River and lake system ecological scheduling method coupled with watershed hydrological response

Abstract

A river-lake system ecological scheduling method coupled with basin hydrological response belongs to the field of reservoir ecological scheduling, and comprises the following steps: firstly, selecting a research area to represent a hydrological station, and drawing a basin hydrological evolution topological graph; secondly, constructing a watershed hydrological response model step by step, and simulating a response process of lake hydrological situation to upstream reservoir drainage; thirdly, putting forward an ecological evaluation index, and quantifying lake hydrological-ecological response; 4, constructing a multi-objective optimization scheduling model of the river-lake system; 5, optimizing the multi-objective optimization scheduling model of the river-lake system; and finally, based on a fuzzy optimization method, recommending an optimal reservoir scheduling rule conforming to decision preference. According to the method, the beneficial benefits such as power generation and water supply of the reservoir are guaranteed, the adverse effect of concentrated water storage of the upstream reservoir on the ecology of the downstream lake can be weakened to the maximum extent, the reservoir scheduling rule with the maximum comprehensive benefits is recommended, and scientific scheduling basis and decision support are provided for green development of a river-lake system.

Description

Technical Field

[0001] The invention belongs to the field of reservoir ecological regulation, and relates to an ecological regulation method for a river-lake system coupled with a basin hydrological response. Background Art

[0002] Lakes are an important part of the world's freshwater resources and play an important role in runoff regulation, flood control safety, agricultural irrigation, regional ecology, etc. However, in order to improve the efficiency of water resource utilization, many water conservancy projects have been planned and built in major river basins in recent years. Large-scale and concentrated water storage has significantly reduced the amount of water discharged from reservoirs during the water storage period, resulting in a drop in lake water levels, an early dry season, and frequent drought events, which has further caused the deterioration of the lake's ecological environment, such as a decrease in biodiversity and a weakening of ecological regulation functions.

[0003] The optimization of reservoir scheduling schemes is crucial to improving the adverse effects of lake ecology and promoting the sustainable development of river and lake systems. In recent years, scholars have increasingly incorporated ecological water demand into scheduling targets and recommended optimized scheduling processes or scheduling rules for the operation and management of reservoirs. For example, He Zhongzheng et al. (A reservoir power generation optimization scheduling method that takes into account the spawning protection of the four major carps [P]. Jiangxi Province: CN202211410932.4, 2023-04-14.) disclosed a reservoir power generation optimization scheduling method that takes into account the spawning protection of the four major carps. The continuous flow increase and continuous days required for the spawning protection of the four major carps are used as the reservoir discharge flow constraints, and a reservoir power generation optimization scheduling model is constructed to optimize the optimal scheduling process of reservoir power generation that takes into account the spawning protection of the four major carps. Li Xinan et al. (Optimization method of water supply-power generation-ecology multi-objective scheduling diagram based on ecological flow [P]. Hubei Province: CN201911080419.1, 2020-02-28.) disclosed a water supply-power generation-ecology multi-objective scheduling diagram optimization method based on ecological flow, which takes the water shortage and overflow of the reservoir discharge flow to the ecological flow threshold of the downstream river as the ecological scheduling target, optimizes the water supply scheduling rules of the reservoir, and coordinates the multiple objectives of the reservoir such as water supply, ecology and power generation.

[0004] However, most of the existing technologies are developed around the ecological needs in the reservoir area or downstream rivers, and the degree of satisfaction of their ecological goals can be directly deduced from the water level or flow of the reservoir. However, the hydrological evolution between reservoirs and lakes is relatively complex, and is affected by multiple factors such as river topography and river-lake water exchange. The lake ecological goals cannot be directly calculated by the reservoir discharge process. This means that the scheduling needs of considering both the lake ecological goals and the reservoir benefit goals cannot be met based solely on the traditional optimization model. On this basis, it is necessary to further construct and couple the basin hydrological response model to simulate the complex hydraulic relationship of the river-lake system, so as to realize the calculation and optimization of the ecological goals. The coupling of the basin hydrological response model significantly increases the complexity and modeling difficulty of the multi-objective optimization scheduling model, and puts forward higher requirements for the multi-objective optimization scheduling of the river-lake system and the analysis of the high-dimensional nonlinear competitive and synergistic relationship between the goals. Summary of the invention

[0005] In response to the problems existing in the prior art, the present invention provides an ecological scheduling method for river-lake systems coupled with basin hydrological responses. While ensuring the benefits of reservoir power generation, water supply, etc., it minimizes the adverse ecological effects of concentrated water storage in upstream reservoirs on downstream lakes, recommends reservoir scheduling rules that maximize comprehensive benefits, and provides scientific scheduling basis and decision-making support for the green development of river-lake systems.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for ecological regulation of river-lake system coupled with basin hydrological response includes the following steps:

[0008] Step 1: Select representative hydrological stations in the study area and draw a topological map of the basin hydrological evolution;

[0009] Step 2: construct a watershed hydrological response model step by step to simulate the response of the lake hydrological regime to the discharge of the upstream reservoir;

[0010] Step 3, propose ecological assessment indicators to quantify the lake hydrological-ecological response;

[0011] Step 4: construct a multi-objective optimization scheduling model for river and lake systems;

[0012] Step 5, optimizing the multi-objective optimization scheduling model of the river-lake system;

[0013] Step 6: Based on the fuzzy optimization method, the optimal reservoir operation rules that meet the decision-making preferences are recommended.

[0014] Furthermore, the specific implementation of step 1 is as follows:

[0015] Step 1.1, collect basin information and analyze characteristics. Collect basin geographic information based on basin topographic maps and river system maps, clarify the distribution of basin water systems, river connection relationships, and water flow directions and paths, analyze the confluence and diversion characteristics of rivers in the study area, the exchange characteristics of river and lake water volume, the inflow and outflow characteristics of lakes, and the seasonal changes in lake morphology.

[0016] Step 1.2, select representative hydrological stations in the basin. Based on the hydrological station network that has been built in the basin, select hydrological stations with long-term, continuous and consistent historical measured data as representative stations for the subsequent construction of the basin hydrological response model. The selection of representative stations should follow the following principles:

[0017] Step 1.2.1, Reservoir representative station: A reservoir outflow station should be set up at the reservoir dam site;

[0018] Step 1.2.2, River representative station: At least one representative station should be selected for each main and tributary river. Specifically, in river sections where tributaries converge or diverge, representative stations should be set up both upstream and downstream of the intersection; in river sections where no tributaries converge or diverge, generally one representative station is sufficient. In cases where the river terrain is complex, a small number of representative stations can be added, but the geographical locations of the stations should not be too close;

[0019] Step 1.2.3, Lake representative station: At least one representative station should be selected within the lake area, and the specific number is determined by the spatial hydrological response characteristics within the lake. If there is no obvious difference in the spatial hydrological response within the lake, that is, the lake water level change process at different spatial locations is almost the same, then select one lake representative station; if there is a significant difference in the spatial hydrological response within the lake, that is, the lake water level height and response time at different spatial locations are inconsistent, then divide the lake into multiple lake areas based on its topographic characteristics and hydrological response characteristics, and set up a representative station in each lake area.

