first... After this adjustment Traffic at time nodes The corresponding target state value The historical best pre-simulation water replenishment flow rate queue of this queue is in Traffic at time nodes Historical best value The current optimal pre-simulation water replenishment flow queue is in Traffic at time nodes Current optimal value Adjust the rate coefficient , Basic disturbance compensation amount Substituting into the first formula, we can obtain: The results were obtained through step-by-step calculations: This result represents the pre-simulated water replenishment flow rate queue. Time node passed the first The adjusted flow rate is closer to the historical and current optimal solutions, which helps to reduce the target state value and optimize the water replenishment effect.

[0071] The present invention discloses a method for determining ecological water replenishment for rivers and lakes. First, a first flow array is obtained, comprising multiple first flows, each corresponding to a river segment obtained based on a river topology map. Then, multiple pre-simulated water replenishment flow queues are substituted into a flow simulation model along with the first flow arrays to obtain multiple pre-simulated flow data queues. Each pre-simulated flow data queue corresponds to a pre-simulated water replenishment flow queue, and each pre-simulated flow data queue includes multiple second flow arrays, each representing the flow of multiple river segments at a predetermined time node. Next, for each pre-simulated water replenishment flow queue, the pre-simulated flow queue and its corresponding pre-simulated flow data queue are substituted into an objective function equation. The output of the objective function equation is used as the target state value of the pre-simulated water replenishment flow queue, where the objective function equation expresses the degree to which the total water replenishment and the flow of multiple river segments meet ecological needs in the future. Finally, each pre-simulated water replenishment flow queue is adjusted based on the multiple target state values.

[0072] This invention scientifically divides river segments based on river topology maps and combines multi-condition sample data to fit and optimize the river segment flow model. It can accurately simulate the flow changes of each river segment at each time node under different water replenishment schemes, providing reliable data support for the evaluation of water replenishment schemes.

[0073] This invention quantifies the merits of different schemes through an objective function, takes into account the ecological flow demand and water resource input of each river section, and iteratively adjusts the water replenishment queue by combining historical and current best schemes, gradually approaching the optimal water replenishment scheme and achieving efficient utilization of water resources.

[0074] The model parameters of this invention can be adjusted according to actual scenarios such as river section ecological needs, hydrological accuracy, and water resource constraints. The samples cover different seasons and hydrological conditions, adapting to the water replenishment simulation and optimization needs of various river basins. The process is standardized and can be implemented.

[0075] This invention clarifies the weight of ecologically sensitive river sections, prioritizes ensuring that ecological flow meets standards, and controls the total water replenishment volume through the weight of water replenishment flow, thereby achieving coordinated development of ecological protection and rational allocation of water resources.

[0076] It should be understood that the sequence number of each step in the above embodiments does not imply 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.

[0077] The following are embodiments of the apparatus of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0078] Figure 3 This is a functional block diagram of the river and lake ecological water replenishment determination device provided in the embodiments of the present invention, with reference to... Figure 3 The river and lake ecological water replenishment determination device includes: a river section status acquisition module 301, a river section flow prediction module 302, a target status determination module 303, and a water replenishment volume adjustment module 304, wherein: The river segment status acquisition module 301 is used to acquire a first flow array, wherein the first flow array includes multiple first flows, each first flow corresponds to a river segment, and the river segment is obtained based on the segmentation of the river topology map; The river section flow prediction module 302 is used to substitute multiple prediction water replenishment flow queues and the first flow array into the flow prediction model to obtain multiple prediction flow data queues. Each prediction flow data queue corresponds to a prediction water replenishment flow queue. The prediction flow data queue includes multiple second flow arrays, and the second flow arrays include flow characteristics of multiple river sections at predetermined time nodes. The target state determination module 303 is used to, for each pre-simulated water replenishment flow queue, substitute the pre-simulated water replenishment flow queue and the corresponding pre-simulated flow data queue into the objective function equation, and use the output of the objective function equation as the target state value of the pre-simulated water replenishment flow queue, wherein the objective function equation expresses the degree to which the total water replenishment and the flow of multiple river sections meet the ecological needs in the future period. The water replenishment adjustment module 304 is used to adjust the water replenishment flow queue for each pre-simulation based on multiple target status values.

