Water resource regulation and control method and system for ecological hydrological benign maintenance of inland river basin

Abstract

The invention discloses a water resource regulation and control method and system for ecological hydrological benign maintenance of an inland river basin, and relates to the technical field of water resource management, and the method comprises the steps: dividing into a plurality of ecological function regions based on the inland river basin; acquiring corresponding ecological hydrological data based on the ecological function area; based on ecological hydrological data, combining with water resource utilization, ecological flow guarantee, pollutant control, soil salinity control and ecological requirements, constructing multi-objective optimization models corresponding to all ecological functional areas and model constraint conditions; introducing a dynamic weight based on the multi-objective optimization model to obtain a dynamic optimization model; obtaining an optimal decision variable based on the dynamic optimization model and a model constraint condition; and obtaining a water resource regulation and control scheme based on the optimal decision variable. On the basis of guaranteeing agricultural production and efficient utilization of water resources, ecological flow is guaranteed, and stability of an ecological system is maintained.

Description

Technical Field

[0001] The present invention relates to the technical field of water resource management, and more particularly to a water resource regulation method and system for maintaining benign eco-hydrology in inland river basins. Background Art

[0002] Currently, water resource management in inland river basins faces a conflict between overexploitation of natural resources and safeguarding ecological needs. Particularly in arid and semi-arid regions, where water resources are limited and the environment is fragile, factors such as overirrigation and excessive water withdrawal can easily lead to water resource depletion, ecosystem degradation, and even soil and water salinization. To achieve sustainable development of river basin ecosystems, a balance must be struck between efficient water resource utilization and the maintenance of healthy ecological and hydrological relationships.

[0003] Existing water resource management methods often focus on optimizing a single objective, such as irrigation optimization or water quality protection, while neglecting the overall coordination of ecological and hydrological relationships. In particular, ensuring agricultural production and water resource utilization while safeguarding ecological flows and maintaining ecosystem stability remains a technical challenge.

[0004] Therefore, how to ensure ecological flow and maintain ecosystem stability on the basis of ensuring agricultural production and efficient use of water resources is an urgent problem that technicians in this field need to solve. Summary of the Invention

[0005] In view of this, the present invention provides a water resource regulation method and system for maintaining the benign ecological hydrology of inland river basins, which guarantees the ecological flow and maintains the stability of the ecosystem on the basis of ensuring agricultural production and efficient use of water resources.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] Water resource regulation methods for maintaining benign eco-hydrology in inland river basins include:

[0008] Based on the division of inland river basins into multiple ecological functional zones;

[0009] Acquiring corresponding eco-hydrological data based on the ecological functional zone;

[0010] Based on the eco-hydrological data, combined with water resource utilization, ecological flow guarantee, pollutant control, soil salinity control and ecological needs, a multi-objective optimization model and model constraints corresponding to all the ecological functional zones are constructed;

[0011] Introducing dynamic weights based on the multi-objective optimization model to obtain a dynamic optimization model;

[0012] Obtaining optimal decision variables based on the dynamic optimization model and the model constraints;

[0013] A water resources regulation plan is obtained based on the optimal decision variables.

[0014] Preferably, the method for constructing the multi-objective optimization model is:

[0015] constructing a first objective function for maximizing water resource utilization based on the eco-hydrological data and the water resource utilization;

[0016] Based on the eco-hydrological data and the ecological flow guarantee, a second objective function for maximizing ecological flow is constructed;

[0017] constructing a third objective function for minimizing pollutant concentration based on the eco-hydrological data and the pollutant control;

[0018] constructing a fourth objective function for minimizing soil salt accumulation based on the eco-hydrological data and the soil salinity control;

[0019] Based on the eco-hydrological data and the ecological demand, constructing a fifth objective function for maximizing the ecological demand;

[0020] The multi-objective optimization model is composed based on the first objective function, the second objective function, the third objective function, the fourth objective function and the fifth objective function.

[0021] Preferably, the multi-objective optimization model is specifically:

[0022] Minimize F(X)'=[f1(X),f2(X),f3(X),f4(X),f5(X)];

[0023] Among them, f1(X) represents the first objective function, f2(X) represents the second objective function, f3(X) represents the third objective function, f4(X) represents the fourth objective function, and f5(X) represents the fifth objective function.

[0024] Preferably, the model constraints specifically include:

[0025] Ecological flow constraints, water quality constraints, salinity constraints, total water resources constraints and minimum economic water use constraints.