[0020] Step 1.3, draw a topological map of the hydrological evolution of the basin. Generalize the water system structure of the basin, take the representative stations selected in step 1.2 as nodes, use straight lines to represent the hydraulic connection between nodes, and use arrows to indicate the flow direction; use rectangles to mark the boundaries of lakes, and indicate the names of reservoirs and representative stations in the study area, so as to form a topological map of the hydrological evolution of the basin that can accurately reflect the temporal and spatial relationship between reservoirs, rivers and lakes.

[0021] Furthermore, the specific implementation of step 2 is as follows:

[0022] Step 2.1, decompose the study area and set up the hydrological response sub-model step by step. Based on the basin hydrological evolution topology map drawn in step 1.3, decompose the study area, set up the hydrological response sub-model for each group of adjacent representative stations, and quantify the basin hydrological response step by step.

[0023] Step 2.1.1, for the representative station of the reservoir and the representative station of the river, the hydrological response submodel takes the hydrological characteristics of the upstream representative station in the adjacent representative station as input variables and the hydrological characteristics of the downstream representative station as output variables, and sequentially constructs the hydrological response submodel through the two steps of determining the function type and optimizing the parameter value. The hydrological characteristics of each representative station can be selected from the water level, water depth, flow or water volume characteristics of the representative station.

[0024] Step 2.1.2, for lake representative stations, when there is only one lake representative station in the study area, the hydrological characteristics of the representative station of the river flowing into the lake are used as input variables and the hydrological characteristics of the lake representative station are used as output variables to construct a lake hydrological response sub-model to quantify the response of the lake hydrological situation to the runoff into the lake. When there are multiple lake representative stations in the study area, one of the lake representative stations is first selected to construct a hydrological response sub-model with the representative station of the river flowing into the lake; then the hydrological characteristics of the selected lake representative station are used as input and the hydrological characteristics of other lake representative stations are used as output to construct a hydrological response sub-model to quantify the hydrological correlation between multiple lake areas within the lake.

[0025] Step 2.2, determine the function type of the hydrological response submodel.

[0026] Step 2.2.1, candidate function types include but are not limited to linear functions, polynomial functions, multivariate polynomial functions or piecewise functions.

[0027] Step 2.2.2: Use the k-fold cross-validation method to train and test all candidate function types. The historical measured data of hydrological characteristics of the selected representative station are used as the data set, which is evenly divided into k subsets. Each time, one subset is selected as the test set, and the remaining k-1 subsets are used as the training set. Each candidate function type is trained and tested.

[0028] Step 2.2.3, evaluate the accuracy and optimize the candidate function types. Select the Pearson correlation coefficient CC, root mean square error RMSE and relative deviation RB as statistical indicators, and quantify the simulation accuracy of each candidate function type with the average value of k training tests. Select the function type with the best simulation accuracy for the hydrological response submodel.

[0029] Step 2.3, optimize the parameter values ​​of the hydrological response sub-model. Use all the data sets in step 2.2.2 to train the function type selected in step 2.2.3 and optimize the parameter values ​​of the hydrological response sub-model.

[0030] Step 2.4, integrate the hydrological response sub-models to form a complete watershed hydrological response model.

[0031] Based on the function type determined in step 2.2 and the parameter values ​​optimized in step 2.3, the hydrological response sub-model structure is determined, and the hierarchically constructed hydrological response sub-models are integrated into a complete watershed hydrological response model.

[0032] When applying the basin hydrological response model, the hydrological response sub-models are applied step by step from upstream to downstream, and the output of the upstream sub-model is used as the input data of the downstream sub-model to simulate the lake water level at each time period. Discharge to upstream reservoirs and interval inflow The step-by-step dynamic response of the process can be characterized as:

[0033] (1)

[0034] Furthermore, the specific implementation of step 3 is as follows:

[0035] The basin hydrological response model can simulate the dynamic response process of lake water level. On this basis, step 3 quantifies the ecological benefits of the lake at different water levels from the two aspects of ecological satisfaction and ecological water shortage, namely the hydrological-ecological response of the lake, based on the ecological water demand process of the lake.

[0036] Step 3.1, quantify the ecological satisfaction of the lake.

[0037] The lake ecological satisfaction index is set to measure whether the water level of each lake area in each period can meet the ecological water level demand; then the ecological satisfaction of each lake area is weighted according to the importance weight of the lake area to obtain the ecological guarantee degree of the lake in each period. The formula is as follows:

[0038] (2)

[0039] (3)

[0040] in, It represents the ecological satisfaction of the lake in period t, which is the weighted average of the ecological satisfaction of each lake area. Indicates the ecological satisfaction of the i-th lake area in period t, and takes a value of 0 or 1. When the simulated water level LV of the representative station of the i-th lake area in the period i,t Not less than ecological demand D i,t When it is believed that the lake area meets the ecological needs, W i,t is 1, otherwise it is 0. represents the importance weight of lake area i, determined based on expert experience, N zone Indicates the number of partitions contained in the lake, satisfying and constraints.

[0041] Step 3.2, quantify the degree of lake ecological water shortage.

[0042] The square of the ratio of the lake ecological water level to the simulated water level is used as an indicator of ecological water shortage to measure the degree of ecological water shortage in each lake area during the period. If the lake area is not short of water, the indicator value is between (0,1]; on the contrary, if the lake area is short of water, the indicator is greater than 1, and the closer the value is to positive infinity, the lower the simulated water level in the period, and the more serious the water shortage. The formula is as follows:

[0043] (4)

[0044] (5)

[0045] in, It represents the ecological water shortage degree of the lake in period t, which is the weighted average of the ecological water shortage degrees of each lake area. It represents the degree of ecological water shortage in the ith lake area in period t, and its value range is (0, +∞).

[0046] Furthermore, the specific implementation of step 4 is as follows:

[0047] Step 4.1, reservoir optimization scheduling diagram and decision variable setting.

[0048] Based on the conventional reservoir dispatching rules, the reservoir optimization dispatching diagram in the multi-objective optimization dispatching is set up in the form of Figure 2 The reservoir optimization dispatching diagram includes three dispatching lines, namely, the output reduction line, the output guarantee line and the output increase line. The three output lines divide the dispatching interval into four output areas, namely, the output reduction area, the output guarantee area, the output increase area 1 and the output increase area 2. The output coefficients of each output area are , , and , satisfying the constraints When reservoir power generation is dispatched based on the dispatch diagram, the output of each period is determined by the output area where the initial water level of the period is located, and the output is equal to the product of the output coefficient and the guaranteed output.

[0049] Therefore, the reservoir optimization dispatching diagram includes two types of decision variables (determined by optimization in step 5), namely, the water level variable in each dispatching period that determines the position of the output line, and the output coefficient variable that determines the output size in each period.

