Tarim river basin water resource optimal configuration method and system based on ecology

Abstract

The invention provides an ecology-based Tarim river basin water resource optimal configuration method and system, and relates to the technical field of water resource optimal configuration, and the method comprises the following steps: S1, data collection and analysis; s2, target setting and constraint condition determination: taking maintenance of stability of a Tarim river basin ecological system as a core, and determining an ecological protection target; s3, establishing a water resource optimal configuration model; s4, formulating and evaluating a scheme; according to the method, a water resource optimal configuration model is constructed through a beetle antennae search algorithm, and the device reduces the probability that complex interaction between water resources and an ecological system cannot be completely and accurately simulated, certain simplification and hypothesis exist, and consequently the model simulation result deviates from the actual situation. And through the strong global search capability and adaptability of the longhorn beetle search algorithm, the system can find a better solution in a shorter time, and the optimization efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water resource optimization configuration, and in particular to an ecology-based water resource optimization configuration method and system for the Tarim River Basin. Background Art

[0002] Optimal allocation of water resources refers to the rational allocation and utilization of water resources through scientific methods and means in water resources management to meet the needs of social and economic development, while protecting and improving the water environment and achieving sustainable use of water resources. The goal of optimal allocation of water resources is to achieve efficient utilization, fair distribution and long-term stable supply of water resources to ensure the sustainable development of human society.

[0003] At present, when optimizing water resources allocation in the Tarim River Basin, scientific optimization of irrigation area water resources allocation is an important means to save water resources and improve the comprehensive benefits of irrigation areas. First, meteorological data, hydrological data, soil data, land use data, ecosystem data (as well as socioeconomic data) of the Tarim River Basin are collected. A model is constructed based on the characteristics of the water resources system in the Tarim River Basin, taking into account possible climate change and socioeconomic development trends in the future. At the same time, a comprehensive evaluation index system is established. Using the established evaluation index system, different water resources allocation plans are evaluated and compared, and the advantages and disadvantages of each plan in terms of different indicators are analyzed. The better plan is selected and the optimized water resources allocation plan is refined into a specific implementation plan. However, although the currently constructed water resources system model and ecological water demand model have taken various factors into consideration as much as possible, due to the complexity of the Tarim River Basin system, it may still be impossible to fully and accurately simulate the complex interaction between water resources and ecosystems. There are certain simplifications and assumptions, which lead to deviations between the model simulation results and the actual situation.

[0004] Therefore, it is necessary to provide a new ecologically based method and system for optimizing water resources allocation in the Tarim River Basin to solve the above technical problems. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention provides an ecologically based method and system for optimizing water resources allocation in the Tarim River Basin.

[0006] The present invention provides an ecologically-based method and system for optimizing water resource allocation in the Tarim River Basin, comprising the following steps:

[0007] S1. Data collection and analysis: Collect hydrological data on precipitation, runoff, and evaporation in the Tarim River Basin, as well as data on the amount of water resources in rivers, lakes, and groundwater and their temporal and spatial distribution. Collect socioeconomic data on the basin's population, economic development, industrial structure, and water quotas. Use statistical analysis and geographic information systems to organize and analyze the collected data.

[0008] S2. Goal setting and constraint determination: With the maintenance of the stability of the Tarim River Basin ecosystem as the core, determine ecological protection goals, and set reasonable economic growth targets based on the basin's socio-economic development plan, while also determining constraints;

[0009] S3. Establish a water resources optimization configuration model. According to the characteristics and research objectives of the Tarim River Basin, and through the longhorn beetle beard search algorithm, the water resources optimization configuration model is constructed. First, the system boundary is clarified and the relevant data of the Tarim River Basin are collected. After the collection is completed, the optimization model can be constructed, and then the parameters and population initialization are performed. At the same time, the iterative search process is carried out. If the number of iterations reaches the preset maximum number of iterations, the algorithm stops. After the algorithm is carried out, the results are output and analyzed;

[0010] S4. Plan formulation and evaluation: Based on the model established by the longicorn beetle search algorithm and combined with the actual situation of the basin, formulate a specific water resources optimization allocation plan and evaluate the formulated plan;

[0011] S5. Plan implementation and monitoring feedback: According to the determined water resources optimization allocation plan, a detailed implementation plan will be formulated, and a complete water resources monitoring system will be established to conduct real-time monitoring of water resources, water use processes, and ecological and environmental changes. At the same time, based on the monitoring data and actual operation conditions, the water resources optimization allocation plan will be evaluated and feedback will be provided in a timely manner.

