Regional wetland carbon sink collaborative management method and system

Abstract

The invention provides a regional wetland carbon sink collaborative management method and system, and relates to the technical field of wetland management, and the method comprises the steps: obtaining remote sensing image data and geographic information data of a target region, and employing an object-oriented classification method to recognize wetland units; arranging a monitoring point at each wetland unit, and calculating the baseline carbon reserve of each wetland unit; establishing a convergence increasing potential evaluation system, and determining a convergence increasing potential upper limit of each wetland unit; constructing a cooperative relation matrix between the wetlands; establishing a synergistic effect calculation rule; establishing an optimization model, setting constraint conditions, and solving the optimization model by adopting an improved genetic algorithm to obtain an optimal management measure configuration scheme of each wetland unit; and implementing corresponding management measures on each wetland unit according to the optimal management measure configuration scheme. The technical problems that in the prior art, regional wetland carbon sink space configuration is unreasonable, a collaborative optimization method is lacked, and the carbon sequestration capacity improvement efficiency is low can be solved.

Description

Technical Field

[0001] This invention relates to the field of wetland management technology, and in particular to a method and system for the coordinated management of regional wetland carbon sequestration. Background Technology

[0002] Wetlands are one of the world's most important carbon sinks, playing a crucial role in the carbon cycle of terrestrial ecosystems. With the proposed goals of "carbon peaking and carbon neutrality," enhancing the carbon sequestration and absorption capacity of wetlands has become an important way to achieve emission reduction targets. Wetland carbon sink management involves the comprehensive application of multiple measures, including vegetation restoration, hydrological regulation, and pollution control. Traditional wetland carbon sink management often implements management measures independently for individual wetland patches, mainly determining management priorities based on indicators such as the degree of wetland degradation and area size. However, there are close connections between different wetland units within a region, such as hydrological connectivity, material cycling, and biological migration. Enhancing the carbon sequestration capacity of a single wetland can have a positive synergistic effect on surrounding wetlands. This synergistic effect is often overlooked in existing management models, leading to insufficient spatial rationality in the allocation of management measures.

[0003] Chinese patent application CN116842351A discloses a method for constructing a carbon sink assessment model for coastal wetlands. This method acquires meteorological data, near-ground image data of evolving and mature areas of coastal wetlands. It uses a first feature extraction network to extract static and temporal variation features of the evolving areas, and a second feature extraction network to extract meteorological features. These static, temporal, and meteorological features are then input into a maturity prediction model to obtain the maturity level of the evolving areas. Finally, the maturity level, meteorological features, and near-ground image data of the mature areas are input into an assessment model to obtain the carbon sink assessment results for the coastal wetlands. This patent improves the carbon sink assessment of evolving coastal wetland areas by considering the impact of the maturity level of the evolving areas on carbon sink capacity, thus improving the accuracy of the assessment. However, this patent does not address how to optimize the configuration of management measures for multiple wetland units at a regional scale, nor does it consider the impact of inter-wetland synergies on carbon sink increments. Summary of the Invention

[0004] In view of this, the present invention provides a method and system for coordinated management of regional wetland carbon sequestration. By assessing the carbon sequestration potential of each wetland, identifying the synergistic relationship between wetlands, and constructing an optimization model, the method maximizes the increase in regional carbon sequestration and achieves efficient resource allocation, thereby solving the technical problems of unreasonable spatial allocation of regional wetland carbon sequestration, lack of synergistic optimization methods, and low efficiency in improving carbon sequestration capacity in the prior art.

[0005] The technical solution of this invention is implemented as follows: On the one hand, the present invention provides a method for the coordinated management of regional wetland carbon sinks, comprising: S1. Acquire remote sensing image data and geographic information data of the target area, identify wetland units using an object-oriented classification method and obtain the boundary, area and type information of each wetland unit; set up monitoring points in each wetland unit, obtain carbon storage-related parameters of vegetation, soil and water through remote sensing monitoring and ground monitoring, and calculate the baseline carbon storage of each wetland unit. S2. Establish a carbon sequestration potential assessment system, determine the set of feasible management measures for each wetland unit, calculate the carbon sequestration increment of each wetland unit under different management measures, and determine the upper limit of carbon sequestration potential for each wetland unit. S3. Identify the hydrological connectivity, spatial proximity, and ecological corridor connectivity among wetlands, construct a matrix of synergistic relationships among wetlands, with matrix elements representing the synergistic impact coefficients between wetland pairs; establish rules for calculating synergistic effects, so that when wetlands implement management measures and obtain carbon sequestration increments, they can generate synergistic carbon sequestration increments for other wetlands through the synergistic impact coefficients. S4. Establish an optimization model with the objective function of maximizing the regional carbon sink increment. The carbon sink increment includes the carbon sink increment generated by the direct implementation of management measures in each wetland and the additional carbon sink increment generated by the synergistic relationship between wetlands. Set constraints and use an improved genetic algorithm to solve the optimization model to obtain the optimal management measure configuration scheme for each wetland unit. S5. Implement corresponding management measures for each wetland unit according to the optimal management measure configuration plan.

[0006] Preferably, after implementing management measures in step S5, the method further includes: Establish a dynamic carbon sink monitoring mechanism and conduct continuous monitoring using the deployed monitoring points. The dynamic monitoring mechanism includes regular remote sensing monitoring and ground monitoring at key time points. The actual carbon storage of each wetland unit at the monitoring time is calculated based on the monitoring data, and the actual cumulative increase of carbon sink in each wetland unit since the implementation of management measures and the total actual cumulative increase of carbon sink in the region are calculated. The actual carbon sequestration increment is compared and analyzed with the expected carbon sequestration increment, and the carbon sequestration realization rate of each wetland unit is calculated. When the overall carbon sequestration achievement rate is lower than the preset threshold or the regional carbon sequestration target is not achieved, the carbon sequestration potential assessment parameters and synergy matrix are updated based on the latest monitoring data, and the optimization solution of step S4 is re-executed to generate the adjusted optimal management measure configuration scheme.

[0007] Preferably, the specific method for setting up monitoring points in each wetland unit in step S1 is as follows: The total number of monitoring points is determined based on the area of ​​the wetland unit. Based on the spatial differentiation characteristics of carbon sinks, each wetland unit is divided into high carbon sink area, medium carbon sink area and low carbon sink area: Carbon sink spatial differentiation characteristic parameters of vegetation cover, topographic elevation and distance from water body are extracted for each wetland unit. Multi-threshold classification rules are used to classify the pixels that meet the conditions of vegetation cover greater than 0.6 and distance from water body less than 50 meters into high carbon sink area, the pixels that meet the conditions of vegetation cover between 0.3 and 0.6 or distance from water body between 50 and 150 meters into medium carbon sink area, and the remaining pixels into low carbon sink area. A stratified random sampling method was adopted to allocate monitoring points to three levels according to the proportions of 40% for high carbon sink areas, 40% for medium carbon sink areas, and 20% for low carbon sink areas. Within each level, random sampling was used to determine the specific spatial location of the monitoring points.

[0008] Preferably, the carbon sequestration potential assessment system established in step S2 includes four dimensions: vegetation restoration potential, soil carbon sequestration potential, hydrological regulation potential, and external disturbance control potential. The carbon sequestration increment of each wetland unit under different management measures includes vegetation carbon sequestration increment and soil carbon sequestration increment. The vegetation carbon sequestration increment is calculated by the difference between the target vegetation biomass and the current vegetation biomass after the implementation of management measures, root-to-stem ratio, vegetation carbon content, wetland area and time correction factor. The soil carbon sequestration increment is calculated by the difference between the target soil organic carbon content and the current soil organic carbon content of each soil layer after the implementation of management measures, soil bulk density, soil layer thickness, wetland area and soil organic carbon accumulation rate constant.

