River basin water right marketization configuration method and device under water-sediment coupling constraint

Abstract

The invention provides a watershed water right marketization configuration method and device under water-sediment coupling constraint, and the method comprises the steps: constructing a water-sediment coupling constraint model which comprises a plurality of constraint conditions, and the constraint conditions are used for constraining the sediment transportation and deposition conditions in a water transportation process; establishing a multi-target water right optimization configuration model based on the importance of various water consumption subjects in the drainage basin and a preset water right distribution strategy; solving the multi-objective water right optimal configuration model by adopting a multi-objective evolutionary algorithm and constraint conditions, and generating a candidate water right configuration solution set; selecting a feasible solution set from the candidate water right configuration solution set based on constraint conditions; scoring each solution in the feasible solution set, and sorting according to a scoring result; and obtaining an optimal water right configuration solution set based on a sorting result. According to the method, the safety and ecological requirements of a watershed water-sediment system can be guaranteed while the water right is reasonably distributed.

Description

Technical Field

[0001] This invention relates to the field of water resources management technology, and in particular to a method and apparatus for market-based allocation of water rights in a river basin under the constraints of water-sediment coupling. Background Technology

[0002] Currently, water scarcity has become a major bottleneck restricting the economic and social development of river basins. To address this, the state is gradually promoting the construction of a water rights system and piloting water rights trading markets. Market-based allocation of water rights has become an important technical means to achieve optimized water resource utilization and integrated river basin management.

[0003] Traditional water resource allocation methods often employ administrative allocation, quota control, or optimization based on single factors such as water user efficiency and economic output, focusing on economic indicators like water input-output efficiency and water demand. However, these methods typically overlook the natural evolution of river systems, particularly failing to organically integrate water resource allocation with sediment transport processes. In reality, in rivers with high sediment content and complex hydraulic conditions, water transport is often accompanied by sediment transport and deposition. Excessive concentration of water resources or localized concentrated use can lead to a sudden increase in water volume in certain river sections, easily exceeding the river's sediment transport capacity and inducing secondary disasters such as siltation, erosion, or river ecological degradation, disrupting the water-sediment balance and affecting the stability of subsequent water supply. Especially in some typical water-sediment coupled basins, existing methods struggle to support system allocation decisions under the three constraints of "ecology-engineering-economy."

[0004] Current water rights allocation methods mostly focus on "water quantity adjustment" as their core objective. Existing technologies have significant shortcomings in the following key aspects: First, although ecological water use is gradually being considered, most are still limited to the perspective of "ecological water demand." Second, insufficient attention is paid to "ecological sediment demand" or "sediment transport capacity," and the ability to quantify sediment processes is weak. There is a lack of systematic modeling and constraint expression, making it difficult to predict and control the problem of "sedimentation caused by water" from the source. Third, the indirect impact of water rights market mechanisms and initial water rights redistribution behavior on the basin's sediment transport capacity, ecological sediment demand guarantee, and the sustainable and stable operation of rivers is ignored.

[0005] Therefore, there is an urgent need for a new method for market-based allocation of water rights in watersheds under the constraints of water-sediment coupling, which can transform from "water balance" to multi-objective coordinated allocation of "water-sediment-ecology", and open up a new path for water rights allocation that takes into account water-sediment coupling constraints, multi-objective optimization of water rights, and dynamic market-based allocation. Summary of the Invention

[0006] This invention provides a method and apparatus for market-based allocation of water rights in a watershed under water-sediment coupling constraints, which addresses the aforementioned problems in the prior art.

[0007] According to one aspect of the present invention, a method for market-based allocation of water rights in a river basin under water-sediment coupling constraints is provided, comprising: A water-sediment coupling constraint model is constructed, which includes multiple constraint conditions. These constraint conditions are used to constrain sediment transport and deposition during water conveyance. Based on the importance of various water users in the basin and the pre-set water rights allocation strategy, a multi-objective water rights optimization allocation model is established. The multi-objective evolutionary algorithm and the aforementioned constraints are used to solve the multi-objective water rights optimization configuration model and generate a set of candidate water rights configuration solutions. Based on the aforementioned constraints, a feasible solution set is selected from the candidate water rights allocation solution set; Each solution in the feasible solution set is scored, and then sorted according to the scoring results; The optimal water rights allocation solution set is obtained based on the sorting results.

[0008] Optionally, the constraints include at least the constraints on river sediment transport capacity, canal siltation risk, ecological sediment transport demand, and ecological flow at river cross-sections.