[0012] Preferably, the method of constructing a water resource optimization configuration model using the longicorn beetle whisker search algorithm specifically includes the following steps:

[0013] S10. Problem Analysis and Model Construction: First, determine the geographical scope of the Tarim River Basin and clearly define the sub-regions it contains. At the same time, collect water resource data within the basin. After completing the collection of relevant data, construct an optimization model.

[0014] S20, the application of the longhorn beetle search algorithm, first initializing the parameters, determining the number of longhorn beetle populations, setting the maximum number of iterations of the algorithm, determining the initial step size of the longhorn beetle search and the parameters related to the step size adjustment strategy, and then randomly generating an initial solution. In the feasible solution space, a set of initial decision variable values are randomly generated for each longhorn beetle individual, and the fitness value of each initial solution is calculated according to the constructed optimization model objective function;

[0015] S30, updating the position of the longhorn beetle. For each longhorn beetle, the positions of its two tentacles are calculated according to the rules of the longhorn beetle whisker search algorithm, and the fitness values corresponding to the positions of the two tentacles of the longhorn beetle are calculated respectively. The longhorn beetle then moves towards the direction of the tentacles with better fitness values, and the position of the longhorn beetle is updated, that is, a new water resource allocation plan is obtained. Finally, the strategy is adjusted according to the step size of the algorithm.

[0016] S40. Termination condition judgment: if the number of iterations reaches the preset maximum number of iterations, the algorithm stops. When the algorithm stops, the individual with the best fitness value is selected from the population. The corresponding decision variable value is the optimal water resource allocation plan, and the optimal plan is analyzed in detail.

[0017] Preferably, the construction of the optimization model in step S10 specifically includes the following steps:

[0018] S11, objective function, which takes maximizing ecological benefits, maximizing social and economic benefits, and maximizing water resource utilization efficiency as multi-objective construction functions;

[0019] S12, decision variables, taking the water resource allocation of each region and each water-using department at different time points as the decision variables;

[0020] S13. Constraints: Consider the total amount of water resources, that is, the total amount of water used by each region and department cannot exceed the available amount of water resources in the basin.

[0021] Preferably, the water resource related data in step S10 include river runoff, precipitation, evaporation and soil moisture.

[0022] Preferably, the constraints in step S2 include total water resource constraints, ecological water use constraints, water use efficiency constraints, and engineering facility constraints.

[0023] The second aspect of the present invention provides an ecologically based Tarim River Basin water resources optimization configuration system, which is applicable to the ecologically based Tarim River Basin water resources optimization configuration method, and is characterized by comprising:

[0024] Data collection and monitoring module: used to collect various water resources related data in the Tarim River Basin in real time;

[0025] Data processing and analysis module: used to organize, store, clean and analyze the massive amount of collected data, remove noise and erroneous data, interpolate and repair missing data, and extract valuable information and features;

[0026] Water resources evaluation module: used to evaluate the water resources quantity, water resources quality, and the degree of water resources development and utilization in the Tarim River Basin;

[0027] Ecological water demand calculation module: used to calculate the water demand of different ecosystem types based on the ecosystem characteristics and needs of the Tarim River Basin;

[0028] Optimization configuration model module: used to establish a water resources optimization configuration model and solve the optimal water resources configuration plan through the beetle whisker search algorithm;

[0029] Scheme generation and evaluation module: used to generate water resource allocation schemes under various scenarios based on the solution results of the optimization configuration model;

[0030] Decision support module: used to provide decision makers with decision support tools and information services.

[0031] Preferably, the various types of water resource related data include meteorological data, hydrological data, soil data, ecological data and socio-economic data;

[0032] The ecosystem types include river ecology, wetland ecology and vegetation ecology.

