Method for measuring and calculating carbon reserve of water body in subsidence ponding area

Abstract

The invention relates to the technical field of mining area data measurement and calculation, and discloses a subsidence ponding area water carbon reserve measurement and calculation method which comprises the following steps: acquiring geological mining condition data of a mining area where a subsidence ponding area is located, and calculating a subsidence data set of the subsidence ponding area; acquiring and preprocessing a remote sensing image data sequence of the subsidence ponding area to generate a ponding area data sequence; carrying out superposition processing on the ponding area data sequence and the subsidence data in a unified coordinate system, and obtaining a reservoir capacity time sequence; sampling at multiple points and calculating organic carbon density data of the water body; calculating water carbon reserves at a set moment; the remote sensing method and the probability integral method are fused, the reservoir capacity information of the ponding area is calculated, field sampling is carried out, the organic carbon density of the water body is measured through experiments, the water body carbon reserve is obtained, the water body carbon reserve of the subsidence ponding area is accurately calculated, reliable technical support is provided for treatment of the coal mining subsidence area, and a more reasonable and effective treatment scheme is provided.

Description

Technical Field

[0001] This invention relates to the field of mining area data calculation technology, and more specifically, to a method for calculating the carbon storage of water bodies in subsidence and waterlogged areas. Background Technology

[0002] Coal resources are an indispensable part of my country's economic development, but the problem of land subsidence caused by large-scale mining is becoming increasingly serious. In mining areas with high groundwater levels, subsidence often leads to groundwater exposure, forming large areas of seasonal or permanent waterlogging. This not only causes waste of land resources, damage to the ecological environment, and conflicts between humans and the land, but also significantly alters the regional carbon cycle. As a transitional zone between aquatic and terrestrial ecosystems, subsidence waterlogged areas have active carbon source and sink functions and are a key link affecting the net carbon balance of mining areas.

[0003] Accurately measuring the carbon storage in subsidence and waterlogged areas is fundamental to assessing the carbon sequestration capacity of mining areas, promoting green mine development, and achieving "dual carbon" goals. However, current measurement methods face three major bottlenecks:

[0004] Underwater topography and reservoir capacity are difficult to determine: The topography of the waterlogged area is complex and changes continuously with subsidence. Traditional measurement methods are costly and time-consuming, making it difficult to obtain underwater topographic data with high spatiotemporal resolution. This leads to inaccurate reservoir capacity calculations and becomes the main source of error in carbon storage estimation.

[0005] Limitations of static carbon reserve accounting: Existing methods are mostly limited to "snapshot" estimation of carbon reserves at a certain point in time, which cannot reflect the dynamic changes of carbon pool with seasons, years and mining activities, let alone predict future trends, and are difficult to meet the needs of adaptive management.

[0006] The mechanism of the carbon cycle is unclear: There is a lack of quantitative description of key processes that control changes in carbon storage, such as inputs (e.g., runoff, sedimentation), outputs (e.g., gas emissions, outflows), and internal transformations (photosynthesis, respiration), leading to a lack of understanding of the formation mechanism and key regulation of carbon sink functions. Summary of the Invention

[0007] The purpose of this invention is to provide a method for calculating the carbon storage in water bodies in subsidence and waterlogged areas in order to solve the above-mentioned problems.

[0008] This invention provides a method for calculating the carbon storage in water bodies in subsidence and waterlogged areas, comprising the following steps:

[0009] Step 100: Obtain geological and mining condition data of the mining area where the subsidence and water accumulation area is located, and calculate the subsidence data set of the subsidence and water accumulation area based on the geological and mining condition data.

[0010] Step 200: Obtain the remote sensing image data sequence of the subsidence water accumulation area and perform preprocessing. Use the water index method to extract the water accumulation boundary data sequence of the subsidence water accumulation area, and generate the water accumulation area data sequence based on the water accumulation boundary data sequence.

[0011] Step 300: Overlay the water accumulation area data sequence and the subsidence data in a unified coordinate system to obtain the reservoir capacity time series;

[0012] Step 400: Using the grid method, multiple sampling points are systematically deployed in the subsidence and water accumulation area to collect multiple water sample data. Based on the multiple water sample data, the organic carbon density data of the water body in the subsidence and water accumulation area at a set time is obtained.

[0013] Step 500: Calculate the water carbon storage at the set time based on the reservoir capacity time series and the water organic carbon density data of the subsidence water area at the set time.

[0014] As a further optimization of the present invention, the following steps are also included:

[0015] Step 600: Construct a carbon dynamics model, input the water carbon storage at the set time in step 500 into the carbon dynamics model, and output the carbon storage change rate.

[0016] Step 700: Based on the carbon storage change rate and the water carbon storage at a set time, generate the dynamic water carbon storage at the set time.