[0009] Optionally, the river channel sediment transport capacity constraint is used to reflect the maximum sediment transport volume that the river channel can carry per unit time, and is defined as:

[0010]

[0011] in: This represents the maximum sediment transport capacity of node i during time period t (kg / s). Let the water flow rate (m³) of node i in time period t be... 3 / s); River slope (dimensionless); m and n are empirical parameters obtained by fitting historical sediment transport observation data; The constraint on the risk of canal siltation is as follows:

[0012] in: Let be the average siltation thickness per unit area (m) of canal system i during time period t. Let i be the cross-sectional area of ​​canal system i (m²) 2 ); For the channel system i in time period sand inflow rate (kg / s or m³) 3 / s); For the channel system i in time period Sand output (kg / s or m³) 3 / s); This represents the maximum allowable siltation threshold for canal system i. t represents the length of the simulation period; i represents the canal segment number; t represents the current period. The ecological sediment transport demand constraint is as follows:

[0013] in: This represents the actual sediment transport at ecological section j during time period t. J represents the minimum ecological sediment transport requirement for ecological section j; J is the set of all key ecological control sections; J is the ecological section number.

[0014] Optionally, the establishment of a multi-objective water rights optimization allocation model based on the importance of various water users within the basin and pre-set water rights allocation strategies includes: At least the importance weight coefficients of various water users should be calculated based on their water use efficiency, water demand intensity, and socio-economic contribution weights. A multi-objective water rights optimization model is established by substituting the weight coefficients of various water users’ importance into a pre-set water rights allocation strategy.

[0015] Optionally, the importance weighting coefficients for various water users are as follows:

[0016] in: denoted as the comprehensive weight of water user i, used to reflect its priority or weight in the water rights allocation model; n represents the number of water users. For water user subject i, the water use efficiency index is used. The per capita water demand intensity index for the region where water user i is located; The per capita GDP contribution value of the region where water user i is located is an indicator; , , These are the weighting coefficients. ; The multi-objective function includes at least maximizing the economic benefits of unit water resource utilization, minimizing the differences in water rights allocation among various water users, and minimizing the regional water resource supply and demand deviation. Wherein, the maximization of economic benefits per unit of water resource utilization is:

[0017] in: This represents the overall water resource output benefit per unit of the system; The economic benefits (such as GDP output) generated by the i-th water user. Let be the water rights allocation for the i-th water user; n is the total number of water users. Minimize the differences in water rights allocation among various water users as follows:

[0018] In the formula, This indicates the degree of difference in water rights allocation among various water users; This represents the average water rights allocation. Minimize the regional water supply and demand imbalance:

[0019] in, This indicates the total deviation between supply and demand; Let be the water demand of the i-th water user.

[0020] Optionally, the co-evolution objective function of the multi-objective water rights optimization allocation model is:

[0021] In the formula, The utility function is a multi-objective benefit vector. The weighted sum; Let be the overall weight of water user i; n be the number of water users; and the water rights allocation for each water user is . .

[0022] Optionally, the step of using a multi-objective evolutionary algorithm and the constraints to solve the multi-objective water rights optimization allocation model and generate a candidate water rights allocation solution set includes: The improved NSGA-III algorithm is used to find the co-evolution objective function of the solution; a market adjustment function is introduced. , represents the unit water price adjustment for water user i in the h-th round of the game. The water user adjusts its simulated water usage behavior based on its marginal revenue and marginal cost:

[0023] in: This represents the water rights adjustment amount for water user i in the next round. To adjust the step size and control the degree of evolution; if This would reduce the amount of water rights allocated. Conversely, it increases the amount of water rights allocated. ; If the water-sediment coupling constraint boundary conditions are violated, then the utility function Introducing a local penalty term, the formula can be expressed as:

[0024] in, This is the penalty intensity coefficient; This represents the violation of the constraints by the i-th water user in the l-th dimension. This indicates the severity or extent of the violation; The final solution set F0 for candidate water rights allocation is obtained.

[0025] Optionally, selecting a feasible solution set from the candidate water rights allocation solution set based on the constraints includes: Determine each configuration solution in the candidate water rights configuration solution set. Does it meet the minimum ecological sediment transport guarantee threshold and maximum sediment transport capacity requirements? If the constraints are met, then define a feasible region screening function. ,otherwise, This allows for the construction of a set of feasible solutions after filtering. .

[0026] Optionally, scoring each solution in the feasible solution set and sorting them according to the scoring results includes: For each configuration solution Construct a three-dimensional sustainable operation scoring system encompassing flood control and sediment transport, ecological environment, and socio-economic factors:

[0027] in: As a scoring vector for sustainable flood and sediment transport operation, It is calculated based at least on the river's sediment transport capacity and the canal system's siltation risk function; As a scoring vector for sustainable operation of the ecological environment, It is calculated based at least on ecological sediment transport requirements and the ecological flow function of the river cross-section; As a scoring vector for sustainable socio-economic operation, It is calculated based on at least the functions of maximizing the economic benefits of unit water resource output, minimizing the differences in water rights allocation among various water users, and minimizing the regional water resource supply and demand deviation.