[0050] Step 4.2, set the objective function. The dispatching objectives include lake ecological objectives and reservoir benefit objectives. Among them, the lake ecological objectives are the objectives of maximizing the lake ecological satisfaction and minimizing the lake ecological water shortage, and the reservoir benefit objectives are the dimensionless objectives of maximizing the reservoir power generation and maximizing the water storage at the end of the flood season. The definitions and formulas of each objective are as follows:

[0051] Step 4.2.1, the goal of maximizing the degree of lake ecological satisfaction. In order to maximize the degree of lake ecological satisfaction, the degree of lake ecological satisfaction in each time period in step 3.1 is weighted. The importance weight of the time period is allocated according to the ecological status of the basin and the basin scheduling needs. Specifically, higher weights should be given to key time periods where ecological water shortages are more frequent, more severe, and scheduling needs are more concerned; and for time periods that can better meet ecological needs in the current situation, the importance weights should be appropriately reduced, and can even be set to 0. The formula is as follows:

[0052] (6)

[0053] in, is the weighted ecological satisfaction degree of the lake in each dispatching period, and They are the overall ecological satisfaction of the lake in period t and the ecological satisfaction of the i-th lake area. is the importance weight of the time period; N period is the number of scheduling periods, satisfying and . is the importance weight of lake region i, N zone is the number of lake partitions that satisfy and .

[0054] Step 4.2.2, objective of minimizing lake ecological water shortage: weight the lake ecological water shortage index for each time period in step 3.2.

[0055] (7)

[0056] in, is the weighted ecological water shortage degree of the lake in each dispatching period, and They are the overall ecological water shortage degree of the lake and the ecological water shortage degree of the i-th lake area in period t respectively.

[0057] Step 4.2.3, the goal of maximizing reservoir power generation is to maximize the average power generation over many years, and make the goal dimensionless based on the average annual power generation of the initial design or historical data.

[0058] (8)

[0059] in, is the dimensionless average power generation of the reservoir over many years; N output To contribute to the protection of the reservoir, is the duration of the scheduling period, is the output coefficient of the time period, which is determined by the output area where the initial water level of the time period is located, and its value is , , or ; is the average annual power generation, N year is the scheduling year number.

[0060] Step 4.2.4, maximizing the reservoir's end-flood water storage: The multi-year average end-flood water storage of the reservoir is the largest, represented by the multi-year average storage capacity at the end of the reservoir's water storage period.

[0061] (9)

[0062] in, V is the dimensionless multi-year average flood season water storage capacity; n is the reservoir capacity at the end of the storage period in the nth year, V max is the total storage capacity of the reservoir.

[0063] Step 4.3, set constraints. The constraints of the multi-objective optimization scheduling model include: water balance constraints, reservoir water level constraints, reservoir discharge flow constraints, hydropower station output constraints, and variable non-negative constraints.

[0064] Furthermore, the specific implementation of step 5 is as follows:

[0065] The optimization and solution of the multi-objective optimization scheduling model follows the general idea of ​​"scheduling process simulation-scheduling rule optimization" and is carried out based on the optimization algorithm.

[0066] Step 5.1, dispatching process simulation. Based on the decision variable values, determine the current reservoir optimization dispatching diagram, take the reservoir runoff process as input, perform water balance calculation, and deduce the reservoir water level, discharge flow and output process. Input the reservoir discharge process into the basin hydrological response model constructed in step 2, deduce the spatial water level response process of the downstream lake, and then evaluate the lake ecological level based on the indicators proposed in step 3, thereby deducing the lake ecological goals and reservoir benefit goals under the current dispatching diagram, and return them to the optimization stage.

[0067] Step 5.2, optimization of dispatching rules. Generate an initial solution set based on the selected optimization algorithm; evaluate and screen the solution set based on the target value calculated in the dispatching process simulation phase in step 5.1; gradually improve the solution set through iterative optimization until the number of iterations is equal to the preset threshold or the target value variation is less than the preset threshold; finally output the preferred approximate Pareto solution set, as well as the corresponding reservoir dispatching process and lake response process. The approximate Pareto solution set includes one or more feasible solutions, each of which corresponds to a set of values ​​of the decision variables described in step 4.1, and a reservoir optimization dispatching diagram corresponding to the current feasible solution can be drawn based on it.

[0068] Furthermore, the specific implementation of step 6 is as follows:

[0069] Step 6.1, calculate the improvement of the optimized dispatching diagram compared with the conventional dispatching. Statistically calculate the optimal and average values ​​of the dispatching objectives and important dispatching characteristics (such as lake water level, reservoir power generation, etc.) of all feasible solutions in the approximate Pareto solution set. Calculate the relative percentage of improvement of each dispatching objective compared with the conventional reservoir dispatching.

[0070] Step 6.2, calculate the relative membership of the scheduling target of the Pareto solution set. The value ranges of various scheduling targets are different, so they are standardized respectively, and the relative membership of the scheduling target of the Pareto solution set is obtained using formula (10).

[0071] (10)

[0072] in, and are the target value and relative membership of the ith scheduling objective of the jth feasible solution, and are the minimum and maximum values ​​of the i-th scheduling objective respectively.

[0073] Step 6.3, calculate the dispatch target weights based on decision preferences. Based on decision preferences, compare the importance of each pair of targets, use "equally important, slightly important, slightly important, relatively important, obviously important, significantly important, very important, very important, extremely important, extremely important, incomparable" as fuzzy tone operators, determine the fuzzy scale value, and describe the relative importance of the targets. Among them, the fuzzy scale values ​​of equally important and incomparable are 0.5 and 1.0 respectively, and the fuzzy scale values ​​of other fuzzy tones are calculated using linear interpolation. Based on the assigned fuzzy tone operator, substitute it into formula (11) to obtain the importance of different targets, and normalize it to obtain the weight of each dispatch target. .

[0074] (11)

[0075] in, Indicates the importance of all scheduling objectives; , , and They represent the importance of goals 1 to 4, respectively, where goal 1 is the most important goal considered by the decision maker; , and They represent the fuzzy scale values ​​of the second, third, and fourth objectives compared to objective 1, respectively, which are determined by the fuzzy mood operator determined by the decision maker.

[0076] Step 6.4, calculate the relative superiority and recommend the optimal scheduling diagram that meets the decision preference. Assume that the relative superiority of the best solution and the worst solution is and , then the relative superiority of the jth feasible solution to the optimal solution is:

[0077] (12)

[0078] in, Represents the relative superiority of the jth feasible solution; represents the weight of the kth scheduling target calculated in step 6.3; represents the relative membership of the kth scheduling objective of the jth feasible solution calculated in step 6.2; and They respectively represent the optimal relative membership and the worst relative membership of the kth scheduling objective in all feasible solutions.

[0079] The relative superiority of all feasible solutions is calculated, and the solution set is sorted based on this. The feasible solution with the largest relative superiority is taken as the optimal solution under this decision preference, and the corresponding reservoir optimization scheduling diagram and scheduling process are recommended to the reservoir.