[0017] As a further optimization of the present invention, the geological and mining condition data includes average mining depth H, mining thickness m, and coal seam dip angle. Expected working face strike length L, dip length l, subsidence coefficient q, horizontal movement coefficient b, main influence radius r, and mining influence propagation angle. And the inflection point offset s;

[0018] The formula for calculating the sinking data is:

[0019] ;

[0020] ;

[0021] in, Representing surface points The subsidence value at that location, D represents the maximum surface subsidence value, and D represents the projected range of the mining area on the coordinate plane. All of these are coordinate variables derived from the mining unit. This represents the variable in a double integral.

[0022] As a further optimization of the present invention, step 200 includes the following specific steps:

[0023] Step 201: Perform radiometric calibration, atmospheric correction, and geometric fine correction on the remote sensing image data sequence;

[0024] Step 202: The corrected remote sensing image data sequence is processed using the improved normalized difference water index method to generate an index image data sequence. The calculation formula for the water index method is as follows:

[0025] ;

[0026] in, This represents the improved normalized difference water index value. This represents the surface reflectance in the green band of satellite imagery. This indicates the surface reflectance in the shortwave infrared band of satellite imagery;

[0027] Step 203: Binarize the exponential image of the specified image phase by setting an empirical threshold, extract water body pixels, and then vectorize them to obtain accurate water accumulation boundary vector data. And calculate its area. ,in, Indicates the phase of an image.

[0028] As a further optimization of the present invention, step 300 includes the following specific steps:

[0029] Step 301: Obtain each time phase Water accumulation boundary vector data Spatial overlay analysis was performed with the subsidence dataset in a unified coordinate system;

[0030] Step 302: For each time phase, determine the water surface elevation of the water accumulation area. ;

[0031] Calculate the reservoir capacity for each time phase. The calculation formula is as follows:

[0032] ;

[0033] in, Indicates phase The reservoir's water storage capacity Indicates phase The area of ​​the waterlogged area, Indicates phase water surface elevation, Point The estimated surface elevation at the location; integration is conducted within the waterlogged area. Represents an area element in Cartesian coordinates;

[0034] Step 303: Combine the reservoir capacity of each time phase. Obtain the reservoir capacity data sequence .

[0035] As a further optimization of the present invention, step 400 includes the following specific steps:

[0036] Step 401: Using the grid sampling method, collect several water samples at different water depths and record the coordinates of each sampling point;

[0037] Step 402: Process the water sample and obtain the total carbon and inorganic carbon content. Calculate the organic carbon content based on the total carbon and inorganic carbon content using the following formula:

[0038] ;

[0039] in, This indicates the total organic carbon content of the water sample. This indicates the total carbon content of the water sample. This indicates the inorganic carbon content of the water sample;

[0040] Step 403: Take the arithmetic mean of the TOC values ​​of all sampling points to obtain... Average organic carbon density of water at any given time .

[0041] As a further optimization of the present invention, the formula for calculating the water carbon storage at the set time in step 500 is as follows:

[0042] ;

[0043] in, This indicates the carbon storage in the water body at a given time.

[0044] As a further optimization of the present invention, the calculation formula for the carbon dynamic model is as follows:

[0045] ;

[0046] in, This represents the organic carbon storage in the water body of the water accumulation area at time t. This represents the rate of change in carbon reserves at time t. This represents the total external carbon input flux at time t. This represents the total carbon output flux at time t. This represents the primary carbon sequestration flux within the water body at time t. This represents the carbon emission flux from respiration and decomposition within the water body at time t.

[0047] As a further optimization of the present invention ;

[0048] ;

[0049] ;

[0050] ;

[0051] ;

[0052] in, Indicates atmospheric deposition. Indicates precipitation. This indicates the concentration of organic carbon in rainwater. This represents dry sedimentation flux. Indicates surface runoff input, This indicates continuous monitoring of flow rate. This indicates the concentration of organic carbon in the surface runoff input water sample. Indicates groundwater input. This indicates the estimated recharge volume from the hydrogeological model. This indicates the concentration of organic carbon in groundwater. Indicates sediment resuspension input. For wind speed, The average water depth, This is an empirical coefficient;

[0053] ;

[0054] ;

[0055] ;

[0056] ;

[0057] in, Indicates surface outflow. Indicates the flow rate monitored at the outlet. Indicates greenhouse gas emissions, This indicates the on-site measured CO2 flux. This indicates the on-site measured CH4 flux. The equivalent factor for the global warming potential of methane. Indicates sedimentation and burial. Indicates the deposition rate, Indicates the organic carbon content of sediments. This refers to the bulk density of the sediment.

