Comprehensive carbon sink assessment method and system for coastal salt marsh vegetation and sediment deposition

Abstract

This invention provides a method and system for assessing the integrated carbon sink of coastal salt marsh vegetation and sediment deposition. The system comprises a vegetation dynamics module, a hydrodynamics module, a carbon dynamics module, and a coupled vegetation dynamics-hydrodynamics-carbon dynamics module. The outputs are divided into the spatiotemporal dynamics of vegetation-water-sand-geomorphology and the spatiotemporal dynamics of ecosystem carbon exchange. These results are used to assess the geomorphic development and carbon sink dynamics of the salt marsh-beach system. Based on the development of a gridded process model, this invention couples the vegetation dynamics model, the hydrodynamics model, and the carbon dynamics model to construct a biogeochemical coupling model that integrates the interactions between biological, hydrological, and geomorphic processes. This model parameterizes the biogeochemical processes of coastal salt marsh vegetation dynamics and sediment carbon sinks, providing an effective assessment technique for the community development and carbon sink dynamics of coastal wetland vegetation.

Description

Technical Field

[0001] The present invention belongs to the technical field of ecological environmental protection, and specifically relates to a method and system for comprehensively evaluating carbon sinks of coastal salt marsh vegetation and sediment deposition, and more particularly to a method for dynamically evaluating coastal wetland salt marsh vegetation growth, community development, tidal movement, sediment transport, plant photosynthesis, soil respiration, gross primary productivity, net ecosystem exchange, and sediment carbon storage using a computer. Background Art

[0002] To address climate change, in addition to controlling carbon emissions, increasing natural carbon sinks is also a key approach, given the high CO2 emissions from industrial production in the context of rapid economic development. Coastal wetlands, as a unique coastal ecosystem, possess extremely high carbon sequestration rates and long-term, sustainable carbon storage capacity. Coastal salt marshes, along with mangroves and seagrasses, are known as "blue carbon" ecosystems. They are among the world's most productive ecosystems, boasting high carbon sequestration rates, long-term carbon storage, and the potential for climate change adaptation. Statistics show that coastal wetlands store an estimated 18.75 tons of carbon annually per square kilometer.

[0003] As a typical biogeomorphic ecosystem, coastal salt marsh vegetation ecosystems exhibit complex biophysical feedbacks between vegetation, hydrology, and sediment components. Carbon exchange within these ecosystems exhibits spatiotemporal heterogeneity, influenced by biological, environmental, and climatic factors. For example, plant phenology is a key factor influencing soil carbon storage in coastal wetlands, with soil carbon storage gradually increasing with the progression of the plant growth cycle. Moderate temperature increases enhance photosynthetic enzyme activity and strengthen plant carbon dioxide absorption capacity. Tidal inundation modulates soil temperature and reduces oxygen concentration, thereby inhibiting soil microbial activity and reducing the decomposition rate of organic matter. Furthermore, tidal sediment transport influences the loss, migration, and burial of organic carbon in sediments, a process that is disrupted by vegetation dynamics, such as sediment interception and erosion resistance. Furthermore, coastal tides typically exhibit two types of hydrological cycles on different timescales: semidiurnal and semilunar. Due to differences in inundation height, frequency, and duration at different habitat elevations, tidal influences on carbon processes in coastal wetland ecosystems can vary significantly.

[0004] Therefore, clarifying the impact of various environmental factors on salt marsh growth and community dynamics, as well as the mechanisms and regulatory mechanisms of carbon sequestration, and exploring the carbon sequestration capacity and storage of salt marshes, along with the research methods and principles, will help us leverage these ecosystems to enhance carbon sequestration. However, the current components of blue carbon in coastal wetlands need to be refined, and existing assessment techniques involve incomplete dynamic data, emission factors, and other relevant measurement parameters, resulting in significant uncertainty in the assessment of the carbon sequestration capacity of coastal salt marsh vegetation and sediments.

[0005] Due to the complexity of hydrological factors such as tidal dynamics, sediment deposition / scouring and salinity changes in the sea-land interface zone, if we only consider wetland vegetation, tidal flat soil and water carbon processes, we may not be able to objectively analyze the basic laws under the interaction of water, sand, vegetation and landforms. Only by combining detailed eco-geomorphology on the interaction between water, sand, vegetation and landforms can we scientifically analyze the carbon cycle process mechanism of coastal ecosystems.

[0006] Assessment techniques based on validated models can help understand and predict the carbon sequestration capacity of coastal salt marsh vegetation and sediments. In recent years, a series of process-based models of vegetation and carbon dynamics have been developed. However, most current modeling techniques focus on the short-term photosynthetic performance of plants in response to climate change, and the parameterization of biological processes is based on simply defined static vegetation modules. These techniques rarely capture the complex interactions between biotic and abiotic processes in coastal wetland ecosystems, and therefore cannot accurately capture the dynamics of biophysical feedback processes that change with vegetation growth, such as water convergence and resistance, and sediment accretion and erosion resistance.

[0007] At present, most ecological models are unable to take into account the impact of complex climate, hydrology, and sediment changes on biogeomorphological and geochemical processes such as coastal wetland landforms, vegetation carbon sequestration, and system carbon cycling. The impact of tidal movement and sediment transport on the vertical and horizontal carbon exchange of biomass carbon and sediment carbon in salt marsh ecosystems has been ignored, resulting in many cases where the carbon sink estimation results are significantly different from the actual values. The patent documents "A method and system for quantitatively estimating carbon reserves in native coastal wetland ecosystems" (CN111488902A) and the patent document "A method and device for estimating carbon sinks in coastal salt marsh wetlands, storage medium and electronic equipment" (CN119007004A) both mainly use empirical model methods, focusing on the short-term photosynthetic performance of plants in response to climate change. The parameterization of biological processes is based on simply delineated static vegetation modules, and there is less detailed characterization of the complex interactions between biological and abiotic processes in coastal wetland ecosystems. In addition, for the unique geographical area of coastal wetlands, the effects of tidal movement and sediment transport on the vertical and horizontal multi-component carbon exchange of biomass carbon and sediment carbon in salt marsh ecosystems are ignored, and this important input carbon sink formed by external sediment deposition is missing.

[0008] To date, the carbon sequestration capacity of coastal salt marsh vegetation and sediments, and the factors influencing it, remain unclear. The differences in carbon sequestration capacity between different salt marsh vegetation and sediments in different habitats also require further study. In general, using existing carbon sequestration calculation methods often makes it difficult to accurately assess the carbon sequestration capacity of coastal salt marsh vegetation and sediments.

[0009] Therefore, clarifying the biophysical feedback mechanism between the biological, ecological, and geomorphological dynamic characteristics of coastal wetland salt marsh ecosystems, accurately evaluating the carbon sequestration capacity of coastal wetland salt marsh vegetation and sediments, and providing a reliable theoretical basis for the management of coastal wetlands have become technical issues that need to be urgently addressed. Summary of the Invention

[0010] In view of the defects in the prior art, the purpose of the present invention is to provide a method and system for comprehensive carbon sink assessment of coastal salt marsh vegetation and sediment deposition.

[0011] The method for comprehensive carbon sink assessment of coastal salt marsh vegetation and sediment deposition provided by the present invention includes:

[0012] Step 1: Measure the organic carbon content of sediments / soils and CO2 flux in salt marshes at the site to be measured, identify the distribution of land features at the site to be measured based on remote sensing image interpretation, and generate a remote sensing image dataset.

[0013] Step 2: Using the distribution of salt marshes and light beaches in remote sensing imagery datasets as the simulation domain, a real-time data-driven model was constructed to build a coupled vegetation dynamics-hydrodynamics-carbon dynamics model;

[0014] Step 3: calibrating the vegetation dynamics-hydrodynamics-carbon dynamics coupled model based on the organic carbon content, salt marsh CO2 flux, land feature type distribution, and measured plant biomass data;

[0015] Step 4: Output the distribution of landforms and carbon flux of coastal salt marsh vegetation and sediment deposition through the calibrated vegetation dynamics-hydrodynamics-carbon dynamics coupling model to obtain the assessment results of spatiotemporal dynamics and carbon sequestration capacity.

[0016] Preferably, the salt marsh CO2 flux measurement method is to use the eddy covariance method or the box method to conduct seasonal positioning observation of the salt marsh CO2 exchange flux.

[0017] The calculation formula for the organic carbon storage and total organic carbon content of each layer in the sediment / soil is:

[0018]

[0019]

[0020] in, Indicates the total organic carbon content of sediment / soil; represents soil organic carbon density; BD represents total soil bulk density; represents the soil organic carbon density of the i-th layer, T represents the total soil thickness; SOC represents the organic carbon content of the soil, and there are n layers of soil; T i represents the thickness of the i-th soil layer; BD i represents the soil bulk density of the i-th layer.

[0021] The remote sensing image interpretation is to interpret and identify multi-phase remote sensing images, obtain the area and coverage ratio of salt marshes and light beaches in the surveyed area and elevation distribution data, perform supervised classification processing and delineate the habitat units of salt marshes, light beaches and water, and optimize the classification results of land feature categories through field verification during the growing season.

[0022] The remote sensing image dataset includes land feature categories of salt marshes, bare beaches and water, area and coverage of the land feature categories, and elevation distribution data.

[0023] Preferably, the real-time acquired data includes meteorological data, terrain elevation, tidal hydrological pattern, sediment content and salinity measured by meteorological stations and hydrological stations.

[0024] The vegetation dynamics-hydrodynamics-carbon dynamics coupling model includes a vegetation dynamics module, a hydrodynamics module, a carbon dynamics module and a coupling module.

[0025] The vegetation dynamics module is a spatial grid matrix consisting of interconnected grids, where each grid connects all adjacent grids. Each connection has a distribution probability associated with vegetation expansion. The relationship N between vegetation settlement and reproduction - seed bank yield, germination rate and survival rate is:

[0026]

[0027]

[0028] Among them, N max represents the maximum seed bank; t v Indicates the month; E indicates the tidal flat elevation; E 0v Indicates the elevation threshold required for seed retention; S v represents the seed bank decay rate; is the sediment coefficient related to sediment particle size; Represents the hydrological tolerance threshold associated with propagule establishment.

[0029] The hydrodynamic module is based on the unsteady shallow water equations and applies a depth-averaged model, including:

[0030] External sediment deposition / erosion rate of muddy beach , the functional relationship between soil matrix sediment deposition / erosion rate in vegetation area and fluid friction coefficient and bottom shear force Net flux of particulate carbon from sediments, silt, and salt marsh litter as a function of vegetation type, seasonal tidal patterns, external sediment load, and hydrodynamic changes ;

[0031] Where c is the vertical average sediment concentration; h is the water depth; t is the time; u is the vertical average velocity component in the x direction; v is the vertical average velocity component in the y direction; ε x represents the sediment diffusion rate in the x direction; ε y represents the diffusion rate in the y direction; Q e represents the erosion flux; Q d represents the deposition flux; represents the bottom bed shear force; p represents the fluid density; g represents the acceleration due to gravity; is the average flow velocity component; C Z represents the Coriolis coefficient; C PC represents the average particle concentration; PC e Indicates the amount of granular carbon washed; PC d Indicates the amount of particulate carbon deposition.