[0028] According to another aspect of the present invention, a device for market-based allocation of water rights in a river basin under water-sediment coupling constraints is provided, comprising: The constraint construction unit is used to construct a water-sediment coupling constraint model, which includes multiple constraint conditions used to constrain sediment transport and siltation during water conveyance. The model building unit is used to establish a multi-objective water rights optimization allocation model based on the importance of various water users in the watershed and the pre-set water rights allocation strategy. The solution unit is used to solve the multi-objective water rights optimization configuration model using a multi-objective evolutionary algorithm and the constraints, and to generate a set of candidate water rights configuration solutions. The selection unit is used to select a feasible solution set from the candidate water rights configuration solution set based on the constraints. A scoring unit is used to score each solution in the feasible solution set and sort them according to the scoring results; The optimal solution acquisition unit is used to obtain the optimal water rights configuration solution set based on the sorting results.

[0029] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to execute the watershed water rights market allocation method under water-sediment coupling constraints according to any embodiment of the present invention.

[0030] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement the watershed water rights market allocation method under water-sediment coupling constraints as described in any embodiment of the present invention.

[0031] The technical solution of this invention constructs a water-sediment coupling constraint model by including constraints to constrain sediment transport and deposition during water conveyance. Based on the importance of various water users within the basin and pre-defined water rights allocation strategies, a multi-objective water rights optimization configuration model is established, enhancing the scientific rigor and feasibility of the configuration scheme. By employing a multi-objective evolutionary algorithm and constraints, the multi-objective water rights optimization configuration model is solved, generating a candidate water rights configuration solution set. Based on the constraints, feasible solutions are selected from the candidate water rights configuration solution set. Each solution in the feasible solution set is scored, and the solutions are ranked according to the scoring results. The optimal water rights configuration solution set is obtained based on the ranking results, thereby achieving real-time feedback and correction in the solution process, ensuring the safety of the basin's water and sediment system and preventing the violation of the rigid constraints of the ecological red line.

[0032] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a flowchart of a watershed water rights market allocation method under water-sediment coupling constraints provided in Embodiment 1 of the present invention; Figure 2 This is a flowchart of a watershed water rights market allocation method under water-sediment coupling constraints provided in Embodiment 2 of the present invention; Figure 3 This is a schematic diagram of a three-dimensional sustainable operation scoring system for flood control and sediment transport, ecological environment, and socio-economic development provided in one embodiment of the present invention; Figure 4 This is a schematic diagram of the Pareto candidate configuration solution set generated by the multi-objective evolutionary algorithm and the Pareto optimal solution set that satisfies the water-sand coupling constraint in one embodiment of the present invention. Figure 5 This is a structural diagram of a watershed water rights market allocation device under water-sediment coupling constraints according to Embodiment 3 of the present invention; Figure 6 This is a schematic diagram of the structure of an electronic device for implementing the water-sediment coupling constraint method for market-based allocation of water rights in a basin, as described in this embodiment of the invention. Detailed Implementation

[0035] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0036] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0037] Example 1 Figure 1 This document provides a flowchart of a watershed water rights market allocation method under water-sediment coupling constraints, as described in Embodiment 1 of the present invention. Figure 1 As shown, the method includes: S101. Construct a water-sediment coupling constraint model, which includes multiple constraint conditions used to constrain sediment transport and siltation during water conveyance.

[0038] The water-sediment coupling constraint model is used to quantitatively model the sediment transport capacity, siltation risk, and ecological sediment transport demand of river and canal systems within a watershed. This model includes multiple constraints to regulate sediment transport and siltation during water conveyance. For example, constraints may include river sediment transport capacity constraints, canal siltation risk constraints, ecological sediment transport demand constraints, and ecological flow constraints at river cross-sections. This embodiment is merely illustrative; other constraints may be used in practice to regulate sediment transport and siltation during water conveyance.

[0039] S102. Based on the importance of various water users in the basin and the pre-set water rights allocation strategy, establish a multi-objective water rights optimization allocation model.

[0040] It is important to clarify that a watershed is a macroscopic natural unit, a river channel is a natural water conveyance channel within the watershed, and a canal system is an artificially constructed water conveyance system. Specifically, a watershed is naturally formed, ranging in size from a few square kilometers of tributary basins to the basins of large rivers, such as the Yangtze River basin, spanning millions of square kilometers. A river channel is the specific water flow path within the watershed, varying in length from several kilometers to thousands of kilometers, conveying natural runoff (rainfall and snowmelt), serving as the "natural carrier" of water resources within the watershed; it also serves ecological, navigational, and flood control functions. A canal system is artificially constructed, ranging from single irrigation canals to irrigation networks covering several counties; it is a man-made water conveyance tool. Ultimately, through the combined efforts of rivers and canals, water resources are delivered to various water users.