[0026] Preferably, the method for obtaining the dynamic optimization model is:

[0027] Introducing corresponding dynamic weights for each objective function based on the multi-objective optimization model;

[0028] The initial value of each dynamic weight is a set value, and the dynamic optimization model is obtained:

[0029] Minimize F(X)=[ω1f1(X),ω2f2(X),ω3f3(X),ω4f4(X),ω5f5(X)];

[0030] ω1+ω2+ω3+ω4+ω5=1;

[0031] Among them, ω1, ω2, ω3, ω4 and ω5 represent the dynamic weights corresponding to the first objective function, the second objective function, the third objective function, the fourth objective function and the fifth objective function respectively.

[0032] Preferably, the dynamic weight is adjusted based on the real-time ecological emergency status;

[0033] The ecological emergency includes: ecological water shortage, water pollution, soil salinization and comprehensive resource shortage;

[0034] When the ecosystem is short of water, adjusting the dynamic weights corresponding to the first objective function and the fifth objective function;

[0035] When the water quality is polluted, adjusting the dynamic weight corresponding to the third objective function;

[0036] When the soil is salinized, adjusting the dynamic weight corresponding to the fourth objective function;

[0037] When the comprehensive resources are in short supply, adjusting the dynamic weights corresponding to all objective functions;

[0038] If multiple ecological emergencies are triggered at the same time, the priority is determined according to the ecological risk level, and the dynamic weight of the objective function corresponding to the high-priority ecological emergency state is increased first, and the dynamic weights of the objective functions corresponding to the remaining ecological emergency states are adjusted proportionally.

[0039] Preferably, the dynamic weight adjustment formula is as follows:

[0040]

[0041] Among them, ω k (t) represents the dynamic weight of the kth objective function after adjustment at time step t, k = [1, 2, 3, 4, 5], represents the initial weight of the kth objective function, and ξ represents the emergency amplification coefficient.

[0042] Preferably, the method for obtaining the optimal decision variable is:

[0043] Based on the dynamic optimization model and the model constraints, NSGA-III or MOEA / D is used to generate a Pareto optimal solution set as the optimal decision variable for each of the ecological functional zones;

[0044] Refining the allocation plan using linear programming or dynamic programming based on the optimal decision variables to obtain a refined plan;

[0045] updating the parameters of the dynamic optimization model based on the deviation between the actual value and the predicted value of the refined solution;

[0046] When the deviation is greater than a threshold, the parameters of the dynamic optimization model are re-labeled.

[0047] Preferably, the method further comprises: performing effect evaluation based on the water resources regulation scheme;

[0048] The indicators for effect evaluation include: ecological health index, economic efficiency and environmental safety;

[0049] After a preset time, the dynamic optimization model is retrained based on historical data, and the dynamic weights of each objective function are corrected to achieve optimization of the dynamic optimization model.

[0050] The water resources regulation system for maintaining the benign eco-hydrology of inland river basins includes: a functional area division module, a data acquisition module, a first model acquisition module, a second model acquisition module, a decision variable acquisition module, and a regulation scheme output module;

[0051] The functional area division module is used to divide the inland river basin into multiple ecological functional areas;

[0052] The data acquisition module is used to acquire corresponding eco-hydrological data based on the ecological functional zone;

[0053] The first model acquisition module is used to construct a multi-objective optimization model and model constraints corresponding to all the ecological functional zones based on the eco-hydrological data in combination with water resource utilization, ecological flow guarantee, pollutant control, soil salinity control and ecological needs;

[0054] The second model acquisition module is used to introduce dynamic weights based on the multi-objective optimization model to obtain a dynamic optimization model;

[0055] The decision variable acquisition module is used to obtain the optimal decision variable based on the dynamic optimization model and the model constraints;

[0056] The control scheme output module is used to obtain a water resource control scheme based on the optimal decision variables.

[0057] The above technical solution demonstrates that, compared to existing technologies, the present invention provides a water resource regulation method and system for maintaining the benign ecohydrology of inland river basins. This system utilizes a multi-objective optimization algorithm to construct a dynamic optimization model that comprehensively considers factors such as ecological flow, water resource utilization efficiency, soil salinity control, and water quality protection. Scheduling strategies are adjusted based on observed data and the dynamic optimization model to maximize water resource utilization efficiency while ensuring ecological flow, water quality, and soil health. Through real-time feedback, prediction, and optimized regulation, this method not only enables rapid response to changes in hydrological processes and scheduling decisions, but also ensures the stability of ecosystem structure and function. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0059] Figure 1 This is a flow chart of the water resources regulation method for maintaining benign eco-hydrology in inland river basins provided by the present invention.