[0033] Compared with related technologies, the ecologically-based method and system for optimizing water resource allocation in the Tarim River Basin provided by the present invention has the following beneficial effects:

[0034] The present invention constructs a water resource optimization configuration model through the longhorn beetle whisker search algorithm. First, the system boundary is clarified and the data related to the Tarim River basin is collected. After the collection is completed, the optimization model can be constructed, and then the parameters are initialized and the population is initialized. At the same time, an iterative search process is performed. If the number of iterations reaches a preset maximum number of iterations, the algorithm stops. After the algorithm is performed, the results are output and analyzed. This device reduces the probability that the complex interaction between water resources and ecosystems cannot be fully and accurately simulated, and there are certain simplifications and assumptions, which lead to deviations between the model simulation results and the actual situation. Moreover, through the powerful global search capability and adaptability of the longhorn beetle whisker search algorithm, the system can find a better solution in a shorter time, thereby improving the optimization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a structural diagram of an ecologically based water resources optimization configuration system for the Tarim River Basin provided by the present invention;

[0036] Figure 2 A flowchart of an ecologically-based method for optimizing water resource allocation in the Tarim River Basin provided by the present invention;

[0037] Figure 3 A flowchart of the method for constructing a water resource optimization configuration model using a longicorn beetle whisker search algorithm provided by the present invention;

[0038] Figure 4This is a flowchart of the process of constructing the optimization model provided by the present invention. DETAILED DESCRIPTION

[0039] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0040] Please refer to Figure 1 、 Figure 2 、 Figure 3 as well as Figure 4 ,in, Figure 1 This is a structural diagram of an ecologically based water resources optimization configuration system for the Tarim River Basin provided by the present invention; Figure 2 A flowchart of an ecologically-based method for optimizing water resource allocation in the Tarim River Basin provided by the present invention; Figure 3 A flowchart of the method for constructing a water resource optimization configuration model using a longicorn beetle whisker search algorithm provided by the present invention; Figure 4 This is a flowchart of the process of constructing the optimization model provided by the present invention.

[0041] Example 1

[0042] In the specific implementation process, Figure 2 、 Figure 3 as well as Figure 4 The method and system for optimizing water resource allocation in the Tarim River basin based on ecology include the following steps:

[0043] S1. Data collection and analysis: Collect hydrological data on precipitation, runoff, and evaporation in the Tarim River Basin, as well as data on the amount of water resources in rivers, lakes, and groundwater and their temporal and spatial distribution. Collect socioeconomic data on the basin's population, economic development, industrial structure, and water quotas. Use statistical analysis and geographic information systems to organize and analyze the collected data.

[0044] It should be noted that data collection includes the collection of water resource-related data, ecological and environmental data, and socio-economic data. Water resource-related data refers to the collection of meteorological data such as precipitation, evaporation, temperature, wind speed, and sunshine hours, as well as hydrological data such as river flow, water level, water quality, groundwater level, and groundwater quality. Precipitation data can reflect the input of water resources, while evaporation data is related to the loss of water resources. Flow and water level data directly reflect the changes in river water volume, and water quality data is crucial for determining the availability of water resources.

[0045] Ecological and environmental data include vegetation type, coverage, and growth status. Different vegetation types have varying water requirements, and changes in vegetation coverage reflect the health of the ecosystem. It also includes wetland area and the biodiversity of wetland ecosystems. Wetlands have important ecological functions and are of great significance to maintaining regional ecological balance.

[0046] Socioeconomic data includes the permanent population of each region, population growth rate, output value of agriculture, industry, and services, and water quotas for each industry. Population size determines the basic demand for domestic water, while population growth trends affect future changes in water resource demand. Agricultural output value is closely related to irrigation water use, and industrial output value and water quotas reflect industrial water use efficiency and demand. By analyzing this data, we can rationally plan water use for each industry and improve water resource utilization efficiency.

[0047] S2. Goal setting and constraint determination: With the maintenance of the stability of the Tarim River Basin ecosystem as the core, determine ecological protection goals, and set reasonable economic growth targets based on the basin's socio-economic development plan, while also determining constraints;

[0048] It should be noted that the constraints in step S2 include total water resources constraints, ecological water use constraints, water use efficiency constraints, and engineering facility constraints;

[0049] Constraints on total water resources: Surface water resources in the Tarim River Basin primarily come from mountain snowmelt and precipitation, with a limited total amount and inter-annual and intra-annual variations. Groundwater resources: Although groundwater is an important component of the Tarim River Basin's water resources, over-exploitation can lead to a series of ecological and environmental problems, including land subsidence and declining groundwater levels.