[0080] Compared with the prior art, the present invention has the following beneficial effects:

[0081] Based on the traditional multi-objective optimization scheduling of reservoirs, the present invention adds the consideration of the ecological objectives of downstream lakes. By constructing a basin hydrological response model, the complex hydrological and ecological response of downstream lakes to the upstream reservoir scheduling process is simulated, and it is coupled to the multi-objective optimization scheduling model of the river-lake system to achieve the joint optimization of lake ecological objectives and reservoir benefit objectives. While ensuring the benefits of the upstream reservoir, the adverse effects of reservoir water storage on the ecology of downstream lakes can be alleviated as much as possible. The fuzzy optimization method is used to recommend optimal scheduling rules under different decision preferences, which provides a model basis for analyzing the benefit conversion mechanism between lake ecology and reservoir benefits, and provides scientific technical support and decision-making basis for the green development of river-lake systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 A flow chart of a river-lake system ecological dispatching method coupled with basin hydrological response provided by the present invention;

[0083] Figure 2 Schematic diagram of the optimal operation rule for the reservoir;

[0084] Figure 3 It is a topological diagram of the hydrological evolution from the Three Gorges Reservoir to the Dongting Lake Basin in the embodiment;

[0085] Figure 4 It is a scatter plot of the approximate Pareto solution of the multi-objective optimization scheduling model in the embodiment; Figure 4 (a) is the lake ecological water shortage degree target and ecological satisfaction degree target of the approximate Pareto solution set; Figure 4 (b) is the reservoir power generation target and flood season water storage target of the approximate Pareto solution set;

[0086] Figure 5 This is the optimized dispatching diagram of the Three Gorges Reservoir recommended based on the decision preference in the embodiment. DETAILED DESCRIPTION

[0087] The present invention is further described below in conjunction with specific embodiments.

[0088] The present invention selects the Yangtze River Basin from the Three Gorges Reservoir to the Dongting Lake Basin to develop an ecological dispatching method for the river-lake system coupled with the hydrological response of the basin. The embodiment focuses on the adverse ecological impact of the concentrated water storage of the upper Yangtze River reservoir group during the water storage period on the downstream Dongting Lake, with the goal of improving the hydrological ecology of Dongting Lake during the water storage period, taking into account the benefits of the Three Gorges Reservoir, optimizing the power generation dispatching diagram of the Three Gorges Reservoir, and providing a scientific basis for the sustainable development of the river-lake system. The specific implementation method is described in detail in combination with the technical scheme and the accompanying drawings, which specifically includes the following steps:

[0089] Step 1: Select representative hydrological stations in the study area and draw a topological map of the basin’s hydrological evolution.

[0090] Step 1.1, collect basin information and analyze characteristics. Based on the topographic map and water system map of the Yangtze River Basin from the Three Gorges Reservoir to Dongting Lake, clarify the distribution of the basin water system, river connection, and water flow direction and path. Specifically:

[0091] The Three Gorges Reservoir is located in the upper reaches of the Yangtze River. Its discharge evolves from west to east along the main channel of the Yangtze River and is diverted in the Jingjiang River Basin. Part of the water flows into Dongting Lake through the Sankou area, and the rest of the water continues to evolve downstream along the main channel of the Yangtze River.

[0092] Dongting Lake is located in the middle reaches of the Yangtze River. In addition to the main stream of the Yangtze River in the Sankou area, the runoff into the lake also includes the four tributaries of the Sishui area (Xiangjiang River, Zijiang River, Yuanjiang River and Lishui River), which then flow out near the Chenglingji hydrological station and merge into the main stream of the Yangtze River. Based on geographical characteristics, the lake area can be divided into three lake areas: East Dongting Lake, West Dongting Lake and South Dongting Lake. There are obvious differences in the hydrological response characteristics of different lake areas.

[0093] Step 1.2, select representative hydrological stations in the basin. Based on the hydrological station network that has been built in the basin, select hydrological stations with long-term, continuous and consistent historical measured data as representative stations for the subsequent construction of the basin hydrological response model. Specifically include:

[0094] Step 1.2.1, Reservoir representative station: Set up a reservoir outflow station at the dam site of the Three Gorges Reservoir;

[0095] Step 1.2.2, river representative stations: set up Zhicheng Station and Shashi Station in the Jingjiang area of ​​the Yangtze River mainstream, Xinjiangkou, Shadaoguan, Mituo Temple, Kangjiagang and Guanjiapu Stations on the five tributaries in the Sankou area, and Shimen, Taoyuan, Taojiang and Xiangtan Stations on the confluence of the four tributaries in the Sishui area;

[0096] Step 1.2.3, lake area representative stations: Based on the spatial hydrological response characteristics within the lake, representative stations were set up in the three lake areas of Dongting Lake, namely Chenglingji Station in East Dongting Lake, Yangliutan Station in South Dongting Lake, and Nanzui Station in West Dongting Lake.

[0097] Step 1.3, draw a topological map of the hydrological evolution of the basin. Generalize the water system structure of the basin, take the representative stations selected in step 1.2 as nodes, use straight lines to represent the hydraulic connection between nodes, and use arrows to indicate the flow direction; use rectangles to mark the boundaries of lakes, and indicate the names of reservoirs and representative stations in the study area, so as to form a topological map of the hydrological evolution of the basin that can accurately reflect the temporal and spatial relationship between reservoirs, rivers and lakes. Figure 3 shown.

[0098] Step 2: construct a watershed hydrological response model step by step to simulate the response process of the lake hydrological situation to the discharge of upstream reservoirs.

[0099] Step 2.1, decompose the study area and set up the hydrological response sub-model step by step. Based on the basin hydrological evolution topology map drawn in step 1.3, decompose the study area, set up the hydrological response sub-model for each group of adjacent representative stations, and quantify the basin hydrological response step by step.

[0100] Step 2.1.1, for the representative station of the reservoir and the representative station of the river, the hydrological response submodel takes the water volume characteristics of the upstream representative station in the adjacent representative station as the input variable and the water volume characteristics of the downstream representative station as the output variable, and sequentially constructs the hydrological response submodel through the two steps of determining the function type and optimizing the parameter value. The hydrological characteristics of each representative station can be selected from the water level, water depth, flow or water volume characteristics of the representative station.

[0101] Step 2.1.2, for the lake representative station, since the study area in the embodiment has 3 lake representative stations, firstly, the Chenglingji representative station of East Dongting Lake is selected, and the water volume characteristics of the river representative stations flowing into the lake (i.e., the 5 representative stations located in the Sankou area and the 4 representative stations located in the Sishui area in step 1.2.2) are used to construct a hydrological response sub-model; then, the water level of Chenglingji station is used as input and the water levels of other lake representative stations (i.e., Yangliutan station of South Dongting Lake and Nanzui station of West Dongting Lake) are used as output to construct a hydrological response sub-model to quantify the hydrological correlation between multiple lake areas within the lake.

[0102] The decomposed hydrological response sub-models of all 10 basins are shown in Table 1.

[0103] Step 2.2, determine the function type of the hydrological response submodel.

[0104] Step 2.2.1, candidate function types include but are not limited to linear functions, polynomial functions, multivariate polynomial functions or piecewise functions.

[0105] Step 2.2.2, use the 5-fold cross-validation method to train and test all candidate function types. The historical measured data of hydrological characteristics of the selected representative stations are used as the data set, which is evenly divided into 5 subsets. Each time, one subset is selected as the test set, and the remaining 4 subsets are used as training sets. Each candidate function type is trained and tested.

[0106] Step 2.2.3, evaluate the accuracy and optimize the candidate function types. Select the Pearson correlation coefficient CC, root mean square error RMSE and relative deviation RB as statistical indicators, and quantify the simulation accuracy of each candidate function type with the average value of five training tests. Select the function type with the best simulation accuracy for the hydrological response submodel.