[0009] Preferably, the specific method for constructing the wetland synergy matrix in step S3 is as follows: Identify the hydrological connectivity between wetlands, including surface hydrological connectivity and groundwater hydrological connectivity. Surface hydrological connectivity is determined by extracting river systems and surface runoff paths using hydrological analysis tools, while groundwater hydrological connectivity is determined by calculating the Pearson correlation coefficient between the water level time series of the two wetlands. Identify the spatial proximity between wetlands by calculating the shortest distance between wetland boundaries and comparing it with a feature scale threshold; Identify the connectivity of ecological corridors between wetlands, and use the minimum cost path analysis method to identify ecological corridors connecting two wetlands; The synergistic impact coefficient is quantified using a comprehensive model based on multi-factor weighting, distance decay, and adjustment for sinking potential. The calculation formula is as follows: In the formula, Let be the synergistic influence coefficient of wetland i on wetland j; It is an indicator of hydrological connectivity intensity; As an indicator of ecological relevance; It is the distance decay function; The function representing the influence of the source wetland area; The influence function of the source wetland's potential for sequestration; and Let be the weighting coefficient, satisfying .

[0010] Preferably, the synergistic effect calculation rule established in step S3 is as follows: When wetlands gain carbon sequestration through management measures, it has a synergistic effect on other wetlands. The formula for calculating the synergistic carbon sequestration effect on other wetlands is as follows: In the formula, The amount of synergistic sinking received by wetland j; For the synergistic gain coefficient; Let be the synergistic influence coefficient of wetland i on wetland j; denoted as , where is the carbon sequestration increment of wetland i; and is the total number of wetland units. After considering the synergistic effect, the total carbon sink increment of wetland j during the planning period is equal to the sum of the carbon sink increment generated by its own direct implementation of management measures and the synergistic carbon sink increment received.

[0011] Preferably, the optimization objective function established in step S4 is: In the formula, For the total increase in regional carbon; Let k be the decision variable, representing whether management measures k are adopted for wetland i. The carbon sequestration increment of wetland i under management measure k; For the synergistic gain coefficient; Let be the synergistic influence coefficient of wetland j on wetland i; Let n be the number of management measures that can be selected for wetland i; n is the total number of wetland units. Let be the decision variable, representing whether management measures are adopted for wetland j. ; Management measures for wetlands The increase in carbon sequestration; The number of management measures available for wetland j; The constraints include resource budget constraints, carbon sequestration potential constraints, uniqueness constraints of management measures, and ecological security constraints. Resource budget constraints ensure that the total cost of implementing management measures for all wetlands does not exceed the total budget. Carbon sequestration potential constraints ensure that the carbon sequestration of each wetland does not exceed its upper limit of carbon sequestration potential. Uniqueness constraints of management measures ensure that each wetland must and can only choose one management measure. Ecological security constraints ensure that the ecological health index of each wetland after implementing management measures is not lower than the ecological security threshold. The ecological health index comprehensively considers the biodiversity index, water quality index, and habitat quality index.

[0012] Preferably, the improved genetic algorithm used in step S4 includes the following steps: Step 1: Initialize the population. Each individual represents a complete management plan. The number of the management measures selected for each wetland is represented by an integer encoding method. The initial population is generated by combining random generation with a greedy strategy based on the potential for increased sinking. Step 2: Calculate the fitness function. For each individual, check whether all constraints are met. If constraints are violated, penalties are applied. The fitness function includes the regional total carbon sink increment, the budget constraint violation penalty, and the ecological security constraint violation penalty. Its calculation formula is as follows: In the formula, For the s-th individual fitness value; For individuals The corresponding increase in total regional carbon sequestration; For individuals The corresponding total cost; For the total budget; This is the threshold for ecological security. For wetlands i in individuals Ecological health index under the corresponding scheme; and This is the penalty coefficient; Step 3: Use an improved tournament selection strategy to perform the selection operation. Randomly select a number of individuals from the population each time and calculate their fitness value and co-contribution. The co-contribution is defined as the proportion of the co-contribution of all wetlands in the corresponding scheme to the total contribution of the wetlands. Take fitness value and co-contribution into account to determine the selection probability. Step 4: Perform crossover operation using the single-point crossover operator. Randomly select a crossover point to exchange the chromosomes of two parent individuals to generate offspring individuals. After crossover, check whether the offspring individuals meet the constraints and repair them accordingly. Step 5: Adopt an adaptive mutation strategy based on cooperative relationships to perform mutation operations. The mutation probability is adaptively adjusted according to the individual fitness. During mutation, a wetland location is randomly selected, and several wetlands with strong cooperative relationships with that wetland are identified. Based on the management measures of the associated wetlands, the management measures of the current wetland are adjusted in a biased manner to enhance the cooperative effect. Step 6: Terminate the iteration when the maximum number of iterations is reached or the improvement of the optimal fitness value of the population over multiple generations is less than the threshold; otherwise, return to step 2 to continue the iteration. Step 7: Output the individual with the highest fitness value as the optimal solution to obtain the optimal management measures configuration scheme for each wetland unit.

[0013] The preferred, improved tournament selection strategy uses the following formula to calculate the selection probability: In the formula, 'a' represents a candidate individual in the tournament; 'h' is the index of the individual in the tournament. Let be the fitness value of individual a; The collaborative contribution of individual a; and q represents the weighting coefficients for fitness and collaborative contribution; q represents the tournament size; based on the calculated selection probability, a roulette wheel method is used to select parent individuals from the tournament individuals to enter the crossover pool.

[0014] In addition, the present invention also provides a regional wetland carbon sequestration collaborative management system to implement the above-described method.

[0015] The present invention has the following advantages over the prior art: This invention, by constructing a synergistic relationship matrix among wetlands and quantifying synergistic impact coefficients, can capture the synergistic promoting effect of carbon sequestration enhancement in a single wetland on surrounding wetlands. This allows the optimization model to consider not only the direct carbon sequestration increment of each wetland but also the additional carbon sequestration increment generated by interactions between wetlands when configuring management measures, thereby improving the spatial rationality and overall effectiveness of regional-scale wetland carbon sequestration management. The invention employs an improved genetic algorithm to introduce synergistic contribution assessment and an adaptive mutation strategy based on synergistic relationships, enhancing the algorithm's ability to perceive the spatial correlation of wetlands and improving the quality and convergence efficiency of the optimization solution. By establishing a dynamic monitoring mechanism, management plans can be adjusted in a timely manner based on the deviation between the actual carbon sequestration enhancement effect and the expected target, realizing a shift from static planning to dynamic management and enhancing the practicality and adaptability of the method. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a diagram illustrating the technical implementation of the present invention; Figure 3 This is a flowchart of the algorithm of the present invention; Figure 4 This is a system framework diagram of the present invention. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0019] like Figure 1 As shown, the present invention provides a method for the coordinated management of regional wetland carbon sinks, comprising: S1. Acquire remote sensing image data and geographic information data of the target area, identify wetland units using an object-oriented classification method and obtain the boundary, area and type information of each wetland unit; set up monitoring points in each wetland unit, obtain carbon storage-related parameters of vegetation, soil and water through remote sensing monitoring and ground monitoring, and calculate the baseline carbon storage of each wetland unit. S2. Establish a carbon sequestration potential assessment system, determine the set of feasible management measures for each wetland unit, calculate the carbon sequestration increment of each wetland unit under different management measures, and determine the upper limit of carbon sequestration potential for each wetland unit. S3. Identify the hydrological connectivity, spatial proximity, and ecological corridor connectivity among wetlands, construct a matrix of synergistic relationships among wetlands, with matrix elements representing the synergistic impact coefficients between wetland pairs; establish rules for calculating synergistic effects, so that when wetlands implement management measures and obtain carbon sequestration increments, they can generate synergistic carbon sequestration increments for other wetlands through the synergistic impact coefficients. S4. Establish an optimization model with the objective function of maximizing the regional carbon sink increment. The carbon sink increment includes the carbon sink increment generated by the direct implementation of management measures in each wetland and the additional carbon sink increment generated by the synergistic relationship between wetlands. Set constraints and use an improved genetic algorithm to solve the optimization model to obtain the optimal management measure configuration scheme for each wetland unit. S5. Implement corresponding management measures for each wetland unit according to the optimal management measure configuration plan.

