Tide level simulation type wetland long-term greenhouse gas flux monitoring method

Abstract

The invention discloses a long-term greenhouse gas flux monitoring method for a tide level simulation type wetland, and relates to the technical field of environmental ecological monitoring, and the method comprises the following steps: obtaining a wetland greenhouse gas flux monitoring demand; carrying out disassembly treatment on the wetland greenhouse gas flux monitoring requirements to obtain standardized monitoring elements; acquiring a plurality of preset monitoring process units; constructing a customized monitoring scheme for each monitoring process unit based on the target execution scheme; and importing the acquired monitoring parameters corresponding to the wetland greenhouse gas flux monitoring requirements into the customized monitoring scheme, carrying out wetland greenhouse gas flux continuous monitoring according to the screened and determined target execution scheme, and generating wetland greenhouse gas flux monitoring data. According to the invention, through the design of demand disassembly-standardization monitoring elements, and in combination with the preset monitoring process unit and the multi-scheme set, scene adaptation of different wetland types and different monitoring demands is realized.

Description

Technical Field

[0001] This invention relates to the technical field of environmental and ecological monitoring, and in particular to a method for long-term greenhouse gas flux monitoring in wetlands using a tidal level simulation model. Background Technology

[0002] As an important source / sink of greenhouse gases in terrestrial ecosystems, wetlands are crucial for accurate monitoring of greenhouse gas fluxes, which is essential for global carbon cycle assessment and climate change research. With the increasing demand for wetland ecological protection and carbon accounting, the need for long-term, continuous, and highly adaptable monitoring of wetland greenhouse gas fluxes is becoming increasingly urgent.

[0003] Traditional methods for monitoring greenhouse gas fluxes in wetlands typically rely on fixed monitoring devices and single process configurations. On the one hand, tidal level is a core factor influencing gas emission environments in tidal wetlands, but traditional methods often employ a single tidal level synchronization approach (such as fixed water level simulation), which is difficult to adapt to the dynamic tidal level scenarios of different wetland types, such as freshwater tidal wetlands and saline estuary wetlands. On the other hand, each time the monitoring scenario is changed, device parameters need to be readjusted and the monitoring process reconfigured, resulting in low efficiency due to repetitive configuration. Furthermore, traditional monitoring processes are mostly serial data acquisition, leading to poor time synchronization of data such as tidal level and gas concentration, further affecting the accuracy of flux estimation. Currently, no effective solutions have been proposed to address the problems of poor scenario scalability, low efficiency of repetitive configuration, and insufficient data synchronization accuracy in tidal wetland greenhouse gas monitoring. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0005] In view of the problems existing in the prior art, the present invention is proposed.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for long-term greenhouse gas flux monitoring in wetlands based on tidal level simulation, the method comprising the following steps: Needs to obtain monitoring information on greenhouse gas fluxes in wetlands; The wetland greenhouse gas flux monitoring requirements are broken down to obtain standardized monitoring elements. The standardized monitoring elements include several core monitoring modules to achieve the wetland greenhouse gas flux monitoring requirements. The core monitoring modules correspond to four key links: tide level synchronization, gas exchange regulation, concentration data acquisition, and flux estimation. Multiple preset monitoring process units are obtained, including a tide level synchronization unit, a gas exchange unit, a concentration monitoring unit, and a data processing unit, and a set of unit execution schemes corresponding to each monitoring process unit is obtained. For each of the monitoring process units, a target execution plan that matches the standardized monitoring elements is selected sequentially from the set of execution plans for each unit, and a customized monitoring plan is constructed based on the target execution plan; The acquired monitoring parameters corresponding to the wetland greenhouse gas flux monitoring requirements are imported into the customized monitoring scheme. Continuous monitoring of wetland greenhouse gas flux is carried out according to the selected target execution scheme, and wetland greenhouse gas flux monitoring data is generated.

[0007] As a preferred embodiment of the tidal level simulation-based long-term greenhouse gas flux monitoring method for wetlands according to the present invention, the method involves: for each monitoring process unit, sequentially selecting a target execution scheme that matches the standardized monitoring elements from the set of execution schemes for each unit, and constructing a customized monitoring scheme based on the target execution scheme, including: Obtain a set of preset mature monitoring schemes, which includes established monitoring schemes that have been verified and adapted to different wetland types and monitoring needs, and each established monitoring scheme is formed by combining the execution schemes of the corresponding monitoring process units; Based on the wetland greenhouse gas flux monitoring requirements, a predetermined monitoring scheme that is consistent with the core requirements of the standardized monitoring elements is retrieved from the set of mature monitoring schemes. If the established monitoring plan is found, then the established monitoring plan is determined as the customized monitoring plan; If the search for the established monitoring scheme fails, then for each monitoring process unit, a target execution scheme that matches the standardized monitoring element is sequentially selected from the set of execution schemes for each unit, and the customized monitoring scheme is constructed based on the target execution scheme.

[0008] As a preferred embodiment of the long-term greenhouse gas flux monitoring method for wetlands based on tidal level simulation described in this invention, wherein: when constructing the customized monitoring scheme based on the target execution scheme, the effectiveness of the customized monitoring scheme is verified. After the verification is passed, the customized monitoring scheme and the corresponding standardized monitoring elements and adaptation scenario information are dynamically updated to the mature monitoring scheme set to generate a new mature monitoring scheme set. The effectiveness verification includes: confirming, through small-scale pilot monitoring, that the monitoring data accuracy of the customized monitoring scheme meets the preset threshold, that the execution schemes of each monitoring process unit are smoothly connected, and that it is adapted to the environmental conditions of the target wetland.

[0009] As a preferred embodiment of the tidal level simulation-based long-term greenhouse gas flux monitoring method for wetlands according to the present invention, the step of sequentially selecting a target execution scheme that matches the standardized monitoring elements from the execution scheme set of each monitoring process unit includes: Acquire historical monitoring data, which includes past wetland greenhouse gas flux monitoring demand information, corresponding standardized monitoring elements, target execution scheme selection results for each monitoring process unit, and monitoring effect verification data. Based on the historical monitoring data, a scheme matching model is constructed. The scheme matching model learns the correspondence between standardized monitoring elements and target execution schemes in the historical data, and establishes mapping rules between input standardized monitoring elements and output target execution schemes of each monitoring process unit. The standardized monitoring elements corresponding to the current wetland greenhouse gas flux monitoring needs are input into the scheme matching model for matching processing. The scheme matching model outputs the target execution scheme for each of the monitoring process units.

[0010] As a preferred embodiment of the tidal level simulation-based long-term greenhouse gas flux monitoring method for wetlands according to the present invention, the step of sequentially selecting a target execution scheme that matches the standardized monitoring elements from the execution scheme set of each monitoring process unit includes: Based on the core monitoring modules in the standardized monitoring elements, retained monitoring units are determined from each of the monitoring process units. The retained monitoring units are the core process units necessary to achieve the current wetland greenhouse gas flux monitoring requirements. Simultaneously determine the set of retention execution schemes that corresponds one-to-one with the retention monitoring unit in each of the set of execution schemes for each unit; For each retention monitoring unit, a target execution plan that matches the standardized monitoring elements is selected sequentially from the corresponding set of retention execution plans.