[0107] Step 2.3, optimize the parameter values ​​of the hydrological response sub-model. Use all the data sets in step 2.2.2 to train the function type selected in step 2.2.3 and optimize the parameter values ​​of the hydrological response sub-model.

[0108] Step 2.4, integrate the hydrological response sub-models to form a complete watershed hydrological response model.

[0109] Based on the function type determined in step 2.2 and the parameter values ​​optimized in step 2.3, the hydrological response sub-model structure is determined, and the hierarchically constructed hydrological response sub-models are integrated into a complete watershed hydrological response model, as shown in Table 1.

[0110] When applying the basin hydrological response model, the hydrological response sub-models are applied step by step from upstream to downstream, and the output of the upstream sub-model is used as the input data of the downstream sub-model to simulate the lake water level at each time period. Discharge to upstream reservoirs and interval inflow The step-by-step dynamic response of the process can be characterized as:

[0111] (1)

[0112] Table 1 Hydrological response model of the Yangtze River Three Gorges-Dongting Lake Basin river and lake system

[0113]

[0114] Step 3: Propose ecological assessment indicators to quantify the lake hydrological-ecological response.

[0115] This embodiment uses the ecological water demand process of Dongting Lake as a reference, and quantifies the ecological benefits of Dongting Lake at different water levels from two aspects: ecological satisfaction and ecological water shortage, namely, the hydrological-ecological response of the lake.

[0116] Step 3.1, quantify the ecological satisfaction of the lake.

[0117] The lake ecological satisfaction index is set to measure whether the water level of each lake area in each period can meet the ecological water level demand; then the ecological satisfaction of each lake area is weighted according to the importance weight of the lake area to obtain the ecological guarantee degree of the lake in each period. The formula is as follows:

[0118] (2)

[0119] (3)

[0120] in, It represents the ecological satisfaction of the lake in period t, which is the weighted average of the ecological satisfaction of each lake area. Indicates the ecological satisfaction of the i-th lake area in period t, and takes a value of 0 or 1. When the simulated water level LV of the representative station of the i-th lake area in the period i,t Not less than ecological demand D i,t When it is believed that the lake area meets the ecological needs, W i,t is 1, otherwise it is 0. The weights of the lake area are 0.5, 0.2 and 0.3 for East Dongting, West Dongting and South Dongting respectively. zone Characterize the three lake areas of Dongting Lake.

[0121] Step 3.2, quantify the degree of lake ecological water shortage.

[0122] The square of the ratio of the lake ecological water level to the simulated water level is used as an indicator of ecological water shortage to measure the degree of ecological water shortage in each lake area during the period. If the lake area is not short of water, the indicator value is between (0,1]; on the contrary, if the lake area is short of water, the indicator is greater than 1, and the closer the value is to positive infinity, the lower the simulated water level in the period, and the more serious the water shortage. The formula is as follows:

[0123] (4)

[0124] (5)

[0125] in, It represents the ecological water shortage degree of the lake in period t, which is the weighted average of the ecological water shortage degrees of each lake area. It represents the degree of ecological water shortage in the ith lake area in period t, and its value range is (0, +∞).

[0126] Step 4: Construct a multi-objective optimization scheduling model for the river-lake system.

[0127] Step 4.1, reservoir optimization scheduling diagram and decision variable setting.

[0128] Based on the conventional reservoir dispatching rules, the reservoir optimization dispatching diagram in the multi-objective optimization dispatching is set up in the form of Figure 2 The reservoir optimization dispatching diagram includes three dispatching lines, namely, the output reduction line, the output guarantee line and the output increase line. The three output lines divide the dispatching interval into four output areas, namely, the output reduction area, the output guarantee area, the output increase area 1 and the output increase area 2. The output coefficients of each output area are , , and , satisfying the constraints When the reservoir power generation is dispatched based on the dispatch diagram, the output of each period is determined by the output area where the initial water level of the period is located, and the output is equal to the product of the output coefficient and the guaranteed output. Referring to the conventional dispatching rules of the Three Gorges Reservoir, the optimized dispatching rules of this embodiment take the ten-day scale, that is, there are 36 periods in a year.

[0129] Therefore, the decision variables of the optimization scheduling diagram of this embodiment include: 108 water level variables of 3 output lines*36 scheduling periods, and 3 output coefficient variables other than the guaranteed output area , and .

[0130] Step 4.2, set the objective function. The dispatching objectives include lake ecological objectives and reservoir benefit objectives. Among them, the lake ecological objectives are the objectives of maximizing the lake ecological satisfaction and minimizing the lake ecological water shortage, and the reservoir benefit objectives are the dimensionless objectives of maximizing the reservoir power generation and maximizing the water storage at the end of the flood season. The definitions and formulas of each objective are as follows:

[0131] Step 4.2.1, the goal of maximizing the degree of lake ecological satisfaction. In order to maximize the degree of lake ecological satisfaction, the degree of lake ecological satisfaction in each time period in step 3.1 is weighted. The importance weight of the time period is allocated according to the ecological status of the basin and the basin scheduling needs. Specifically, higher weights should be given to key time periods where ecological water shortages are more frequent, more severe, and scheduling needs are more concerned; and for time periods that can better meet ecological needs in the current situation, the importance weights should be appropriately reduced, and can even be set to 0. The formula is as follows:

[0132] (6)

[0133] in, is the weighted ecological satisfaction degree of the lake in each dispatching period, and They are the overall ecological satisfaction of the lake in period t and the ecological satisfaction of the i-th lake area. is the importance weight of the time period. Since this embodiment focuses on the ecological response of Dongting Lake during the reservoir impoundment period (September and October), the weight of the first, middle and last three decades of September and October is 1 / (6 decades * 60 years) = 1 / 360, and the weight of the scheduling period of other months is 0; N period The number of optimized scheduling periods is 36 decades*60 years=2160.

[0134] Step 4.2.2, objective of minimizing lake ecological water shortage: weight the lake ecological water shortage index for each time period in step 3.2.

[0135] (7)

[0136] in, is the weighted ecological water shortage degree of the lake in each dispatching period, and They are the overall ecological water shortage degree of the lake and the ecological water shortage degree of the i-th lake area in period t respectively.

[0137] Step 4.2.3, the goal of maximizing reservoir power generation is to maximize the average power generation over many years, and make the goal dimensionless based on the average annual power generation of the initial design or historical data.

[0138] (8)

[0139] in, is the dimensionless average power generation of the reservoir over many years; N output To ensure the output of the Three Gorges Reservoir, 499kW is used. is the duration of the dispatch period, i.e. ten days, is the output coefficient of the time period; is the average annual power generation, the designed annual power generation of the Three Gorges Reservoir is 84.7 billion kWh, N year The total number of years involved in optimized scheduling is 60 years.

[0140] Step 4.2.4, maximizing the reservoir's end-flood water storage: The multi-year average end-flood water storage of the reservoir is the largest, represented by the multi-year average storage capacity at the end of the reservoir's water storage period.