[0020] like Figure 2As shown, the technical implementation process of this invention is as follows: 1) Construction of a regional wetland unit identification and monitoring system: acquiring remote sensing images and geographic information data, identifying wetland units using an object-oriented classification method, deploying stratified random monitoring points based on the spatial differentiation characteristics of carbon sinks, and calculating the baseline carbon storage of each wetland unit through ground surveys and remote sensing inversion; 2) Assessment of wetland carbon sink enhancement potential: establishing a four-dimensional assessment system of vegetation restoration, soil carbon sequestration, hydrological regulation, and external disturbance control, determining the set of feasible management measures for each wetland, calculating the increase in vegetation carbon sink and soil carbon sink under different management measures, and determining the upper limit of enhancement potential; 3) Identification and quantification of inter-wetland synergistic relationships: identifying the hydrological connectivity, spatial proximity, and ecological corridor connectivity between wetlands, and adopting multi-factor... 4) A comprehensive model integrating sub-weighting, distance decay, and carbon sequestration potential adjustment is used to quantify the synergistic impact coefficient and establish rules for calculating synergistic carbon sequestration; 5) A regional carbon sequestration increment maximization optimization model is constructed and solved, establishing a dual objective function including direct carbon sequestration and synergistic carbon sequestration, setting four types of constraints: resource budget, carbon sequestration potential, uniqueness of management measures, and ecological security, and using an improved genetic algorithm that incorporates synergistic contribution assessment and adaptive mutation strategy to solve the problem, obtaining the optimal management measure configuration scheme for each wetland unit; 6) The synergistic management scheme is implemented and dynamically monitored, with management measures implemented according to spatial priority, and the actual carbon sequestration increment is calculated by combining regular remote sensing monitoring and key time-point ground monitoring. When the carbon sequestration realization rate is low, the scheme is readjusted and optimized based on the latest data.

[0021] In one embodiment of the present invention, step S1 includes: Determine the geographical extent of the target area, and acquire multi-temporal remote sensing image data and geographic information data of the area. The remote sensing image data includes optical remote sensing images and synthetic aperture radar (SAR) images, and the geographic information data includes digital elevation model (DEM) data, land use data, and water system vector data. An object-oriented wetland classification method is used to identify wetland units within a region. Specifically, the method includes: first, preprocessing the remote sensing imagery, including radiometric, geometric, and atmospheric corrections; then, segmenting the imagery into several objects based on a multi-scale segmentation algorithm, setting the segmentation scale parameter to 50-100, the shape factor to 0.3-0.5, and the compactness to 0.5-0.7; next, extracting the spectral, texture, geometric, and water index features for each object, including the Normalized Difference Water Index (NDWI) and the Modified Normalized Difference Water Index (MNDWI); finally, using a Support Vector Machine (SVM) classifier or a Random Forest classifier to classify wetland types, identifying the wetland units within the region, determining the number of wetland units to be n, and obtaining the boundary vector data and area of ​​each wetland unit. (i=1,2,...,n) and wetland type information; Based on remote sensing imagery and geographic information data, spatial differentiation parameters of carbon sinks for each wetland unit were extracted. Normalized Variational Vegetation Index (NVA) was calculated from multispectral remote sensing imagery. and enhanced vegetation index The vegetation index was converted into vegetation cover using a pixel-based binary model. The conversion formula is: in The vegetation index value is for bare soil. The vegetation index value represents the area of ​​complete vegetation cover. Elev and slope information within each wetland are extracted from the DEM data. Based on the water boundary vector data extracted from remote sensing imagery, the distance from each pixel to the nearest water boundary is calculated using the Euclidean distance tool in GIS software. Generate a raster layer showing the distance from the water body; For each wetland unit, spatial differentiation analysis of carbon sinks was conducted based on vegetation cover, topographic elevation, and distance from water bodies, dividing the wetlands into three levels: high-carbon sink areas, medium-carbon sink areas, and low-carbon sink areas. The classification rule involved extracting spatial differentiation characteristic parameters of carbon sinks based on vegetation cover, topographic elevation, and distance from water bodies for each wetland unit, and employing a multi-threshold classification rule to classify units based on vegetation cover... Greater than 0.6 and distance from water body Pixels smaller than 50 meters are designated as high carbon sink zones, which will meet the requirements for vegetation cover. Between 0.3 and 0.6 or at a distance from the water body Pixels between 50 and 150 meters are designated as medium-carbon sink areas, and the remaining pixels as low-carbon sink areas. For wetlands with significant topographic relief, elevation factors must also be considered, prioritizing the designation of low-lying, waterlogged areas as high-carbon sink areas. The area proportions of the three levels within each wetland unit are calculated using GIS software and denoted as follows: , and ; Based on the spatial differentiation characteristics of wetland units, a monitoring point layout scheme was designed. The total number of monitoring points for each wetland unit was determined. The monitoring points were determined based on wetland area: 3 monitoring points for areas less than 10 hectares, 5 monitoring points for areas between 10 and 50 hectares, and 8 to 12 monitoring points for areas greater than 50 hectares. A stratified randomized allocation method based on spatial heterogeneity of carbon sinks was used, distributing monitoring points to three levels in a ratio of 40% for high-carbon sink areas, 40% for medium-carbon sink areas, and 20% for low-carbon sink areas. , , If the calculation result is a decimal, it is rounded to the nearest integer. Random sampling is used within each level to determine the specific spatial location of the monitoring points. A layered random point generation tool in the GIS software is used to randomly generate a corresponding number of monitoring point coordinates within each level area, ensuring that the minimum distance between monitoring points is greater than 50 meters to guarantee spatial independence. A spatial distribution map and coordinate list of monitoring points are output to guide the on-site deployment of monitoring points. According to the monitoring point deployment plan, field surveys and equipment installation were conducted at each monitoring point location to carry out baseline carbon sink background surveys. Soil profile samples were collected at the monitoring points, with sampling done in three layers: 0-10 cm, 10-30 cm, and 30-50 cm. Approximately 500 grams of soil sample were collected from each layer, and the organic carbon content of each layer was determined. (Unit: g / kg), Soil bulk density (Unit: g / cm³) 3 ), where d represents the soil depth; simultaneously, eddy covariance flux monitoring systems or static box method monitoring devices are deployed to monitor CO2 and CH4 fluxes and obtain baseline carbon flux data. and (Unit: μmol / (m)) 2 At each monitoring point, the quadratic method was used to investigate the vegetation community structure, record vegetation species, height, and cover, and measure the aboveground biomass of the vegetation. This data is used to verify the biomass data retrieved from remote sensing. In addition, water level monitoring equipment is deployed in various wetlands to obtain water level data. Data; water samples were collected and dissolved oxygen levels were measured. ,salinity Dissolved organic carbon concentration Water quality parameters; temperature obtained from weather stations ,precipitation Photosynthetically active radiation Meteorological data, etc., are used to construct a complete wetland environment monitoring dataset; Based on remote sensing data and ground monitoring data, the baseline carbon storage of each wetland unit was calculated. First, the spatial distribution of aboveground biomass in each wetland was estimated using the regression relationship between vegetation index and biomass. The regression model was as follows: Where a, b, and c are empirical coefficients calibrated based on wetland type and measured ground biomass data, representing the ground monitoring points. A regression model was established using the sample data, and the coefficients were determined using the least squares method. After the model was established, the NDVI raster data was substituted into the model to obtain the spatial distribution of biomass in the entire wetland. ; Baseline carbon storage The calculation formula is: in, The vegetation carbon storage of wetland i is expressed in tC. Soil carbon storage (unit: tC). Dissolved organic carbon reserves in water bodies (unit: tC); vegetation carbon storage The calculation formula is: in, Spatial average aboveground biomass (unit: g / m²) 2 This was obtained by averaging the biomass raster data of the entire wetland. The ratio of root to stem; Carbon content of vegetation; Wetland area (unit: m²) 2 );coefficient Used for unit conversion; Soil carbon storage The calculation formula is: in, The spatial average value of soil organic carbon content in the d-th layer (unit: g / kg) is obtained by calculating the arithmetic mean of the measured values ​​of samples from the same layer at each monitoring point. The spatial average of the bulk density of the d-th soil layer (unit: g / cm³) 3 ); The thickness of the d-th soil layer (unit: cm); coefficient Used for unit conversion; Dissolved organic carbon reserves in water bodies The calculation formula is: in, The concentration of dissolved organic carbon in water (unit: mg / L) is obtained through laboratory analysis of collected water samples. The volume of wetland water (unit: m³) 3 ), Calculation method For, among which The average water depth is expressed in meters (m). The percentage of water area; coefficient Used for unit conversion.