[0011] As a preferred embodiment of the tidal level simulation-based long-term greenhouse gas flux monitoring method for wetlands described in this invention, the method further includes: Using a pre-defined monitoring process control module, the operation status and data generation of continuous monitoring of wetland greenhouse gas flux are monitored in real time. If the wetland greenhouse gas flux monitoring data is found to be fully generated and meets the preset monitoring cycle requirements, then the monitoring process is confirmed to be complete, and the operating resources of each of the retained monitoring units (or monitoring process units) are released. These operating resources include sensor power supply resources, data transmission link resources, and storage cache resources; and / or, During the continuous monitoring of greenhouse gas flux in wetlands, if a manual stop command is received, or an abnormal operating state is detected (including monitoring data accuracy consistently below a preset threshold, monitoring process unit connection failure, and environmental adaptability failure), the monitoring process control module will be used to stop any monitoring process unit in the customized monitoring scheme and save the collected monitoring data and current operating parameters.

[0012] As a preferred embodiment of the tidal level simulation-based long-term greenhouse gas flux monitoring method for wetlands described in this invention, the step of importing the acquired monitoring parameters corresponding to the wetland greenhouse gas flux monitoring requirements into the customized monitoring scheme, conducting continuous monitoring of wetland greenhouse gas fluxes, and generating wetland greenhouse gas flux monitoring data includes: Using the customized monitoring scheme, based on the monitoring parameters, the target execution schemes corresponding to each monitoring process unit are run in parallel. The parallel operation is achieved through a multi-channel synchronous acquisition mechanism to ensure that the execution process of each monitoring process unit does not interfere with each other. The monitoring process data generated during the execution of each of the target execution schemes are stored in the monitoring database. The monitoring process data includes tide level synchronization accuracy data, gas exchange rate data, real-time gas concentration raw data, data processing intermediate results, and environmental adaptation status data. The monitoring process data from the monitoring database is called up, and the wetland greenhouse gas flux monitoring data is generated through data integration and verification. The integration and verification includes timestamp alignment, data accuracy filtering, outlier removal, and cross-unit data consistency verification.

[0013] As a preferred embodiment of the tidal level simulation-based long-term greenhouse gas flux monitoring method for wetlands according to the present invention, the step of calling up the monitoring process data from the monitoring database and generating the wetland greenhouse gas flux monitoring data through data integration and verification includes: Based on the dependencies of each target execution scheme, a first execution scheme with a first calling priority and a second execution scheme with a second calling priority are determined among the target execution schemes; the second calling priority is higher than the first calling priority, and the first execution scheme is a basic type monitoring scheme (including the target execution scheme corresponding to the tide level synchronization unit), and the second execution scheme is a correlation type monitoring scheme that depends on basic data (including the target execution schemes corresponding to the gas exchange unit, concentration monitoring unit, and data processing unit). The first monitoring process data generated during the execution of each of the first execution schemes is stored in the first monitoring database. The first monitoring process data includes tide level synchronization accuracy data, tide level change time sequence data, and tide level adaptation verification data. When the second execution scheme is run in parallel, second monitoring process data is generated based on the first monitoring process data called from the first monitoring database, and the second monitoring process data is stored in the second monitoring database; the second monitoring process data includes gas exchange rate data calibrated based on tide data, real-time gas concentration data associated with tide level, and intermediate results of flux estimation calculated based on basic data; Data from the first and second monitoring databases are retrieved, and timestamp alignment, cross-database data consistency verification, and dependency verification are performed in priority order to finally generate the wetland greenhouse gas flux monitoring data.

[0014] The device applied to the above-mentioned method for long-term greenhouse gas flux monitoring in tidal-simulated wetlands includes the following modules: a demand processing module for acquiring wetland greenhouse gas flux monitoring demands; the demand processing module is further used to decompose the wetland greenhouse gas flux monitoring demands to obtain standardized monitoring elements; the standardized monitoring elements are used to indicate the core monitoring modules for achieving the monitoring demands, and the core monitoring modules correspond to four key links: tidal level synchronization, gas exchange regulation, concentration data acquisition, and flux estimation. The monitoring scheme configuration module is used to acquire multiple preset monitoring process units, including: tide level synchronization unit, gas exchange unit, concentration monitoring unit, and data processing unit, and to acquire the unit execution scheme set corresponding to each monitoring process unit; the monitoring scheme configuration module is also used to select target execution schemes that match the standardized monitoring elements from each set of unit execution schemes for each monitoring process unit, and to construct customized monitoring schemes based on the target execution schemes; The implementation scheme of the tide synchronization unit includes transmitting natural tide level changes to the monitoring area through a water-filled U-shaped connecting pipe with no gas residue, so that the water level in the monitoring area is synchronized with the natural tide level; the implementation scheme of the gas exchange unit includes using a weak open-circuit gas exchange method to carry out extremely low-speed gas exchange, and adjusting the gas concentration in the gas chamber to avoid the accumulation of greenhouse gases; the implementation scheme of the concentration monitoring unit includes forming a closed loop between the gas chamber and the gas analyzer to continuously record the concentration data of CO2, CH4, and N2O in the gas chamber; the implementation scheme of the data processing unit includes using a sliding window fitting method to analyze the concentration data and estimate the greenhouse gas flux in the wetland. The monitoring execution module is used to import the monitoring parameters corresponding to the wetland greenhouse gas flux monitoring requirements into the customized monitoring scheme; the monitoring execution module is also used to control each monitoring process unit to carry out continuous monitoring of wetland greenhouse gas flux according to the selected target execution scheme, and generate wetland greenhouse gas flux monitoring data.

[0015] The present invention also discloses a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described method for long-term greenhouse gas flux monitoring in tidal-simulation wetlands.

[0016] The beneficial effects of this invention are as follows: The method of this invention, through the design of "demand decomposition—standardized monitoring elements," combined with pre-set monitoring process units and a set of multiple schemes, achieves scenario adaptation for different wetland types and monitoring needs, solving the problem of poor scenario scalability in traditional methods. Through mechanisms such as mature monitoring scheme set retrieval and dynamic updating of customized schemes, it reduces repetitive configuration work when changing monitoring scenarios, significantly improving monitoring configuration efficiency. Through designs such as retained monitoring unit screening, parallel operation of monitoring processes, and priority data linkage, it ensures the time synchronization of tidal level and gas data, improving the accuracy of flux monitoring. Simultaneously, the design of scheme matching models and process control modules further enhances the automated adaptation capability and operational stability of monitoring schemes. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments 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. Wherein: Figure 1 This is a schematic diagram of the overall process of a tidal level simulation-based long-term greenhouse gas flux monitoring method for wetlands proposed in this invention. Figure 2 This is a schematic diagram of the logic framework of a tidal level simulation wetland long-term greenhouse gas flux monitoring device proposed in this invention. Detailed Implementation

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0019] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0020] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0021] Reference Figure 1 As an embodiment of the present invention, a method for long-term greenhouse gas flux monitoring in wetlands based on tidal level simulation is provided. This method includes the following steps.