[0032] Preferably, in the carbon dynamics module, the functional relationship between plant photosynthetic rate, photosynthetic enzyme activity, chlorophyll fluorescence parameters, autotrophic respiration-climate, soil and hydrological conditions, as well as canopy carbon uptake, layered leaf area index and canopy conductance / photosynthetic limitation function is:

[0033]

[0034]

[0035]

[0036]

[0037]

[0038]

[0039]

[0040]

[0041] The canopy level photosynthetic model is:

[0042]

[0043]

[0044]

[0045]

[0046]

[0047]

[0048]

[0049]

[0050] The leaf level and canopy level development of plants are based on:

[0051]

[0052]

[0053]

[0054]

[0055]

[0056]

[0057] in, represents the total carbon uptake at the leaf level; represents the net photosynthetic product at the leaf level; Indicates respiration at the leaf level; represents the photosynthesis rate limited by Rubisco; represents the finite rate of RuBP regeneration photosynthesis; represents the maximum rate of Rubisco activity; J represents the electron transport rate; Indicates the maximum rate of electron transfer; represents photosynthetically active radiation; Indicates the CO2 compensation point in the absence of dark respiration; represents the Michaelis constant of CO2; represents the Michaelis constant of O2; O represents the oxygen concentration; represents the curvature of the standard rod number response curve of the electron transport rate; α represents the quantum efficiency; Indicates air temperature; Indicates the CO2 concentration in the atmosphere; is the intercellular CO2 concentration; represents the coefficient of influence of flooding on plant photosynthesis; is the correction coefficient of the temperature response curve; θ represents the curvature of the PAR response curve of the electron transfer rate; represents the stomatal conductance of leaves; 、 represent the maximum and minimum leaf stomatal conductance, respectively; f(·) represents a function with · as the independent variable, where f is the corresponding calculation rule; Indicates V at 25°Ccmax or J max Parameter indicates the value of V cmax or J max The value of represents the activation enthalpy; represents the deactivation enthalpy; represents the entropy of desaturation equilibrium; R represents the correction factor; represents the total canopy-level carbon uptake at the canopy level; represents the net photosynthesis at the canopy level; represents respiration at the canopy level; represents the net canopy-level assimilation of sunlight-exposed leaves; represents the net canopy-level assimilation of shaded leaves; represents the relative average photon flux density on the leaf illuminated by sunlight; represents the relative average photon flux density on the shaded leaves; Represents the direct component of light radiation incident on the top of the awning; Represents the scattered component of light radiation incident on the top of the awning; represents the light radiation incident on the top of the leaf canopy; represents the sunny side leaf area index; represents the shaded leaf area index; K represents the extinction coefficient; β represents the solar altitude angle; t represents time; is the leaf nitrogen content; Indicates the maximum leaf nitrogen content; is the stomatal conductance of the leaf on the sunny side; is the stomatal conductance of leaves on the shaded side; LAI represents leaf area index; represents the leaf area index at the top of the leaf canopy; represents the maximum leaf area index; Indicates the accumulated temperature; All represent leaf canopy parameters; Indicates the nitrogen content of leaves when the minimum photosynthetic rate occurs; They represent the accumulated temperature when the maximum leaf area index and the maximum leaf nitrogen content appear respectively; All represent the correction coefficients for leaf area and leaf nitrogen content, x = v, j, r; Indicates the average daily temperature.

[0058] Preferably, the change rate of carbon accumulation and carbon partition coefficient of salt marsh plant biomass under climate, soil and hydrological conditions in the coupling module is:

[0059]

[0060]

[0061]

[0062] The functional relationship between plant litter organic carbon decomposition rate and litter quality, soil and hydrological factors is:

[0063] dL / dt = L0- (k1+ k2)L

[0064] dF / dt = k3L - (k2+ k4+ k5)F

[0065] dH / dt = (k4+ k5) F- k6H

[0066] Soil CO2 emissions - the functional relationship between CO2 release from soil organic matter decomposition and the temperature sensitivity of soil heterotrophic respiration, and the relationship function of coupled CO2 emissions with changes in soil moisture and salinity is:

[0067]

[0068] The net flux of soluble carbon in sediments is a function of vegetation type, seasonal tidal pattern, and runoff changes:

[0069]

[0070] Among them, AGB represents plant aboveground biomass; GB represents total biomass accumulation; NPP represents net primary productivity; represents litter biomass; BGB represents underground biomass; E represents tidal flat elevation; f represents mean tidal range; g represents biomass isometric distribution coefficient; L represents undecomposed litter content; t represents time; L0 represents litter input; F represents total humus storage capacity; H represents complete humus content; k1, k2, k3, k4, k5, and k6 represent parameters related to the decomposition rate of litter components; R s represents soil CO2 emissions; R p represents the maximum soil respiration rate; represents the slope of the response of respiration rate to changes in soil moisture; C θ Represents parameters related to soil moisture; f s Indicates Q 10 Function; Q 10 represents the temperature sensitivity of soil heterotrophic respiration; T s Indicates soil temperature; represents the divergence of mass flow due to diffusion; f DC represents the soluble carbon flux; D represents the hydrodynamic diffusion tensor; C DC Indicates the concentration of a fluid-soluble carbon source or sink C represents the soluble carbon concentration in pore water; represents the Darcy velocity vector; represents porosity; represents the fluid density; It represents the ratio of the volume occupied by water in the pores to the pore volume; represents the sediment density; Q represents the organic carbon flux in the sediment.

[0071] In step 4, the hydrodynamic module parameters are updated by outputting the biomass matrix of the change rate of salt marsh plant biomass carbon accumulation and carbon distribution coefficient under the climate, soil and hydrological conditions, and the variables of the vegetation dynamic module and the carbon dynamic module are updated by monitoring the time series of water depth data and water level at the hydrological station. The simulation deviation is checked and judged whether the error meets the preset requirements.

[0072] If the preset requirements are met, the calculated results of the feature type distribution and carbon flux are output. If the preset requirements are not met, step 2 is executed to review and calibrate the input parameters of the model, or to perform a sensitivity analysis to detect the sensitivity of the output results to the input parameters, and adjust the parameters until the error meets the preset requirements.

[0073] The calculation results include the area of salt marshes and beaches, total carbon absorption at leaf level , leaf level net photosynthetic product and breathing at the leaf level Respiration with soil The harmony.

[0074] According to the present invention, a coastal salt marsh vegetation and sediment deposition integrated carbon sink assessment system is provided, which includes a vegetation dynamics-hydrodynamics-carbon dynamics coupling model.

[0075] Determine the organic carbon content of sediments / soils and CO2 flux in salt marshes at the site to be measured, identify the distribution of land features at the site to be measured based on remote sensing image interpretation, and generate a remote sensing image dataset.

[0076] The distribution of salt marshes and light beaches in remote sensing imagery datasets was used as the simulation domain, and a coupled vegetation dynamics-hydrodynamics-carbon dynamics model was constructed using real-time data-driven models.

[0077] The vegetation dynamics-hydrodynamics-carbon dynamics coupled model was calibrated based on the organic carbon content, salt marsh CO2 flux, land feature type distribution, and measured plant biomass data;

[0078] The coverage area and carbon flux of coastal salt marsh vegetation and sediment deposition were output through the calibrated vegetation dynamics-hydrodynamics-carbon dynamics coupling model to obtain the assessment results of spatiotemporal dynamics and carbon sequestration capacity.

[0079] Preferably, the salt marsh CO2 flux measurement method is to use the eddy covariance method or the box method to conduct seasonal positioning observation of the salt marsh CO2 exchange flux.

[0080] The calculation formula for the organic carbon storage and total organic carbon content of each layer in the sediment / soil is:

[0081]

[0082]

[0083] in, Indicates the total organic carbon content of sediment / soil; represents soil organic carbon density; BD represents total soil bulk density; represents the soil organic carbon density of the i-th layer, T represents the total soil thickness; SOC represents the organic carbon content of the soil, and there are n layers of soil; T i represents the thickness of the i-th soil layer; BD i represents the soil bulk density of the i-th layer.

[0084] The remote sensing image interpretation is to interpret and identify multi-phase remote sensing images, obtain the area and coverage ratio of salt marshes and light beaches in the surveyed area and elevation distribution data, perform supervised classification processing and delineate the habitat units of salt marshes, light beaches and water, and optimize the classification results of land feature categories through field verification during the growing season.

[0085] The remote sensing image dataset includes land feature categories of salt marshes, bare beaches and water, area and coverage of the land feature categories, and elevation distribution data.

[0086] Preferably, the real-time acquired data includes meteorological data, terrain elevation, tidal hydrological pattern, sediment content and salinity measured by meteorological stations and hydrological stations.

[0087] The vegetation dynamics-hydrodynamics-carbon dynamics coupling model includes a vegetation dynamics module, a hydrodynamics module, a carbon dynamics module and a coupling module.

[0088] The vegetation dynamics module is a spatial grid matrix consisting of interconnected grids, where each grid connects all adjacent grids. Each connection has a distribution probability associated with vegetation expansion. The relationship N between vegetation settlement and reproduction - seed bank yield, germination rate and survival rate is:

[0089]

[0090]

[0091] Among them, N max represents the maximum seed bank; t v Indicates the month; E indicates the tidal flat elevation; E 0v Indicates the elevation threshold required for seed retention; S v represents the seed bank decay rate; is the sediment coefficient related to sediment particle size; Represents the hydrological tolerance threshold associated with propagule establishment.

[0092] The hydrodynamic module is based on the unsteady shallow water equations and applies a depth-averaged model, including:

[0093] External sediment deposition / erosion rate of muddy beach , the functional relationship between soil matrix sediment deposition / erosion rate in vegetation area and fluid friction coefficient and bottom shear force Net flux of particulate carbon from sediments, silt, and salt marsh litter as a function of vegetation type, seasonal tidal patterns, external sediment load, and hydrodynamic changes ;

[0094] Where c is the vertical average sediment concentration; h is the water depth; t is the time; u is the vertical average velocity component in the x direction; v is the vertical average velocity component in the y direction; ε x represents the sediment diffusion rate in the x direction; ε y represents the diffusion rate in the y direction; Q e represents the erosion flux; Q d represents the deposition flux; represents the bottom bed shear force; p represents the fluid density; g represents the acceleration due to gravity; is the average flow velocity component; C Z represents the Coriolis coefficient; C PC represents the average particle concentration; PC e Indicates the amount of granular carbon washed; PC d Indicates the amount of particulate carbon deposition.