[0022] In one embodiment of the present invention, step S2 includes: Establish an assessment index system for the carbon sequestration potential of wetlands, including four dimensions: vegetation restoration potential, soil carbon sequestration potential, hydrological regulation potential, and external disturbance control potential. For each wetland unit, identify a set of feasible management measures. ,in The number of management measures available for wetland i. Management measures include, but are not limited to: vegetation restoration measures, including replanting native vegetation, natural restoration through enclosure, and removal of invasive species; water level control measures, including constructing sluice gates to control water levels, dredging ditches to improve hydrological connectivity, and adjusting the frequency of water replenishment and drainage; soil improvement measures, including applying organic fertilizers or biochar to increase soil organic matter, microbial inoculation to promote carbon fixation, and soil desalination or acidification treatment; and pollution control measures, including converting farmland back to wetlands to reduce human interference, reducing agricultural non-point source pollution input, and constructing ecological interception zones. A baseline option of not taking any measures is also provided. The corresponding increase in foreign exchange reserves is zero; A carbon sequestration potential calculation model is established to calculate the carbon sequestration increment of each wetland under different management measures. For wetland i, management measures are adopted... The increase in carbon sequestration during the planning period T years The calculation formula is: in, The increase in vegetation carbon sequestration (unit: tC), The increase in soil carbon sequestration (unit: tC); It should be noted that the carbon sequestration increment assessment of this invention focuses on two carbon pools: vegetation and soil. It does not separately consider the potential for increasing dissolved organic carbon (DOC) in water bodies for the following reasons: First, the DOC concentration in wetland water is mainly controlled by external inputs and internal decomposition processes, resulting in relatively small concentration changes and strong stability. Therefore, the incremental potential achievable through management measures is limited. Second, the actual carbon sequestration effect of DOC in water bodies depends on its final destination. Some DOC is released back into the atmosphere through microbial decomposition, and some is transported out of the wetland system with water flow. Only the portion that settles into the sediment and is buried for a long period constitutes a stable carbon sink, and its increase in carbon sequestration is difficult to quantify accurately. Third, conventional wetland management measures mainly achieve carbon sequestration by promoting vegetation growth and increasing soil organic matter content. The direct impact mechanism on DOC concentration in water bodies is unclear. Therefore, this invention focuses on the carbon storage in water bodies. It serves as a baseline assessment indicator, but the controllable increment of the water body carbon pool is not considered in the assessment of carbon sequestration potential and optimization decision-making. In dynamic monitoring, changes in water body DOC concentration are still continuously monitored as an auxiliary assessment indicator of the carbon cycle process in wetland ecosystems; Increase in vegetation carbon sequestration The calculation formula is: in, Management measures Target vegetation biomass after implementation (unit: g / m³) 2 The value is determined based on the wetland type and the type of measure. For vegetation restoration measures, the reference value for the natural wetland of that wetland type can be taken. Current vegetation biomass (unit: g / m³) 2 ), that is, the information obtained in step S1 ; The recoverable area ratio represents the percentage of wetland area that can be affected by management measures, with a value ranging from 0 to 1. This is a time correction factor used to convert vegetation restoration in the next T years into an equivalent increase in carbon sequestration. The calculation formula is as follows: , where r is the vegetation recovery rate constant, taking a value of 0.3 to 0.5 per year for rapidly recovering herbaceous wetlands and 0.1 to 0.2 per year for slower-recovering woody wetlands; coefficient Used for unit conversion; Soil carbon sequestration increase The calculation formula is: in, Management measures The target organic carbon content (unit: g / kg) of the soil in layer d after implementation shall be determined according to the soil type and management measures, and shall not exceed the organic carbon saturation content of the soil. The organic carbon content of the d-th soil layer is (unit: g / kg), which is the value measured in step S1; Soil bulk density (unit: g / cm³) 3 ); Soil layer thickness (unit: cm); Wetland area (unit: m²) 2 ); This represents the proportion of recoverable area. Let be the cumulative rate constant of organic carbon in the d-th soil layer (unit: year), with values ​​ranging from 0.08 to 0.15 for surface soil, 0.05 to 0.10 for middle soil, and 0.03 to 0.06 for bottom soil; T is the planning period (unit: year); coefficient Used for unit conversion; Determine the upper limit of the carbon sequestration potential for each wetland unit. The calculation formula is: That is, the carbon sequestration increment corresponding to the measure with the largest carbon sequestration increase among all feasible management measures is taken as the upper limit of the carbon sequestration potential of the wetland. At the same time, the type of management measure and the required cost to achieve the maximum carbon sequestration potential are recorded. And the carbon sequestration intensity per unit area corresponding to each management measure (Unit: tC / hm) 2 This indicator is used for calculating potential weights in subsequent collaborative relationship identification.