[0022] Step 1: Obtain the monitoring requirements for greenhouse gas fluxes in wetlands; The system can receive user-submitted wetland greenhouse gas flux monitoring requests through the interactive interface of the field monitoring terminal or the remote data platform interface. These requests can include detailed information such as the type of wetland to be monitored (e.g., freshwater tidal wetland, saline estuary wetland), monitoring period (e.g., quarterly continuous monitoring, rainy season intensive monitoring), accuracy requirements (e.g., ppm-level concentration accuracy, ±5% flux estimation error), and target gas type (e.g., combination of CO2, CH4, and N2O). The system records these requests in a structured JSON format and stores them in a local SQLite database. The database uses a partitioned storage strategy (partitioned by wetland type + monitoring period) for subsequent steps.

[0023] Step 2: Decompose the wetland greenhouse gas flux monitoring requirements to obtain standardized monitoring elements; the standardized monitoring elements include several core monitoring modules to achieve the wetland greenhouse gas flux monitoring requirements, and the core monitoring modules correspond to four key links: tide level synchronization, gas exchange regulation, concentration data acquisition, and flux estimation. The algorithm utilizes a rule engine and semantic parsing-based requirement decomposition method to perform targeted analysis on the acquired monitoring requirements. The rule engine pre-defines core dimension tags (wetland type, monitoring cycle, accuracy requirements, target gas) and associated rules (such as the implicit constraint "monitoring frequency ≥ 1 time / hour" corresponding to "intensified monitoring during the rainy season"). The semantic parsing module extracts key information (including explicit and implicit information) from user requirements using natural language processing (NLP) technology and matches it with the pre-determined tags. It then extracts the core monitoring modules required to achieve the requirements. Each core monitoring module corresponds to an independent functional link in the monitoring process. Each core monitoring module is defined in detail, including its core functions, input parameters, output data, and collaborative relationships with other modules.

[0024] For example, a wetland greenhouse gas flux monitoring requirement of "continuous monitoring of freshwater tidal wetlands for one month during the rainy season, requiring ppm-level CO2 and CH4 concentration accuracy and ±5% flux error" can be automatically broken down into corresponding core monitoring modules: Module 1, Tide Level Synchronization; Core function: Synchronize the natural tide level of the target wetland to the monitoring area; Input parameters: Historical tide level time series data of the target wetland (CSV format, timestamp accuracy to the second, water level accuracy ±0.1cm), water level benchmark value of the monitoring area; Output data: Real-time tide level synchronization accuracy data, water level time series data of the monitoring area; Collaboration relationship: Provides tidal environmental data for the subsequent gas exchange control module. Module 2, Gas Exchange Control; Core function: Adjust the gas exchange rate of the gas chamber to avoid greenhouse gas accumulation; Input parameters: Water level data output by the tide level synchronization module, preset concentration threshold of the target gas; Output data: Real-time gas exchange rate data, gas chamber concentration pre-control results; Collaboration relationship: Receives the output data of the tide level synchronization module and provides a stable gas chamber environment for the concentration data acquisition module. Module 3, Concentration Data Acquisition; Core Function: Continuously acquires target gas concentrations in the gas chamber; Input Parameters: Gas chamber environmental data output from the gas exchange control module, analyzer calibration parameters; Output Data: Real-time gas concentration time-series data, data validity markers; Collaboration Relationship: Receives output data from the gas exchange control module, providing raw concentration data for the flux estimation module. Module 4, Flux Estimation; Core Function: Calculates wetland greenhouse gas flux values; Input Parameters: Concentration data output from the concentration data acquisition module, water level data output from the tide level synchronization module; Output Data: Greenhouse gas flux time-series data, flux reliability assessment report; Collaboration Relationship: Receives output data from the concentration data acquisition module and the tide level synchronization module, forming the final monitoring results.

[0025] Standardized monitoring elements are a targeted and structured decomposition of the monitoring needs for greenhouse gas fluxes in wetlands, used to clarify the specific functional requirements for monitoring tasks. Simultaneously, standardized monitoring elements serve as a core bridge connecting user monitoring needs with customized monitoring solutions. By breaking down complex monitoring requirements into independent core monitoring modules and configurable parameter constraints, standardized inputs are provided for matching execution plans of subsequent monitoring process units. While the expression of monitoring needs is flexible and unordered, the actual required monitoring functionalities are limited. This step decomposes complex monitoring needs into clearly defined core monitoring modules, simplifying the selection and combination process of subsequent execution plans, while improving the adaptability and reusability of monitoring plans. This enables the system to quickly respond to scenarios with different wetland types and monitoring needs, effectively solving the core problems of single strategies and low efficiency due to repetitive configuration in traditional monitoring methods.

[0026] Step 3: Obtain multiple preset monitoring process units, including tide level synchronization unit, gas exchange unit, concentration monitoring unit, and data processing unit, and obtain the set of unit execution schemes corresponding to each monitoring process unit; The monitoring process units are functionally independent yet collaboratively operated units in the wetland greenhouse gas flux monitoring process. Each unit is responsible for completing a specific monitoring function, working together through parameterized configuration and data linkage mechanisms to cover the entire monitoring process. The system predefines multiple monitoring process units, including tide level synchronization units, gas exchange units, concentration monitoring units, and data processing units. Each unit can be independently invoked or combined to operate according to monitoring needs.

[0027] The unit execution scheme set is a collection of specific implementation schemes available for each monitoring process unit, adapted to the needs of different wetland monitoring scenarios. Each unit execution scheme set contains several execution schemes. For example, the unit execution scheme set corresponding to the tide level synchronization unit includes a water-filled U-tube synchronization scheme (transmitting tide level without gas residue), a pressure sensor synchronization scheme (high-precision water level signal transmission), and a dual-redundant synchronization scheme (U-tube + sensor dual verification); the unit execution scheme set corresponding to the gas exchange unit includes a weak open-circuit ultra-low-speed exchange scheme (avoiding gas accumulation), a dynamic speed-adjusting exchange scheme (adjusting the rate according to concentration fluctuations), and a low-loss exchange scheme (reducing gas adsorption loss); the execution scheme of the concentration monitoring unit includes forming a closed-loop loop between the gas chamber and the gas analyzer to continuously record the concentration data of CO2, CH4, and N2O in the gas chamber; the execution scheme of the data processing unit includes using a sliding window fitting method to analyze the concentration data and estimate the wetland greenhouse gas flux. This step provides a variety of unit and scheme selections, enabling the system to flexibly adapt to different wetland types and scenarios with different monitoring accuracies.