[0041] Water users include businesses, farms, and other entities. This embodiment can employ various indicators to assess the importance of different water users, including water use efficiency, water demand intensity, and socioeconomic contribution weights. The pre-defined water rights allocation strategy can be a function that allocates water rights to each water user based on their importance; this function can be configured as needed. The multi-objective water rights optimization configuration model is based on the constructed multi-objective function and the importance of different water users to allocate water rights to each water user.

[0042] In one embodiment, the water rights allocation function for each water user can be jointly set according to a multi-objective function and the importance of various water users, that is, the water rights allocation for each water user is jointly determined by the multi-objective function and the importance of various water users.

[0043] S103. Using a multi-objective evolutionary algorithm and the aforementioned constraints, solve the multi-objective water rights optimization configuration model and generate a candidate water rights configuration solution set.

[0044] A multi-objective optimization algorithm can be used to solve the multi-objective water rights optimization configuration model. The solution process is constrained by multiple constraints in the water-sediment coupling constraint model, thereby adjusting the parameters in the multi-objective water rights optimization configuration model and performing iterative calculations. The calculation ends when the iteration stopping condition is met, and multiple water rights configuration solutions are obtained to construct a candidate water rights configuration solution set.

[0045] The multi-objective evolutionary algorithm used can be either an existing or an improved version; this embodiment does not impose any specific limitations. The objective function of the multi-objective water rights optimization allocation model can be constructed based on the importance of various water users and the pre-set water rights allocation strategy.

[0046] S104. Based on the constraints, select a feasible solution set from the candidate water rights configuration solution set.

[0047] In this embodiment, it can be determined whether each water rights allocation solution in the candidate water rights allocation solution set satisfies the constraint conditions. When the constraint conditions are satisfied, the water rights allocation solution can be regarded as a feasible solution, and then a feasible solution set can be constructed.

[0048] S105. Score each solution in the feasible solution set and sort them according to the scoring results.

[0049] In this embodiment, multiple indicators can be constructed to comprehensively score each solution, and each feasible solution can be ranked based on the comprehensive score. For example, the solutions can be ranked in descending order of score, with higher scores indicating that the feasible solution best meets the model's requirements. This leads to a water rights allocation scheme that meets the safety and ecological requirements of the watershed's water and sediment system. The scoring functions for each indicator can be set based on factors such as river sediment transport capacity, canal siltation risk, ecological sediment transport demand, river cross-section ecological flow, economic benefits per unit of water resource utilization, differences in water rights allocation among water users, and regional water supply and demand imbalances.

[0050] S106. Obtain the optimal water rights allocation solution set based on the sorting results. Based on the sorting results, multiple Pareto optimal solutions can be selected, which means multiple optimal water rights allocation schemes can be obtained.

[0051] The technical solution of this invention constructs a water-sediment coupling constraint model by including constraints to constrain sediment transport and deposition during water conveyance. Based on the importance of various water users within the basin and pre-defined water rights allocation strategies, a multi-objective water rights optimization configuration model is established, enhancing the scientific rigor and feasibility of the configuration scheme. By employing a multi-objective evolutionary algorithm and constraints, the multi-objective water rights optimization configuration model is solved, generating a candidate water rights configuration solution set. Based on the constraints, feasible solutions are selected from the candidate water rights configuration solution set. Each solution in the feasible solution set is scored, and the solutions are ranked according to the scoring results. The optimal water rights configuration solution set is obtained based on the ranking results, thereby achieving real-time feedback and correction in the solution process, ensuring the safety of the basin's water and sediment system and preventing the violation of the rigid constraints of the ecological red line.

[0052] Example 2 Figure 2 This is a flowchart illustrating a watershed water rights market allocation method under water-sediment coupling constraints, as provided in Embodiment 2 of the present invention. Figure 2 As shown, the method includes: S201. Construct a water-sediment coupling constraint model, which includes multiple constraint conditions used to constrain sediment transport and siltation during water conveyance.

[0053] In one embodiment, the constraints include at least the river channel sediment transport capacity constraint, canal system siltation risk constraint, ecological sediment transport demand constraint, and river cross-section ecological flow constraint.

[0054] Among them, the river channel sediment transport capacity constraint is used to reflect the maximum amount of sediment that the river channel can carry per unit time, which can be defined in this embodiment as:

[0055]

[0056] in: This represents the maximum sediment transport capacity of node i during time period t (kg / s). Let the water flow rate (m³) of node i in time period t be... 3 / s); River slope (dimensionless); , m, n are empirical parameters obtained by fitting historical sediment transport observation data.