[0023] In one embodiment of the present invention, step S3 includes: The spatial relationships between wetlands are identified, including three aspects: hydrological connectivity, spatial proximity, and ecological corridor connectivity. For hydrological connectivity identification, based on the digital elevation model (DEM) and river system vector data obtained in step S1, hydrological analysis tools are used to extract river systems and surface runoff paths within the region to determine whether surface water connections exist between wetlands. If a runoff path exists between wetland i and wetland j with a length of less than 5 kilometers, they are considered to have surface hydrological connectivity. Simultaneously, based on the groundwater level monitoring data of each wetland in step S1... and The Pearson correlation coefficient of the water level time series of two wetlands is calculated to analyze the time-lag correlation of water level changes. If the correlation coefficient is greater than 0.6 and there is a clear water level gradient, it is considered to have groundwater connectivity. For spatial proximity identification, based on the wetland boundary vector data obtained in step S1, the Euclidean distance between any two wetland geocenters is calculated in GIS software. Simultaneously calculate the shortest distance to the wetland boundary. ,when Less than the feature scale threshold (Generally, a value of 2-5 kilometers) indicates that the two wetlands are considered to be spatially proximate. Regarding ecological corridor connectivity identification, based on the land use data and vegetation cover raster data obtained in step S1, the minimum cost path analysis method is used to identify ecological corridors connecting the two wetlands. Resistance factors include land use type (construction land has the highest resistance, forest and grassland have the lowest), vegetation cover (higher cover means lower resistance), and linear characteristics such as roads and rivers (highways have high resistance, rivers have low resistance). If there is a connection path between the two wetlands with a cumulative resistance cost less than a threshold, and the path width is greater than the minimum ecological corridor width (50-100 meters), then ecological corridor connectivity is considered present. Construct a collaborative relationship matrix R among wetlands. This is... A square matrix, matrix elements This represents the synergistic impact coefficient of wetland i on wetland j. The synergistic impact coefficient is quantified using a comprehensive model based on multi-factor weighting, distance decay, and sinking potential adjustment. The specific calculation formula is as follows: In the formula, Let be the synergistic influence coefficient of wetland i on wetland j; It is an indicator of hydrological connectivity intensity; As an indicator of ecological relevance; It is the distance decay function; The function representing the influence of the source wetland area; The influence function of the source wetland's potential for sequestration; and Let be the weighting coefficient, satisfying For wetlands dominated by hydrological connectivity (such as river wetlands and lake wetlands), take For wetlands where ecological connectivity is dominant (such as isolated marsh wetlands), take ; Hydrological connectivity strength index The calculation formula is: in, As an indicator of surface hydrological connectivity, if there is a surface runoff path between wetlands i and j, then... ,otherwise ; The groundwater connectivity index is calculated using the following formula: ,in The Pearson correlation coefficient is the time series of water levels in the two wetlands. The correlation threshold is set to 0.5; and The weighting coefficient is typically taken as... This indicates that the impact of surface hydrological connectivity is greater than that of groundwater hydrological connectivity. Ecological correlation index The calculation formula is: in, The species similarity coefficient is calculated using the Jaccard similarity coefficient, i.e. ,in and The number of species in wetlands i and j are respectively obtained by statistical analysis of vegetation survey data at each monitoring point in step S1. The number of common species; This is an indicator of ecological corridor connectivity; if an ecological corridor exists between two wetlands, then... ,in To accumulate resistance costs, For reference, the resistance cost is set at 10,000. If no ecological corridor exists, then... ; and As the weighting coefficient, this embodiment takes... ; Distance decay function Using the Gaussian decay model, the calculation formula is as follows: in, The distance between the centroids of wetlands i and j is in km. The characteristic distance scale (unit: km) represents the effective range of the synergistic effect, and is generally determined based on the scale of the study area. For small-scale areas (area less than 100 km²), the effective range is less than 100 km². 2 The value is taken as 2-3 km, for medium-scale regions (area 100-500 km²). 2 The value is taken as 3-5 km, for large-scale regions (areas greater than 500 km²). 2 The value is taken as 5-10 km; Source wetland area influence function This reflects the impact of the source wetland's own size on the synergistic effect, and the calculation formula is as follows: in, The area of ​​source wetland i (unit: hm²) 2 ), The average area of ​​all wetlands in the region (unit: hm²) 2 ), The area influence coefficient ranges from 0.2 to 0.4, indicating that the larger the wetland area, the stronger the synergistic influence on other wetlands, but the growth rate decreases. Influence function of source wetland sequestration potential This reflects the moderating effect of the source wetland's sequestration potential on the intensity of the synergistic effect. The calculation formula is as follows: in, The upper limit of the carbon sequestration potential of source wetland i (unit: tC), which is the value calculated in step S2; The average carbon sequestration potential of all wetlands in the region (unit: tC); The potential adjustment coefficient ranges from 0.3 to 0.5, indicating that the greater the carbon sequestration potential of a wetland, the stronger the synergistic promoting effect of its carbon sequestration increment on adjacent wetlands. Establish rules for calculating synergistic effects: When wetlands implement management measures and gain carbon sequestration increments, they generate synergistic carbon sequestration increases for other wetlands. The formula for calculating the synergistic carbon sequestration increase received by other wetlands is as follows: In the formula, The amount of synergistic sinking received by wetland j; For the synergistic gain coefficient; Let be the synergistic influence coefficient of wetland i on wetland j; Let be the carbon sink increment of wetland i; n be the total number of wetland units; the summation symbol represents the sum of the synergistic effects of all other wetlands on wetland j; the calculation rule for this synergistic effect is to use a weighted cumulative model to capture the synergistic effects of multiple source wetlands on the same recipient wetland, through the synergistic gain coefficient. Adjusting the overall strength of synergistic effects enables the optimization model to quantitatively assess the additional carbon sink increments generated by wetland interactions; After considering synergistic effects, the total carbon sequestration increment of wetland j during the planning period The calculation formula is: in, The increase in carbon sequestration obtained by wetland j through its own management measures m This refers to the additional carbon sink increase resulting from synergistic effects.

[0024] In one embodiment of the present invention, step S4 includes: To facilitate mathematical modeling, decision variables are defined. , indicating whether wetland i is subject to management measures k, when This indicates that management measures have been adopted. ,when This indicates that the management measure will not be adopted; only one management measure can be selected for each wetland, including the "no measure taken" option. In the implementation of the genetic algorithm, integer encoding is used to improve encoding efficiency. This indicates the measure number selected for wetland i, with a one-to-one correspondence between the two coding methods; Establish an optimization objective function with the goal of maximizing the regional carbon aggregate increment: In the formula, For the total increase in regional carbon; Let k be the decision variable, representing whether management measures k are adopted for wetland i. The carbon sequestration increment of wetland i under management measure k; For the synergistic gain coefficient; Let be the synergistic influence coefficient of wetland j on wetland i; Let n be the number of management measures that can be selected for wetland i; n is the total number of wetland units. Let be the decision variable, representing whether management measures are adopted for wetland j. ; Management measures for wetlands The increase in carbon sequestration; Let be the number of management measures available for wetland j; the first term represents the sum of the direct carbon sequestration increments from the management measures implemented by each wetland itself, where... The calculation results from step S2; the second term represents the additional carbon sink increase considering the synergistic effect between wetlands, where For the cooperative gain coefficient, Let R be the synergistic influence coefficient of wetland j on wetland i, derived from the synergistic relationship matrix R in step S3; Set the constraints as follows: Constraint 1, Resource Budget Constraint: in, Implement management measures for wetlands The required costs (unit: 10,000 yuan) include project implementation costs, material costs, labor costs, etc. For the "No action taken" option... Its cost ; Total budget (unit: 10,000 yuan); Constraint 2, Foreign Exchange Gain Potential Constraint: Ensure that the amount of sediment accumulation in each wetland does not exceed the maximum potential allowed by its physical and ecological conditions; Constraint 3, Uniqueness of Management Measures: Ensure that each wetland must have only one management measure, including the option of not taking any measures; Constraint 4, Ecological security constraint: in, For wetland i in implementing management measures The subsequent ecological health index comprehensively considers indicators such as biodiversity, water quality, and habitat quality, with basic data coming from the environmental monitoring dataset in step S1; An ecological security threshold of 0.6 to 0.7 is set to ensure that management measures do not lead to ecological function degradation. Ecological Health Index The calculation formula is: in, For biodiversity index, Water quality index, The three indices are normalized to the [0,1] range to represent the habitat quality index. , These are weighting coefficients, with values ​​of 0.4, 0.3, and 0.3 respectively. Biodiversity Index Based on the assessment of vegetation species richness, the calculation formula is as follows: in, Implement management measures for wetlands The expected number of species is derived from the vegetation survey data in step S1 and adjusted according to the type of management measures. This is the reference number of species for this wetland type; when the ratio exceeds 1, it is taken as 1. Water quality index Based on the assessment of the concentration of major pollutants in the water body, the calculation formula is as follows: in, , , Implement management measures for wetland i respectively The expected concentrations of total nitrogen, total phosphorus, and chemical oxygen demand (mg / L) are derived from the water quality monitoring data in step S1 and adjusted according to the type of management measures (pollution control measures can reduce pollutant concentrations, and water level control measures can reduce concentrations through the dilution effect). , , The water quality standard limit is determined by selecting the corresponding surface water environmental quality standard (such as Class III or Class IV standard) based on the wetland functional zoning. If the calculation result is less than 0, then 0 is taken. Habitat Quality Index Based on vegetation cover and hydrological stability assessments, the calculation formula is as follows: in, Implement management measures for wetlands The expected vegetation cover is derived from step S1 and adjusted according to management measures (vegetation restoration measures can increase cover). The water level fluctuation range (m) caused by management measures is used. For water level control measures, it is necessary to assess their impact on water level stability. When no control is implemented, the natural fluctuation value monitored in step S1 is taken. The water level fluctuation threshold is typically set at 0.5m. When fluctuations exceed this threshold, habitat quality declines. For the "No action taken" option... Ecological Health Index The baseline ecological health index calculated from the monitoring data in step S1 is used directly without adjustment.