[0095] Preferably, in the carbon dynamics module, the functional relationship between plant photosynthetic rate, photosynthetic enzyme activity, chlorophyll fluorescence parameters, autotrophic respiration-climate, soil and hydrological conditions, as well as canopy carbon uptake, layered leaf area index and canopy conductance / photosynthetic limitation function is:

[0096]

[0097]

[0098]

[0099]

[0100]

[0101]

[0102]

[0103]

[0104] The canopy level photosynthetic model is:

[0105]

[0106]

[0107]

[0108]

[0109]

[0110]

[0111]

[0112]

[0113] The leaf level and canopy level development of plants are based on:

[0114]

[0115]

[0116]

[0117]

[0118]

[0119]

[0120] in, represents the total carbon uptake at the leaf level; represents the net photosynthetic product at the leaf level; Indicates respiration at the leaf level; represents the photosynthesis rate limited by Rubisco; represents the finite rate of RuBP regeneration photosynthesis; represents the maximum rate of Rubisco activity; J represents the electron transport rate; Indicates the maximum rate of electron transfer; represents photosynthetically active radiation; Indicates the CO2 compensation point in the absence of dark respiration; represents the Michaelis constant of CO2; represents the Michaelis constant of O2; O represents the oxygen concentration; represents the curvature of the standard rod number response curve of the electron transport rate; α represents the quantum efficiency; Indicates air temperature; Indicates the CO2 concentration in the atmosphere; is the intercellular CO2 concentration; represents the coefficient of influence of flooding on plant photosynthesis; is the correction coefficient of the temperature response curve; θ represents the curvature of the PAR response curve of the electron transfer rate; represents the stomatal conductance of leaves; 、 represent the maximum and minimum leaf stomatal conductance, respectively; f(·) represents a function with · as the independent variable, where f is the corresponding calculation rule; Indicates V at 25°C cmax or J max Parameter indicates the value of V cmax or J max The value of represents the activation enthalpy; represents the deactivation enthalpy; represents the entropy of desaturation equilibrium; R represents the correction factor; represents the total canopy-level carbon uptake at the canopy level; represents the net photosynthesis at the canopy level; represents respiration at the canopy level; represents the net canopy-level assimilation of sunlight-exposed leaves; represents the net canopy-level assimilation of shaded leaves; represents the relative average photon flux density on the leaf illuminated by sunlight; represents the relative average photon flux density on the shaded leaves; Represents the direct component of light radiation incident on the top of the awning; Represents the scattered component of light radiation incident on the top of the awning; represents the light radiation incident on the top of the leaf canopy; represents the sunny side leaf area index; represents the shaded leaf area index; K represents the extinction coefficient; β represents the solar altitude angle; t represents time; is the leaf nitrogen content; Indicates the maximum leaf nitrogen content; is the stomatal conductance of the leaf on the sunny side; is the stomatal conductance of leaves on the shaded side; LAI represents leaf area index; represents the leaf area index at the top of the leaf canopy; represents the maximum leaf area index; Indicates the accumulated temperature; All represent leaf canopy parameters; Indicates the nitrogen content of leaves when the minimum photosynthetic rate occurs; They represent the accumulated temperature when the maximum leaf area index and the maximum leaf nitrogen content appear respectively; All represent the correction coefficients for leaf area and leaf nitrogen content, x = v, j, r; Indicates the average daily temperature.

[0121] Preferably, the change rate of carbon accumulation and carbon partition coefficient of salt marsh plant biomass under climate, soil and hydrological conditions in the coupling module is:

[0122]

[0123]

[0124]

[0125] The functional relationship between plant litter organic carbon decomposition rate and litter quality, soil and hydrological factors is:

[0126] dL / dt = L0- (k1+ k2)L

[0127] dF / dt = k3L - (k2+ k4+ k5)F

[0128] dH / dt = (k4+ k5) F- k6H

[0129] Soil CO2 emissions - the functional relationship between CO2 release from soil organic matter decomposition and the temperature sensitivity of soil heterotrophic respiration, and the relationship function of coupled CO2 emissions with changes in soil moisture and salinity is:

[0130]

[0131] The net flux of soluble carbon in sediments is a function of vegetation type, seasonal tidal pattern, and runoff changes:

[0132]

[0133] Among them, AGB represents plant aboveground biomass; GB represents total biomass accumulation; NPP represents net primary productivity; represents litter biomass; BGB represents underground biomass; E represents tidal flat elevation; f represents mean tidal range; g represents biomass isometric distribution coefficient; L represents undecomposed litter content; t represents time; L0 represents litter input; F represents total humus storage capacity; H represents complete humus content; k1, k2, k3, k4, k5, and k6 represent parameters related to the decomposition rate of litter components; R s represents soil CO2 emissions; R prepresents the maximum soil respiration rate; represents the slope of the response of respiration rate to changes in soil moisture; C θ Represents parameters related to soil moisture; f s Indicates Q 10 Function; Q 10 represents the temperature sensitivity of soil heterotrophic respiration; T s Indicates soil temperature; represents the divergence of mass flow due to diffusion; f DC represents the soluble carbon flux; D represents the hydrodynamic diffusion tensor; C DC Indicates the concentration of a fluid-soluble carbon source or sink C represents the soluble carbon concentration in pore water; represents the Darcy velocity vector; represents porosity; represents the fluid density; It represents the ratio of the volume occupied by water in the pores to the pore volume; represents the sediment density; Q represents the organic carbon flux in the sediment.

[0134] The parameters of the hydrodynamic module are updated through the output biomass matrix of the change rate of salt marsh plant biomass carbon accumulation and carbon distribution coefficient under the aforementioned climatic, soil and hydrological conditions. The variables of the vegetation dynamic module and the carbon dynamic module are updated through the time series of water depth data and water level monitored by the hydrological station. The simulation deviation is checked and judged whether the error meets the preset requirements.

[0135] If the preset requirements are met, the calculation results of the land feature type distribution and carbon flux are output. If the preset requirements are not met, module 2 is triggered to review and correct the input parameters of the model, or perform sensitivity analysis to detect the sensitivity of the output results to the input parameters, and adjust the parameters until the error meets the preset requirements.

[0136] The calculation results include the area of salt marshes and beaches, total carbon absorption at leaf level , leaf level net photosynthetic product and breathing at the leaf level Respiration with soil The harmony.

[0137] Compared with the prior art, the present invention has the following beneficial effects:

[0138] 1. Based on the development of a grid-based process model, the present invention couples the vegetation dynamics model, the hydrodynamics model, and the carbon dynamics model to construct a biogeochemical coupling model that integrates the interactions among biological, hydrological, and geomorphological processes, providing a reliable theoretical basis for the management of coastal wetlands.

[0139] 2. The present invention includes a carbon cycle multi-process calculation module, and also incorporates the spatiotemporal dynamics of carbon sink indicators such as lateral carbon exchange caused by sediment erosion, transportation, and deposition, such as sediment carbon loss, migration, and burial, thereby evaluating the spatiotemporal dynamics and carbon sink capacity of coastal salt marsh vegetation and sediments.

[0140] 3. This invention integrates the interactions among biological, hydrological and geomorphological processes, uses numerical methods based on modeling processes to quantify the spatiotemporal dynamics of vegetation, and parameterizes the biogeochemical processes of coastal salt marsh vegetation dynamics and sediment carbon sinks, which helps to provide an effective assessment technology for the community development and carbon sink dynamics of coastal wetland vegetation. BRIEF DESCRIPTION OF THE DRAWINGS

[0141] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0142] Figure 1 This is a flow chart of the integrated carbon sink assessment method for coastal salt marsh vegetation and sediment deposition;

[0143] Figure 2 Schematic diagram of TSOC content in sediments of Jiuduansha salt marsh habitat;

[0144] Figure 3 Schematic diagram of the observation and simulation results of the Jiuduansha salt marsh distribution from 2000 to 2020;

[0145] Figure 4 Schematic diagram of the observation and simulation results of the Jiuduansha contour distribution from 2000 to 2020;

[0146] Figure 5 Schematic diagram of the observation and simulation results of the monthly NEE dynamics of Jiuduansha salt marsh vegetation in 2020;

[0147] Figure 6 Schematic diagram of the observation and simulation results of the spatial distribution of Jiuduansha salt marsh from 2000 to 2020;

[0148] Figure 7 Schematic diagram of the simulation results of the spatial distribution of GPP and NEE in Jiuduansha from 2000 to 2020;

[0149] Figure 8 Schematic diagram of the simulation results of sediment flux and carbon sequestration in the Jiuduansha salt marsh habitat in 2020. DETAILED DESCRIPTION

[0150] The present invention will be described in detail below with reference to specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those skilled in the art, several changes and improvements can be made without departing from the scope of the present invention. These all fall within the scope of protection of the present invention.

[0151] To describe the biogeochemical processes of coastal wetland vegetation-water-mudflat ecosystems, systematically evaluate the carbon sequestration capacity of coastal salt marsh vegetation and sediments, and provide a reliable theoretical basis for coastal wetland management, the present invention provides a comprehensive carbon sequestration assessment method for coastal salt marsh vegetation and sediment deposition. The method uses a computer to analyze the dynamics of coastal wetland salt marsh vegetation growth, community development, tidal movement, sediment transport, plant photosynthesis, soil respiration, gross primary productivity, net ecosystem exchange, and sediment carbon storage, including:

[0152] Step 1: Determine sediment or soil organic carbon content and salt marsh CO2 flux.

[0153] The sediment / soil organic carbon (SOC) content determination and carbon storage calculation method includes: after air-drying the sediment / soil sample, crushing the sample with a wooden hammer to separate the plant roots in the sample and remove debris such as stones and insects. After mixing, 1 kg of the sample is passed through a 2 mm sieve, 10-20 g is finely ground with a mortar and passed through a 100-mesh sieve, and 0.5 g is placed in a 10 ml centrifuge tube and acidified with 10% dilute hydrochloric acid for 24 hours to remove inorganic carbon components. The sample is then rinsed with Mill-Q water to neutrality and dried in a 60°C oven to constant weight. The SOC content of the treated sample is determined using a CHNO elemental analyzer (the analysis accuracy is within 5%).

[0154] The calculation of organic carbon storage (SOC) and total organic carbon content (TSOC) of each layer of sediment / soil is as follows: the soil organic carbon content of layer i is the soil organic carbon density of layer i multiplied by the soil mass of layer i. The soil mass is obtained by multiplying the soil layer thickness by the soil bulk density:

[0155]

[0156] The total organic carbon content was obtained by summing the soil organic carbon contents of n layers according to the following formula:

[0157]

[0158] Where, is the total sediment / soil total organic carbon content, SOC is the soil organic carbon content, represents the soil organic carbon density, represents the soil organic carbon density in the i-th layer, T iis the thickness of the i-th soil layer, BD i is the soil bulk density of the i-th layer. BD is the total soil bulk density; T is the total soil thickness; there are n soil layers in total.

[0159] The salt marsh CO2 flux measurement and calculation method includes: using eddy covariance or box method technology to conduct seasonal positioning observations of the CO2 exchange flux of the Jiuduansha salt marsh in the Yangtze River estuary, and by quantifying the net exchange of the ecosystem, soil respiration and total ecosystem respiration, to grasp the CO2 flux characteristics between the salt marsh wetland and the atmosphere.

[0160] In more preferred examples, taking Jiuduansha as an example, Figure 2 The TSOC content of salt marsh sediments shown in Figure 1 indicates measurement locations. C1, C2, C5, C6, C7, C10, C11, C12, C1+, S2, and X1 represent measurement locations. Monitoring results from 2022 show that total organic carbon in sediments ranged from 0.36 to 3.97 g / kg, calculated as an average of 2.41 g / kg. The lowest value occurred at C10 in winter, and the highest at C1 in autumn. The total organic carbon in summer sediments ranged from 0.43 to 3.78 g / kg, with an average of 2.22 g / kg. The lowest value occurred at S2 and the highest value occurred at C1+. The total organic carbon in autumn sediments ranged from 0.9 to 3.97 g / kg, with an average of 2.58 g / kg. The lowest value occurred at C7 and the highest value occurred at C1. The total organic carbon in winter sediments ranged from 0.36 to 3.81 g / kg, with an average of 2.44 g / kg. The lowest value occurred at C10 and the highest value occurred at C12.