[0057] The constraint on the risk of canal siltation is as follows:

[0058] in: Let be the average siltation thickness per unit area (m) of canal system i during time period t. Let i be the cross-sectional area of ​​canal system i (m²) 2 ); For the channel system i in time period sand inflow rate (kg / s or m³) 3 / s); For the channel system i in time period Sand output (kg / s or m³) 3 / s); This represents the maximum allowable siltation threshold for canal system i. t represents the simulation period length; i represents the canal segment number; and t indicates the current period. The canal siltation risk constraint sets a maximum permissible threshold for canal siltation risk by simulating the evolution of sediment deposition within the sediment transport channel. This threshold is used to limit high-risk schemes in the configuration solution space and prevent excessive siltation of the canal system.

[0059] The ecological sediment transport demand constraint is based on the sediment transport rate requirements of typical ecological sections. A spatiotemporally distributed lower limit boundary for ecological sediment transport is constructed, and the ecological sediment transport demand constraint can be expressed as:

[0060] in: This represents the actual sediment transport at ecological section j during time period t. J represents the minimum ecological sediment transport requirement for ecological section j; J is the set of all key ecological control sections; J is the ecological section number.

[0061] S202. Calculate the importance weight coefficients of various water users based at least on their water use efficiency, water demand intensity, and socio-economic contribution weights.

[0062] In one embodiment, the importance weighting coefficients for various water users are as follows:

[0063] in: denoted as the comprehensive weight of water user i, used to reflect its priority or weight in the water rights allocation model; n represents the number of water users. For water user subject i, the water use efficiency index is used. The per capita water demand intensity index for the region where water user i is located; The per capita GDP contribution value of the region where water user i is located is an indicator; , , These are weighting coefficients. Weight values ​​can be obtained using methods such as the analytic hierarchy process (AHP) and entropy weighting, or they can be manually set based on practical experience or policy preferences. Each weighting coefficient satisfies a normalization condition. .

[0064] S203. Based on the multi-objective function and the importance weight coefficients of various water users, the pre-set water rights allocation strategy is substituted to establish a multi-objective water rights optimization allocation model.

[0065] In this embodiment, the pre-defined water rights allocation strategy can be a function that allocates water rights to each water user based on the importance of each user. This water rights allocation function can be set as needed. The multi-objective water rights optimization configuration model is a model that allocates water rights to each water user based on the constructed multi-objective function and the importance of various water users.

[0066] Its multi-objective function includes at least maximizing the economic benefits of unit water resource utilization, minimizing the differences in water rights allocation among various water users, and minimizing the regional water resource supply and demand deviation.

[0067] In one embodiment, the economic benefit of unit water resource utilization is maximized as follows:

[0068] in: This represents the overall water resource output benefit per unit of the system; The economic benefits (such as GDP output) generated by the i-th water user. Let be the water rights allocation for the i-th water user; n is the total number of water users. Minimize the differences in water rights allocation among various water users as follows:

[0069] In the formula, This indicates the degree of difference in water rights allocation among various water users; This represents the average water rights allocation. Minimize the regional water supply and demand imbalance:

[0070] in, This indicates the total deviation between supply and demand; Let be the water demand of the i-th water user.

[0071] The function for allocating water rights to each water user can be:

[0072] For a multi-objective benefit vector, (such as economic benefits, water use equity, regional coordination, etc.); Let be the overall weight of water user i.

[0073] In one embodiment, it is assumed that the model has n water users, and the water rights allocation for each water user is... , Given the comprehensive weight of water users, the collaborative evolution objective function of the constructed multi-objective water rights optimization allocation model is:

[0074] In the formula, The utility function is a multi-objective benefit vector. The weighted sum; Let be the overall weight of water user i; n be the number of water users; and the water rights allocation for each water user is . .

[0075] S204. Using a multi-objective evolutionary algorithm and the aforementioned constraints, solve the multi-objective water rights optimization configuration model and generate a set of candidate water rights configuration solutions.

[0076] In one embodiment, a distributed multi-objective evolutionary algorithm, specifically an improved version of the NSGA-III algorithm, is used to solve the cooperative evolution objective function. The improved NSGA-III algorithm is a market-mechanism-based multi-agent cooperative evolutionary algorithm, possessing local optimum avoidance capabilities and water user behavior simulation functions. During algorithm execution, water users must simultaneously satisfy the constraints.

[0077] Introducing market adjustment function , represents the unit water price adjustment for water user i in the h-th round of the game. The water user adjusts its simulated water usage behavior based on its marginal revenue and marginal cost:

[0078] in: This represents the water rights adjustment amount for water user i in the next round. To adjust the step size and control the degree of evolution; if This would reduce the amount of water rights allocated. Then proceed with the next iteration calculation; otherwise, increase the water rights allocation amount. Then proceed with the next iteration calculation.