[0028] Step 4: For each monitoring process unit, select the target execution plan that matches the standardized monitoring elements from the set of execution plans for each unit, and build a customized monitoring plan based on the target execution plan; Based on the standardized monitoring elements obtained from the above steps, each monitoring process unit is sequentially traversed. For each monitoring process unit, a target execution plan that matches the core requirements of the standardized monitoring elements is selected from its corresponding set of unit execution plans. Then, these target execution plans are combined to form a complete customized monitoring plan. For example, if the standardized monitoring elements include "freshwater tidal wetland, continuous monitoring during the rainy season, ppm-level concentration accuracy, and avoidance of CH4 accumulation," then the matching target execution plans are: the tidal level synchronization unit selects the water-filled U-shaped tube synchronization plan (no gas residue suitable for wetland environment), the gas exchange unit selects the weak open-circuit ultra-low-speed exchange plan (to prevent CH4 accumulation), the concentration monitoring unit selects the closed-loop cyclic acquisition plan (to ensure ppm-level accuracy), and the data processing unit selects the sliding window fitting plan (to adapt to the characteristics of continuous monitoring data).

[0029] A customized monitoring solution is a combination of multiple target execution plans that align with standardized monitoring elements. This step enables on-demand selection and rapid combination of monitoring solutions, achieving dynamic adaptation of the monitoring process. It allows the system to construct highly adaptable solutions based on specific wetland monitoring needs, effectively solving the core problems of traditional monitoring methods, such as single strategies and inefficient repetitive configuration.

[0030] Step 5: Import the acquired monitoring parameters corresponding to the wetland greenhouse gas flux monitoring requirements into the customized monitoring scheme, carry out continuous monitoring of wetland greenhouse gas flux according to the selected target implementation scheme, and generate wetland greenhouse gas flux monitoring data.

[0031] The process involves importing the acquired monitoring parameters corresponding to the wetland greenhouse gas flux monitoring requirements (such as target wetland type parameters, monitoring cycle duration parameters, gas analyzer calibration parameters, and tide level synchronization reference values) into a customized monitoring scheme. Then, the monitoring and data acquisition process is initiated, and the customized monitoring scheme is run according to the selected target execution plan, conducting continuous monitoring of wetland greenhouse gas fluxes and generating wetland greenhouse gas flux monitoring data. This data may include time-series data on tide level synchronization accuracy, real-time concentration data of CO2, CH4, and N2O in gas cells, gas exchange rate regulation data, greenhouse gas flux estimation results, and flux reliability assessment data. This step, through the customized monitoring scheme, enables one-click initiation of long-term continuous monitoring tasks, achieving automation and standardization of wetland greenhouse gas flux monitoring, improving the stability of the monitoring process and the accuracy of data acquisition, and automatically generating multi-dimensional monitoring data to provide reliable basic information for subsequent wetland ecological analysis and greenhouse gas emission assessment. Through the above steps, this application addresses the problems of traditional wetland monitoring technologies relying on fixed monitoring procedures and device configurations, which makes them difficult to adapt to different wetland types and monitoring needs, and requires repeated device parameter adjustments for each monitoring session, resulting in low efficiency. This application divides the monitoring process into multiple independent monitoring process units and provides various optional execution schemes for each unit, enabling flexible expansion of monitoring scenarios. After obtaining wetland monitoring requirements, standardized monitoring elements are obtained through decomposition and processing. Based on this information, a customized monitoring scheme is constructed by selecting matching target execution schemes from a pre-set set of unit execution schemes. In this process, no large-scale modification of the entire monitoring device is required; only the execution schemes of the corresponding monitoring process units need to be adjusted to adapt to new wetland scenarios. Furthermore, the pre-set multiple unit execution schemes avoid repetitive debugging and configuration work for each monitoring session, significantly shortening the preparation cycle for monitoring tasks and improving monitoring efficiency. Therefore, this application effectively solves the core problems of single strategy and low efficiency of repetitive configuration in long-term greenhouse gas flux monitoring of tidal level simulation wetlands, significantly improving the adaptability and configuration efficiency of wetland monitoring schemes.

[0032] In some embodiments, for each monitoring process unit, a target execution plan that matches the standardized monitoring elements is sequentially selected from the set of execution plans for each unit, and a customized monitoring plan is constructed based on the target execution plan, including: For each monitoring process unit, a target execution plan that matches the standardized monitoring elements is selected sequentially from the set of execution plans for each unit. A customized monitoring plan is then constructed based on the target execution plan, including: Obtain a set of preset mature monitoring schemes. The set of mature monitoring schemes includes established monitoring schemes that have been verified and adapted to different wetland types and monitoring needs. Each established monitoring scheme is formed by combining the execution schemes of the corresponding monitoring process unit. Based on the monitoring needs of greenhouse gas flux in wetlands, we searched for established monitoring schemes that are consistent with the core requirements of standardized monitoring elements from a set of mature monitoring schemes. If a pre-existing monitoring plan is found, it will be designated as a customized monitoring plan. If the search for the established monitoring plan fails, then for each monitoring process unit, the target execution plan that matches the standardized monitoring elements is selected from the set of execution plans for each unit in turn, and a customized monitoring plan is built based on the target execution plan.

[0033] Among them, based on known wetland types (such as freshwater tidal wetlands and saltwater estuary wetlands), monitoring needs (such as quarterly continuous monitoring and rainy season intensive monitoring) and verified monitoring schemes, a set of mature monitoring schemes is pre-constructed. These mature monitoring schemes are composed of different monitoring process units and their execution schemes. The schemes in the set of mature monitoring schemes can be directly adapted to the known monitoring needs of common scenarios.

[0034] When a new wetland greenhouse gas flux monitoring request is received, the request is broken down to extract key standardized monitoring elements. These standardized monitoring elements are then matched with established monitoring schemes from a set of mature monitoring schemes. The matching process is primarily based on the wetland type suitability, the accuracy of the monitoring, and the monitoring cycle. If an established monitoring scheme that highly matches the monitoring request is found, it is identified as the customized monitoring scheme corresponding to this request. If no highly matching scheme is found, then based on the standardized monitoring elements, for each monitoring process unit, a target execution scheme that matches the elements is selected from the corresponding unit execution scheme set. By combining these execution schemes, a customized monitoring scheme that meets specific monitoring requirements is dynamically constructed.

[0035] This step significantly reduces preparation time for monitoring tasks by pre-setting a set of mature monitoring schemes and retrieving a pre-defined scheme from it. Once a pre-defined monitoring scheme is found, it can be used directly for monitoring without the need to re-select and execute schemes, greatly improving the efficiency of monitoring configuration. When the pre-defined monitoring schemes cannot meet new monitoring needs, customized monitoring schemes can be flexibly constructed through the dynamic combination of monitoring process unit execution schemes to adapt to special scenarios such as high turbidity wetlands and low concentration gas emission wetlands. This approach enhances the scenario adaptability of the monitoring schemes, enabling them to better cope with diverse wetland monitoring needs. Furthermore, the modular and scheme-based monitoring process design reduces the complexity of monitoring configuration. Users do not need to delve into debugging device parameters; they only need to match the corresponding scheme according to the monitoring requirements, thereby lowering the operational threshold for field monitoring and improving the practical usability of the monitoring schemes.