[0141] (9)

[0142] in, V is the dimensionless multi-year average flood season water storage capacity;n is the storage capacity at the end of the water storage period in the nth year. In this embodiment, the storage capacity of the Three Gorges Reservoir on November 1 is used as a representative. max is the total storage capacity of the Three Gorges Reservoir, taking 39.3 billion m 3 .

[0143] Step 4.3, set constraints. The constraints of the multi-objective optimization scheduling model include: water balance constraints, reservoir water level constraints, reservoir discharge flow constraints, hydropower station output constraints, and variable non-negative constraints.

[0144] Step 5: Optimize the multi-objective optimization scheduling model of the river-lake system.

[0145] The optimization and solution of the multi-objective optimization scheduling model follows the general idea of ​​"scheduling process simulation-scheduling rule optimization". This embodiment is based on the epsilon-NSGA-II algorithm.

[0146] Step 5.1, dispatching process simulation. Based on the decision variable values, determine the current reservoir optimization dispatching diagram, take the Three Gorges Reservoir inflow runoff process as input, perform water balance calculation, and deduce the reservoir water level, discharge flow and output process. Input the reservoir discharge process into the basin hydrological response model constructed in step 2, deduce the spatial water level response process of Dongting Lake, and then evaluate the lake ecological level based on the indicators proposed in step 3, thereby deduce the lake ecological goals and reservoir benefit goals under the current dispatching diagram, and return them to the optimization stage.

[0147] Step 5.2, dispatch rule optimization. Generate an initial solution set based on the selected optimization algorithm; evaluate and screen the solution set based on the target value calculated in the dispatch process simulation phase in step 5.1; gradually improve the solution set through iterative optimization until the number of iterations equals the preset threshold; finally output the preferred approximate Pareto solution set, as well as the corresponding reservoir dispatch process and lake response process. Figure 4 (a) shows the lake ecological water shortage degree target and ecological satisfaction degree target of the approximate Pareto solution set preferred by the embodiment, Figure 4 (b) in the figure shows the reservoir power generation target and flood season water storage target of the approximate Pareto solution set.

[0148] Step 6: Based on the fuzzy optimization method, the optimal reservoir operation rules that meet the decision-making preferences are recommended.

[0149] Step 6.1, calculate the improvement capacity of the optimized dispatch diagram compared with the conventional dispatch. Statistically calculate the optimal values ​​and average values ​​of the dispatch objectives and important dispatch characteristics of all feasible solutions in the approximate Pareto solution set. Compared with the conventional dispatch of the reservoir, calculate the relative percentage of improvement of each dispatch objective as shown in Table 2.

[0150] Table 2 Comparison of scheduling objectives and characteristics between optimized scheduling rules and conventional scheduling rules

[0151]

[0152] Step 6.2, calculate the relative membership of the dispatching target of the Pareto solution set. There are differences in the value ranges of various dispatching targets, which are standardized respectively, and the relative membership of the dispatching target of the Pareto solution set is obtained using formula (10). In the embodiment, the lake ecological satisfaction degree target, the reservoir power generation target, and the reservoir and flood season water storage target are the larger the better, and the lake ecological water shortage degree target is the smaller the better.

[0153] (10)

[0154] in, and are the target value and relative membership of the ith scheduling objective of the jth feasible solution, and are the minimum and maximum values ​​of the i-th scheduling objective respectively.

[0155] Step 6.3, calculate the dispatch target weight according to the decision preference. According to the decision preference, the importance of each pair of targets is compared, and "equally important, slightly important, slightly important, relatively important, obviously important, significantly important, very important, very important, extremely important, extremely important, incomparable" is used as the fuzzy mood operator to determine the fuzzy scale value to describe the relative importance of the targets. Among them, the fuzzy scale values ​​of equally important and incomparable are 0.5 and 1.0 respectively, and the fuzzy scale values ​​of other fuzzy tones are calculated using linear interpolation. In this embodiment, the lake ecological satisfaction target is taken as the most important, the same as the lake ecological water shortage target, and significantly more important than the reservoir power generation target and the reservoir flood end water storage target. The fuzzy expected importance of the four targets is (0.5, 0.5, 0.75, 0.75).

[0156] Based on the assigned fuzzy tone operator, we bring it into formula (11) to get the importance of different targets. After normalization, we get the weight of each scheduling target: =(0.375, 0.375, 0125, 0.125).

[0157] (11)

[0158] in, Indicates the importance of all scheduling objectives; , , and They represent the importance of goals 1 to 4, respectively, where goal 1 is the most important goal considered by the decision maker; , and They represent the fuzzy scale values ​​of the second, third, and fourth objectives compared to objective 1, respectively, which are determined by the fuzzy mood operator determined by the decision maker.

[0159] Step 6.4 calculates the relative superiority and recommends the optimal scheduling diagram that meets the decision preference. Assume that the relative superiority of the best and worst solutions are and , then the relative superiority of the jth feasible solution to the optimal solution is:

[0160] (12)

[0161] in, Represents the relative superiority of the jth feasible solution; represents the weight of the kth scheduling target calculated in step 6.3; represents the relative membership of the kth scheduling objective of the jth feasible solution calculated in step 6.2; and They respectively represent the optimal relative membership and the worst relative membership of the kth scheduling objective in all feasible solutions.

[0162] In the embodiment, the maximum value of the relative superiority is 0.830, and the target relative membership of the corresponding feasible solution is (0.8571, 0.7825, 0.8884, 0.8333). The scheduling diagram is as follows: Figure 5 As shown in Figure 1, this is the optimal reservoir operation diagram recommended under this decision preference.

[0163] The above-described embodiments merely express the implementation methods of the present invention, but they cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A method for ecological regulation of river-lake systems coupled with basin hydrological response, characterized in that: The ecological dispatching method of the river-lake system comprises the following steps: Step 1: Select representative hydrological stations in the study area and draw a topological map of the basin hydrological evolution; Step 2: construct a watershed hydrological response model step by step to simulate the response of the lake hydrological regime to the discharge of the upstream reservoir; Step 3, propose ecological assessment indicators to quantify the lake hydrological-ecological response; The dynamic response process of lake water level is simulated by basin hydrological response model. Based on the ecological water demand process of lake, the ecological benefits of lake under different water levels are quantified from two aspects: ecological satisfaction and ecological water shortage, and the hydrological-ecological response of lake is obtained. Step 4: construct a multi-objective optimization scheduling model for river and lake systems; Step 5, optimizing the multi-objective optimization scheduling model of the river-lake system; the optimization and solution of the multi-objective optimization scheduling model follows the overall idea of ​​"scheduling process simulation-scheduling rule optimization"; Step 6: Based on the fuzzy optimization method, the optimal reservoir operation rules that meet the decision-making preferences are recommended; Calculate the improvement capability of the optimized scheduling diagram compared with the conventional scheduling, calculate the relative membership of the scheduling objectives of the Pareto solution set, calculate the relative superiority of the scheduling objective weights based on the decision preference, and recommend the optimal scheduling diagram that meets the decision preference.