[0060] Figure 2 This is a flow chart of the multi-objective optimization model construction method provided by the present invention.

[0061] Figure 3 Schematic diagram of the water resources regulation system structure for benign maintenance of eco-hydrology in inland river basins provided by the present invention.

[0062] Figure 4 This is a structural block diagram of the computer device provided by the present invention. DETAILED DESCRIPTION

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0064] Example 1

[0065] like Figure 1 As shown, the embodiment of the present invention discloses a water resources regulation method for maintaining the benign eco-hydrology of an inland river basin, comprising:

[0066] Based on the division of inland river basins into multiple ecological functional zones;

[0067] Obtain corresponding eco-hydrological data based on ecological functional zones;

[0068] Based on eco-hydrological data, a multi-objective optimization model and model constraints corresponding to all ecological functional zones were constructed in combination with water resource utilization, ecological flow guarantee, pollutant control, soil salinity control and ecological needs;

[0069] Based on the multi-objective optimization model, dynamic weights are introduced to obtain a dynamic optimization model;

[0070] Obtain the optimal decision variables based on the dynamic optimization model and model constraints;

[0071] The water resources regulation plan is obtained based on the optimal decision variables.

[0072] Example 2

[0073] The embodiment of the present invention discloses a water resources regulation method for maintaining benign eco-hydrology in an inland river basin, comprising:

[0074] The inland river basins are divided into several ecological functional zones.

[0075] Preferably, ecological functional zones are divided based on inland river basins by comprehensively considering factors such as hydrological characteristics, ecosystems, land use and human activities.

[0076] This embodiment divides inland river basins based on hydrological characteristics and ecological functions, divides ecological functional zones according to land use and water resource utilization, and optimizes the division method in combination with a hydrological-ecological model.

[0077] After inland river basins are divided into different ecological functional zones, differentiated regulatory measures can be implemented to take into account water resource utilization, ecological protection and social and economic development, and achieve multi-objective coordinated development.

[0078] Obtain corresponding eco-hydrological data based on ecological functional zones.

[0079] Preferably, field surveys are conducted to obtain eco-hydrological data corresponding to each ecological functional zone according to relevant standard methods, providing technical data for regulatory technology.

[0080] Preferably, the eco-hydrological data includes: hydrological data, water resources development and utilization data, water environment data, ecological data and soil data;

[0081] Hydrological data: According to the relevant provisions of the "Hydrological Survey Specification" (SL196), survey precipitation, runoff, evapotranspiration, groundwater and other data;

[0082] Water resources development and utilization data: Survey the basic situation of ecological functional zones, including water dispatch data of reservoirs, rivers, and lakes, ecological water demand data, economic water demand data, actual total water supply, actual ecological water supply, and total water supply demand;

[0083] Water environment data: In accordance with relevant regulations such as the "Water Environment Monitoring Specifications" (SL219) and the "Surface Water Environmental Quality Standards" (GB3838), investigate pollutant concentration data (such as total nitrogen and total phosphorus) in ecological functional zones;

[0084] Ecological data: According to relevant regulations such as the "Ecological Environment Monitoring Standards" (such as GB / T 18921-2002) and the "Biodiversity Monitoring Methods" (GB / T22191-2008), survey and obtain ecological flow demand data;

[0085] Soil data: Soil salt concentration data were obtained based on the Soil Environmental Quality Standard (GB 15618-1995) and the Technical Specification for Soil Monitoring (GB / T 18301-2001).

[0086] Based on eco-hydrological data and combined with water resource utilization, ecological flow guarantee, pollutant control, soil salinity control and ecological needs, a multi-objective optimization model and model constraints corresponding to all ecological functional zones are constructed.

[0087] Preferably, Figure 2 As shown in Figure 2, the construction method of the multi-objective optimization model is:

[0088] Based on eco-hydrological data and combined with water resource utilization, the first objective function of maximizing water resource utilization is constructed;

[0089] Based on eco-hydrological data and ecological flow guarantee, the second objective function of maximizing ecological flow guarantee is constructed;

[0090] Based on eco-hydrological data and pollutant control, a third objective function of minimizing pollutant concentration is constructed;

[0091] Based on eco-hydrological data and soil salinity control, a fourth objective function to minimize soil salt accumulation was constructed;

[0092] Based on eco-hydrological data and ecological needs, a fifth objective function that maximizes ecological needs is constructed;

[0093] A multi-objective optimization model is composed based on the first objective function, the second objective function, the third objective function, the fourth objective function and the fifth objective function.