[0036] In one embodiment, when a customized monitoring scheme is built based on the target execution scheme, the effectiveness of the customized monitoring scheme is verified. After the verification is passed, the customized monitoring scheme and the corresponding standardized monitoring elements and adaptation scenario information are dynamically updated to the mature monitoring scheme set to generate a new mature monitoring scheme set. The effectiveness verification includes: confirming through small-scale pilot monitoring that the monitoring data accuracy of the customized monitoring plan meets the preset threshold, that the execution plan of each monitoring process unit is smoothly connected, and that it is suitable for the environmental conditions of the target wetland.

[0037] When the established monitoring scheme cannot meet the monitoring needs of greenhouse gas flux in wetlands, based on the standardized monitoring elements obtained from the breakdown of monitoring needs, for each monitoring process unit, a suitable target execution scheme is selected from the unit execution scheme set in turn. After combining and constructing a customized monitoring scheme, the effectiveness is verified through small-scale pilot monitoring. Once the customized monitoring scheme passes the effectiveness verification, the scheme, the corresponding standardized monitoring elements, and the appropriate wetland type, monitoring cycle, and other scenario information are synchronously written into the mature monitoring scheme set through the monitoring scheme management module to generate a new mature monitoring scheme set.

[0038] This step involves dynamically updating the set of mature monitoring solutions, enabling the system to quickly respond to new wetland monitoring needs without requiring large-scale modifications to monitoring devices or processes. This significantly improves the adaptability and response speed of the monitoring solutions. The dynamic update mechanism allows the set of mature monitoring solutions to be continuously expanded and iterated. As wetland monitoring scenarios diversify and technologies upgrade, the system can continuously refine effective solutions to adapt to new scenarios, thereby better addressing the monitoring needs of different wetland types and different accuracy requirements.

[0039] In one embodiment, for each monitoring process unit, a target execution plan that matches the standardized monitoring elements is sequentially selected from the set of execution plans for each unit, including: Acquire historical monitoring data, which includes past wetland greenhouse gas flux monitoring demand information, corresponding standardized monitoring elements, target execution scheme selection results for each monitoring process unit, and monitoring effect verification data. Based on historical monitoring data, a scheme matching model is constructed. The scheme matching model learns the correspondence between standardized monitoring elements and target execution schemes in historical data, and establishes mapping rules between input standardized monitoring elements and output target execution schemes of each monitoring process unit. The standardized monitoring elements corresponding to the current wetland greenhouse gas flux monitoring needs are input into the scheme matching model for matching processing. The scheme matching model outputs the target execution scheme for each monitoring process unit.

[0040] The aforementioned scheme matching model provides a mapping relationship between standardized monitoring elements and unit execution schemes. It automatically matches the target execution schemes for each monitoring process unit, reducing reliance on manual experience-based selection. The process for establishing this scheme matching model can be as follows: Historical monitoring data is extracted from the monitoring database. This data should include records of execution scheme selections for each monitoring process unit under different wetland scenarios, monitoring parameter settings, data accuracy results, environmental adaptation feedback, etc. The historical monitoring data is preprocessed, including anomaly removal, data format standardization, and scenario labeling, to facilitate subsequent model learning. Then, based on the preprocessed historical monitoring data, a suitable machine learning method (such as random forest or lightweight decision tree) is selected to build the scheme matching model, adapting to the low-complexity data requirements of wetland monitoring scenarios. For example, to construct a random forest model, the input features are determined based on the core dimensions of standardized monitoring elements, including wetland type labels, monitoring cycle duration, concentration accuracy threshold, and target gas type. The number of decision trees is set to 100-200 based on the amount of historical data, balancing model accuracy and computational efficiency. The output dimensions are consistent with the number of monitoring process units, with each output dimension corresponding to a target execution scheme category for a monitoring process unit. Then, the preprocessed historical monitoring data is divided into training and testing sets in a 7:3 ratio. The random forest model is trained using the training set, and the splitting rules of the decision trees are adjusted through out-of-bag evaluation to ensure that the execution schemes output by the model are as consistent as possible with the schemes validated in actual testing. During training, stratified sampling can be used to divide the dataset to avoid model bias caused by uneven sample distribution. The trained random forest model is evaluated using a test set, and metrics such as the model's scheme matching accuracy and scene adaptation coverage are calculated. Based on the evaluation results, it is determined whether the model meets the requirements. If the model performance does not meet the requirements, the model can be adjusted and optimized. Specific optimization options include: increasing the number of decision trees to improve generalization ability, supplementing historical data of specific wetland scenarios for incremental training, and adjusting the weights of input features to strengthen the matching priority of core requirements.

[0041] After the scheme matching model is established, standardized monitoring elements can be matched based on the model: when there is a new wetland greenhouse gas flux monitoring requirement, the decomposed standardized monitoring elements are input into the scheme matching model. The model performs matching processing through the voting mechanism of the internal decision tree based on the input element information, and outputs the target execution scheme for each monitoring process unit such as the tide level synchronization unit and the gas exchange unit. Then, these target execution schemes are combined and applied to the monitoring process to build a customized monitoring scheme.

[0042] In one embodiment, for each monitoring process unit, a target execution plan that matches the standardized monitoring elements is sequentially selected from the set of execution plans for each unit, including: Based on the core monitoring modules in the standardized monitoring elements, the retained monitoring units are determined from each monitoring process unit. The retained monitoring units are the core process units necessary to achieve the current wetland greenhouse gas flux monitoring needs. Simultaneously determine the set of retention execution plans that corresponds one-to-one with the retention monitoring unit in the set of execution plans for each unit; For each retention monitoring unit, a target execution plan that matches the standardized monitoring elements is selected sequentially from the corresponding set of retention execution plans.

[0043] Based on the core requirements of standardized monitoring elements, essential units for the current monitoring scenario are selected from predefined monitoring process units; these are the retained monitoring units. These units are the core components for completing the target monitoring task and will be adjusted according to different needs in different wetland monitoring scenarios. For example, in an indoor simulated wetland gas flux monitoring scenario, synchronization with natural tide levels is not required. In this case, the retained monitoring units are a gas exchange unit, a concentration monitoring unit, and a data processing unit. The corresponding set of retained execution schemes includes adaptation schemes for each unit: a weak open-circuit, extremely low-speed exchange scheme for the gas exchange unit, a closed-circuit cyclic acquisition scheme for the concentration monitoring unit, and a sliding window fitting scheme for the data processing unit. For each retained monitoring unit, a target execution scheme that matches the standardized monitoring elements is sequentially selected from the corresponding set of retained execution schemes. The selected target execution scheme is the optimal implementation scheme for that unit in the current wetland monitoring scenario.