[0025] An improved genetic algorithm is used to solve the above optimization model. The algorithm inputs include: the number of wetland units n and the wetland area provided in step S1. Baseline carbon storage Step S2 provides the carbon sequestration amount for each wetland management measure. Upper limit of foreign exchange increase potential Implementation costs Step S3 provides the collaborative relationship matrix R (i.e., all...). Value), cooperative gain coefficient ; and constraint parameters and The algorithm output includes: the optimal combination of decision variables. Optimal management measures for each wetland, and the total regional carbon sequestration increment. Carbon sequestration increment allocation of each wetland, spatial priority distribution map, and resource allocation scheme; like Figure 3 As shown, the specific solution steps of the improved genetic algorithm are as follows: Step 1: Initialize the population. Each individual represents a complete management plan, encoded using integers, and each individual is represented as a vector. ,in This represents the management measure number selected by wetland i in the s-th individual. Indicates that no measures will be taken. This indicates that wetland i selects the k-th management measure. Set the population size to [value]. The value is 50-100. The population is initialized using a combination of random generation and heuristic generation. 70% of the individuals are generated completely randomly, and 30% of the individuals are generated using a greedy strategy based on the potential for increasing carbon sinks. That is, management measures are allocated to wetlands with high potential for increasing carbon sinks and high cost-effectiveness. Step 2: Calculate the fitness function. For each individual, check whether all constraints are met. If constraints are violated, penalties are applied. The fitness function includes the regional total carbon sink increment, the budget constraint violation penalty, and the ecological security constraint violation penalty. Its calculation formula is as follows: In the formula, For the s-th individual fitness value; For individuals The corresponding increase in total regional carbon sequestration; For individuals The corresponding total cost; For the total budget; This is the threshold for ecological security. For wetlands i in individuals Ecological health index under the corresponding scheme; and This is the penalty coefficient; the penalty coefficient should be large enough to ensure that the feasible solution is better than the infeasible solution. It is 2 to 5 times the average increase in carbon sequestration. This is 3 to 10 times the average increase in carbon sequestration. Step 3: An improved tournament selection strategy is used. Each time, q individuals are randomly selected from the population (the tournament size q ranges from 3 to 5), and their fitness and co-contribution are calculated. Co-contribution Defined as the proportion of synergistic carbon sequestration generated by all wetlands in scheme a for individual a to the total carbon sequestration: in This represents the collaborative contribution of the a-th individual; This indicates an indicator function, which is 1 if individual j selects a management measure, and 0 otherwise; This represents the carbon sequestration increment generated by the actual management measures selected by wetland j in the corresponding scheme of individual a; Let R be the synergistic influence coefficient of wetland j on wetland i, derived from the synergistic relationship matrix R in step S3; For individual a, the total regional carbon sequestration increment; In tournament selection, fitness value and collaborative contribution are considered together, and the selection probability is determined. The calculation formula is: Where 'a' represents a candidate individual in the tournament; and 'h' is the index of the individual in the tournament. Let be the fitness value of individual a; The collaborative contribution of individual a; and The weighting coefficients for fitness and collaborative contribution are taken as follows: Based on the calculated selection probabilities, a roulette wheel method is used to select parent individuals from tournament individuals to enter the crossover pool; Step 4: Perform crossover using the single-point crossover operator. Randomly select a crossover point to exchange the chromosomes of two parent individuals, generating two offspring individuals. The crossover probability is... Set to 0.7 to 0.85. After crossover, it is necessary to check whether the offspring individuals meet the constraints. If the constraints are violated, remediation is carried out. The remediation strategy is as follows: if the total cost exceeds the budget, start with wetlands with low cost-effectiveness and change their management measures to no measures until the budget constraints are met; if the ecological security constraints are violated, the management measures that lead to an excessively low ecological health index will be replaced with eco-friendly measures. Step 5: Perform mutation operations using an adaptive mutation strategy based on cooperative relationships. For each individual in the population, the mutation probability is calculated. The mutation is performed on the material, and the mutation probability is adjusted using an adaptive strategy. The calculation formula is as follows: in, Let be the mutation probability of the s-th individual. and These represent the minimum and maximum mutation probabilities, with values ​​of 0.01 and 0.10, respectively. Let be the fitness value of individual s. This represents the current maximum fitness value of the population. This represents the current average fitness value of the population. This formula indicates that individuals with lower fitness have a higher probability of mutation, which is beneficial for increasing population diversity. During mutation, a wetland location is randomly selected, and several wetlands with the strongest cooperative relationship with that wetland are identified (based on the cooperative influence coefficient from step S3). If the top 3 wetlands have already selected high carbon sequestration measures, then we tend to select high carbon sequestration measures for the current wetland as well to enhance the synergistic effect; otherwise, we consider reducing the investment. The specific variation method is to randomly select a new measure different from the current measure from the set of optional management measures for the wetland and replace it. Step 6: Set the maximum number of iterations The number of generations is 200 to 500, and a convergence criterion is set: if the improvement of the optimal fitness value of the population is less than 0.1% for 20 consecutive generations, the algorithm is considered to have converged and the iteration is terminated early; otherwise, return to step two to continue the iteration. Step 7: Output the optimal solution. After the algorithm terminates, the individual with the highest fitness value is output as the optimal solution. Decoding yields the optimal management measures for each wetland. Calculate the total increase in regional carbon sequestration Generate a carbon sequestration increment allocation table for each wetland, draw a spatial priority distribution map, and formulate a resource allocation plan to clarify the implementation sequence and funding allocation for each wetland management measure; The core of this improved genetic algorithm lies in the introduction of a collaborative contribution evaluation mechanism and an adaptive mutation strategy based on collaborative relationships. The collaborative contribution evaluation ensures that the selection operation not only focuses on the total carbon sink increment of individuals but also emphasizes the degree of contribution of collaborative effects among wetlands, thereby guiding the algorithm to evolve towards schemes with high collaborative benefits. The adaptive mutation strategy utilizes the collaborative relationship matrix constructed in step S3, prioritizing the adjustment of wetlands with strong collaborative relationships with high carbon sink wetlands during mutation, enhancing the algorithm's ability to perceive spatial correlations and improving solution quality and convergence efficiency.

[0026] In one embodiment of the present invention, step S5 includes: Based on the optimization results of step S4, corresponding management measures are implemented in each wetland unit according to spatial priority. The spatial priority is based on the contribution of each wetland to carbon sequestration increment, with wetlands with higher contributions being implemented first. At the same time, the continuity of geographical location is considered, and for adjacent wetlands with strong synergistic relationships, synchronous or sequential implementation strategies are adopted to maximize the synergistic effect.