[0094] Preferably, the utilization efficiency of water resources is demonstrated by improving the matching degree between water resource supply and demand, and the corresponding first objective function f1(X) is specifically:

[0095]

[0096] Among them, Q i (t) represents the actual water supply of each ecological functional zone i, D i (t) represents the water supply demand of each ecological functional zone i, and n represents the number of ecological functional zones.

[0097] Preferably, the first objective function f1(X) is used to measure the matching efficiency of water resource supply and demand, and to minimize f1(X), that is, to make the actual water supply as close to the total demand as possible, reducing waste or gaps. Close to total water supply demand When f1(X) approaches 0, it indicates optimal efficiency (the water supply just meets the demand and there is no waste); if the water supply is far below the demand, f1(X) approaches 1, indicating extremely low efficiency.

[0098] Preferably, the actual water supply Q of ecological functional zone i i (t) The water supply demand D i (t), i.e. Q i (t)≥D i (t), where D i (t) = E i (t)+C i (t), E i (t) represents the ecological water demand of ecological functional zone i, C i (t) represents the economic water demand of ecological functional zone i, E i (t) is determined by ecological flow and wetland water demand, C i (t) Includes agricultural water, industrial water and domestic water.

[0099] Preferably, in order to ensure the benign maintenance of the ecological-hydrological relationship, it is necessary to ensure that the ecological flow demand is fully guaranteed. A difference term is used to measure the degree of ecological flow guarantee, and then the second objective function f2(X) for maximum ecological flow guarantee is obtained:

[0100]

[0101] Among them, E f,min,i (t) represents the minimum ecological flow threshold, Q e,i (t) represents the actual ecological water supply.

[0102] Preferably, minimizing the second objective function f2(X) can prioritize ecological base flow and avoid ecosystem collapse. e,i (t)≥E f,min,i (t), this item is 0, indicating that the ecological flow meets the standard.

[0103] Preferably, the ecological flow demand of ecological functional zone i needs to meet the minimum threshold value E f,min,i (t):

[0104] Q e,i (t)≥E f,min,i (t);

[0105] Q e,i (t) = α i (t)·Q i (t);

[0106] Among them, α i (t) represents the ecological function zone i in Q i The proportion of water allocated to ecological use in (t), 0≤α i (t)≤1.

[0107] Preferably, a third objective function f3(X) is constructed to minimize the concentration of pollutants. The goal is to minimize the water quality deviation and ensure that the water quality is effectively protected. Specifically,

[0108]

[0109] Among them, C p,i (t) represents the pollutant concentration in ecological function zone i at time step t, C p,std,i (t) represents the standard limit of ecological functional zone i at time step t; f3(X) counts the pollutant concentrations (such as total nitrogen and total phosphorus) exceeding the standard limit in all ecological functional zones. Minimize f3(X) to ensure that the water quality meets the standard. If C p,i (t)≤C P,std,,i (t), this item is 0, indicating that the water quality meets the standard.

[0110] Preferably, the accumulation of soil salt is controlled by adjusting the irrigation amount and irrigation depth. The goal is to minimize salt accumulation, ensure that water quality is effectively protected and maintain soil health. Based on this, the fourth objective function f4(X) for minimizing soil salt accumulation is constructed:

[0111]

[0112] Among them, Q irr,i (τ) represents the irrigation water volume of ecological functional zone i at time τ, C slat,i (τ) represents the irrigation salt concentration of ecological functional zone i at time τ, L slat,i (τ) represents the amount of salt leaching in ecological functional zone i at time τ.

[0113] f4(X) is used to calculate the net salt accumulation from the initial time to time t, reflecting the health of the soil. Minimizing f4(X) inhibits salt accumulation. The smaller the value, the healthier the soil.

[0114] Preferably, the soil salinity concentration S in ecological functional zone i is s,i (t) is:

[0115]

[0116] Among them, S S,std,i Indicates the threshold value, soil salt concentration S s,i (t) needs to be lower than the threshold S s，std,i (t), prevent salinization.

[0117] Preferably, the ecological demand is maximized by minimizing the negative value, and the fifth objective function f5(X) of maximizing the ecological demand is constructed:

[0118]

[0119] Among them, Q e,i (t) represents the actual ecological water supply of ecological functional zone i, E i (t) represents the ecological water demand of ecological functional zone i.

[0120] f5(X) promotes the actual ecological water supply Q by minimizing negative values (i.e. maximizing positive values). e,i (t) As close as possible to or even exceeding the ecological water requirement E i (t), giving priority to meeting ecological water needs; It represents the ratio of actual ecological water supply to ecological water demand. If Q e,i (t) = E i (t), then the ratio is 1 (completely satisfied).