[0161] Step 2: Based on the types of coastal wetlands identified by remote sensing image interpretation, determine the area and coverage data of each land feature type of the coastal wetland to be evaluated in the remote sensing images of each time period.

[0162] Taking Jiuduansha as an example, its main salt marsh species are Spartina alterniflora (S.alterniflora), Phragmites australis (P. australis), and Scirpus mariqueter (S. mariqueter). Figure 3 The results of observation and simulation of the distribution of Jiuduansha salt marsh during the study period of 2000-2020 are shown. Figure 3 The upper part shows that the total area of Jiuduansha salt marsh vegetation increased from 28.5km 2 Increased to 97.5km 2Overall, the populations of Spartina alterniflora and Phragmites australis showed rapid and slow expansion trends, respectively, while the coverage area of Scirpus maritima gradually decreased. Figure 3 The regression analysis in the lower part shows strong similarity and statistical significance between the observed and modeled vegetation areas.

[0163] Figure 4 The figure shows the observed and simulated contour distribution of Jiuduansha during the study period of 2000–2020. As shown in the figure, the simulated terrain evolution of Jiuduansha is characterized by simultaneous horizontal expansion and vertical sedimentation. The terrain elevation is positively correlated with the sedimentation rate, indicating that the expansion rate at the 2 m contour is 1.4 times and 1.2 times that at 1 m and 0 m, respectively. Figure 4 The regression analysis in the lower part shows strong similarity and statistical significance between the observed and modeled vegetation areas.

[0164] The remote sensing image dataset interpretation method used is remote sensing image interpretation. Taking the Jiuduansha Wetland National Nature Reserve in the Yangtze River Estuary as an example, the area, coverage ratio and elevation distribution data of salt marshes and light beaches were obtained by interpreting and identifying multi-phase remote sensing images. ENVI 5.2 software was used for supervised classification processing. Habitat units such as coastal salt marshes, light beaches and inland dam buffer zones were delineated using the ArcGIS 10.0 platform. Field verification during the growing season was used to further optimize the ground feature classification results. Figure 6 、 Figure 7 For example, the area, coverage ratio and elevation distribution data of salt marshes and light beaches identified by interpretation are used as input data for the plant-water-sand-carbon process model.

[0165] Step 3: Generate a remote sensing image dataset of the coastal wetland to be assessed within the target time period. This dataset includes landforms such as salt marshes, bare beaches, and water. The distribution of the identified landforms is interpreted and used as input data for the vegetation dynamics module and the water dynamics module.

[0166] Step 4: Using the regional salt marsh and beach distribution as the simulation domain, and using the meteorological data, terrain elevation, tidal hydrological pattern, sediment content and salinity obtained from meteorological and hydrological stations as model driving parameters, a vegetation dynamics-hydrodynamics-carbon dynamics coupling model was constructed.

[0167] Using a method that combines ecological process analysis with empirical relationships, the authors couple plant dynamics, hydrodynamics, and carbon dynamics in coastal wetland ecosystems. This includes vertical carbon exchange in vegetation due to plant phenology, such as gross primary productivity, net primary productivity, ecosystem respiration, and net ecosystem exchange. Furthermore, a coupled model of vegetation dynamics, hydrodynamics, and carbon dynamics was constructed, combining field experiments and remote sensing imagery interpretation data. Specifically, detailed parameterization of biological processes such as plant growth, reproduction, and establishment in coastal wetlands under tidal conditions was performed. The biophysical feedbacks between tidal flat water and sediment movement and vegetation processes were comprehensively considered, and the important carbon sink of allochthonous sediment deposition was incorporated into the model for detailed calculations and measurement.

[0168] The construction of the vegetation dynamics-hydrodynamics-carbon dynamics coupling model includes:

[0169] Step S4.1: Vegetation dynamics module.

[0170] In MATLAB ® The platform constructs a spatial grid matrix (1×1 m resolution) composed of interconnected grids. These grids are connected to all adjacent grids, and each connection has a distribution probability associated with vegetation expansion. The spatial and temporal dynamics of salt marsh plants are driven by seasonal variations in species-specific seed banks. Based on the biological characteristics of marsh herbaceous plants, heterogeneous and uniform expansion of vegetation is achieved through propagule dispersal and clonal integration strategies. During the propagule dispersal phase, seeds or seedlings from the dispersal center are randomly distributed to a ring of peripheral grids at a Chebyshev distance from the initial plant grid. The survival probability of reproductive seeds or seedlings depends on the hydrodynamic suitability of the breeding site. The closer the propagule is to the sea, the lower the altitude, and the greater the inundation stress, the lower the reproductive rate. Once sexual propagules are successfully established, plants enter the asexual integration phase, during which vegetation patches are rapidly formed through vegetative tillering. During this phase, vegetation grids are regularly transferred from the central grid to the peripheral grids through lateral expansion. For both sexual reproduction and asexual integration, seedlings will successfully establish and divide in grids at altitudes that allow survival, as grids above a critical altitude are considered ineffective establishment sites. The model considers the competitive balance among salt marsh species, including spatial preemption, succession, and suppression.

[0171] The relationship between vegetation settlement and reproduction - seed bank yield, germination rate, and survival rate is based on the following formula:

[0172]

[0173]

[0174] Where N max is the maximum seed bank, t vis the month, E is the tidal flat elevation, E 0v The required elevation threshold for seed retention, S v is the seed bank decay rate, is the sediment coefficient related to sediment particle size, Hydrological tolerance thresholds associated with propagules are established.

[0175] Step S4.2: Hydrodynamic simulation framework.

[0176] The parameterization of tidal motion is based on unsteady shallow-water equations. Since vertical density stratification in a three-dimensional model is optional for the current research objectives, a two-dimensional version (depth-averaged model) was applied to improve computational efficiency. The hydromorphological dynamics computational system consists of horizontal momentum equations, continuity equations, sediment transport equations, and a turbulence closure. During the tidal cycle, the riverbed level varies with the deposition and erosion of suspended and surface sediments. The transport of suspended sediment is simulated using convection-diffusion equations based on long-term geomorphological development. Erosion and deposition fluxes from viscous transport are calculated during the sediment transport simulation, and bottom shear stress, which is positively correlated with the vertical average flow velocity, is estimated.

[0177] The exogenous sediment deposition / erosion rate of the muddy beach is based on the following formula:

[0178]

[0179] Where C is the vertical average sediment concentration, h is the water depth, t is the time, u is the vertical average velocity component in the x direction, v is the vertical average velocity component in the y direction, and ε x is the sediment diffusion rate in the x direction, ε y is the diffusion rate in the y direction, Q e is the erosion flux, Q d is the deposition flux.

[0180] The functional relationship between the sediment deposition / erosion rate of the soil matrix in the vegetation area, the fluid friction coefficient and the bottom bed shear force is based on the following formula:

[0181]

[0182] Where, is the bottom bed shear force, p is the fluid density, g is the acceleration due to gravity, is the average flow velocity component, C Z is the Coriolis coefficient.

[0183] The net flux of particulate carbon in sediments and salt marsh litter is a function of vegetation type, seasonal tidal pattern, external sediment load, and hydrodynamic changes, according to the following formula:

[0184]

[0185] Where C PC is the average particle concentration, PC e is the granular carbon washout amount, PC d is the amount of particulate carbon deposition.

[0186] Step S4.3: Plant photosynthetic carbon fixation and respiration simulation framework, that is, the carbon dynamics module.

[0187] Leaf-level carbon uptake by plants is determined as the difference between net photosynthetic product and respiration. Net photosynthetic rate is regulated by the photosynthesis rate limited by Rubisco (ribulose-1,5-bisphosphate carboxylase / oxygenase) and the photosynthesis rate limited by RuBP (ribulin-1,5-bisphosphate) regeneration. The photosynthetic rate is also regulated by stomatal conductance, which is determined by photosynthetically active radiation (par), air temperature, and atmospheric CO2 concentration above the forest canopy, and by the inter-grid CO2 concentration. Maximum carboxylation efficiency (V cmax ) and electron transfer rate (J max The responses of these two key photosynthetic variables (e.g., photosynthetic rate, photosynthetic rate, and photosynthetic rate) to environmental variables were used to calculate the multi-enzyme kinetics of photosynthesis. The photosynthetic rate reaches a maximum at the optimal altitude and then gradually decreases under flood and drought stress, while also moving away from the optimal altitude.

[0188] Total canopy-level carbon uptake was further separated into net photosynthate and respiration at the canopy level. Total canopy photosynthesis consists of contributions from sunlit and shaded leaves. Separation in two horizontal layers of equal depth was achieved by an integrated sun / shade algorithm. The par-number incidence (PARi) at the top of the canopy was divided into direct and diffuse components, and the allocation fraction of the sum of the par-numbers was defined as follows. Assuming that the canopy is horizontally uniform and leaves are evenly distributed and oriented, the leaf area index (LAI), extinction coefficient and sun elevation angle jointly determine the PARi content at different canopy levels. The relative average photon flux density on sunlit and shaded leaves was defined using the diffuse component of the par-number and the total PARi, respectively. Due to the uneven distribution of leaf nitrogen content across the canopy, considering V cmax 、J max Carbon uptake and emission at the canopy level were calculated using linear functions based on the respiration within the canopy. Leaf and canopy development are key determinants of radiation interception, primarily driven by temperature. Therefore, the response of vegetation to cumulative air temperature was quantified by scaling the annual maximum vegetation-specific LAI and NL.

[0189] Typically, changes in soil respiration are described by an exponential function with an independent variable (i.e., temperature) and a fixed temperature sensitivity. However, rising water levels negatively affect respiration rates because increased inundation pressure leads to a persistent decrease in effective soil oxygen concentrations in coastal wetlands. Actual respiration fluxes were quantified using a function based on a modified exponential water level, assuming that tidal cover acts as a downward regulator of respiration discharge rates.

[0190] The functional relationship between the plant photosynthetic rate, photosynthetic enzyme activity, chlorophyll fluorescence parameters, autotrophic respiration and climate, soil and hydrological conditions, as well as canopy carbon uptake, layered leaf area index and canopy conductance / photosynthetic limitation function, is based on the following formula:

[0191]

[0192]

[0193]

[0194]

[0195]

[0196]

[0197]

[0198]

[0199] Where, is the total carbon uptake at the leaf level, is the net photosynthetic product at the leaf level, For the breathing at the leaf level, Rubisco limits the rate of photosynthesis. is the limiting rate of RuBP regeneration in photosynthesis, is the maximum rate of Rubisco activity, J is the electron transfer rate, is the maximum rate of electron transfer, is photosynthetically active radiation, is the CO2 compensation point in the absence of dark respiration, is the Michaelis constant of CO2, is the Michaelis constant of O2, O is the oxygen concentration, is the curvature of the standard rod number response curve of the electron transport rate, α is the quantum efficiency, is the air temperature, is the intercellular CO2 concentration, is the CO2 concentration in the atmosphere, is the coefficient of influence of flooding on plant photosynthesis, is the correction coefficient of the temperature response curve, θ is the curvature of the PAR response curve of the electron transfer rate, represents the stomatal conductance of leaves, 、 represent the maximum and minimum leaf stomatal conductance respectively, f(·) represents a function with · as the independent variable, where f is the corresponding calculation rule.