[0027] In one embodiment of the present invention, the method further includes: A dynamic carbon sequestration monitoring mechanism will be established, utilizing the monitoring point system deployed in step S1 to conduct continuous monitoring after the implementation of management measures. This mechanism comprises two subsystems: regular remote sensing monitoring and ground-based monitoring at key time points. For regular remote sensing monitoring, multispectral remote sensing images of the study area will be acquired quarterly, and vegetation parameters for each wetland, including NDVI, EVI, and vegetation cover, will be extracted using the same methods as in step S1. Biomass AGB was estimated using a calibrated regression model, and vegetation recovery was monitored by time-series changes in vegetation parameters. SAR images were acquired every six months to monitor changes in wetland hydrological conditions, including parameters such as water area and flooding frequency. For ground monitoring at key time points, ground re-measurements were conducted at the monitoring points established in step S1 at the 3rd, 6th, 12th, and 24th months after the implementation of management measures, and soil samples were collected to determine soil organic carbon content. Carbon flux was determined using the eddy covariance method or the static box method. and Investigate vegetation community structure and measure biomass. Obtain water level Data on environmental factors such as water quality; Based on monitoring data, the actual carbon storage of each wetland at monitoring time t was calculated. The calculation method and steps in S1 The calculation method is the same, using the latest parameter values ​​at the monitoring time and substituting them into the formula. Specifically, the calculation is as follows: First, based on the measured biomass values ​​at the ground monitoring points... The parameters of the remote sensing biomass inversion model were updated, and then the distribution of total wetland biomass was calculated using the updated model and remote sensing images at the monitoring time. The results were then substituted into the vegetation carbon storage formula to calculate... Based on the soil organic carbon content measured at ground monitoring points Calculate the average and substitute it into the soil carbon storage formula. Based on the dissolved organic carbon concentration of the water sample analysis and water level monitoring values calculate Finally, summing the results yields... ; Calculate the actual cumulative increase in carbon sequestration for each wetland since the implementation of management measures: The total actual cumulative increase in carbon sequestration in the calculation area: The actual carbon sequestration increment is compared with the carbon sequestration increment expected by the optimization model in step S4, and the carbon sequestration realization rate of each wetland is calculated: in, The expected carbon sequestration increment of wetland i in the optimization results of step S4 includes both self-sinking and synergistic sinking. When the sinking realization rate... When the rate is between 80% and 120%, the management effect is considered to be in line with expectations; when When this occurs, it indicates that the foreign exchange increase effect is less than expected, requiring analysis of the reasons and consideration of adjustments to management measures; when This indicates that the effect of increasing carbon dioxide emissions exceeded expectations and can provide experience and reference for other wetlands; Through a dynamic monitoring mechanism, the dynamic changes in regional wetland carbon sequestration can be grasped in real time, problems in the management process can be identified in a timely manner, and data support can be provided for the adjustment and optimization of management measures to ensure the effective implementation and continuous improvement of the collaborative management plan. When the monitoring results show that the overall carbon sequestration achievement rate is low or the regional carbon sequestration target is not achieved, the carbon sequestration potential assessment parameters in step S2 and the collaborative relationship matrix in step S3 can be updated based on the latest monitoring data, and the optimization solution in step S4 can be re-executed to generate an adjusted collaborative management plan, forming a closed-loop iterative adaptive management mechanism.

[0028] In addition, such as Figure 4 As shown, the present invention also provides a regional wetland carbon sequestration collaborative management system, comprising: The wetland unit identification and monitoring module is used to acquire remote sensing images and geographic information data, identify wetland units using an object-oriented classification method, determine the layout scheme of monitoring points based on the spatial differentiation characteristics of carbon sinks, collect ground monitoring data, and calculate the baseline carbon storage of each wetland unit. The carbon sequestration potential assessment module is used to establish an assessment system that includes vegetation restoration potential, soil carbon sequestration potential, hydrological regulation potential, and external disturbance control potential. It determines the set of management measures that can be implemented for each wetland, calculates the increase in vegetation carbon sequestration and soil carbon sequestration under different management measures, and determines the upper limit of carbon sequestration potential for each wetland. The collaborative relationship construction module is used to identify the hydrological connectivity, spatial proximity and ecological corridor connectivity between wetlands. It adopts a comprehensive model of multi-factor weighting, distance attenuation and sinking potential adjustment to quantify the collaborative impact coefficient, construct a collaborative relationship matrix between wetlands and establish calculation rules for collaborative sinking. The optimization decision module is used to establish an optimization objective function that takes the maximization of regional carbon aggregate increment as the goal and considers direct carbon sequestration and synergistic carbon sequestration. It sets resource budget constraints, carbon sequestration potential constraints, management measure uniqueness constraints, and ecological security constraints. An improved genetic algorithm is used to solve the optimization model to obtain the optimal management measure configuration scheme for each wetland unit. The implementation and dynamic monitoring module is used to implement management measures according to spatial priority. It acquires dynamic carbon sink data through regular remote sensing monitoring and key time-point ground monitoring, calculates the actual carbon sink increment and the carbon sink achievement rate, and triggers parameter updates and scheme re-optimization when the carbon sink achievement rate is low or the regional carbon sink target is not achieved.

[0029] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for coordinated management of regional wetland carbon sequestration, characterized in that, include: S1. Acquire remote sensing image data and geographic information data of the target area, identify wetland units using an object-oriented classification method and obtain the boundary, area and type information of each wetland unit; set up monitoring points in each wetland unit, obtain carbon storage-related parameters of vegetation, soil and water through remote sensing monitoring and ground monitoring, and calculate the baseline carbon storage of each wetland unit. S2. Establish a carbon sequestration potential assessment system, determine the set of feasible management measures for each wetland unit, calculate the carbon sequestration increment of each wetland unit under different management measures, and determine the upper limit of carbon sequestration potential for each wetland unit. S3. Identify the hydrological connectivity, spatial proximity, and ecological corridor connectivity among wetlands, construct a matrix of synergistic relationships among wetlands, with matrix elements representing the synergistic impact coefficients between wetland pairs; establish rules for calculating synergistic effects, so that when wetlands implement management measures and obtain carbon sequestration increments, they can generate synergistic carbon sequestration increments for other wetlands through the synergistic impact coefficients. S4. Establish an optimization model with the objective function of maximizing the regional carbon sink increment. The carbon sink increment includes the carbon sink increment generated by the direct implementation of management measures in each wetland and the additional carbon sink increment generated by the synergistic relationship between wetlands. Set constraints and use an improved genetic algorithm to solve the optimization model to obtain the optimal management measure configuration scheme for each wetland unit. S5. Implement corresponding management measures for each wetland unit according to the optimal management measure configuration plan.

2. The method for coordinated management of regional wetland carbon sequestration according to claim 1, characterized in that, After implementing management measures in step S5, the following is also included: Establish a dynamic carbon sink monitoring mechanism and conduct continuous monitoring using the deployed monitoring points. The dynamic monitoring mechanism includes regular remote sensing monitoring and ground monitoring at key time points. The actual carbon storage of each wetland unit at the monitoring time is calculated based on the monitoring data, and the actual cumulative increase of carbon sink in each wetland unit since the implementation of management measures and the total actual cumulative increase of carbon sink in the region are calculated. The actual carbon sequestration increment is compared and analyzed with the expected carbon sequestration increment, and the carbon sequestration realization rate of each wetland unit is calculated. When the overall carbon sequestration achievement rate is lower than the preset threshold or the regional carbon sequestration target is not achieved, the carbon sequestration potential assessment parameters and synergy matrix are updated based on the latest monitoring data, and the optimization solution of step S4 is re-executed to generate the adjusted optimal management measure configuration scheme.