[0044] In one embodiment, the method of the present invention further includes: Using a pre-defined monitoring process control module, the operation status and data generation of continuous monitoring of wetland greenhouse gas flux are monitored in real time. If the wetland greenhouse gas flux monitoring data has been fully generated and meets the preset monitoring cycle requirements, then the monitoring process is confirmed to be complete, and the operating resources of each retained monitoring unit (or monitoring process unit) are released. These operating resources include sensor power supply resources, data transmission link resources, and storage cache resources; and / or, During the continuous monitoring of greenhouse gas fluxes in wetlands, if a manual stop command is received, or an abnormal operating state is detected (including monitoring data accuracy consistently below the preset threshold, monitoring process unit connection failure, and environmental adaptability failure), the monitoring process control module will be used to stop any monitoring process unit in the customized monitoring scheme and save the collected monitoring data and current operating parameters.

[0045] The preset monitoring process control module is an independent software component integrated into the wetland monitoring terminal. It is responsible for real-time collection of the operational status codes (status code definitions: 0 = normal, 1 = warning, 2 = fault) and data feedback information of each monitoring process unit, including tide level synchronization and gas exchange. It synchronizes the work progress of each unit through periodic polling and status code triggering, while simultaneously verifying whether the accuracy of the monitoring data meets preset thresholds. Once the monitoring process control module confirms the completion of the monitoring task, it immediately triggers resource release: cutting off the power supply circuits of unnecessary sensors through the hardware control interface, closing redundant remote data transmission links, and clearing temporary storage cache. Simultaneously, it writes the task completion time and resource release record to the local log, providing a basis for subsequent equipment maintenance and energy consumption statistics. If the termination condition is triggered, the monitoring process control module will simultaneously perform three operations: sending a hardware interrupt signal to the target monitoring process unit to suspend operation, backing up the current monitoring data to local solid-state storage, and recording the abnormal status code and notifying related units to simultaneously pause, avoiding data gaps or equipment idle operation, and ensuring that each unit responds smoothly to the termination command. This step utilizes a management and control module to precisely release resources, reducing ineffective energy consumption during long-term wetland monitoring. Simultaneously, it monitors anomalies in real time and quickly terminates monitoring, avoiding the invalid collection of low-precision data and improving the stability and reliability of monitoring tasks. Users can terminate tasks at any time without waiting for the cycle to end, enhancing the operational flexibility of field monitoring. Furthermore, this management and control module supports parallel monitoring of multiple monitoring points. Through a resource priority scheduling mechanism, it prioritizes the stable operation of core units such as tide level synchronization and concentration acquisition, adapting to the needs of multi-point synchronous monitoring scenarios in wetlands.

[0046] In one embodiment, the acquired monitoring parameters corresponding to the wetland greenhouse gas flux monitoring requirements are imported into a customized monitoring scheme to conduct continuous monitoring of wetland greenhouse gas fluxes and generate wetland greenhouse gas flux monitoring data, including: By utilizing a customized monitoring solution, and based on the monitoring parameters, the target execution plans corresponding to each monitoring process unit are run in parallel. Parallel execution is achieved through a multi-channel synchronous acquisition mechanism to ensure that the execution process of each monitoring process unit does not interfere with each other. The monitoring process data generated during the execution of each target plan is stored in the monitoring database. The monitoring process data includes tide level synchronization accuracy data, gas exchange rate data, real-time gas concentration raw data, data processing intermediate results, and environmental adaptation status data. The monitoring process data is retrieved from the monitoring database, and wetland greenhouse gas flux monitoring data is generated through data integration and verification. The integration and verification includes timestamp alignment, data accuracy filtering, outlier removal, and cross-unit data consistency verification.

[0047] Before monitoring begins, monitoring parameters (such as wetland type baseline values, monitoring cycle duration, analyzer calibration coefficients, and tide level synchronization thresholds) are imported into a customized monitoring scheme. This allows the target execution schemes of each monitoring process unit to match the corresponding operating thresholds and acquisition frequencies based on these parameters. A database enables data interaction and timestamp synchronization between units. Furthermore, the hardware parallel mechanism of a multi-channel data acquisition unit ensures synchronized acquisition of data from units such as tide level synchronization and gas exchange, guaranteeing that the execution processes of each unit do not interfere with each other. Additionally, low-power data exchange and status synchronization between monitoring units in complex field environments can be achieved through methods such as 485 bus communication and wireless LoRa links.

[0048] During the execution of each target implementation plan, the generated monitoring process data (such as real-time tide level, gas exchange rate, and raw concentration data) are written to the monitoring database every 10 seconds. After the monitoring cycle ends, the process data in the database is retrieved, and the final wetland greenhouse gas flux monitoring data is generated through integration and verification logic such as timestamp alignment and precision filtering. The wetland greenhouse gas flux monitoring data may include tide level-concentration correlation time series curves, daily average greenhouse gas flux values, and flux change trend graphs within the monitoring cycle. This step, by running the execution plans of each monitoring process unit in parallel through multiple channels, can fully utilize the hardware resources of the data logger, improve the time continuity and data synchronization of long-term monitoring, and avoid time difference errors caused by serial acquisition. Centralizing the monitoring process data into the database enables unified management and traceability of multi-dimensional data, ensuring the time consistency and integrity of data such as tide level and concentration. At the same time, the monitoring database supports local SD card backup and scheduled cloud synchronization, avoiding the risk of data loss in the field and improving the security of monitoring data.

[0049] In one embodiment, monitoring data from various monitoring processes in the monitoring database are retrieved, and wetland greenhouse gas flux monitoring data are generated through data integration and verification, including: Based on the dependencies of each target execution scheme, the first execution scheme with the first calling priority and the second execution scheme with the second calling priority are determined. The second calling priority is higher than the first calling priority, and the first execution scheme is a basic monitoring scheme (including the target execution scheme corresponding to the tide level synchronization unit), while the second execution scheme is a correlation monitoring scheme that depends on basic data (including the target execution schemes corresponding to the gas exchange unit, concentration monitoring unit, and data processing unit). The first monitoring process data generated during the execution of each first execution scheme is stored in the first monitoring database. The first monitoring process data includes tide level synchronization accuracy data, tide level change time sequence data, and tide level adaptation verification data. When the second execution scheme is run in parallel, the second monitoring process data is generated based on the first monitoring process data called from the first monitoring database, and the second monitoring process data is stored in the second monitoring database. The second monitoring process data includes gas exchange rate data calibrated based on tide data, real-time gas concentration data associated with tide level, and intermediate results of flux estimation calculated based on basic data. Data from the first and second monitoring databases are retrieved, and timestamp alignment, cross-database data consistency verification, and dependency verification are performed in priority order to ultimately generate wetland greenhouse gas flux monitoring data.