[0050] Ecological water use constraints include river ecological base flow constraints and wetland and natural vegetation ecological water demand constraints. River ecological base flow constraints are to maintain the basic functions of river ecosystems. A certain ecological base flow must be guaranteed. Based on the ecological characteristics, hydrological conditions and relevant research results of the river, the minimum ecological base flow standards for different river sections in different seasons are determined.

[0051] Ecological water demand constraints for wetlands and natural vegetation: determine their ecological water demand based on their area, type, and growth patterns;

[0052] Water use efficiency constraints: Consider the potential for improving water use efficiency in various industries, formulate reasonable water quotas and efficiency indicators, and limit the waste of water resources;

[0053] Engineering facility constraints include water conservancy project storage and regulation capacity constraints and water transfer project water transfer capacity constraints. Reservoirs and sluices in the Tarim River Basin have certain storage and regulation capacity and water supply capacity constraints.

[0054] The water transfer capacity of water transfer projects is limited. The water transfer capacity of channels and pipelines is limited, which affects the transportation and distribution of water resources. Based on the design parameters and actual operation of the water transfer projects, the upper limit of their water transfer capacity is determined as a constraint in water resource allocation to avoid the failure of water resources to be distributed to various regions and departments as planned due to insufficient water transfer capacity.

[0055] At the same time, the goal setting includes ecological protection goals, social and economic development goals, and comprehensive benefit maximization goals. The ecological protection goals include maintaining the health of the river ecosystem, ensuring the ecological base flow of the Tarim River, maintaining suitable water flow conditions in the river channel, ensuring the survival and reproduction of aquatic organisms, maintaining the integrity and biodiversity of the river ecosystem, and protecting and restoring the wetland ecosystem. Wetlands are known as the "lungs of the earth" and play an important role in regulating climate, purifying water quality, and providing habitats.

[0056] The socio-economic development goals are to meet the demand for domestic water, guarantee basic domestic water for residents in the basin, improve water quality, improve residents' living conditions, and support sustainable agricultural development. Agriculture is an important industry in the Tarim River Basin. The optimal allocation of water resources should ensure water for agricultural irrigation and promote increased agricultural production and income.

[0057] The goal of maximizing comprehensive benefits is to comprehensively consider multiple goals of ecological protection and social and economic development, and to construct an objective function for maximizing comprehensive benefits through reasonable weight allocation. Under the premise of meeting the basic needs of ecological protection and social and economic development, the optimal solution for overall benefits is sought;

[0058] S3. Establish a water resources optimization configuration model. According to the characteristics and research objectives of the Tarim River Basin, and through the longhorn beetle beard search algorithm, the water resources optimization configuration model is constructed. First, the system boundary is clarified and the relevant data of the Tarim River Basin are collected. After the collection is completed, the optimization model can be constructed, and then the parameters and population initialization are performed. At the same time, the iterative search process is carried out. If the number of iterations reaches the preset maximum number of iterations, the algorithm stops. After the algorithm is carried out, the results are output and analyzed;

[0059] It should be noted that the Beetle Antennae Search Algorithm (BAS) is a bioinspired optimization algorithm inspired by the foraging behavior of longhorn beetles in nature. It simulates the process of longhorn beetles using their antennae to detect the surrounding environment and find food, and is designed to solve complex multimodal optimization problems.

[0060] The core idea of the longhorn beetle antenna search algorithm is to imitate the longhorn beetle's behavior of sensing the difference in odor concentration in the environment through its left and right antennae to determine the direction and distance of movement;

[0061] The specific steps of constructing a water resources optimization allocation model using the longicorn beard search algorithm include:

[0062] S10. Problem Analysis and Model Construction: First, determine the geographical scope of the Tarim River Basin and clearly define the sub-regions it contains. At the same time, collect water resource data within the basin. After completing the collection of relevant data, construct an optimization model.