[0200] V at 25°C cmax or J max (Note: 30°C for C4 species).

[0201] is the activation enthalpy, reflecting the exponential growth rate of the function below the optimal value;

[0202] is the deactivation enthalpy, describing the rate of decrease of the function above the optimal value;

[0203] is the entropy of desaturation equilibrium, R is the correction factor, is the coefficient of influence of flooding on plant growth.

[0204] Biomass accumulation was calculated using a canopy-based vegetation photosynthesis model, accounting for biomass losses caused by tidal movement. To cope with tidal inundation stress, salt marsh plants shift biomass to belowground organs due to an equiaxed allocation strategy and antioxidant defense mechanisms, enabling stable colonization and efficient reproduction. Consequently, the biomass conversion factor changes with increasing elevation of the plant's habitat and accounts for the seasonal accumulation of aboveground and belowground biomass.

[0205] The canopy level photosynthetic model is based on the following formula:

[0206]

[0207]

[0208]

[0209]

[0210]

[0211]

[0212]

[0213]

[0214] Where, is the total canopy-level carbon uptake at the canopy level, is the net photosynthesis at the canopy level, for respiration at the canopy level, is the net canopy-level assimilation of sunlight-exposed leaves, is the net canopy level assimilation of shaded leaves, is the leaf nitrogen content, is the relative average photon flux density on the sunlight-exposed leaf, is the direct component of light radiation incident on the top of the awning. The relative average photon flux density on the shade blades is the scattered component of light radiation incident on the top of the awning. is the relative average photon flux density on the shaded leaves, is the scattered component of light radiation incident on the top of the awning, is the incident light radiation from the top of the leaf canopy, is the stomatal conductance of the leaf on the sunny side, is the stomatal conductance of the leaf on the shade side, Leaf area index at the top of the leaf canopy.

[0215] is the sunny side leaf area index, is the shade leaf area index, is the extinction coefficient, is the solar altitude angle.

[0216] The leaf level and canopy level development of the plant are based on the following formula,

[0217]

[0218]

[0219]

[0220]

[0221]

[0222]

[0223] Where, is the nitrogen content of the leaves, is the maximum leaf nitrogen content, is the leaf area index, is the maximum leaf area index, is the accumulated temperature, is the leaf canopy parameter, is the nitrogen content of leaves when the minimum photosynthetic rate occurs, It is the accumulated temperature when the maximum leaf area index and maximum leaf nitrogen content appear.

[0224] is the correction factor for leaf area and leaf nitrogen content, The average daily temperature.

[0225] Vegetation forms patches through the dispersal of propagules and clonal integration. The presence of vegetation affects water velocity, sedimentation flux, and erosion flux, thus affecting the amount of particulate carbon washed away and accumulated. Conversely, tidal movement and sediment deposition determine the elevation and stability of sediments. These factors directly influence the hydrological tolerance threshold of vegetation in S4.1, which in turn affects the number of surviving propagules.

[0226] The expansion of vegetation affects the leaf area index, which in turn affects total carbon uptake at the leaf level. The expansion of vegetation patches affects root activity and organic matter input, which in turn affects leaf respiration. In step S4.2, changes in water levels caused by tidal movement affect air temperature and leaf area index, which in turn affects total carbon uptake at the leaf level. Changes in soil oxygen concentration caused by water level changes affect stomatal conductance and leaf respiration, which in turn affects photosynthetic efficiency.

[0227] Step S4.4: Coupling method of vegetation dynamics-hydrodynamics-carbon dynamics model.

[0228] In the hydrodynamics module, salt marsh vegetation is encoded as rigid cylinders that do not tilt or sway. Physical plant properties for the cylinders' density, diameter, and height are converted from the vegetation dynamics simulation at each time step. Salt marsh biological activity acts as a biological disturbance to water flow and sediment transport. The drag exerted by the aboveground plant components on tidal currents is included as an additional source of flow resistance. Suspended sediment intercepted by plants from tidal currents can increase platform elevation, and the organic deposition contributed by plants is calculated based on aboveground biomass. Belowground components are tightly integrated with sediment, enhancing the erosion resistance of surface sediments. Net elevation change is determined as the difference between total sedimentation flux and erosion flux.

[0229] Assuming that water barrier cover acts as a downward regulator of respiratory emission rates, a function based on a modified exponential water level is used to describe changes in soil respiration under waterlogged conditions. When exposed surface sediments are tidally inundated, gas diffusion and evaporation from the soil surface are hindered because the water barrier created by tidal inundation interferes with gas release from the soil layer or tidal water. Model outputs for vegetation, water dynamics, and carbon dynamics are interleaved on a daily basis.

[0230] After each time step of the salt marsh dynamics simulation, new vegetation and elevation distribution maps are used to initiate calculations of the carbon dynamics model.

[0231] The net ecosystem carbon exchange (NEE) of a salt marsh is the difference between gross primary production (GPP) and ecosystem respiration (ER).

[0232] The change rate of carbon accumulation and carbon partition coefficient of salt marsh plant biomass under the above climatic, soil and hydrological conditions is based on the following formula:

[0233]

[0234]

[0235]

[0236] Where AGB is the aboveground biomass of plants, GB is the total biomass accumulation, and NPP is the net primary productivity. is the litter biomass, BGB is the belowground biomass, E is the tidal flat elevation, f is the mean tidal range, and g is the biomass isometric distribution coefficient.

[0237] The functional relationship between the organic carbon decomposition rate of plant litter and litter quality, soil and hydrological factors is based on the following formula:

[0238] dL / dt = L0- (k1+ k2)L

[0239] dF / dt = k3L - (k2+ k4+ k5)F

[0240] dH / dt = (k4+ k5) F- k6H

[0241] Where L is the content of undecomposed litter, L0 is the litter input, F is the total humus pool capacity, H is the complete humus content, and k1, k2, k3, k4, k5, and k6 are all correlation coefficients with the decomposition rate of litter components.

[0242] The soil CO2 emissions - CO2 release from soil organic matter decomposition (aerobic) and soil heterotrophic respiration temperature sensitivity (Q 10 The relationship between CO2 emissions and soil moisture and salinity changes is coupled according to the following formula:

[0243]

[0244] Where R s is soil CO2 emission (soil respiration), R p is the maximum soil respiration rate, C θis a parameter related to soil moisture content, represents the slope of the response of respiration rate to changes in soil moisture, f s Q 10 Function, T s is the soil temperature.

[0245] The net flux of soluble carbon in sediments as a function of vegetation type, seasonal tidal pattern, and runoff changes is based on the following formula:

[0246]

[0247] Where, represents the divergence of mass flow due to diffusion, f DC is the soluble carbon flux, D is the hydrodynamic diffusion tensor, C DC is the concentration of the fluid soluble carbon source or sink, C is the pore water soluble carbon concentration, represents the Darcy velocity vector, represents the porosity, represents the fluid density, It represents the ratio of the volume of water in the pores to the pore volume. is the sediment density, and Q is the organic carbon flux in the sediment.

[0248] Step 5: Calibrate the model parameters based on the measured soil organic carbon content, system CO2 flux, land feature distribution data identified by remote sensing images, and plant biomass data measured in the field.

[0249] The study couples plant dynamics, hydrodynamics, and carbon dynamics in coastal wetland ecosystems, including vertical carbon exchange in vegetation driven by plant phenology, such as gross primary productivity, net primary productivity, ecosystem respiration, and net ecosystem exchange. Field experiments and remote sensing image interpretation data were combined to develop a coupled vegetation-hydrodynamic-carbon dynamics model. Detailed parameterization of biological processes such as plant growth, reproduction, and establishment under tidal conditions was performed, and biophysical feedbacks between vegetation physiological activities and water and sediment movement were considered.

[0250] Step 6: Use the model to output the coverage area and carbon flux of coastal wetland salt marsh vegetation and sediments to obtain the assessment results of the spatiotemporal dynamics of salt marsh vegetation and sediments and their carbon sequestration capacity.

[0251] Take Jiuduansha as an example. Figure 5 The results show the monthly dynamics of the Net Ecosystem Exchange (NEE) of the Jiuduansha Salt Marsh vegetation during the study period of 2020. Figure 5 As shown in the lower panel, the NEE values of Spartina alterniflora, Phragmites australis, and Scirpus maritima were 97.5, 39.5, and 24.6 g C m, respectively.-2 month -1 The results indicate that the carbon exchange capacity of native Phragmites australis and Scirpus maritima is weaker than that of the exotic Spartina alterniflora. High carbon uptake fluxes of native Phragmites australis and Scirpus maritima mainly occur in spring and summer, while NEE in autumn and winter are characterized by low carbon dioxide uptake and emission, respectively. Figure 7 The simulation results of the spatial distribution of GPP and NEE in Jiuduansha from 2000 to 2020 are shown.

[0252] Figure 8 The results showed that the sediment flux of Jiuduansha salt marsh habitat was 5.38×10 6 t, converted into carbon sink is 1.30×10 4 tC.

[0253] The output biomass matrix, which measures the rate of change of saltmarsh plant biomass carbon accumulation and carbon partitioning coefficient under the described climatic, soil, and hydrological conditions, is further used to update the hydrodynamic parameters of the hydrodynamic model, including rigid cylinder properties, water depth data, and critical shear stress for erosion. The hydrodynamic module then begins with the updated input data. After each time step of the hydrodynamic simulation, a time series of water depth data and water levels is used to update the variables of the vegetation and carbon dynamics modules. Time series of water depth and water levels monitored by hydrological stations serve as input to initiate the hydrodynamic module. As the model runs, these evolving data are used to update the variables of the vegetation dynamics and carbon dynamics modules (i.e., plant photosynthesis and respiration). Furthermore, the elevation layout is modified by overlaying sediments. Vegetated grids outside the hydrological stress survival threshold are replaced with mudflat grids, and the unvegetated grid between the mudflat and the ocean is updated using a reference to the 0 m isobath (based on a local datum). With the updated hydrological, geomorphological, and biochemical parameters, the carbon dynamics module continues until the next step of the vegetation simulation is restarted. Thereafter, the hydrological and biogeochemical processes operated as a feedback loop. Due to the stochastic nature of hydrodynamics and plant dynamics, the coupled model was run ten times to check for simulation bias. The simulation results were then verified against the measured data to determine if the error met the pre-set requirements. If so, the calculated results for land feature distribution and carbon flux were output, including the area of salt marshes and shoals, as well as the total primary productivity (GPP), which is the total carbon uptake at the leaf level. , Ecosystem Respiration (ER), i.e., respiration at the leaf level Respiration with soil and net ecosystem exchange (NEE), i.e., net photosynthetic product at the leaf level. If not, proceed to step 4, review and calibrate the model input parameters, or perform sensitivity analysis to detect the sensitivity of the output results to the input parameters, and adjust the parameters until the error meets the preset requirements.