2. The ecological dispatching method of river-lake system coupled with basin hydrological response according to claim 1 is characterized in that: The specific implementation of step 1 is as follows: Step 1.1, collect watershed information and analyze characteristics; Step 1.2, select representative hydrological stations in the basin; based on the existing hydrological station network in the basin, select hydrological stations with long-term, continuous and consistent historical measured data as representative stations for the subsequent construction of the basin hydrological response model; Step 1.3, draw a topological map of the hydrological evolution of the basin; generalize the water system structure of the basin, use the representative stations selected in step 1.2 as nodes, use straight lines to represent the hydraulic connection between nodes, and use arrows to indicate the flow direction; use rectangles to mark the boundaries of lakes, and indicate the names of reservoirs and representative stations in the study area to form a topological map of the hydrological evolution of the basin.

3. The ecological dispatching method of river-lake system coupled with basin hydrological response according to claim 2 is characterized in that: In step 1.2, the selection of representative stations should follow the following principles: Step 1.2.1, Reservoir representative station: A reservoir outflow station should be set up at the reservoir dam site; Step 1.2.2, River representative station: At least one representative station should be selected for each main and tributary river; specifically, in the river section where tributaries flow into or diverge, representative stations should be set up both upstream and downstream of the intersection; In river sections where there are no tributaries or diversions, a representative station is set up, and additional representative stations are added in cases where the river terrain is complex; Step 1.2.3, lake representative station: at least one representative station should be selected inside the lake area, and the specific number is determined according to the spatial hydrological response characteristics inside the lake; if there is no obvious difference in the spatial hydrological response inside the lake, then one lake representative station can be selected; if there is a significant difference in the spatial hydrological response inside the lake, then it will be divided into multiple lake areas according to the lake's topographic characteristics and hydrological response characteristics, and a representative station will be set up in each lake area.

4. The ecological dispatching method of river-lake system coupled with basin hydrological response according to claim 2 is characterized in that: The specific implementation of step 2 is as follows: Step 2.1, decompose the study area and set up the hydrological response sub-model step by step; based on the basin hydrological evolution topology map obtained in step 1.3, decompose the study area, set up the hydrological response sub-model for each group of adjacent representative stations, and quantify the basin hydrological response step by step; Step 2.2, determine the function type of the hydrological response sub-model; Step 2.3, optimizing the parameter values ​​of the hydrological response sub-model; using all the data sets in step 2.2.2 to train the function type selected in step 2.2.3, and optimizing and determining the parameter values ​​of the hydrological response sub-model; Step 2.4, integrating the hydrological response sub-models to form a complete watershed hydrological response model; Based on the function type determined in step 2.2 and the parameter values ​​optimized in step 2.3, determine the structure of the hydrological response sub-model, and integrate the hierarchically constructed hydrological response sub-models into a complete watershed hydrological response model; When applying the basin hydrological response model, the hydrological response sub-models are applied step by step from upstream to downstream, and the output of the upstream sub-model is used as the input data of the downstream sub-model to simulate the lake water level at each time period. Discharge to upstream reservoirs and interval inflow The step-by-step dynamic response of the process can be characterized as follows: （1）。 5. The method for ecological dispatching of river-lake system coupled with basin hydrological response according to claim 4, characterized in that: The step 2.1 is specifically as follows: Step 2.1.1, for the reservoir representative station and the river representative station, the hydrological response sub-model takes the hydrological characteristics of the upstream representative station in the neighboring representative station as the input variable and the hydrological characteristics of the downstream representative station as the output variable, and constructs the hydrological response sub-model in sequence through the two steps of determining the function type and optimizing the parameter value; Hydrological characteristics of each representative station Select the water level, water depth, flow or water volume characteristics of the representative station; Step 2.1.2: For lake representative stations, when there is only one lake representative station in the study area, the hydrological characteristics of the river representative station flowing into the lake are used as input variables and the hydrological characteristics of the lake representative station are used as output variables to construct a lake hydrological response sub-model to quantify the response of the lake hydrological regime to the runoff into the lake; when there are multiple lake representative stations in the study area, one of the lake representative stations is first selected to construct a hydrological response sub-model with the river representative station flowing into the lake; Then, the hydrological characteristics of the selected lake representative station are used as input and the hydrological characteristics of other lake representative stations are used as output to construct a hydrological response sub-model to quantify the hydrological correlation between multiple lake areas within the lake. The step 2.2 is specifically as follows: Step 2.2.1, the candidate function types include linear function, polynomial function, multivariate polynomial function or piecewise function; Step 2.2.2, use the k-fold cross-validation method to train and test all candidate function types; use the historical measured data of the hydrological characteristics of the selected representative station as the data set, divide it evenly into k subsets, select one subset as the test set each time, and the remaining k-1 subsets as the training set, and train and test each candidate function type; Step 2.2.3, evaluate the accuracy and optimize the candidate function types; select the Pearson correlation coefficient CC, root mean square error RMSE and relative deviation RB as statistical indicators, quantify the simulation accuracy of each candidate function type with the average value of k training tests, and select the function type with the best simulation accuracy for the hydrological response submodel.

6. The ecological dispatching method of river-lake system coupled with basin hydrological response according to claim 4 is characterized in that: The specific implementation of step 3 is as follows: Step 3.1, quantify the ecological satisfaction of the lake; The lake ecological satisfaction index is set to measure whether the water level of each lake area in the lake at each time period can meet the ecological water level demand; then the ecological satisfaction of each lake area is weighted according to the importance weight of the lake area to obtain the ecological guarantee degree of the lake at that time period; the formula is as follows: （2） （3） in, It represents the ecological satisfaction of the lake in period t, which is the weighted average of the ecological satisfaction of each lake area; Indicates the ecological satisfaction of the i-th lake area in period t, with a value of 0 or 1; the simulated water level LV of the representative station of the i-th lake area in that period i,t Not less than ecological demand D i,t When it is believed that the lake area meets the ecological needs, W i,t is 1, otherwise it is 0; represents the importance weight of lake area i, determined based on expert experience, N zone Indicates the number of partitions contained in the lake, satisfying and Constraints; Step 3.2, quantify the degree of lake ecological water shortage; The square of the ratio of the lake ecological water level to the simulated water level is used as the ecological water shortage index to measure the ecological water shortage degree of each lake area in the period; if the lake area is not short of water, the index value is between (0,1]; on the contrary, if the lake area is short of water, the index is greater than 1, and the closer the value is to positive infinity, the lower the simulated water level is during the period, and the more serious the water shortage is; the formula is as follows: （4） （5） in, It represents the ecological water shortage degree of the lake in period t, which is the weighted average of the ecological water shortage degree of each lake area; It represents the degree of ecological water shortage in the ith lake area in period t, and its value range is (0, +∞).