[0058] As a further optimization of the present invention ;

[0059] ;

[0060] in, This indicates the concentration of chlorophyll a in the water. This represents the maximum photosynthetic rate per unit of chlorophyll a under optimal light conditions. Indicates the light attenuation coefficient of water body. This represents the light utilization efficiency factor of the water column. This represents the daily average irradiance of photosynthetically active radiation received by the water surface. This indicates the proportion of photosynthetically active radiation to total solar radiation. Indicates the duration of sunshine.

[0061] The beneficial effects of this invention are as follows: On the one hand, this invention integrates remote sensing methods with probability integral methods, using remote sensing images to extract the water accumulation boundary of coal mining subsidence areas, and simultaneously using the predicted parameters of the working face and geological and mining conditions to predict the surface subsidence basin topography through probability integral methods. The water accumulation boundary extracted from the remote sensing images is then matched with the predicted subsidence topography using coordinates to calculate the water accumulation area's reservoir capacity information. On the other hand, on-site sampling of the water accumulation in the study area is conducted, and the organic carbon density of the water body is measured experimentally to obtain the water body's carbon storage, accurately calculating the water body's carbon storage in the subsidence water accumulation area. This provides reliable technical support for the governance of coal mining subsidence areas and proposes more reasonable and effective governance solutions.

[0062] Compared to traditional methods for calculating carbon storage in water bodies, this invention can more conveniently and quickly calculate the underwater storage capacity of water accumulation areas, thereby accurately measuring the carbon storage in water bodies, gaining a deeper understanding of the carbon storage, flow, and transformation mechanisms in the region, providing basic data for regional carbon cycle research, providing a scientific basis for formulating carbon emission reduction policies, ecological compensation policies, and other related policies, improving the ecological environment of coal mining subsidence areas, and providing great assistance for the governance of coal mining subsidence areas. Attached Figure Description

[0063] Figure 1 This is a flowchart of the water carbon storage calculation method of the present invention;

[0064] Figure 2 This is a water accumulation boundary data map calculated using the probability integral method of the present invention;

[0065] Figure 3 This invention relates to a water accumulation boundary map extracted from remote sensing images;

[0066] Figure 4 It is a water accumulation boundary map obtained by superimposing the water accumulation boundary data map calculated by the probability integral method of the present invention with the water accumulation boundary map extracted based on remote sensing imagery. Detailed Implementation

[0067] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed merely to enable those skilled in the art to better understand and implement the subject matter described herein. Furthermore, features described in some examples may be combined in other examples.

[0068] like Figure 1 As shown, a method for calculating the carbon storage in water bodies in subsidence and waterlogging areas includes the following steps:

[0069] Step 100: Obtain geological and mining condition data of the mining area where the subsidence and water accumulation area is located, and calculate the subsidence data set of the subsidence and water accumulation area based on the geological and mining condition data.

[0070] In an optional embodiment of the present invention, the geological and mining condition data include the average mining depth H, mining thickness m, and coal seam dip angle. Expected working face strike length L, dip length l, subsidence coefficient q, horizontal movement coefficient b, main influence radius r, and mining influence propagation angle. And the inflection point offset s.

[0071] Using a probability integral method model, the three-dimensional surface movement and deformation field caused by mining is predicted. The formula for calculating the subsidence data is as follows:

[0072] ;

[0073] ;

[0074] in, Representing surface points The subsidence value at that location, D represents the maximum surface subsidence value, and D represents the projected range of the mining area on the coordinate plane. All of these are coordinate variables derived from the mining unit. Represents the variable in a double integral;

[0075] Based on the calculation results, a high-resolution surface subsidence contour map and a digital elevation model (DEM) are generated, which yields the predicted topographic data after subsidence, i.e., the subsidence dataset. .

[0076] Step 200: Obtain the remote sensing image data sequence of the subsidence water accumulation area and perform preprocessing. Use the water index method to extract the water accumulation boundary data sequence of the subsidence water accumulation area, and generate the water accumulation area data sequence based on the water accumulation boundary data sequence.

[0077] In an optional embodiment of the present invention, the specific steps for obtaining and preprocessing the remote sensing image data sequence of the subsidence water accumulation area are as follows:

[0078] Radiometric calibration, atmospheric correction (such as using FLAASH or 6S models), and geometric fine correction are performed on the images to ensure the accuracy of ground feature reflectance and spatial location.

[0079] An improved normalized differential water index method is used for automatic identification. The calculation formula for the water index method is as follows:

[0080] ;

[0081] in, This represents the improved normalized difference water index value. This represents the surface reflectance in the green band of satellite imagery (such as Landsat 8 Band 3). This indicates the surface reflectance in the shortwave infrared band (such as Landsat 8 Band 6) of satellite imagery;

[0082] By setting an experience threshold (usually 100%) The index image is binarized to extract water body pixels, which are then vectorized to obtain accurate water boundary vector data. And calculate its area. ,in Represents the time phase of an image.