[0063] It should be noted that the construction of the optimization model in step S10 specifically includes the following steps:

[0064] S11, objective function, which takes maximizing ecological benefits, maximizing social and economic benefits, and maximizing water resource utilization efficiency as multi-objective construction functions;

[0065] S12, decision variables, taking the water resource allocation of each region and each water-using department at different time points as the decision variables;

[0066] S13, Constraints, consider the total amount of water resources constraints, that is, the total amount of water used by each region and department cannot exceed the available amount of water resources in the basin;

[0067] Meanwhile, the water resource related data in step S10 include river runoff, precipitation, evaporation and soil moisture;

[0068] S20, the application of the longhorn beetle search algorithm, first initializing the parameters, determining the number of longhorn beetle populations, setting the maximum number of iterations of the algorithm, determining the initial step size of the longhorn beetle search and the parameters related to the step size adjustment strategy, and then randomly generating an initial solution. In the feasible solution space, a set of initial decision variable values are randomly generated for each longhorn beetle individual, and the fitness value of each initial solution is calculated according to the constructed optimization model objective function;

[0069] It should be noted that when initializing parameters, the length of the beetle's body (step length) is initialized first. This parameter determines the distance the beetle moves each time it searches. If the step length is too large, the algorithm may skip the optimal solution, while if the step length is too small, the search speed will be too slow. For the optimal allocation of water resources in the Tarim River Basin, the step length needs to be determined based on the scale and complexity of the water resources system.

[0070] Search accuracy is used to determine the conditions for the algorithm to stop searching. That is, when the set search accuracy is reached, the algorithm considers that a sufficiently good solution has been found and stops. The search accuracy is usually set according to the requirements of the optimization results for the specific problem;

[0071] The maximum number of iterations is an upper limit set to prevent the algorithm from looping infinitely. The maximum number of iterations should be determined by comprehensively considering the complexity of the problem and the computing resources. For the optimal allocation of water resources in the Tarim River Basin;

[0072] Random seed: The random seed is used to initialize the random number generator to ensure the repeatability of the algorithm. If the same random seed is used in different runs, the initial population and search path of the algorithm will be the same, which facilitates comparison and analysis of the results.

[0073] The beetle's perception range parameter simulates the beetle's ability to perceive its surrounding environment and determines the range of its exploration of the surrounding solution space during the search process;

[0074] Population initialization: First, determine the population size, which is the number of individuals in the initial population. Then generate initial individuals. Each individual represents a possible water resource allocation plan, usually composed of a set of variables representing the water resource allocation of each water-using department or region. According to the actual situation of the Tarim River Basin, these variables can include the allocation of domestic water, agricultural water, industrial water, and ecological water. Finally, check and correct the initial individuals to ensure that they meet all constraints. If there are individuals that do not meet the constraints, they need to be corrected.

[0075] S30, updating the position of the longhorn beetle. For each longhorn beetle, the positions of its two tentacles are calculated according to the rules of the longhorn beetle whisker search algorithm, and the fitness values corresponding to the positions of the two tentacles of the longhorn beetle are calculated respectively. The longhorn beetle then moves towards the direction of the tentacles with better fitness values, and the position of the longhorn beetle is updated, that is, a new water resource allocation plan is obtained. Finally, the strategy is adjusted according to the step size of the algorithm.

[0076] It should be noted that for each longhorn beetle, an n-dimensional unit vector needs to be randomly generated at each iteration. Where n is the number of decision variables, this unit vector represents the search direction of the longhorn beetle, and the position of the tentacles is calculated. The longhorn beetle uses two tentacles to perceive the surrounding environment. Based on the current position of the longhorn beetle The positions of the two tentacles are determined by moving a certain distance in two opposite directions. Assuming the step length is δ, the position formulas of the two tentacles are:

[0077]

[0078] Wherein, the step size δ can be adjusted according to the number of iterations. It usually decreases gradually with the increase of the number of iterations to improve the search accuracy. In the initial stage, the step size can be set to a relatively large value, such as 0.1. As the iterations proceed, it can be gradually reduced according to a certain attenuation formula. The attenuation formula is as follows:

[0079]

[0080] Where, δ k is the step size of the kth iteration, δ0 is the initial step size, and K is the maximum number of iterations;

[0081] Fitness assessment: Calculate the fitness of the tentacle. Substitute the water resource allocation plan represented by the positions of the two tentacles into the previously constructed fitness function for calculation. In the ecologically based optimization of water resource allocation in the Tarim River Basin, the fitness function usually comprehensively considers multiple objectives such as ecological benefits, economic benefits, and social benefits.