7. The ecological dispatching method of river-lake system coupled with basin hydrological response according to claim 6 is characterized in that: The specific implementation of step 4 is as follows: Step 4.1, reservoir optimization operation diagram and decision variable setting; Based on the conventional reservoir dispatching rules, a reservoir optimization dispatching diagram in multi-objective optimization dispatching is set; the reservoir optimization dispatching diagram includes three dispatching lines, namely, the output reduction line, the output guarantee line and the output increase line; the three output lines divide the dispatching interval into four output areas, namely, the output reduction area, the output guarantee area, the output increase area 1 and the output increase area 2; the output coefficients of each output area are respectively , , and , satisfying the constraints ; When the reservoir power generation is dispatched based on the dispatch diagram, the output of each period is determined by the output area where the initial water level of the period is located, and the output is equal to the product of the output coefficient and the guaranteed output; The reservoir optimization dispatching diagram includes two types of decision variables, namely, the water level variable in each dispatching period that determines the output line position, and the output coefficient variable that determines the output size in each period; Step 4.2, set the objective function; the dispatching objectives include lake ecological objectives and reservoir benefit objectives; among them, the lake ecological objectives are the objectives of maximizing the lake ecological satisfaction and minimizing the lake ecological water shortage, and the reservoir benefit objectives are the dimensionless objectives of maximizing the reservoir power generation and maximizing the water storage at the end of the flood season; Step 4.3, set constraints; the constraints of the multi-objective optimization scheduling model include: water balance constraints, reservoir water level constraints, reservoir discharge flow constraints, hydropower station output constraints, and variable non-negative constraints.

8. The method for ecological dispatching of river-lake system coupled with basin hydrological response according to claim 7, characterized in that: In step 4.2, the definitions and formulas of each target are as follows: Step 4.2.1, the goal of maximizing the degree of lake ecological satisfaction; in order to maximize the degree of lake ecological satisfaction, the degree of lake ecological satisfaction in each period in step 3.1 is weighted; the importance weight of the period is allocated according to the ecological status of the basin and the basin scheduling needs; specifically, for key periods with more frequent ecological water shortages, more severe levels, and more attention to scheduling needs, higher weights should be given; and for periods that can better meet ecological needs in the current situation, the importance weight is appropriately reduced, and can even be set to 0; the formula is as follows: （6） in, is the weighted ecological satisfaction degree of the lake in each dispatching period, and They are the overall ecological satisfaction of the lake and the ecological satisfaction of the i-th lake area in period t respectively; is the importance weight of the time period; N period is the number of scheduling periods, satisfying and ; is the importance weight of lake region i, N zone is the number of lake partitions that satisfy and ; Step 4.2.2, minimizing the ecological water shortage degree of the lake: weighting the ecological water shortage degree index of each period in step 3.2; （7） in, is the weighted ecological water shortage degree of the lake in each dispatching period, and are the overall ecological water shortage degree of the lake and the ecological water shortage degree of the i-th lake area in period t respectively; Step 4.2.3, the goal of maximizing reservoir power generation: the average power generation over many years is maximized, and the goal is dimensionless based on the annual average power generation of the initial design or historical data statistics; （8） in, is the dimensionless average power generation of the reservoir over many years; N output To contribute to the protection of the reservoir, is the duration of the scheduling period, is the output coefficient of the time period, which is determined by the output area where the initial water level of the time period is located, and its value is , , or ; is the average annual power generation, N year is the scheduling year number; Step 4.2.4, maximizing the reservoir storage at the end of the flood season: the multi-year average end-of-flood storage of the reservoir is the largest, represented by the multi-year average storage capacity at the end of the reservoir storage period; （9） in, V is the dimensionless multi-year average flood season water storage capacity; n is the reservoir capacity at the end of the storage period in the nth year, V max is the total storage capacity of the reservoir.

9. The ecological dispatching method of river-lake system coupled with basin hydrological response according to claim 7 is characterized in that: The specific implementation of step 5 is as follows: Step 5.1, dispatching process simulation; based on the decision variable values, determine the current reservoir optimization dispatching diagram, take the reservoir runoff process as input, perform water balance calculation, and deduce the reservoir water level, discharge flow and output process; input the reservoir discharge process into the basin hydrological response model constructed in step 2, deduce the spatial water level response process of the downstream lake, and then evaluate the lake ecological level based on the indicators proposed in step 3, thereby deduce the lake ecological target and reservoir benefit target values ​​under the current dispatching diagram, and return them to the optimization stage; Step 5.2, scheduling rule optimization: generating an initial solution set based on the selected optimization algorithm; Evaluate and screen the solution set based on the target value calculated in step 5.1 during the simulation phase of the scheduling process; Through iterative optimization, the solution set is gradually improved until the number of iterations is equal to the preset threshold or the target value variation is less than the preset threshold; finally, the preferred approximate Pareto solution set and the corresponding reservoir scheduling process and lake response process are output; the approximate Pareto solution set includes one or more feasible solutions, each feasible solution corresponds to a set of values ​​of the decision variables described in step 4.1, based on which the reservoir optimization scheduling diagram corresponding to the current feasible solution can be drawn.

10. The method for ecological regulation of river-lake system coupled with basin hydrological response according to claim 9, characterized in that: The specific implementation of step 6 is as follows: Step 6.1, calculate the improvement capacity of the optimized dispatching diagram compared with the conventional dispatching; statistically calculate the optimal values ​​and average values ​​of the dispatching objectives and important dispatching characteristics of all feasible solutions in the approximate Pareto solution set; and calculate the relative percentage of improvement of each dispatching objective compared with the conventional dispatching of the reservoir; Step 6.2, calculate the relative membership of the scheduling target of the Pareto solution set; the value ranges of various scheduling targets are different, so they are standardized respectively, and the relative membership of the scheduling target of the Pareto solution set is obtained using formula (10); （10） in, and are the target value and relative membership of the ith scheduling objective of the jth feasible solution, and are the minimum and maximum values ​​of the i-th scheduling objective respectively; Step 6.3, calculate the dispatch target weights based on the decision preference; based on the decision preference, compare the importance of each pair of targets, use "equally important, slightly important, slightly important, relatively important, obviously important, significantly important, very important, very important, extremely important, extremely important, incomparable" as the fuzzy tone operator, determine the fuzzy scale value, and describe the relative importance of the targets; among them, the fuzzy scale values ​​of equally important and incomparable are 0.5 and 1.0 respectively, and the fuzzy scale values ​​of other fuzzy tones are calculated using linear interpolation; based on the assigned fuzzy tone operator, substitute it into formula (11) to obtain the importance of different targets, and normalize it to obtain the weight of each dispatch target ; （11） in, Indicates the importance of all scheduling objectives; , , and They represent the importance of goals 1 to 4, respectively, where goal 1 is the most important goal considered by the decision maker; , and They represent the fuzzy scale values ​​of the second, third, and fourth objectives, respectively, compared with objective 1, which are determined by the fuzzy mood operator determined by the decision maker; Step 6.4, calculate the relative superiority and recommend the optimal scheduling diagram that meets the decision preference; assuming that the relative superiority of the best and worst solutions are and , then the relative superiority of the jth feasible solution to the optimal solution is: （12） in, Represents the relative superiority of the jth feasible solution; represents the weight of the kth scheduling target calculated in step 6.3; represents the relative membership of the kth scheduling objective of the jth feasible solution calculated in step 6.2; and They represent the optimal relative membership and the worst relative membership of the kth scheduling objective in all feasible solutions respectively; The relative superiority of all feasible solutions is calculated, and the solution set is sorted based on this. The feasible solution with the largest relative superiority is taken as the optimal solution under this decision preference, and the corresponding reservoir optimization scheduling diagram and scheduling process are recommended to the reservoir.

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