[0254] In addition to the existing technology of quantitative analysis of soil carbon storage and vertical CO2 flux in salt marsh and beach habitats, the complex interaction between biological and abiotic processes in coastal wetland ecosystems is also described in detail. By integrating the interaction between biological, hydrological and geomorphological processes, taking into account the impact of complex climate, hydrology, and sediment changes on biogeomorphological and geochemical processes such as coastal wetland geomorphology, vegetation carbon sequestration and system carbon cycle, a numerical method based on modeling processes is used to quantify the spatiotemporal dynamics of vegetation. In addition to considering the growth and reproduction dynamics of salt marsh vegetation (propagule spread, seedling growth, interspecific competition), vegetation dynamics (plant spread, establishment, growth and death) and biomass carbon accumulation (gross primary production, ecosystem respiration, net ecosystem carbon exchange) on environmental climate, the authors also analyzed the relationship between the growth and reproduction dynamics of salt marsh vegetation (propagule spread, seedling growth, interspecific competition), vegetation dynamics (plant spread, establishment, growth and death), and biomass carbon accumulation (gross primary production, ecosystem respiration, net ecosystem carbon exchange) and environmental climate. Adaptability also considers the biological feedbacks (flow resistance, sediment interception, and erosion resistance) exerted by coastal salt marsh activity on water and sediment processes, as well as water and sediment dynamics (tidal movement, sediment transport, and riverbed evolution). Physical feedbacks (seed entrainment, sediment supply, and biomass loss) exerted by water and sediment processes on salt marsh activity are also considered. These include flooding stress, drag, water convergence, elevation change, erosion resistance, sediment deposition, gas sequestration, cooling, tidal scour, sediment interception, gas diffusion obstruction, and carbon sequestration. These processes encompass the feedback interactions between biophysical processes in tidal environments. Fine-scale derivation of the bio-physical feedback relationships between salt marsh vegetation dynamics and geomorphic changes is performed, and the biogeochemical processes linking coastal salt marsh vegetation dynamics and sediment carbon sinks are parameterized. This allows for a more accurate and integrated assessment of plant growth and reproduction, water and sediment movement, biomass growth, salt marsh CO2 fluxes, and sediment carbon sinks, providing effective assessment techniques for the community development and carbon sink dynamics of coastal wetland vegetation.

[0255] According to the present invention, a coastal salt marsh vegetation and sediment deposition integrated carbon sink assessment system includes a vegetation dynamics-hydrodynamics-carbon dynamics coupling model, which includes a vegetation dynamics module, a hydrodynamics module, a carbon dynamics module and a coupling module.

[0256] like Figure 1 As shown, soil organic carbon data, gas carbon flux data, remote sensing image data and environmental climate data represent the initial input data required for model operation, and these data participate in the parameterization of biogeochemical processes in the model.

[0257] Determine the organic carbon content of sediments / soils and CO2 flux in salt marshes at the site to be measured, identify the distribution of land features at the site to be measured based on remote sensing image interpretation, and generate a remote sensing image dataset.

[0258] The distribution of salt marshes and light beaches in remote sensing imagery datasets was used as the simulation domain, and a coupled vegetation dynamics-hydrodynamics-carbon dynamics model was constructed using real-time data-driven models.

[0259] The vegetation dynamics-hydrodynamics-carbon dynamics coupled model was calibrated based on the organic carbon content, salt marsh CO2 flux, land feature type distribution, and measured plant biomass data;

[0260] The coverage area and carbon flux of coastal salt marsh vegetation and sediment deposition were output through the calibrated vegetation dynamics-hydrodynamics-carbon dynamics coupling model to obtain the assessment results of spatiotemporal dynamics and carbon sequestration capacity.

[0261] The salt marsh CO2 flux measurement method is to use the eddy correlation method or the box method to perform seasonal positioning observation on the salt marsh CO2 exchange flux.

[0262] The calculation formula for the organic carbon storage and total organic carbon content of each layer in the sediment / soil is:

[0263]

[0264]

[0265] in, Indicates the total organic carbon content of sediment / soil; represents soil organic carbon density; BD represents total soil bulk density; represents the soil organic carbon density of the i-th layer; T represents the total soil thickness; SOC represents the organic carbon content of the soil, and there are n layers of soil; T i represents the thickness of the i-th soil layer; BD i represents the soil bulk density of the i-th layer.

[0266] The remote sensing image interpretation is to interpret and identify multi-phase remote sensing images, obtain the area and coverage ratio of salt marshes and light beaches in the surveyed area and elevation distribution data, perform supervised classification processing and delineate the habitat units of salt marshes, light beaches and water, and optimize the classification results of land feature categories through field verification during the growing season.

[0267] The remote sensing image dataset includes land feature categories of salt marshes, bare beaches and water, area and coverage of the land feature categories, and elevation distribution data.

[0268] The real-time data obtained include meteorological data, terrain elevation, tidal hydrological pattern, sediment content and salinity obtained by meteorological stations and hydrological stations.

[0269] The vegetation dynamics module includes seed germination, seedling growth, sexual reproduction, asexual cloning, interspecific competition, habitat occupation, and integration and expansion processes, which cover the physiological activities of vegetation growth and reproduction and population expansion.

[0270] The vegetation dynamics module is a spatial grid matrix consisting of interconnected grids, where each grid connects all adjacent grids. Each connection has a distribution probability associated with vegetation expansion. The relationship N between vegetation settlement and reproduction - seed bank yield, germination rate and survival rate is:

[0271]

[0272]

[0273] Among them, N max represents the maximum seed bank; t v Indicates the month; E indicates the tidal flat elevation; E 0v Indicates the elevation threshold required for seed retention; S v represents the seed bank decay rate; is the sediment coefficient related to sediment particle size; Represents the hydrological tolerance threshold associated with propagule establishment.

[0274] The hydrodynamic module includes tidal movement, sediment transport, and terrain development processes, which cover the impact of water and sediment dynamics on riverbed topography development.

[0275] The hydrodynamic module is based on the unsteady shallow water equations and applies a depth-averaged model, including:

[0276] External sediment deposition / erosion rate of muddy beach , the functional relationship between soil matrix sediment deposition / erosion rate in vegetation area and fluid friction coefficient and bottom shear force Net flux of particulate carbon from sediments, silt, and salt marsh litter as a function of vegetation type, seasonal tidal patterns, external sediment load, and hydrodynamic changes ;

[0277] Where c is the vertical average sediment concentration; h is the water depth; t is the time; u is the vertical average velocity component in the x direction; v is the vertical average velocity component in the y direction; ε x represents the sediment diffusion rate in the x direction; ε y represents the diffusion rate in the y direction; Q e represents the erosion flux; Q d represents the deposition flux; represents the bottom bed shear force; p represents the fluid density; g represents the acceleration due to gravity; is the average flow velocity component; C Z represents the Coriolis coefficient; C PC represents the average particle concentration; PC e Indicates the amount of granular carbon washed; PC d Indicates the amount of particulate carbon deposition.

[0278] The carbon dynamics module includes leaf-level photosynthesis, canopy-level photosynthesis, electron transport, shuttle efficiency, leaf area growth, withering and littering, soil respiration, leaf respiration, and primary productivity processes. These processes cover the spatiotemporal dynamics of carbon exchange in vegetation and tidal flat systems.

[0279] In the carbon dynamics module, the functional relationships among plant photosynthetic rate, photosynthetic enzyme activity, chlorophyll fluorescence parameters, autotrophic respiration-climate, soil and hydrological conditions, as well as canopy carbon uptake, layered leaf area index and canopy conductance / photosynthetic limitation function are as follows:

[0280]

[0281]

[0282]

[0283]

[0284]

[0285]

[0286]

[0287]

[0288] The canopy level photosynthetic model is:

[0289]

[0290]

[0291]

[0292]

[0293]

[0294]

[0295]

[0296]

[0297] The leaf level and canopy level development of plants are based on:

[0298]

[0299]

[0300]

[0301]

[0302]

[0303]

[0304] in, represents the total carbon uptake at the leaf level; represents the net photosynthetic product at the leaf level; Indicates respiration at the leaf level; represents the photosynthesis rate limited by Rubisco; represents the finite rate of RuBP regeneration photosynthesis; represents the maximum rate of Rubisco activity; J represents the electron transport rate; Indicates the maximum rate of electron transfer; represents photosynthetically active radiation; Indicates the CO2 compensation point in the absence of dark respiration; represents the Michaelis constant of CO2; represents the Michaelis constant of O2; O represents the oxygen concentration; represents the curvature of the standard rod number response curve of the electron transport rate; α represents the quantum efficiency; Indicates air temperature; Indicates the CO2 concentration in the atmosphere; is the intercellular CO2 concentration; represents the coefficient of influence of flooding on plant photosynthesis; is the correction coefficient of the temperature response curve; θ represents the curvature of the PAR response curve of the electron transfer rate; represents the stomatal conductance of leaves; 、 represent the maximum and minimum leaf stomatal conductance, respectively; f(·) represents a function with · as the independent variable, where f is the corresponding calculation rule; Indicates V at 25°C cmax or J max Parameter indicates the value of V cmax or J max The value of represents the activation enthalpy; represents the deactivation enthalpy; represents the entropy of desaturation equilibrium; R represents the correction factor; represents the total canopy-level carbon uptake at the canopy level; represents the net photosynthesis at the canopy level; represents respiration at the canopy level; represents the net canopy-level assimilation of sunlight-exposed leaves; represents the net canopy-level assimilation of shaded leaves; represents the relative average photon flux density on the leaf illuminated by sunlight; represents the relative average photon flux density on the shaded leaves; Represents the direct component of light radiation incident on the top of the awning; Represents the scattered component of light radiation incident on the top of the awning; represents the light radiation incident on the top of the leaf canopy; represents the sunny side leaf area index; represents the shaded leaf area index; K represents the extinction coefficient; β represents the solar altitude angle; t represents time; is the leaf nitrogen content; Indicates the maximum leaf nitrogen content; is the stomatal conductance of the leaf on the sunny side; is the stomatal conductance of leaves on the shaded side; LAI represents leaf area index; represents the leaf area index at the top of the leaf canopy; represents the maximum leaf area index; Indicates the accumulated temperature; All represent leaf canopy parameters; Indicates the nitrogen content of leaves when the minimum photosynthetic rate occurs; They represent the accumulated temperature when the maximum leaf area index and the maximum leaf nitrogen content appear respectively; All represent the correction coefficients for leaf area and leaf nitrogen content, x = v, j, r; Indicates the average daily temperature.

[0305] The coupled module of vegetation dynamics-hydrodynamics-carbon dynamics includes flooding stress, drag, water convergence, elevation change, erosion resistance, sediment deposition, gas isolation, cooling, tidal scour, sediment interception, obstruction of gas diffusion, and carbon sequestration. These processes cover the mutual feedback between biophysical processes in the tidal environment.