[0082] Direction selection and movement, select the direction of movement, according to the fitness comparison results, the longhorn beetle chooses to move in the direction of the tentacles with better fitness, and updates the position of the longhorn beetle. The longhorn beetle moves a certain distance in the selected direction and updates its own position. The new position It can be calculated by the following formula:

[0083]

[0084] Where α is an adjustment coefficient (usually between 0 and 1) used to control the actual distance of each move. It is the optimal direction vector selected based on the fitness comparison results. In this way, the longhorn beetles gradually move to areas with better fitness and find better water resource allocation solutions;

[0085] Step size adjustment: In order to quickly explore a larger solution space in the early stage of the search and to finely search for the local optimal solution in the later stage, the step size needs to be adjusted with the number of iterations;

[0086] Repeat the iterations, repeating the above steps of updating the beetle's position, evaluating its fitness, selecting and moving its direction, and adjusting its step size, until the preset termination condition is met (such as reaching the maximum number of iterations or the fitness value converges to a certain accuracy);

[0087] S40, judging the termination condition: if the number of iterations reaches the preset maximum number of iterations, the algorithm stops. After the algorithm stops, the individual with the best fitness value is selected from the population. The corresponding decision variable value is the optimal water resource allocation plan, and the optimal plan is analyzed in detail;

[0088] It should be noted that, based on the number of iterations, a fixed number of iterations is set: a maximum number of iterations N is determined in advance. When the algorithm reaches this number, the algorithm is terminated and the number of iterations is adjusted based on the convergence situation. In addition to the fixed maximum number of iterations, the number of iterations can also be dynamically adjusted according to the convergence situation of the algorithm.

[0089] Based on the objective function value, based on the objective function value ε2, when the absolute value of the difference between the objective function values obtained in two adjacent iterations is less than ε2, it is considered that the algorithm has converged to a stable solution and meets the termination condition;

[0090] Based on the position change of the longicorn beetle, a position change threshold ε3 is set, and the change of the longicorn beetle position after each iteration is calculated. If the maximum position change of all longicorn beetle individuals is less than ε3 in several consecutive iterations, it means that the longicorn beetle population has basically stabilized and there is no obvious search progress, and the algorithm can be terminated.

[0091] S4. Plan formulation and evaluation: Based on the model established by the longicorn beetle search algorithm and combined with the actual situation of the basin, formulate a specific water resources optimization allocation plan and evaluate the formulated plan;

[0092] It should be noted that the plan was formulated to generate a preliminary plan based on the results of the optimization algorithm. Using optimization algorithms such as the longhorn beetle search algorithm, the water resources in the Tarim River Basin were optimized under the constraints of ecological water demand, total water resources, and water demand of various departments. The water resource allocation for each water-using department (such as agriculture, industry, domestic use, and ecology) in different regions and time periods was obtained.

[0093] Adjust the plan based on actual conditions, taking into account the temporal and spatial distribution characteristics of water resources. The Tarim River Basin has scarce precipitation and uneven temporal and spatial distribution. In summer, the melting of mountain snow and ice creates a flood season, while in winter, it is a dry season.

[0094] Program evaluation, water supply and demand balance assessment, calculation of water supply and demand for each region and department at different times, determination of whether water demand is met, analysis of water shortages or surpluses and their impact on economic and social development;

[0095] Ecological impact assessment, analyzing the impact of the plan on the Tarim River Basin ecosystem, including river ecology, wetland ecology, and vegetation ecology;

[0096] Socio-economic impact assessment: assess the impact of the plan on socio-economic development in the basin, analyzing agriculture, industry, daily life, etc. In agriculture, analyze the impact of the plan on crop yields and agricultural industrial structure adjustment to determine whether it is conducive to the sustainable development of agriculture;

[0097] S5. Plan implementation and monitoring feedback: Develop a detailed implementation plan based on the determined water resource optimization plan, establish a comprehensive water resource monitoring system, and conduct real-time monitoring of water resource quantities, water use processes, and ecological and environmental changes. Simultaneously, provide timely evaluation and feedback on the water resource optimization plan based on monitoring data and actual operation conditions.