[0079] Figure 4 This is a functional block diagram of the electronic device provided in an embodiment of the present invention. For example... Figure 4 As shown, the electronic device 4 in this embodiment includes a processor 400 and a memory 401, wherein the memory 401 stores a computer program 402 that can run on the processor 400. When the processor 400 executes the computer program 402, it implements the steps in the above-described methods and embodiments for determining river and lake ecological water replenishment, for example... Figure 1 Steps 101 to 104 are shown.

[0080] For example, the computer program 402 may be divided into one or more modules / units, which are stored in the memory 401 and executed by the processor 400 to complete the present invention.

[0081] The electronic device 4 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. The electronic device 4 may include, but is not limited to, a processor 400 and a memory 401. Those skilled in the art will understand that... Figure 4 This is merely an example of electronic device 4 and does not constitute a limitation on electronic device 4. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 4 may also include input / output devices, network access devices, buses, etc.

[0082] The processor 400 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0083] The memory 401 can be an internal storage unit of the electronic device 4, such as a hard disk or memory. The memory 401 can also be an external storage device of the electronic device 4, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 401 can include both internal and external storage units of the electronic device 4. The memory 401 is used to store the computer program 402 and other programs and data required by the electronic device 4. The memory 401 can also be used to temporarily store data that has been output or will be output.

[0084] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments 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 as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the aforementioned method embodiments, and will not be repeated here.

[0085] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0086] Those skilled in the art will recognize that the units and algorithm steps of the various examples 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 implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0087] In the embodiments provided by this invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0088] The units described as separate components may or may not be physically separate. 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 the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0089] Furthermore, the functional units in the various embodiments of the present invention 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 as a software functional unit.

[0090] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various methods and apparatus embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0091] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for determining ecological water replenishment for rivers and lakes, characterized in that, include: Obtain the first flow array, which includes multiple first flows, each of which corresponds to a river segment. The river segments are obtained based on the segmentation of the river topology map. Multiple pre-simulated water replenishment flow queues are substituted into the flow simulation model along with the first flow array to obtain multiple pre-simulated flow data queues. Each pre-simulated flow data queue corresponds to a pre-simulated water replenishment flow queue. The pre-simulated flow data queue includes multiple second flow arrays, which represent the flow of multiple river sections at predetermined time nodes. For each pre-simulated water replenishment flow queue, the pre-simulated water replenishment flow queue and the corresponding pre-simulated flow data queue are substituted into the objective function equation, and the output of the objective function equation is used as the target state value of the pre-simulated water replenishment flow queue. The objective function equation expresses the degree to which the total water replenishment and the flow of multiple river segments meet the ecological needs in the future period. Adjust each pre-simulation water replenishment flow queue based on multiple target state values.

2. The method for determining ecological water replenishment for rivers and lakes according to claim 1, characterized in that, The flow prediction model includes multiple river segment flow models. The step of substituting multiple predicted water replenishment flow queues and the first flow array into the flow prediction model to obtain multiple predicted flow data queues includes: For each pre-simulation water replenishment flow queue, perform the following steps: The water replenishment flow is taken out sequentially from the pre-simulated water replenishment flow queue and used as the water replenishment flow for the source river section; For each river segment except the source segment, the flow of the upstream segment is extracted from the first flow array as the replenishment flow of the river segment; For each river segment, the flow rate of this river segment extracted from the first flow array and the water replenishment flow rate are substituted into the river segment flow model to obtain the simulated flow rate; Multiple simulated traffic flows are combined into a second traffic array; Add the second flow array to the pre-simulated flow data queue; If the traversal of the pre-simulated water replenishment flow queue is not completed, the second flow array is used as the first flow array, and the process jumps to the step of taking out the water replenishment flow from the pre-simulated water replenishment flow queue in sequence as the water replenishment flow of the source river section.

3. The method for determining ecological water replenishment for rivers and lakes according to claim 2, characterized in that, The flow prediction model includes multiple river segment flow models, which are constructed based on multiple sample flows, including: Multiple sample datasets are obtained. Each sample dataset includes the upstream river flow and the current river flow. Each sample dataset corresponds to a label flow of the current river flow. The time point corresponding to the label flow of the current river flow is later than the time point corresponding to the current river flow in the sample dataset. Substitute the multiple sample datasets into the first fitting equation to obtain multiple outputs of the fitting equation, where each output corresponds to a sample dataset; Based on the multiple outputs and the labeled flow rates of the river segment corresponding to the multiple sample datasets, the fitting deviation of the fitting equation is determined; If the fitting deviation is greater than the deviation threshold, then the multiple parameters of the fitting equation are adjusted according to the fitting deviation, and the process jumps to the step of substituting the multiple sample datasets into the first fitting equation to obtain the multiple outputs of the fitting equation. Otherwise, the fitted equation is used as the river segment flow model.