[0079] When the constraints in the water-sediment coupling constraint model are violated during the solution process, the utility function... Introducing a local penalty term, the formula for introducing a local penalty term can be expressed as:

[0080] in, This is the penalty intensity coefficient; This refers to the violation of the i-th water user in the l-th dimension of the constraints (in this embodiment, this may include four dimensions, such as river sediment transport capacity, canal siltation risk, ecological sediment transport demand, and river cross-section ecological flow requirements). This indicates the severity or extent of the violation.

[0081] The final solution set F0 for candidate water rights allocation is obtained.

[0082] S205. Based on the constraints, select a feasible solution set from the candidate water rights configuration solution set.

[0083] In this embodiment, it can be determined whether each water rights allocation solution in the candidate water rights allocation solution set satisfies the constraint conditions. When the constraint conditions are satisfied, the water rights allocation solution can be regarded as a feasible solution, and then a feasible solution set can be constructed.

[0084] In one embodiment, step S205 includes determining each configuration solution in the candidate water rights configuration solution set. Does it meet the minimum ecological sediment transport guarantee threshold and maximum sediment transport capacity requirements? If the constraints are met, then define a feasible region screening function. ,otherwise, This allows for the construction of a set of feasible solutions after filtering. .

[0085] S206. Score each solution in the feasible solution set and sort them according to the scoring results.

[0086] In one embodiment, step S206 includes: for each configuration solution Construct a three-dimensional sustainable operation scoring system encompassing flood control and sediment transport, ecological environment, and socio-economic factors:

[0087] in: The scoring vector for sustainable operation of flood control and sediment transport (including but not limited to river sediment transport capacity and canal siltation risk); The scoring vector for sustainable operation of the ecological environment (including but not limited to ecological sediment transport demand and ecological flow requirements of river sections); This is a scoring vector for sustainable socio-economic operation (including maximizing economic benefits per unit of water resource output, water use equity, and coordinated regional development). The figure below illustrates the feasible solution set for water user i. The four configuration solutions are the sustainable operation score vector results in the three dimensions of flood control and sediment transport, ecological environment, and socio-economic aspects. For example... Figure 3 The example demonstrates the sustainable operation score vector results of four feasible solutions x1, x2, x3, and x4 in the feasible solution set F1 of water user i in three dimensions: flood control and sediment transport, ecological environment, and socio-economic aspects.

[0088] In this embodiment, a non-dominated ranking method can be used (i.e., when a configuration solution A is not inferior to configuration solution B in all score vector values ​​of the three-dimensional sustainable operation score, and is superior to configuration solution B in at least one vector dimension, configuration solution A is said to dominate configuration solution B) to compare the three-dimensional sustainable operation score vectors of all configuration solutions in F1. Through this ranking process, the Pareto optimal solution set F* is extracted, that is, F* is a subset of F1, and there is no other configuration solution other than F* that is superior to any configuration solution in F* in all score vector values ​​of the three-dimensional sustainable operation score; F* is then taken as the optimal configuration solution set.

[0089] S207. Obtain the optimal water rights allocation solution set based on the sorting results. Based on the sorting results, multiple Pareto optimal solutions can be selected, which means multiple optimal water rights allocation schemes can be obtained.

[0090] Figure 4 The diagram illustrates the Pareto candidate configuration solution set generated by the market-based multi-objective evolutionary algorithm and the Pareto optimal solution set that satisfies the water-sediment coupling constraint. In one embodiment, a dynamic risk feedback mechanism for transactions can also be introduced to predict and assess the risks of sediment transport and ecological supply disruption during the configuration process. If a preset risk threshold is triggered, an automatic intervention strategy is activated, including limiting the volume of water rights transactions, freezing transactions, or revising the configuration plan.

[0091] Specifically, the dynamic risk feedback mechanism for transactions includes real-time prediction and analysis of potential sediment transport and ecological supply disruption risks that may arise after the implementation of the allocation plan in the watershed. This risk assessment is based on one or more of the following indicators: a. the flow-to-sediment ratio of the adjusted river section, b. the water demand guarantee rate of downstream ecological functional zones, c. the frequency of historical flow interruption events, and d. the changing trend of sediment concentration at key nodes.

[0092] The technical solution of this invention introduces a water-sediment coupling constraint model, comprehensively considering the river's sediment transport capacity, canal siltation risk, and ecological sediment transport needs, and constructs a multi-objective water rights optimization allocation model. This achieves dynamic coordination and synergistic optimization of water use efficiency improvement, economic benefits maximization, water-sediment balance, and ecological protection goals, significantly improving the scientific nature and feasibility of the allocation scheme. By establishing a "dynamic water market allocation mechanism" with water-sediment constraints as the entry condition, and introducing a dynamic feedback mechanism for transaction risks and an automatic intervention strategy for violations, it can accurately identify sediment transport risks and ecological supply disruptions that may occur during water rights transactions. Through threshold judgment and transaction limit setting, it can achieve real-time feedback and correction, ensuring the safety of the basin's water-sediment system and preventing the rigid constraints of the ecological red line from being breached.