[0098] It should be noted that the implementation of the plan requires the formulation of a detailed implementation plan. Based on the optimized allocation plan, each task is broken down into specific departments and links, and time nodes for each task are set to create a timetable. For new water conservancy projects, the time for each stage, including project preparation, construction, and final acceptance, should be planned.

[0099] For project construction and facility operation, a detailed implementation plan is formulated. Based on the optimized configuration plan, each task is broken down into specific departments and links, and time nodes for each task are set. A timetable is drawn up. For new water conservancy projects, the time for each stage, including project preparation, construction, and final acceptance, is planned;

[0100] Project construction and facility operation: Promote the construction of relevant water conservancy projects according to the requirements of the plan, establish a scientific water conservancy facility operation and management system, ensure smooth water resource allocation, and rationally dispatch reservoir water release and channel water delivery based on real-time water conditions and water demand information;

[0101] Policy support and public participation. The government has introduced relevant policies to provide support for the optimal allocation of water resources, strengthened publicity and education, and raised the awareness of residents in the basin about water resource protection and optimal allocation. By organizing publicity activities and conducting water-saving education, the government guides the public to form a water-saving awareness, encourages the public to participate in water resource supervision, and report water waste and pollution.

[0102] Example 2

[0103] refer to Figure 1 As shown, the second aspect of the present invention provides an ecologically-based Tarim River Basin water resources optimization configuration system, which is applicable to the ecologically-based Tarim River Basin water resources optimization configuration method, and is characterized by comprising:

[0104] Data collection and monitoring module: used to collect various water resources related data in the Tarim River Basin in real time;

[0105] Data processing and analysis module: used to organize, store, clean and analyze the massive amount of collected data, remove noise and erroneous data, interpolate and repair missing data, and extract valuable information and features;

[0106] Water resources evaluation module: used to evaluate the water resources quantity, water resources quality, and the degree of water resources development and utilization in the Tarim River Basin;

[0107] Ecological water demand calculation module: used to calculate the water demand of different ecosystem types based on the ecosystem characteristics and needs of the Tarim River Basin;

[0108] Optimization configuration model module: used to establish a water resources optimization configuration model and solve the optimal water resources configuration plan through the beetle whisker search algorithm;

[0109] Scheme generation and evaluation module: used to generate water resource allocation schemes under various scenarios based on the solution results of the optimization configuration model;

[0110] Decision support module: used to provide decision makers with decision support tools and information services.

[0111] Preferably, the various types of water resource related data include meteorological data, hydrological data, soil data, ecological data, and socioeconomic data;

[0112] Ecosystem types include river ecology, wetland ecology and vegetation ecology.

[0113] The circuits and controls involved in the present invention are all prior art and will not be described in detail here.

[0114] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for optimizing water resources allocation in the Tarim River Basin based on ecology, characterized in that: The following steps are involved: S1. Data collection and analysis: Collect hydrological data on precipitation, runoff, and evaporation in the Tarim River Basin, as well as data on the amount of water resources in rivers, lakes, and groundwater and their temporal and spatial distribution. Collect socioeconomic data on the basin's population, economic development, industrial structure, and water quotas. Use statistical analysis and geographic information systems to organize and analyze the collected data. S2. Goal setting and constraint determination: With the maintenance of the stability of the Tarim River Basin ecosystem as the core, determine ecological protection goals, and set reasonable economic growth targets based on the basin's socio-economic development plan, while also determining constraints; S3. Establish a water resources optimization configuration model. According to the characteristics and research objectives of the Tarim River Basin, and through the longhorn beetle beard search algorithm, the water resources optimization configuration model is constructed. First, the system boundary is clarified and the relevant data of the Tarim River Basin are collected. After the collection is completed, the optimization model can be constructed, and then the parameters and population initialization are performed. At the same time, the iterative search process is carried out. If the number of iterations reaches the preset maximum number of iterations, the algorithm stops. After the algorithm is carried out, the results are output and analyzed; S4. Plan formulation and evaluation: Based on the model established by the longicorn beetle search algorithm and combined with the actual situation of the basin, formulate a specific water resources optimization allocation plan and evaluate the formulated plan; S5. Plan implementation and monitoring feedback: According to the determined water resources optimization allocation plan, a detailed implementation plan will be formulated, and a complete water resources monitoring system will be established to conduct real-time monitoring of water resources, water use processes, and ecological and environmental changes. At the same time, based on the monitoring data and actual operation conditions, the water resources optimization allocation plan will be evaluated and feedback will be provided in a timely manner.