[0121] Preferably, the multi-objective optimization model is specifically:

[0122] Minimize F(X)'=[f1(X),f2(X),f3(X),f4(X),f5(X)];

[0123] Among them, f1(X) represents the first objective function, f2(X) represents the second objective function, f3(X) represents the third objective function, f4(X) represents the fourth objective function, and f5(X) represents the fifth objective function.

[0124] Preferably, the model constraints specifically include:

[0125] Ecological flow constraints, water quality constraints, salinity constraints, total water resources constraints and minimum economic water use constraints.

[0126] Preferably, ecological flow constraints:

[0127] Water quality constraints:

[0128] Salt Constraints:

[0129] Constraints on total water resources:

[0130] Minimum guarantee constraints for economic water use:

[0131] Based on the multi-objective optimization model, dynamic weights are introduced to obtain a dynamic optimization model.

[0132] Preferably, the method for obtaining the dynamic optimization model is:

[0133] Introduce corresponding dynamic weights for each objective function based on the multi-objective optimization model;

[0134] The initial value of each dynamic weight is the set value, and the dynamic optimization model is obtained:

[0135] Minimize F(X)=[ω1f1(X),ω2f2(X),ω3f3(X),ω4f4(X),ω5f5(X)];

[0136] ω1+ω2+ω3+ω4+ω5=1;

[0137] Among them, ω1, ω2, ω3, ω4 and ω5 represent the dynamic weights corresponding to the first objective function, the second objective function, the third objective function, the fourth objective function and the fifth objective function respectively.

[0138] Preferably, in this embodiment, the initial value of each dynamic weight is 0.2.

[0139] Preferably, based on the dynamic optimization model, rolling time domain optimization is performed: the prediction time domain T is set (such as the next 7 days), and at each time step t, the model parameters are updated based on the latest data to generate an optimization plan for the next T period.

[0140] Preferably, the dynamic weights are adjusted based on the real-time ecological emergency status;

[0141] Ecological emergencies include: ecological water shortage, water pollution, soil salinization and comprehensive resource shortage;

[0142] When the ecosystem is short of water, the dynamic weights corresponding to the first objective function and the fifth objective function are adjusted;

[0143] When water quality is polluted, the dynamic weight corresponding to the third objective function is adjusted;

[0144] When soil salinization occurs, the dynamic weight corresponding to the fourth objective function is adjusted;

[0145] When comprehensive resources are scarce, adjust the dynamic weights corresponding to all objective functions;

[0146] If multiple ecological emergencies are triggered at the same time, the priority is determined according to the ecological risk level, and the dynamic weight of the objective function corresponding to the high-priority ecological emergency state is increased first, and the dynamic weights of the objective functions corresponding to the remaining ecological emergency states are adjusted proportionally.

[0147] Preferably, the ecological water shortage judgment condition is: Q e,i (t)<λE f,min,i (t), at this time, the weights of ω1 and ω5 are increased to trigger emergency water replenishment.

[0148] Preferably, the water pollution determination condition is: C p,i (t)>γC p,std,i At this time, adjust the ω3 weight, start the purification facilities, and switch the water source (such as recycled water).

[0149] Preferably, the soil salinization determination conditions are: At this time, the ω4 weight is adjusted, the irrigation amount is reduced, and the leaching program is triggered.

[0150] Preferably, the comprehensive resource shortage determination conditions are: At this time, adjust the weight values of ω1, ω2, ω3, ω4 and ω5, reduce the weight of economic water use, and give priority to ecological and domestic water use.

[0151] Preferably, λ, γ, and δ all represent safety factors, which are calibrated through historical disaster data or machine learning to avoid frequent false triggering.

[0152] Preferably, the dynamic weight adjustment formula is as follows:

[0153]

[0154] Among them, ω k (t) represents the dynamic weight of the kth objective function after adjustment at time step t, k = [1, 2, 3, 4, 5], represents the initial weight of the kth objective function, ξ represents the emergency amplification coefficient, and the others in the formula refer to the situation where the ecological emergency state is not in progress, that is, the dynamic weight of the objective function that is not in progress is calculated based on Adjustment.

[0155] Preferably, ξ = 1, 2, 3, and 4 represent no emergency, mild emergency, moderate emergency, and severe emergency, respectively. If multiple ecological emergencies are triggered simultaneously, this embodiment dynamically adjusts the weights based on the priority order of ecological water shortage > water pollution > soil salinization, prioritizing the weights of high-priority targets and adjusting the remaining targets proportionally. Once the indicators return to a safe range for a period of T, the initial weights are restored.