[0093] Example 3 Figure 3 This is a schematic diagram of a watershed water rights market allocation device under water-sediment coupling constraints provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes: The constraint construction unit 301 is used to construct a water-sediment coupling constraint model, which includes multiple constraint conditions. These constraint conditions are used to constrain sediment transport and siltation during the water conveyance process. Model building unit 302 is used to establish a multi-objective water rights optimization configuration model based on the importance of various water users in the basin and the pre-set water rights allocation strategy. The solution unit 303 is used to solve the multi-objective water rights optimization configuration model using a multi-objective evolutionary algorithm and the constraints, and to generate a set of candidate water rights configuration solutions. Selection unit 304 is used to select a feasible solution set from the candidate water rights configuration solution set based on the constraints; The scoring unit 305 is used to score each solution in the feasible solution set and sort them according to the scoring results; The optimal solution acquisition unit 306 is used to obtain the optimal water rights configuration solution set based on the sorting results.

[0094] The water-sediment coupling constraint basin water rights market allocation device provided in the embodiments of the present invention can execute the message data water-sediment coupling constraint basin water rights market allocation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0095] Example 4 Figure 6A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0096] like Figure 6 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0097] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0098] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a watershed water rights market allocation method under water-sediment coupling constraints.

[0099] In some embodiments, a method for market-based allocation of water rights in a watershed under water-sediment coupling constraints can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the water-sediment coupling constraint method for market-based allocation of water rights in a watershed described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform a water-sediment coupling constraint method for market-based allocation of water rights in a watershed by any other suitable means (e.g., by means of firmware).

[0100] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0101] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0102] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0103] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0104] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0105] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0106] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0107] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for market-based allocation of water rights in a river basin under water-sediment coupling constraints, characterized in that, include: A water-sediment coupling constraint model is constructed, which includes multiple constraint conditions. These constraint conditions are used to constrain sediment transport and deposition during water conveyance. Based on the importance of various water users in the basin and the pre-set water rights allocation strategy, a multi-objective water rights optimization allocation model is established. The multi-objective evolutionary algorithm and the aforementioned constraints are used to solve the multi-objective water rights optimization configuration model and generate a set of candidate water rights configuration solutions. Based on the aforementioned constraints, a feasible solution set is selected from the candidate water rights allocation solution set; Each solution in the feasible solution set is scored, and then sorted according to the scoring results; The optimal water rights allocation solution set is obtained based on the sorting results.

2. The method for market-based allocation of water rights in a basin under water-sediment coupling constraints according to claim 1, characterized in that, The constraints include at least the constraints on river sediment transport capacity, canal siltation risk, ecological sediment transport demand, and ecological flow at river cross-sections.

3. The method for market-based allocation of water rights in a basin under water-sediment coupling constraints according to claim 2, characterized in that, The river channel sediment transport capacity constraint is used to reflect the maximum sediment transport volume that a river channel can carry per unit time, and is defined as follows: in: This represents the maximum sediment transport capacity of node i during time period t; Let i be the water flow rate at node i during time period t; River slope; m and n are empirical parameters obtained by fitting historical sediment transport observation data; The constraint on the risk of canal siltation is as follows: in: The average siltation thickness per unit area of ​​canal system i during time period t; Let be the cross-sectional area of ​​canal system i; For the channel system i in time period sand inflow rate (kg / s or m³) 3 / s); For the channel system i in time period The amount of sand produced; This represents the maximum allowable siltation threshold for canal system i. t represents the length of the simulation period; i represents the canal segment number; t represents the current period. The ecological sediment transport demand constraint is as follows: in: This represents the actual sediment transport at ecological section j during time period t. J represents the minimum ecological sediment transport requirement for ecological section j; J is the set of all key ecological control sections; J is the ecological section number.

4. The method for market-based allocation of water rights in a basin under water-sediment coupling constraints according to claim 1, characterized in that, The aforementioned multi-objective water rights optimization allocation model is established based on the importance of various water users within the watershed and pre-set water rights allocation strategies, including: At least the importance weight coefficients of various water users should be calculated based on their water use efficiency, water demand intensity, and socio-economic contribution weights. A multi-objective water rights optimization model is established by substituting the weight coefficients of various water users’ importance into a pre-set water rights allocation strategy.