2. The method for optimizing water resources allocation in the Tarim River Basin based on ecology according to claim 1 is characterized in that: The specific steps of constructing the water resources optimization configuration model by the longicorn beetle search algorithm include: S10. Problem Analysis and Model Construction: First, determine the geographical scope of the Tarim River Basin and clearly define the sub-regions it contains. At the same time, collect water resource data within the basin. After completing the collection of relevant data, construct an optimization model. S20, the application of the longhorn beetle search algorithm, first initializing the parameters, determining the number of longhorn beetle populations, setting the maximum number of iterations of the algorithm, determining the initial step size of the longhorn beetle search and the parameters related to the step size adjustment strategy, and then randomly generating an initial solution. In the feasible solution space, a set of initial decision variable values are randomly generated for each longhorn beetle individual, and the fitness value of each initial solution is calculated according to the constructed optimization model objective function; S30, updating the position of the longhorn beetle. For each longhorn beetle, the positions of its two tentacles are calculated according to the rules of the longhorn beetle whisker search algorithm, and the fitness values corresponding to the positions of the two tentacles of the longhorn beetle are calculated respectively. The longhorn beetle then moves towards the direction of the tentacles with better fitness values, and the position of the longhorn beetle is updated, that is, a new water resource allocation plan is obtained. Finally, the strategy is adjusted according to the step size of the algorithm. S40. Termination condition judgment: if the number of iterations reaches the preset maximum number of iterations, the algorithm stops. When the algorithm stops, the individual with the best fitness value is selected from the population. The corresponding decision variable value is the optimal water resource allocation plan, and the optimal plan is analyzed in detail.

3. The method for optimizing water resources allocation in the Tarim River Basin based on ecology according to claim 2 is characterized in that: The construction of the optimization model in step S10 specifically includes the following steps: S11, objective function, which takes maximizing ecological benefits, maximizing social and economic benefits, and maximizing water resource utilization efficiency as multi-objective construction functions; S12, decision variables, taking the water resource allocation of each region and each water-using department at different time points as the decision variables; S13. Constraints: Consider the total amount of water resources, that is, the total amount of water used by each region and department cannot exceed the available amount of water resources in the basin.

4. The method for optimizing water resources allocation in the Tarim River Basin based on ecology according to claim 3 is characterized in that: The water resource related data in step S10 include river runoff, precipitation, evaporation and soil moisture.

5. The method for optimizing water resources allocation in the Tarim River Basin based on ecology according to claim 4 is characterized in that: The constraints in step S2 include total water resource constraints, ecological water use constraints, water use efficiency constraints, and engineering facility constraints.

6. An ecologically based water resource optimization configuration system for the Tarim River Basin, applicable to the ecologically based water resource optimization configuration method for the Tarim River Basin according to any one of claims 1 to 5, characterized in that: include: Data collection and monitoring module: used to collect various water resources related data in the Tarim River Basin in real time; Data processing and analysis module: used to organize, store, clean and analyze the massive amount of collected data, remove noise and erroneous data, interpolate and repair missing data, and extract valuable information and features; Water resources evaluation module: used to evaluate the water resources quantity, water resources quality, and the degree of water resources development and utilization in the Tarim River Basin; Ecological water demand calculation module: used to calculate the water demand of different ecosystem types based on the ecosystem characteristics and needs of the Tarim River Basin; Optimization configuration model module: used to establish a water resources optimization configuration model and solve the optimal water resources configuration plan through the beetle whisker search algorithm; Scheme generation and evaluation module: used to generate water resource allocation schemes under various scenarios based on the solution results of the optimization configuration model; Decision support module: used to provide decision makers with decision support tools and information services.

7. The method for optimizing water resources allocation in the Tarim River basin based on ecology according to claim 6 is characterized in that: The various types of water resources-related data include meteorological data, hydrological data, soil data, ecological data, and socio-economic data; The ecosystem types include river ecology, wetland ecology and vegetation ecology.

Images