[0156] The optimal decision variables are obtained based on the dynamic optimization model and model constraints.

[0157] Preferably, the method for obtaining the optimal decision variables is:

[0158] Based on the dynamic optimization model and model constraints, NSGA-III or MOEA / D is used to generate the Pareto optimal solution set as the optimal decision variable for each ecological functional zone;

[0159] Refining the allocation plan using linear programming or dynamic programming based on the optimal decision variables to obtain a refined plan;

[0160] Based on the deviation between the actual value and the predicted value of the refined solution, the parameters of the dynamic optimization model are updated;

[0161] When the deviation is greater than the threshold, the parameters of the dynamic optimization model are re-labeled.

[0162] Preferably, the optimal decision variables include at least: the total water supply Q of each ecological functional zone total,i (t), the actual ecological water supply Q of ecological functional zone i e,i (t), the irrigation water volume Q of ecological functional zone i irr,i (t).

[0163] Preferably, the stratified optimization is carried out with the total water supply Q total,i (t) as an example:

[0164] Global layer: Use NSGA-III or MOEA / D to generate Pareto optimal solution set and determine the total water supply Q of each ecological functional zone total,i (t):

[0165] Obtain real-time monitoring data and forecast time domain T and input them into the dynamic optimization model. Based on the model constraints, the Pareto front solution set is obtained, which is the total water supply Q of each ecological functional zone. total,i (t).

[0166] Local layer: Each ecological functional zone is based on Q total,i (t) Use linear programming (LP) or dynamic programming (DP) to refine allocation plans (e.g., agricultural irrigation volume, reservoir water release volume):

[0167] Q based on global layer allocation total,i(t) Refine the allocation plan, such as agricultural / industrial water use and ecological water replenishment timing.

[0168] Feedback correction mechanism: The allocation results at the local level feed back to the global level constraints to form a closed-loop optimization. At each time step t+1, the deviation between the actual water supply and the predicted value is compared and the model parameters are updated:

[0169] Ensure that after a period of time, the actual water supply is ≥ the planned water supply;

[0170] If the deviation exceeds 10%, the model parameters will be recalibrated.

[0171] The water resources regulation plan is obtained based on the optimal decision variables.

[0172] Preferably, a water resource regulation plan is obtained based on the optimal decision variables. The water resource regulation plan specifically includes: reservoir water release plan (time, flow), irrigation quota (allocated by farmers / irrigation areas), artificial water replenishment instructions (such as wetland emergency water replenishment), etc.

[0173] Preferably, Q total,i (t) as an example, the executable instructions in the water resources control plan are:

[0174] Instruction 1: Reservoir A releases water Q at time t release (t) = 50m 3 / s;

[0175] Instruction 2: Irrigation zone B reduces irrigation volume to 0.7 times the original volume from t+1 to t+3.

[0176] Situational response and dynamic adjustment:

[0177] Input real-time monitoring data (flow, water quality, salinity) and external events (such as weather warnings), and adjust the dynamic weights of the corresponding objective functions in the dynamic optimization model according to the real-time ecological emergency status:

[0178] For example, in the ecological water shortage scenario: reduce the weight of economic water use and prioritize ecological flow;

[0179] Trigger condition: actual ecological water supply Q e,i (t)<0.8E f,min,i (t), meteorological drought index (SPI) ≤ -1.5;

[0180] Adjustment action: Based on the analysis of historical disaster data, when SPI ≤ -1.5, ecological water shortage is a mild emergency, and doubling the ecological flow weight can reduce the risk of ecological degradation by 80%. Based on the above dynamic weight adjustment formula, the dynamic weight of the second objective function is adjusted: ecological flow weight w2←2w2;

[0181] Execution layer: Start groundwater emergency water supply (such as increasing pumping volume by 10m 3 / h).

[0182] Preferably, the method further includes: conducting effect evaluation based on the water resources regulation plan;

[0183] Indicators for effect evaluation include: ecological health index, economic efficiency and environmental safety;

[0184] After a preset time, the dynamic optimization model is retrained based on historical data, and the dynamic weights of each objective function are corrected to achieve optimization of the dynamic optimization model.

[0185] Preferably, the ecological health index includes: wetland water level compliance rate and vegetation coverage rate; economic efficiency includes: GDP output per unit of water resources; environmental safety includes: number of days with excessive salinity and water quality compliance rate.