[0306] The change rate of carbon accumulation and carbon partition coefficient of salt marsh plant biomass under climate, soil and hydrological conditions in the coupling module is:

[0307]

[0308]

[0309]

[0310] The functional relationship between plant litter organic carbon decomposition rate and litter quality, soil and hydrological factors is:

[0311] dL / dt = L0- (k1+ k2)L

[0312] dF / dt = k3L - (k2+ k4+ k5)F

[0313] dH / dt = (k4+ k5) F- k6H

[0314] Soil CO2 emissions - the functional relationship between CO2 release from soil organic matter decomposition and the temperature sensitivity of soil heterotrophic respiration, and the relationship function of coupled CO2 emissions with changes in soil moisture and salinity is:

[0315]

[0316] The net flux of soluble carbon in sediments is a function of vegetation type, seasonal tidal pattern, and runoff changes:

[0317]

[0318] Among them, AGB represents plant aboveground biomass; GB represents total biomass accumulation; NPP represents net primary productivity; represents litter biomass; BGB represents underground biomass; E represents tidal flat elevation; f represents mean tidal range; g represents biomass isometric distribution coefficient; L represents undecomposed litter content; t represents time; L0 represents litter input; F represents total humus storage capacity; H represents complete humus content; k1, k2, k3, k4, k5, and k6 represent parameters related to the decomposition rate of litter components; R s represents soil CO2 emissions; R p represents the maximum soil respiration rate; represents the slope of the response of respiration rate to changes in soil moisture; C θ Represents parameters related to soil moisture; f s Indicates Q 10 Function; Q 10 represents the temperature sensitivity of soil heterotrophic respiration; T s Indicates soil temperature; represents the divergence of mass flow due to diffusion; f DC represents the soluble carbon flux; D represents the hydrodynamic diffusion tensor; C DC Indicates the concentration of a fluid-soluble carbon source or sink C represents the soluble carbon concentration in pore water; represents the Darcy velocity vector; represents porosity; represents the fluid density; It represents the ratio of the volume occupied by water in the pores to the pore volume; represents the sediment density; Q represents the organic carbon flux in the sediment.

[0319] The parameters of the hydrodynamic module are updated through the output biomass matrix of the change rate of salt marsh plant biomass carbon accumulation and carbon distribution coefficient under the aforementioned climatic, soil and hydrological conditions. The variables of the vegetation dynamic module and the carbon dynamic module are updated through the time series of water depth data and water level monitored by the hydrological station. The simulation deviation is checked and judged whether the error meets the preset requirements.

[0320] If the preset requirements are met, the calculation results of land feature distribution and carbon flux will be output, including the area of salt marshes and light beaches, as well as primary productivity, ecosystem respiration and net ecosystem exchange value; if the preset requirements are not met, module 2 will be triggered to review and correct the input parameters of the model, or perform sensitivity analysis to detect the sensitivity of the output results to the input parameters, and adjust the parameters until the error meets the preset requirements.

[0321] The output results are divided into the spatiotemporal dynamics of vegetation-water-sand-landform and the spatiotemporal dynamics of ecosystem carbon exchange, that is, carbon sequestration capacity. These results are used to evaluate the landform development and carbon sequestration dynamics of salt marsh-beach systems.

[0322] The above describes specific embodiments of the present invention. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. The embodiments of this application and the features in the embodiments may be combined with each other in any manner unless there is a conflict.

Claims

1. A method for comprehensive carbon sink assessment of coastal salt marsh vegetation and sediment deposition, characterized in that: include: Step 1: Measure the organic carbon content of sediments / soils and CO2 flux in salt marshes at the site to be measured, identify the distribution of land features at the site to be measured based on remote sensing image interpretation, and generate a remote sensing image dataset. Step 2: Using the distribution of salt marshes and light beaches in remote sensing imagery datasets as the simulation domain, a real-time data-driven model was constructed to build a coupled vegetation dynamics-hydrodynamics-carbon dynamics model; Step 3: calibrating the vegetation dynamics-hydrodynamics-carbon dynamics coupled model based on the organic carbon content, salt marsh CO2 flux, land feature type distribution, and measured plant biomass data; Step 4: The calibrated vegetation dynamics-hydrodynamics-carbon dynamics coupled model is used to output the distribution of landforms and carbon fluxes of coastal salt marsh vegetation and sediment deposition, thereby obtaining assessment results of spatiotemporal dynamics and carbon sequestration capacity. The vegetation dynamics-hydrodynamics-carbon dynamics coupling model includes a vegetation dynamics module, a hydrodynamics module, a carbon dynamics module and a coupling module; The change rate of carbon accumulation and carbon partition coefficient of salt marsh plant biomass under climate, soil and hydrological conditions in the coupling module is: The functional relationship between plant litter organic carbon decomposition rate and litter quality, soil and hydrological factors is: dL / dt = L0 - (k1 + k2)L dF / dt = k3L - (k2 + k4 + k5)F dH / dt = (k4 + k5) F- k6H Soil CO2 emissions - the functional relationship between CO2 release from soil organic matter decomposition and the temperature sensitivity of soil heterotrophic respiration, and the relationship function of coupled CO2 emissions with changes in soil moisture and salinity is: The net flux of soluble carbon in sediments is a function of vegetation type, seasonal tidal pattern, and runoff changes: Among them, AGB represents plant aboveground biomass; GB represents total biomass accumulation; NPP stands for net primary productivity; represents litter biomass; BGB indicates belowground biomass; E represents the tidal flat elevation; f represents the mean tidal range; g represents the biomass isometric distribution coefficient; L represents the content of undecomposed litter; t represents time; L0 represents litter input; F represents the total humus storage capacity; H represents the complete humus content; k1, k2, k3, k4, k5, and k6 all represent parameters related to the decomposition rate of litter components; R s represents soil CO2 emissions; R p represents the maximum soil respiration rate; represents the slope of the response of respiration rate to changes in soil moisture content; C θ Indicates parameters related to soil moisture content; f s Indicates Q 10 function; Q 10 represents the temperature sensitivity of soil heterotrophic respiration; T s Indicates soil temperature; represents the divergence of mass flow due to diffusion; f DC represents the soluble carbon flux; D represents the hydrodynamic diffusion tensor; C DC Indicates the concentration of a fluid-soluble carbon source or sink C represents the soluble carbon concentration in pore water; represents the Darcy velocity vector; represents porosity; represents the fluid density; It represents the ratio of the volume occupied by water in the pores to the pore volume; represents sediment density; Q represents the organic carbon flux in sediments; In the step 4, the parameters of the hydrodynamic module are updated by outputting the biomass matrix of the change rate of the salt marsh plant biomass carbon accumulation and the carbon distribution coefficient under the climate, soil and hydrological conditions, and the variables of the vegetation dynamic module and the carbon dynamic module are updated by the time series of the water depth data and water level monitored by the hydrological station, and the simulation deviation is checked to determine whether the error meets the preset requirements; If the preset requirements are met, the calculated results of the feature type distribution and carbon flux are output. If the preset requirements are not met, step 2 is executed to review and calibrate the input parameters of the model, or to perform a sensitivity analysis to detect the sensitivity of the output results to the input parameters, and adjust the parameters until the error meets the preset requirements. The calculation results include the area of salt marshes and beaches, total carbon absorption at leaf level , leaf level net photosynthetic product and breathing at the leaf level Respiration with soil The harmony.

2. The method for comprehensive carbon sink assessment of coastal salt marsh vegetation and sediment deposition according to claim 1, characterized in that: The salt marsh CO2 flux measurement method is to use the eddy covariance method or the box method to conduct seasonal positioning observation of the salt marsh CO2 exchange flux; The calculation formula for the organic carbon storage and total organic carbon content of each layer in the sediment / soil is: in, Indicates the total organic carbon content of sediment / soil; represents soil organic carbon density; BD represents total soil bulk density; T represents the total soil thickness; represents the soil organic carbon density in the i-th layer; SOC represents the organic carbon content of the soil, and there are n soil layers; T i represents the thickness of the i-th soil layer; BD i represents the soil bulk density of the i-th layer; The remote sensing image interpretation is to interpret and identify multi-phase remote sensing images, obtain the area and coverage ratio of salt marshes and light beaches in the surveyed area, and the elevation distribution data, perform supervised classification processing and delineate the habitat units of salt marshes, light beaches and water, and optimize the classification results of land feature categories through field verification during the growing season; The remote sensing image dataset includes land feature categories of salt marshes, bare beaches and water, area and coverage of the land feature categories, and elevation distribution data.

3. The method for comprehensive carbon sink assessment of coastal salt marsh vegetation and sediment deposition according to claim 1, characterized in that: The vegetation dynamics-hydrodynamics-carbon dynamics coupling model includes a vegetation dynamics module, a hydrodynamics module, a carbon dynamics module and a coupling module; The hydrodynamic module is based on the unsteady shallow water equations and applies a depth-averaged model, including: External sediment deposition / erosion rate of muddy beach , the functional relationship between soil matrix sediment deposition / erosion rate in vegetation area and fluid friction coefficient and bottom shear force Net flux of particulate carbon from sediments, silt, and salt marsh litter as a function of vegetation type, seasonal tidal patterns, external sediment load, and hydrodynamic changes ; Where c represents the vertical average sediment content; h represents water depth; t represents time; u represents the vertical average velocity component in the x direction; v represents the component of the vertical average velocity in the y direction; ε x represents the sediment diffusion rate in the x direction; ε y represents the diffusion rate in the y direction; Q e represents the erosion flux; Q d represents the deposition flux; represents the bottom bed shear force; p represents the fluid density; g represents the acceleration due to gravity; is the average flow velocity component; C Z represents the Coriolis coefficient; C PC represents the average particle concentration; PC e Indicates the amount of particulate carbon flushing; PC d Indicates the amount of particulate carbon deposition; The real-time data obtained include meteorological data, terrain elevation, tidal hydrological pattern, sediment content and salinity obtained by meteorological stations and hydrological stations; The vegetation dynamics module is a spatial grid matrix consisting of interconnected grids, where each grid connects all adjacent grids. Each connection has a distribution probability associated with vegetation expansion. The relationship N between vegetation settlement and reproduction - seed bank yield, germination rate and survival rate is: Among them, N max represents the maximum seed bank; t v Indicates the month; E represents the tidal flat elevation; E 0v Indicates the elevation threshold required for seed retention; S v represents the seed bank decay rate; is the sediment coefficient related to sediment particle size; Represents the hydrological tolerance threshold associated with propagule establishment.

4. The method for comprehensive carbon sink assessment of coastal salt marsh vegetation and sediment deposition according to claim 3, characterized in that: In the carbon dynamics module, the functional relationships among plant photosynthetic rate, photosynthetic enzyme activity, chlorophyll fluorescence parameters, autotrophic respiration-climate, soil and hydrological conditions, as well as canopy carbon uptake, layered leaf area index and canopy conductance / photosynthetic limitation function are as follows: The canopy level photosynthetic model is: The leaf level and canopy level development of plants are based on: in, represents the total carbon uptake at the leaf level; represents the net photosynthetic product at the leaf level; Indicates respiration at the leaf level; represents the photosynthesis rate limited by Rubisco; represents the finite rate of RuBP regeneration photosynthesis; represents the maximum rate of Rubisco activity; J represents the electron transfer rate; Indicates the maximum rate of electron transfer; represents photosynthetically active radiation; Indicates the CO2 compensation point in the absence of dark respiration; represents the Michaelis constant of CO2; represents the Michaelis constant of O2; O represents the oxygen concentration; The curvature of the standard rod number response curve representing the electron transport rate; α represents quantum efficiency; Indicates air temperature; Indicates the CO2 concentration in the atmosphere; is the intercellular CO2 concentration; represents the coefficient of influence of flooding on plant photosynthesis; is the correction coefficient of the temperature response curve; θ represents the curvature of the PAR response curve of electron transport rate; represents the stomatal conductance of leaves; 、 represent the maximum and minimum leaf stomatal conductance, respectively; f(·) represents a function with · as the independent variable, where f is the corresponding calculation rule; Indicates V at 25°C cmax or J max The value of Parameter indicates V cmax or J max The value of represents the activation enthalpy; represents the deactivation enthalpy; represents the entropy of the desaturation equilibrium; R represents the correction factor; represents the total canopy-level carbon uptake at the canopy level; represents the net photosynthesis at the canopy level; represents respiration at the canopy level; represents the net canopy-level assimilation of sunlight-exposed leaves; represents the net canopy-level assimilation of shaded leaves; represents the relative average photon flux density on the leaf illuminated by sunlight; represents the relative average photon flux density on the shaded leaves; Represents the direct component of light radiation incident on the top of the awning; Represents the scattered component of light radiation incident on the top of the awning; represents the light radiation incident on the top of the leaf canopy; represents the sunny side leaf area index; represents the shaded leaf area index; K represents the extinction coefficient; β represents the solar altitude angle; t represents time; is the leaf nitrogen content; Indicates the maximum leaf nitrogen content; is the stomatal conductance of the leaf on the sunny side; is the stomatal conductance of the leaf on the shaded side; LAI stands for leaf area index; represents the leaf area index at the top of the leaf canopy; represents the maximum leaf area index; Indicates the accumulated temperature; All represent leaf canopy parameters; Indicates the nitrogen content of leaves when the minimum photosynthetic rate occurs; They represent the accumulated temperature when the maximum leaf area index and the maximum leaf nitrogen content appear respectively; All represent the correction coefficients for leaf area and leaf nitrogen content, x = v, j, r; Indicates the average daily temperature.