4. The method for determining river and lake ecological water replenishment according to claim 3, characterized in that, The first fitting equation is: In the formula, For the first River section Traffic at specific time points The weighting coefficients for the exponent frequency. For the first River section Traffic at specific time points For the first River section Traffic at specific time points As the first coefficient, As the second coefficient, The intercept coefficient, This represents the maximum exponential number.

5. The method for determining ecological water replenishment for rivers and lakes according to claim 1, characterized in that, The objective function equation is: In the formula, For the first The flow weight of each river section For the first River section Traffic at specific time points For the first Ecological demand flow of the river section For water replenishment flow weighting, This represents the total number of time points. The total number of river sections. The corresponding water replenishment flow queue in the pre-rehearsal Traffic at specific time points.

6. The method for determining river and lake ecological water replenishment according to any one of claims 1-5, characterized in that, The adjustment of each pre-simulation water replenishment flow queue based on multiple target state values ​​includes: Multiple target status queues are obtained, where each target status queue corresponds to a pre-simulation water replenishment flow queue, and the target status queue includes the target status values ​​that have been adjusted in the pre-simulation water replenishment flow queue in previous iterations. For each target state value, add it to the target state queue corresponding to the pre-simulated water replenishment flow queue; For each target state queue, find the minimum value from the target state queue as the historical best value, and take the pre-simulated water replenishment flow queue corresponding to the historical best value as the historical best pre-simulated water replenishment flow queue. Find the minimum value among the multiple target state values ​​and take it as the current optimal value. Then, take the pre-simulation water replenishment flow queue corresponding to the current optimal value as the current optimal pre-simulation water replenishment flow queue. For each pre-simulated water replenishment flow queue, adjustments are made based on the historical best pre-simulated water replenishment flow queue and the current best pre-simulated water replenishment flow queue.

7. The method for determining ecological water replenishment for rivers and lakes according to claim 6, characterized in that, The adjustment of each pre-simulated water replenishment flow queue based on the historical best pre-simulated water replenishment flow queue and the current best pre-simulated water replenishment flow queue includes: For each pre-simulated water replenishment flow queue, adjustments are made based on the first formula, the historical best pre-simulated water replenishment flow queue, and the current best pre-simulated water replenishment flow queue, wherein the first formula is: In the formula, For the first The corresponding pre-reaction water replenishment flow queue after the second adjustment Traffic at specific time points For the first The corresponding pre-reaction water replenishment flow queue after the second adjustment Traffic at specific time points The corresponding historical optimal pre-simulation water replenishment flow queue Traffic at specific time points The corresponding water replenishment flow rate in the current optimal pre-simulation queue Traffic at specific time points For the first The target state value of the pre-simulated water replenishment flow queue after the second adjustment. This is the best historical value. This is the current optimal value. The first adjustment rate coefficient, This is the second adjustment rate coefficient. This is the basic disturbance compensation amount.

8. A device for determining ecological water replenishment in rivers and lakes, characterized in that, For implementing the method for determining river and lake ecological water replenishment as described in any one of claims 1-7, the river and lake ecological water replenishment determination device comprises: The river segment status acquisition module is used to acquire the first flow array, which includes multiple first flows, each of which corresponds to a river segment. The river segments are obtained based on the segmentation of the river topology map. The river section flow prediction module is used to substitute multiple prediction water replenishment flow queues and the first flow array into the flow prediction model to obtain multiple prediction flow data queues. Each prediction flow data queue corresponds to a prediction water replenishment flow queue. The prediction flow data queue includes multiple second flow arrays, and the second flow arrays include flow characteristics of multiple river sections at predetermined time nodes. The target state determination module is used to, for each pre-simulated water replenishment flow queue, substitute the pre-simulated water replenishment flow queue and the corresponding pre-simulated flow data queue into the objective function equation, and use the output of the objective function equation as the target state value of the pre-simulated water replenishment flow queue. The objective function equation expresses the degree to which the total water replenishment and the flow of multiple river segments meet the ecological needs in the future period. as well as, The water replenishment adjustment module is used to adjust the water replenishment flow rate of each pre-simulation queue based on multiple target status values.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7 above.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7 above.

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