[0186] Optimally, scheduling strategies are adjusted based on observational data and integrated multi-objective optimization models to maximize water resource utilization efficiency while safeguarding ecological flow, water quality, and soil health. Through real-time feedback, prediction, and optimization, we can not only respond to sudden hydrological changes but also ensure long-term ecological and environmental sustainability.

[0187] Example 3

[0188] like Figure 3 The water resources regulation system for maintaining the benign eco-hydrology of inland river basins includes: a functional area division module, a data acquisition module, a first model acquisition module, a second model acquisition module, a decision variable acquisition module, and a regulation scheme output module;

[0189] Functional zone division module, used to divide inland river basins into multiple ecological functional zones;

[0190] A data acquisition module is used to obtain corresponding eco-hydrological data based on ecological functional zones;

[0191] The first model acquisition module is used to construct multi-objective optimization models and model constraints corresponding to all ecological functional zones based on eco-hydrological data combined with water resource utilization, ecological flow guarantee, pollutant control, soil salinity control and ecological needs;

[0192] The second model acquisition module is used to introduce dynamic weights based on the multi-objective optimization model to obtain a dynamic optimization model;

[0193] A decision variable acquisition module is used to obtain the optimal decision variables based on the dynamic optimization model and model constraints;

[0194] The control scheme output module is used to obtain the water resources control scheme based on the optimal decision variables.

[0195] Preferably, the function implementation method of each module in this embodiment corresponds to the content of the above method one by one, and will not be repeated here.

[0196] Example 4

[0197] Based on the same inventive concept, the present invention further provides a computer device, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0198] Memory for storing computer programs;

[0199] The processor, when used to execute the program stored in the memory, can implement the water resources regulation method for maintaining the benign ecological hydrology of inland river basins as in Example 1 or 2.

[0200] like Figure 4 As shown, the electronic device may include: a processor 41, a communications interface 42, a memory 43, and a communication bus 44, wherein the processor 41, the communications interface 42, and the memory 43 communicate with each other via the communication bus 44. The processor 41 may call the logic instructions in the memory 43 to execute the water resources regulation method for maintaining the benign eco-hydrology of an inland river basin in Example 1 or 2.

[0201] In addition, the logic instructions in the aforementioned memory 43 can be implemented in the form of a software functional unit and, when sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present invention.

[0202] The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program code.

[0203] The above technical solution demonstrates that the present invention provides a water resource regulation method and system for maintaining healthy eco-hydrology in inland river basins. Using a multi-objective optimization algorithm, a dynamic optimization model is constructed that comprehensively considers factors such as ecological flow, water resource utilization efficiency, soil salinity control, and water quality protection. Scheduling strategies are adjusted based on observed data and the dynamic optimization model to maximize water resource utilization efficiency while simultaneously safeguarding ecological flow, water quality, and soil health. Through real-time feedback, prediction, and optimized regulation, this method not only enables rapid response to changes in hydrological processes and scheduling decisions, but also ensures the stability of ecosystem structure and function.

[0204] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0205] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A water resources regulation method for maintaining benign eco-hydrology in inland river basins, characterized by: include: Based on the division of inland river basins into multiple ecological functional zones; Acquiring corresponding eco-hydrological data based on the ecological functional zone; Based on the eco-hydrological data, combined with water resource utilization, ecological flow guarantee, pollutant control, soil salinity control and ecological needs, a multi-objective optimization model and model constraints corresponding to all the ecological functional zones are constructed; Introducing dynamic weights based on the multi-objective optimization model to obtain a dynamic optimization model; Obtaining optimal decision variables based on the dynamic optimization model and the model constraints; A water resources regulation plan is obtained based on the optimal decision variables.

2. The water resources regulation method for maintaining benign eco-hydrology in inland river basins according to claim 1, characterized in that: The method for constructing the multi-objective optimization model is: constructing a first objective function for maximizing water resource utilization based on the eco-hydrological data and the water resource utilization; Based on the eco-hydrological data and the ecological flow guarantee, a second objective function for maximizing ecological flow is constructed; constructing a third objective function for minimizing pollutant concentration based on the eco-hydrological data and the pollutant control; constructing a fourth objective function for minimizing soil salt accumulation based on the eco-hydrological data and the soil salinity control; Based on the eco-hydrological data and the ecological demand, constructing a fifth objective function for maximizing the ecological demand; The multi-objective optimization model is composed based on the first objective function, the second objective function, the third objective function, the fourth objective function and the fifth objective function.