[0050] To determine the priority of execution plans, the dependencies and preconditions of each plan can be clearly defined during the monitoring plan design phase. The results of basic plans serve as the core input for related plans; therefore, basic plans are defined as having the highest priority, while related plans are started synchronously with the output of basic data. For example, the execution plan of the gas exchange unit depends on the real-time tide data from the tide synchronization unit (tide height determines the contact area between the gas chamber and the wetland, thus affecting the gas exchange rate), and the execution plan of the concentration monitoring unit depends on the gas chamber environmental data of the gas exchange unit. Therefore, the execution plan of the tide synchronization unit is determined as the first execution plan, running preferentially when monitoring starts, and the generated tide synchronization accuracy data and tide change time-series data are stored in the first monitoring database.

[0051] After the first execution scheme continuously and stably outputs tide level data (stability criteria: data accuracy ≥ preset threshold for 30 consecutive seconds, no data loss), the second execution scheme (the schemes for gas exchange, concentration monitoring, and data processing units) is started in parallel. During operation, these second execution schemes call the tide level data from the first monitoring database in real time through a data interface (using a RESTful API) to dynamically calibrate their own operating parameters (e.g., the gas exchange unit adjusts the exchange rate threshold according to the tide level: exchange rate ≤ 0.3 L / min when the tide level ≥ 1m; exchange rate 0.5-1 L / min when the tide level < 1m). Based on the called tide level data, the second execution scheme generates calibrated gas exchange rate data, real-time concentration data associated with the tide level, and other second monitoring process data, and stores this data in the second monitoring database according to timestamps. This step utilizes monitoring and data acquisition resources more efficiently by prioritizing execution based on dependencies and storing data in layers: the stable output of the basic schemes provides reliable input for the related schemes, avoiding acquisition errors caused by data dependencies; at the same time, the related schemes run in parallel, making full use of the multi-channel hardware capabilities of the data acquisition unit, thereby improving the efficiency and data quality of long-term wetland monitoring while ensuring data consistency over time.

[0052] refer to Figure 2 The present invention also discloses an apparatus for long-term greenhouse gas flux monitoring in the above-mentioned tidal level simulation wetland. The apparatus includes: a demand processing module for acquiring wetland greenhouse gas flux monitoring demand; the demand processing module is further used to decompose the wetland greenhouse gas flux monitoring demand to obtain standardized monitoring elements; the standardized monitoring elements are used to indicate the core monitoring module for realizing the monitoring demand, and the core monitoring module corresponds to four key links: tidal level synchronization, gas exchange regulation, concentration data acquisition, and flux estimation. The monitoring scheme configuration module is used to acquire multiple preset monitoring process units, including: a tide level synchronization unit, a gas exchange unit, a concentration monitoring unit, and a data processing unit, and to acquire a set of unit execution schemes corresponding to each monitoring process unit. The monitoring scheme configuration module is also used to sequentially select target execution schemes that match the standardized monitoring elements from each set of unit execution schemes for each monitoring process unit, and to construct customized monitoring schemes based on the target execution schemes. Specifically, the execution scheme of the tide level synchronization unit includes transmitting natural tide level changes to the monitoring area through a water-filled U-shaped connecting pipe with no gas residue, synchronizing the water level in the monitoring area with the natural tide level; the execution scheme of the gas exchange unit includes using a weak open-circuit gas exchange method for extremely low-speed gas exchange to adjust the gas concentration in the gas chamber to avoid greenhouse gas accumulation; the execution scheme of the concentration monitoring unit includes forming a closed-loop loop between the gas chamber and the gas analyzer to continuously record the concentration data of CO2, CH4, and N2O in the gas chamber; and the execution scheme of the data processing unit includes using a sliding window fitting method to analyze the concentration data and estimate the wetland greenhouse gas flux. The monitoring execution module is used to import the monitoring parameters corresponding to the wetland greenhouse gas flux monitoring requirements into the customized monitoring scheme; the monitoring execution module is also used to control each monitoring process unit to carry out continuous monitoring of wetland greenhouse gas flux according to the selected target execution scheme, and generate wetland greenhouse gas flux monitoring data.

[0053] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements a method for long-term greenhouse gas flux monitoring in wetlands based on tidal level simulation as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0054] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for long-term greenhouse gas flux monitoring in wetlands using tidal level simulation, characterized in that, The method includes the following steps: Needs to obtain monitoring information on greenhouse gas fluxes in wetlands; The wetland greenhouse gas flux monitoring requirements are broken down to obtain standardized monitoring elements. The standardized monitoring elements include several core monitoring modules to achieve the wetland greenhouse gas flux monitoring requirements. The core monitoring modules correspond to four key links: tide level synchronization, gas exchange regulation, concentration data acquisition, and flux estimation. Multiple preset monitoring process units are obtained, including a tide level synchronization unit, a gas exchange unit, a concentration monitoring unit, and a data processing unit, and a set of unit execution schemes corresponding to each monitoring process unit is obtained. For each of the monitoring process units, a target execution plan that matches the standardized monitoring elements is selected sequentially from the set of execution plans for each unit, and a customized monitoring plan is constructed based on the target execution plan; The acquired monitoring parameters corresponding to the wetland greenhouse gas flux monitoring requirements are imported into the customized monitoring scheme. Continuous monitoring of wetland greenhouse gas flux is carried out according to the selected target execution scheme, and wetland greenhouse gas flux monitoring data is generated.

2. The method for long-term greenhouse gas flux monitoring in wetlands using tidal level simulation as described in claim 1, characterized in that: For each of the monitoring process units, a target execution plan that matches the standardized monitoring elements is sequentially selected from the set of execution plans for each unit, and a customized monitoring plan is constructed based on the target execution plan, including: Obtain a set of preset mature monitoring schemes, which includes established monitoring schemes that have been verified and adapted to different wetland types and monitoring needs, and each established monitoring scheme is formed by combining the execution schemes of the corresponding monitoring process units; Based on the wetland greenhouse gas flux monitoring requirements, a predetermined monitoring scheme that is consistent with the core requirements of the standardized monitoring elements is retrieved from the set of mature monitoring schemes. If the established monitoring plan is found, then the established monitoring plan is determined as the customized monitoring plan; If the search for the established monitoring scheme fails, then for each monitoring process unit, a target execution scheme that matches the standardized monitoring element is sequentially selected from the set of execution schemes for each unit, and the customized monitoring scheme is constructed based on the target execution scheme.

3. The method for long-term greenhouse gas flux monitoring in wetlands using tidal level simulation as described in claim 2, characterized in that: When the customized monitoring scheme is constructed based on the target execution scheme, the effectiveness of the customized monitoring scheme is verified. After the verification is passed, the customized monitoring scheme and the corresponding standardized monitoring elements and adaptation scenario information are dynamically updated to the mature monitoring scheme set to generate a new mature monitoring scheme set. The effectiveness verification includes: confirming, through small-scale pilot monitoring, that the monitoring data accuracy of the customized monitoring scheme meets the preset threshold, that the execution schemes of each monitoring process unit are smoothly connected, and that it is adapted to the environmental conditions of the target wetland.