5. A coastal salt marsh vegetation and sediment deposition integrated carbon sink assessment system, characterized in that: Includes a coupled vegetation dynamics-hydrodynamics-carbon dynamics model; The vegetation dynamics-hydrodynamics-carbon dynamics coupling model includes a vegetation dynamics module, a hydrodynamics module, a carbon dynamics module and a coupling module; Determine the organic carbon content of sediments / soils and CO2 flux in salt marshes at the site to be measured, identify the distribution of land features at the site to be measured based on remote sensing image interpretation, and generate a remote sensing image dataset. The distribution of salt marshes and light beaches in remote sensing imagery datasets was used as the simulation domain, and a coupled vegetation dynamics-hydrodynamics-carbon dynamics model was constructed using real-time data-driven models. The vegetation dynamics-hydrodynamics-carbon dynamics coupled model was calibrated based on the organic carbon content, salt marsh CO2 flux, land feature type distribution, and measured plant biomass data; The calibrated vegetation dynamics-hydrodynamics-carbon dynamics coupled model was used to output the coverage area and carbon flux of coastal salt marsh vegetation and sediment deposition, and the spatiotemporal dynamics and carbon sequestration capacity were evaluated. The change rate of carbon accumulation and carbon partition coefficient of salt marsh plant biomass under climate, soil and hydrological conditions in the coupling module is: The functional relationship between plant litter organic carbon decomposition rate and litter quality, soil and hydrological factors is: dL / dt = L0 - (k1 + k2)L dF / dt = k3L - (k2 + k4 + k5)F dH / dt = (k4 + k5) F- k6H Soil CO2 emissions - the functional relationship between CO2 release from soil organic matter decomposition and the temperature sensitivity of soil heterotrophic respiration, and the relationship function of coupled CO2 emissions with changes in soil moisture and salinity is: The net flux of soluble carbon in sediments is a function of vegetation type, seasonal tidal pattern, and runoff changes: Among them, AGB represents plant aboveground biomass; GB represents total biomass accumulation; NPP stands for net primary productivity; represents litter biomass; BGB indicates belowground biomass; E represents the tidal flat elevation; f represents the mean tidal range; g represents the biomass isometric distribution coefficient; L represents the content of undecomposed litter; t represents time; L0 represents litter input; F represents the total humus storage capacity; H represents the complete humus content; k1, k2, k3, k4, k5, and k6 all represent parameters related to the decomposition rate of litter components; R s represents soil CO2 emissions; R p represents the maximum soil respiration rate; represents the slope of the response of respiration rate to changes in soil moisture content; C θ Indicates parameters related to soil moisture content; f s Indicates Q 10 function; Q 10 represents the temperature sensitivity of soil heterotrophic respiration; T s Indicates soil temperature; represents the divergence of mass flow due to diffusion; f DC represents the soluble carbon flux; D represents the hydrodynamic diffusion tensor; C DC Indicates the concentration of a fluid-soluble carbon source or sink C represents the soluble carbon concentration in pore water; represents the Darcy velocity vector; represents porosity; represents the fluid density; It represents the ratio of the volume occupied by water in the pores to the pore volume; represents sediment density; Q represents the organic carbon flux in sediments; The parameters of the hydrodynamic module are updated by outputting the biomass matrix of the change rate of the salt marsh plant biomass carbon accumulation and carbon partition coefficient under the aforementioned climate, soil and hydrological conditions. The variables of the vegetation dynamic module and the carbon dynamic module are updated by monitoring the time series of the water depth data and water level at the hydrological station. The simulation deviation is checked and whether the error meets the preset requirements is determined. If the preset requirements are met, the calculated results of the feature type distribution and carbon flux are output. If the preset requirements are not met, the second module is triggered to review and correct the input parameters of the model, or perform sensitivity analysis to detect the sensitivity of the output results to the input parameters, and adjust the parameters until the error meets the preset requirements. The calculation results include the area of salt marshes and beaches, total carbon absorption at leaf level , leaf level net photosynthetic product and breathing at the leaf level Respiration with soil The harmony.

6. The coastal salt marsh vegetation and sediment deposition integrated carbon sink assessment system according to claim 5, characterized in that: The salt marsh CO2 flux measurement method is to use the eddy covariance method or the box method to conduct seasonal positioning observation of the salt marsh CO2 exchange flux; The calculation formula for the organic carbon storage and total organic carbon content of each layer in the sediment / soil is: in, Indicates the total organic carbon content of sediment / soil; represents soil organic carbon density; BD represents total soil bulk density; T represents the total soil thickness; represents the soil organic carbon density in the i-th layer; SOC represents the organic carbon content of the soil, and there are n soil layers; T i represents the thickness of the i-th soil layer; BD i represents the soil bulk density of the i-th layer; The remote sensing image interpretation is to interpret and identify multi-phase remote sensing images, obtain the area and coverage ratio of salt marshes and light beaches in the surveyed area, and the elevation distribution data, perform supervised classification processing and delineate the habitat units of salt marshes, light beaches and water, and optimize the classification results of land feature categories through field verification during the growing season; The remote sensing image dataset includes land feature categories of salt marshes, bare beaches and water, area and coverage of the land feature categories, and elevation distribution data.

7. The coastal salt marsh vegetation and sediment deposition integrated carbon sink assessment system according to claim 5, characterized in that: The hydrodynamic module is based on the unsteady shallow water equations and applies a depth-averaged model, including: External sediment deposition / erosion rate of muddy beach , the functional relationship between soil matrix sediment deposition / erosion rate in vegetation area and fluid friction coefficient and bottom shear force Net flux of particulate carbon from sediments, silt, and salt marsh litter as a function of vegetation type, seasonal tidal patterns, external sediment load, and hydrodynamic changes ; Where c represents the vertical average sediment content; h represents water depth; t represents time; u represents the vertical average velocity component in the x direction; v represents the component of the vertical average velocity in the y direction; ε x represents the sediment diffusion rate in the x direction; ε y represents the diffusion rate in the y direction; Q e represents the erosion flux; Q d represents the deposition flux; represents the bottom bed shear force; p represents the fluid density; g represents the acceleration due to gravity; is the average flow velocity component; C Z represents the Coriolis coefficient; C PC represents the average particle concentration; PC e Indicates the amount of particulate carbon flushing; PC d Indicates the amount of particulate carbon deposition; The real-time data obtained include meteorological data, terrain elevation, tidal hydrological pattern, sediment content and salinity obtained by meteorological stations and hydrological stations; The vegetation dynamics module is a spatial grid matrix consisting of interconnected grids, where each grid connects all adjacent grids. Each connection has a distribution probability associated with vegetation expansion. The relationship N between vegetation settlement and reproduction - seed bank yield, germination rate and survival rate is: Among them, N max represents the maximum seed bank; t v Indicates the month; E represents the tidal flat elevation; E 0v Indicates the elevation threshold required for seed retention; S v represents the seed bank decay rate; is the sediment coefficient related to sediment particle size; Represents the hydrological tolerance threshold associated with propagule establishment.

8. The coastal salt marsh vegetation and sediment deposition integrated carbon sink assessment system according to claim 7, characterized in that: In the carbon dynamics module, the functional relationships among plant photosynthetic rate, photosynthetic enzyme activity, chlorophyll fluorescence parameters, autotrophic respiration-climate, soil and hydrological conditions, as well as canopy carbon uptake, layered leaf area index and canopy conductance / photosynthetic limitation function are as follows: The canopy level photosynthetic model is: The leaf level and canopy level development of plants are based on: in, represents the total carbon uptake at the leaf level; represents the net photosynthetic product at the leaf level; Indicates respiration at the leaf level; represents the photosynthesis rate limited by Rubisco; represents the finite rate of RuBP regeneration photosynthesis; represents the maximum rate of Rubisco activity; J represents the electron transfer rate; Indicates the maximum rate of electron transfer; represents photosynthetically active radiation; Indicates the CO2 compensation point in the absence of dark respiration; represents the Michaelis constant of CO2; represents the Michaelis constant of O2; O represents the oxygen concentration; The curvature of the standard rod number response curve representing the electron transport rate; α represents quantum efficiency; Indicates air temperature; Indicates the CO2 concentration in the atmosphere; is the intercellular CO2 concentration; represents the coefficient of influence of flooding on plant photosynthesis; is the correction coefficient of the temperature response curve; θ represents the curvature of the PAR response curve of electron transport rate; represents the stomatal conductance of leaves; 、 represent the maximum and minimum leaf stomatal conductance, respectively; f(·) represents a function with · as the independent variable, where f is the corresponding calculation rule; Indicates V at 25°C cmax or J max The value of Parameter indicates V cmax or J max The value of represents the activation enthalpy; represents the deactivation enthalpy; represents the entropy of the desaturation equilibrium; represents the correction factor; represents the total canopy-level carbon uptake at the canopy level; represents the net photosynthesis at the canopy level; represents respiration at the canopy level; represents the net canopy-level assimilation of sunlight-exposed leaves; represents the net canopy-level assimilation of shaded leaves; represents the relative average photon flux density on the leaf illuminated by sunlight; represents the relative average photon flux density on the shaded leaves; Represents the direct component of light radiation incident on the top of the awning; Represents the scattered component of light radiation incident on the top of the awning; represents the light radiation incident on the top of the leaf canopy; represents the sunny side leaf area index; represents the shaded leaf area index; represents the extinction coefficient; β represents the solar altitude angle; t represents time; is the leaf nitrogen content; Indicates the maximum leaf nitrogen content; is the stomatal conductance of the leaf on the sunny side; is the stomatal conductance of the leaf on the shaded side; LAI stands for leaf area index; represents the leaf area index at the top of the leaf canopy; represents the maximum leaf area index; Indicates the accumulated temperature; All represent leaf canopy parameters; Indicates the nitrogen content of leaves when the minimum photosynthetic rate occurs; They represent the accumulated temperature when the maximum leaf area index and the maximum leaf nitrogen content appear respectively; All represent the correction coefficients for leaf area and leaf nitrogen content, x = v, j, r; Indicates the average daily temperature.

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