3. The water resources regulation method for maintaining benign eco-hydrology in inland river basins according to claim 2, characterized in that: The multi-objective optimization model is specifically: Minimize F(X)'=[f1(X),f2(X),f3(X),f4(X),f5(X)]; Among them, f1(X) represents the first objective function, f2(X) represents the second objective function, f3(X) represents the third objective function, f4(X) represents the fourth objective function, and f5(X) represents the fifth objective function.

4. The water resources regulation method for maintaining benign eco-hydrology in inland river basins according to claim 1, characterized in that: The model constraints specifically include: Ecological flow constraints, water quality constraints, salinity constraints, total water resources constraints and minimum economic water use constraints.

5. The water resources regulation method for maintaining benign eco-hydrology in inland river basins according to claim 3 is characterized in that: The method for obtaining the dynamic optimization model is: Introducing corresponding dynamic weights for each objective function based on the multi-objective optimization model; The initial value of each dynamic weight is a set value, and the dynamic optimization model is obtained: Minimize F(X)=[ω1f1(X),ω2f2(X),ω3f3(X),ω4f4(X),ω5f5(X)]; ω1+ω2+ω3+ω4+ω5=1; Among them, ω1, ω2, ω3, ω4 and ω5 represent the dynamic weights corresponding to the first objective function, the second objective function, the third objective function, the fourth objective function and the fifth objective function respectively.

6. The water resources regulation method for maintaining benign eco-hydrology in inland river basins according to claim 5, characterized in that: The dynamic weight is adjusted based on the real-time ecological emergency status; The ecological emergency includes: ecological water shortage, water pollution, soil salinization and comprehensive resource shortage; When the ecosystem is short of water, adjusting the dynamic weights corresponding to the first objective function and the fifth objective function; When the water quality is polluted, adjusting the dynamic weight corresponding to the third objective function; When the soil is salinized, adjusting the dynamic weight corresponding to the fourth objective function; When the comprehensive resources are in short supply, adjusting the dynamic weights corresponding to all objective functions; If multiple ecological emergencies are triggered at the same time, the priority is determined according to the ecological risk level, and the dynamic weight of the objective function corresponding to the high-priority ecological emergency state is increased first, and the dynamic weights of the objective functions corresponding to the remaining ecological emergency states are adjusted proportionally.

7. The water resources regulation method for maintaining benign eco-hydrology in inland river basins according to claim 6, characterized in that: The dynamic weight adjustment formula is as follows: Among them, ω k (t) represents the dynamic weight of the kth objective function after adjustment at time step t, k = [1, 2, 3, 4, 5], represents the initial weight of the kth objective function, and ξ represents the emergency amplification coefficient.

8. The water resources regulation method for maintaining benign eco-hydrology in inland river basins according to claim 7, characterized in that: The method for obtaining the optimal decision variables is: Based on the dynamic optimization model and the model constraints, NSGA-III or MOEA / D is used to generate a Pareto optimal solution set as the optimal decision variable for each of the ecological functional zones; Refining the allocation plan using linear programming or dynamic programming based on the optimal decision variables to obtain a refined plan; updating the parameters of the dynamic optimization model based on the deviation between the actual value and the predicted value of the refined solution; When the deviation is greater than a threshold, the parameters of the dynamic optimization model are re-labeled.

9. The water resources regulation method for maintaining benign eco-hydrology in inland river basins according to claim 1, characterized in that: Also includes: Conducting an effectiveness evaluation based on the water resources regulation plan; The indicators for effect evaluation include: ecological health index, economic efficiency and environmental safety; After a preset time, the dynamic optimization model is retrained based on historical data, and the dynamic weights of each objective function are corrected to achieve optimization of the dynamic optimization model.

10. A water resource regulation system for maintaining benign eco-hydrology in an inland river basin, applied to a water resource regulation method for maintaining benign eco-hydrology in an inland river basin as claimed in any one of claims 1 to 9, characterized in that: include: Functional area division module, data acquisition module, first model acquisition module, second model acquisition module, decision variable acquisition module and control scheme output module; The functional area division module is used to divide the inland river basin into multiple ecological functional areas; The data acquisition module is used to acquire corresponding eco-hydrological data based on the ecological functional zone; The first model acquisition module is used to construct a multi-objective optimization model and model constraints corresponding to all the ecological functional zones based on the eco-hydrological data in combination with water resource utilization, ecological flow guarantee, pollutant control, soil salinity control and ecological needs; The second model acquisition module is used to introduce dynamic weights based on the multi-objective optimization model to obtain a dynamic optimization model; The decision variable acquisition module is used to obtain the optimal decision variable based on the dynamic optimization model and the model constraints; The control scheme output module is used to obtain a water resource control scheme based on the optimal decision variables.

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