4. The method for long-term greenhouse gas flux monitoring in wetlands using tidal level simulation as described in claim 1, characterized in that: The step of sequentially selecting target execution schemes that match the standardized monitoring elements from the set of execution schemes for each monitoring process unit includes: Acquire historical monitoring data, which includes past wetland greenhouse gas flux monitoring demand information, corresponding standardized monitoring elements, target execution scheme selection results for each monitoring process unit, and monitoring effect verification data. Based on the historical monitoring data, a scheme matching model is constructed. The scheme matching model learns the correspondence between standardized monitoring elements and target execution schemes in the historical data, and establishes mapping rules between input standardized monitoring elements and output target execution schemes of each monitoring process unit. The standardized monitoring elements corresponding to the current wetland greenhouse gas flux monitoring needs are input into the scheme matching model for matching processing. The scheme matching model outputs the target execution scheme for each of the monitoring process units.

5. The method for long-term greenhouse gas flux monitoring in wetlands using tidal level simulation as described in claim 1, characterized in that: The step of sequentially selecting target execution schemes that match the standardized monitoring elements from the set of execution schemes for each monitoring process unit includes: Based on the core monitoring modules in the standardized monitoring elements, retained monitoring units are determined from each of the monitoring process units. The retained monitoring units are the core process units necessary to achieve the current wetland greenhouse gas flux monitoring requirements. Simultaneously determine the set of retention execution schemes that corresponds one-to-one with the retention monitoring unit in each of the set of execution schemes for each unit; For each retention monitoring unit, a target execution plan that matches the standardized monitoring elements is selected sequentially from the corresponding set of retention execution plans.

6. The method for long-term greenhouse gas flux monitoring in wetlands using tidal level simulation as described in claim 1, characterized in that: The method further includes: Using a pre-set monitoring process control module, the operation status and data generation of continuous monitoring of greenhouse gas flux in wetlands are monitored in real time. If the wetland greenhouse gas flux monitoring data is found to be fully generated and meets the preset monitoring cycle requirements, then the monitoring process is confirmed to be complete, and the operating resources of each of the retained monitoring units are released. These operating resources include sensor power supply resources, data transmission link resources, and storage cache resources; and / or, During the continuous monitoring of greenhouse gas flux in wetlands, if a manual stop command is received or an abnormal operating state is detected, the monitoring process control module will be used to stop any monitoring process unit in the customized monitoring scheme and save the collected monitoring data and current operating parameters.

7. The method for long-term greenhouse gas flux monitoring in wetlands using tidal level simulation as described in claim 1, characterized in that: The step of importing the acquired monitoring parameters corresponding to the wetland greenhouse gas flux monitoring requirements into the customized monitoring scheme to conduct continuous monitoring of wetland greenhouse gas fluxes and generate wetland greenhouse gas flux monitoring data includes: Using the customized monitoring scheme, based on the monitoring parameters, the target execution schemes corresponding to each monitoring process unit are run in parallel. The parallel operation is achieved through a multi-channel synchronous acquisition mechanism to ensure that the execution process of each monitoring process unit does not interfere with each other. The monitoring process data generated during the execution of each of the target execution schemes are stored in the monitoring database. The monitoring process data includes tide level synchronization accuracy data, gas exchange rate data, real-time gas concentration raw data, data processing intermediate results, and environmental adaptation status data. The monitoring process data from the monitoring database is called up, and the wetland greenhouse gas flux monitoring data is generated through data integration and verification. The integration and verification includes timestamp alignment, data accuracy filtering, outlier removal, and cross-unit data consistency verification.

8. The method for long-term greenhouse gas flux monitoring in wetlands using tidal level simulation as described in claim 7, characterized in that: The step of calling up the monitoring process data from the monitoring database and generating the wetland greenhouse gas flux monitoring data through data integration and verification includes: Based on the dependencies of each target execution scheme, a first execution scheme with a first call priority and a second execution scheme with a second call priority are determined among the target execution schemes; the second call priority is higher than the first call priority, and the first execution scheme is a basic class monitoring scheme, while the second execution scheme is an association class monitoring scheme that depends on basic data; The first monitoring process data generated during the execution of each of the first execution schemes is stored in the first monitoring database. The first monitoring process data includes tide level synchronization accuracy data, tide level change time sequence data, and tide level adaptation verification data. When the second execution scheme is run in parallel, second monitoring process data is generated based on the first monitoring process data called from the first monitoring database, and the second monitoring process data is stored in the second monitoring database; the second monitoring process data includes gas exchange rate data calibrated based on tide data, real-time gas concentration data associated with tide level, and intermediate results of flux estimation calculated based on basic data; Data from the first and second monitoring databases are retrieved, and timestamp alignment, cross-database data consistency verification, and dependency verification are performed in priority order to finally generate the wetland greenhouse gas flux monitoring data.

9. An apparatus for using the tidal level simulation-based long-term greenhouse gas flux monitoring method for wetlands as described in claim 1, characterized in that: include: The demand processing module is used to obtain the monitoring demand for greenhouse gas fluxes in wetlands. The demand processing module is also used to break down the wetland greenhouse gas flux monitoring demand to obtain standardized monitoring elements; the standardized monitoring elements are used to indicate the core monitoring module to achieve the monitoring demand, and the core monitoring module corresponds to four key links: tide level synchronization, gas exchange regulation, concentration data acquisition, and flux estimation. The monitoring scheme configuration module is used to acquire multiple preset monitoring process units, including: tide level synchronization unit, gas exchange unit, concentration monitoring unit, and data processing unit, and to acquire the unit execution scheme set corresponding to each monitoring process unit; the monitoring scheme configuration module is also used to select target execution schemes that match the standardized monitoring elements from each set of unit execution schemes for each monitoring process unit, and to construct customized monitoring schemes based on the target execution schemes; The implementation scheme of the tide synchronization unit includes transmitting natural tide level changes to the monitoring area through a water-filled U-shaped connecting pipe with no gas residue, so that the water level in the monitoring area is synchronized with the natural tide level; the implementation scheme of the gas exchange unit includes using a weak open-circuit gas exchange method to carry out extremely low-speed gas exchange, and adjusting the gas concentration in the gas chamber to avoid the accumulation of greenhouse gases; the implementation scheme of the concentration monitoring unit includes forming a closed loop between the gas chamber and the gas analyzer to continuously record the concentration data of CO2, CH4, and N2O in the gas chamber; the implementation scheme of the data processing unit includes using a sliding window fitting method to analyze the concentration data and estimate the greenhouse gas flux in the wetland. The monitoring execution module is used to import the monitoring parameters corresponding to the wetland greenhouse gas flux monitoring requirements into the customized monitoring scheme; the monitoring execution module is also used to control each monitoring process unit to carry out continuous monitoring of wetland greenhouse gas flux according to the selected target execution scheme, and generate wetland greenhouse gas flux monitoring data.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the long-term greenhouse gas flux monitoring method for tidal level simulation wetlands as described in any one of claims 1 to 8.

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