5. The method for market-based allocation of water rights in a basin under water-sediment coupling constraints according to claim 4, characterized in that, The importance weighting coefficients for each type of water user are as follows: in: denoted as the comprehensive weight of water user i, used to reflect its priority or weight in the water rights allocation model; n represents the number of water users. For water user subject i, the water use efficiency index is used. The per capita water demand intensity index for the region where water user i is located; The per capita GDP contribution value of the region where water user i is located is an indicator; , , These are the weighting coefficients. ; The multi-objective function includes at least maximizing the economic benefits of unit water resource utilization, minimizing the differences in water rights allocation among various water users, and minimizing the regional water resource supply and demand deviation. Wherein, the maximization of economic benefits per unit of water resource utilization is: in: This represents the overall water resource output benefit per unit of the system; The economic benefits generated by the i-th water user; Let be the water rights allocation for the i-th water user; n is the total number of water users. Minimize the differences in water rights allocation among various water users as follows: In the formula, This indicates the degree of difference in water rights allocation among various water users; This represents the average water rights allocation. Minimize the regional water supply and demand imbalance: in, This indicates the total deviation between supply and demand; Let be the water demand of the i-th water user.

6. The method for market-based allocation of water rights in a basin under water-sediment coupling constraints according to claim 5, characterized in that, The collaborative evolution objective function of the multi-objective water rights optimization allocation model is: In the formula, The utility function is a multi-objective benefit vector. The weighted sum; Let be the overall weight of water user i; n be the number of water users; and the water rights allocation for each water user is . .

7. The method for market-based allocation of water rights in a basin under water-sediment coupling constraints according to claim 6, characterized in that, The process of using a multi-objective evolutionary algorithm and the aforementioned constraints to solve the multi-objective water rights optimization allocation model and generate a candidate water rights allocation solution set includes: The improved NSGA-III algorithm is used to find the co-evolution objective function of the solution; a market adjustment function is introduced. , represents the unit water price adjustment for water user i in the h-th round of the game. The water user adjusts its simulated water usage behavior based on its marginal revenue and marginal cost: in: This represents the water rights adjustment amount for water user i in the next round. To adjust the step size and control the degree of evolution; if This would reduce the amount of water rights allocated. Conversely, it increases the amount of water rights allocated. ; If the water-sediment coupling constraint boundary conditions are violated, then the utility function Introducing a local penalty term, the formula can be expressed as: in, This is the penalty intensity coefficient; This represents the violation of the constraints by the i-th water user in the l-th dimension. This indicates the severity or extent of the violation; The final solution set F0 for candidate water rights allocation is obtained.

8. The method for market-based allocation of water rights in a river basin under water-sediment coupling constraints according to claim 7, characterized in that, The selection of a feasible solution set from the candidate water rights allocation solution set based on the constraints includes: Determine each configuration solution in the candidate water rights configuration solution set. Does it meet the minimum ecological sediment transport guarantee threshold and maximum sediment transport capacity requirements? If the constraints are met, then define a feasible region screening function. ,otherwise, This allows for the construction of a set of feasible solutions after filtering. .

9. The method for market-based allocation of water rights in a basin under water-sediment coupling constraints according to claim 1, characterized in that, The step of scoring each solution in the feasible solution set and sorting them according to the scoring results includes: For each configuration solution Construct a three-dimensional sustainable operation scoring system encompassing flood control and sediment transport, ecological environment, and socio-economic factors: in: As a scoring vector for sustainable flood and sediment transport operation, It is calculated based at least on the river's sediment transport capacity and the canal system's siltation risk function; As a scoring vector for sustainable operation of the ecological environment, It is calculated based at least on ecological sediment transport requirements and the ecological flow function of the river cross-section; As a scoring vector for sustainable socio-economic operation, It is calculated based on at least the functions of maximizing the economic benefits of unit water resource output, minimizing the differences in water rights allocation among various water users, and minimizing the regional water resource supply and demand deviation.

10. A device for market-based allocation of water rights in a river basin under water-sediment coupling constraints, characterized in that, include: The constraint construction unit is used to construct a water-sediment coupling constraint model, which includes multiple constraint conditions used to constrain sediment transport and siltation during water conveyance. The model building unit is used to establish a multi-objective water rights optimization allocation model based on the importance of various water users in the watershed and the pre-set water rights allocation strategy. The solution unit is used to solve the multi-objective water rights optimization configuration model using a multi-objective evolutionary algorithm and the constraints, and to generate a set of candidate water rights configuration solutions. The selection unit is used to select a feasible solution set from the candidate water rights configuration solution set based on the constraints. A scoring unit is used to score each solution in the feasible solution set and sort them according to the scoring results; The optimal solution acquisition unit is used to obtain the optimal water rights configuration solution set based on the sorting results.

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