3. The method for coordinated management of regional wetland carbon sequestration according to claim 1, characterized in that, The specific method for setting up monitoring points in each wetland unit in step S1 is as follows: The total number of monitoring points is determined based on the area of ​​the wetland unit. Based on the spatial differentiation characteristics of carbon sinks, each wetland unit is divided into high carbon sink area, medium carbon sink area and low carbon sink area: Carbon sink spatial differentiation characteristic parameters of vegetation cover, topographic elevation and distance from water body are extracted for each wetland unit. Multi-threshold classification rules are used to classify the pixels that meet the conditions of vegetation cover greater than 0.6 and distance from water body less than 50 meters into high carbon sink area, the pixels that meet the conditions of vegetation cover between 0.3 and 0.6 or distance from water body between 50 and 150 meters into medium carbon sink area, and the remaining pixels into low carbon sink area. A stratified random sampling method was adopted to allocate monitoring points to three levels according to the proportions of 40% for high carbon sink areas, 40% for medium carbon sink areas, and 20% for low carbon sink areas. Within each level, random sampling was used to determine the specific spatial location of the monitoring points.

4. The method for coordinated management of regional wetland carbon sinks according to claim 1, characterized in that, The carbon sequestration potential assessment system established in step S2 includes four dimensions: vegetation restoration potential, soil carbon sequestration potential, hydrological regulation potential, and external disturbance control potential. The carbon sequestration increment of each wetland unit under different management measures includes vegetation carbon sequestration increment and soil carbon sequestration increment. The vegetation carbon sequestration increment is calculated by the difference between the target vegetation biomass and the current vegetation biomass after the implementation of management measures, root-to-stem ratio, vegetation carbon content, wetland area and time correction factor. The soil carbon sequestration increment is calculated by the difference between the target soil organic carbon content and the current soil organic carbon content of each soil layer after the implementation of management measures, soil bulk density, soil layer thickness, wetland area and soil organic carbon accumulation rate constant.

5. The method for coordinated management of regional wetland carbon sequestration according to claim 1, characterized in that, The specific method for constructing the wetland synergy matrix in step S3 is as follows: Identify the hydrological connectivity between wetlands, including surface hydrological connectivity and groundwater hydrological connectivity. Surface hydrological connectivity is determined by extracting river systems and surface runoff paths using hydrological analysis tools, while groundwater hydrological connectivity is determined by calculating the Pearson correlation coefficient between the water level time series of the two wetlands. Spatial proximity between wetlands is identified by comparing the shortest distance between wetland boundaries with a feature scale threshold. Identify the connectivity of ecological corridors between wetlands, and use the minimum cost path analysis method to identify ecological corridors connecting two wetlands; The synergistic impact coefficient is quantified using a comprehensive model based on multi-factor weighting, distance decay, and adjustment for sinking potential. The calculation formula is as follows: In the formula, Let be the synergistic influence coefficient of wetland i on wetland j; It is an indicator of hydrological connectivity intensity; As an indicator of ecological relevance; It is the distance decay function; The function representing the influence of the source wetland area; The influence function of the source wetland's potential for sequestration; and Let be the weighting coefficient, satisfying .

6. The method for coordinated management of regional wetland carbon sinks according to claim 1, characterized in that, The synergy calculation rule established in step S3 is as follows: When wetlands gain carbon sequestration through management measures, it has a synergistic effect on other wetlands. The formula for calculating the synergistic carbon sequestration effect on other wetlands is as follows: In the formula, The amount of synergistic sinking received by wetland j; For the synergistic gain coefficient; Let be the synergistic influence coefficient of wetland i on wetland j; For the increase in carbon sequestration of wetland i; n represents the total number of wetland units; After considering the synergistic effect, the total carbon sink increment of wetland j during the planning period is equal to the sum of the carbon sink increment generated by its own direct implementation of management measures and the synergistic carbon sink increment received.

7. The method for coordinated management of regional wetland carbon sinks according to claim 1, characterized in that, The optimization objective function established in step S4 is: In the formula, For the total increase in regional carbon; Let k be the decision variable, representing whether management measures k are adopted for wetland i. The carbon sequestration increment of wetland i under management measure k; For the synergistic gain coefficient; Let be the synergistic influence coefficient of wetland j on wetland i; Let n be the number of management measures that can be selected for wetland i; n is the total number of wetland units. Let be the decision variable, representing whether management measures are adopted for wetland j. ; Management measures for wetlands The increase in carbon sequestration; The number of management measures available for wetland j; The constraints include resource budget constraints, carbon sequestration potential constraints, uniqueness constraints of management measures, and ecological security constraints. Resource budget constraints ensure that the total cost of implementing management measures for all wetlands does not exceed the total budget. Carbon sequestration potential constraints ensure that the carbon sequestration of each wetland does not exceed its upper limit of carbon sequestration potential. Uniqueness constraints of management measures ensure that each wetland must and can only choose one management measure. Ecological security constraints ensure that the ecological health index of each wetland after implementing management measures is not lower than the ecological security threshold. The ecological health index comprehensively considers the biodiversity index, water quality index, and habitat quality index.

8. The method for coordinated management of regional wetland carbon sinks according to claim 7, characterized in that, The improved genetic algorithm used in step S4 includes the following steps: Step 1: Initialize the population. Each individual represents a complete management plan. The number of the management measures selected for each wetland is represented by an integer encoding method. The initial population is generated by combining random generation with a greedy strategy based on the potential for increased sinking. Step 2: Calculate the fitness function. For each individual, check whether all constraints are met. If constraints are violated, penalties are applied. The fitness function includes the regional total carbon sink increment, the budget constraint violation penalty, and the ecological security constraint violation penalty. Its calculation formula is as follows: In the formula, For the s-th individual fitness value; For individuals The corresponding increase in total regional carbon sequestration; For individuals The corresponding total cost; For the total budget; This is the threshold for ecological security. For wetlands i in individuals Ecological health index under the corresponding scheme; and This is the penalty coefficient; Step 3: Use an improved tournament selection strategy to perform the selection operation. Randomly select a number of individuals from the population each time and calculate their fitness value and co-contribution. The co-contribution is defined as the proportion of the co-contribution of all wetlands in the corresponding scheme to the total contribution of the wetlands. Take fitness value and co-contribution into account to determine the selection probability. Step 4: Perform crossover operation using the single-point crossover operator. Randomly select a crossover point to exchange the chromosomes of two parent individuals to generate offspring individuals. After crossover, check whether the offspring individuals meet the constraints and repair them accordingly. Step 5: Adopt an adaptive mutation strategy based on cooperative relationships to perform mutation operations. The mutation probability is adaptively adjusted according to the individual fitness. During mutation, a wetland location is randomly selected, and several wetlands with strong cooperative relationships with that wetland are identified. Based on the management measures of the associated wetlands, the management measures of the current wetland are adjusted in a biased manner to enhance the cooperative effect. Step 6: Terminate the iteration when the maximum number of iterations is reached or the improvement of the optimal fitness value of the population over multiple generations is less than the threshold; otherwise, return to step 2 to continue the iteration. Step 7: Output the individual with the highest fitness value as the optimal solution to obtain the optimal management measures configuration scheme for each wetland unit.

9. The method for coordinated management of regional wetland carbon sinks according to claim 8, characterized in that, The formula for calculating the selection probability in the improved tournament selection strategy is as follows: In the formula, 'a' represents a candidate individual in the tournament; 'h' is the index of the individual in the tournament. Let be the fitness value of individual a; The collaborative contribution of individual a; and q represents the weighting coefficients for fitness and collaborative contribution; q represents the tournament size; based on the calculated selection probability, a roulette wheel method is used to select parent individuals from the tournament individuals to enter the crossover pool.

10. A regional wetland carbon sequestration collaborative management system, characterized in that, The system is used to implement the method as described in any one of claims 1-9.

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