[0083] Step 300: Overlay the water accumulation area data sequence and the subsidence data in a unified coordinate system to obtain the reservoir capacity time series;

[0084] In an optional embodiment of the present invention, step 300 includes the following specific steps:

[0085] Each acquired time phase Water accumulation boundary vector data With sinking dataset Perform spatial overlay analysis under a unified coordinate system;

[0086] For each time phase, determine the water surface elevation of the water accumulation area. (This can be determined using elevation or water level monitoring data from nearby non-subsidence areas);

[0087] Calculate the water volume for each time phase, i.e., the reservoir capacity. The calculation formula is as follows:

[0088] ;

[0089] in, Indicates phase The reservoir's water storage capacity Indicates phase The area of ​​the waterlogged area, Indicates phase water surface elevation, Point The estimated surface elevation at the location; integration is conducted within the waterlogged area. This represents the area element in the Cartesian coordinate system, and represents the area of ​​the water accumulation region. The variable of integration when performing double integration on the horizontal plane (XY plane);

[0090] By processing multi-temporal images, a data sequence of reservoir capacity can be obtained. , which serves as the mandatory input variable for the following carbon dynamics model.

[0091] Step 400: Using the grid method, multiple sampling points are systematically deployed in the subsidence and water accumulation area to collect multiple water sample data. Based on the multiple water sample data, the organic carbon density data of the water body in the subsidence and water accumulation area at a set time is obtained.

[0092] In an optional embodiment of the present invention, step 400 includes the following specific steps:

[0093] Using a grid sampling method, 10-20 water samples were collected from water accumulation areas at different water depths, and the coordinates of the sampling points were recorded.

[0094] During collection, a 500ml water sample was collected using a manual sampler, stored in a polyethylene plastic bottle, labeled with the corresponding number, and brought back to the laboratory.

[0095] Water samples were injected into a high-temperature combustion tube (850℃) and a low-temperature reaction tube, respectively. The water sample in the high-temperature combustion tube underwent high-temperature catalytic oxidation, converting both organic compounds and inorganic carbonates into carbon dioxide. The water sample in the low-temperature reaction tube was acidified, causing inorganic carbonates to decompose into carbon dioxide. The carbon dioxide generated from both processes was sequentially introduced into a non-dispersive infrared detector to measure the total carbon (TC) and inorganic carbon (IC) in the water, respectively. The difference between total carbon and inorganic carbon is the total organic carbon content (TOC), calculated using the following formula:

[0096] ;

[0097] in, This indicates the total organic carbon content of the water sample. This indicates the total carbon content of the water sample. This indicates the inorganic carbon content of the water sample;

[0098] The arithmetic mean of the TOC values ​​at all sampling points is used to obtain the average organic carbon density of the water body at the initial time. .

[0099] Step 500: Calculate the water carbon storage at the set time based on the reservoir capacity time series and the water organic carbon density data of the subsidence area at the set time;

[0100] In an optional embodiment of the present invention, the formula for calculating the carbon storage in the water at a given time is as follows:

[0101] ;

[0102] in, This indicates the carbon storage in the water body at a given time.

[0103] It should be noted that by combining remote sensing methods with probabilistic integration methods, the boundaries of water accumulation and subsidence topography can be predicted to obtain underwater reservoir capacity. Combined with the organic carbon density of the water body, the total carbon storage of the water body can be calculated, providing technical support for assessing the carbon storage of coal mining subsidence areas. This has played an important role in the comprehensive management of coal mining subsidence areas and improved the ecological environment of these areas. Through the integration of remote sensing and probabilistic integration methods, large-scale, high-timeliness, and low-cost dynamic monitoring of underwater reservoir capacity has been achieved, solving the primary technical bottleneck in carbon storage measurement.

[0104] In an optional embodiment of the present invention, the following steps are further included:

[0105] Step 600: Construct a carbon dynamics model, input the water carbon storage at the set time in step 500 into the carbon dynamics model, and output the carbon storage change rate.

[0106] The calculation formula for the carbon dynamics model is as follows:

[0107] ;

[0108] in, This represents the organic carbon storage in the water body of the water accumulation area at time t. This represents the rate of change in carbon reserves at time t. This represents the total external carbon input flux at time t. This represents the total carbon output flux at time t. This represents the primary carbon sequestration flux within the water body at time t. This represents the carbon emission flux from respiration and decomposition within the water body at time t.

[0109] ;

[0110] ;

[0111] ;

[0112] ;

[0113] ;

[0114] in, Indicates atmospheric deposition. Indicates precipitation. This indicates the concentration of organic carbon in rainwater. This represents dry deposition flux, which can be referenced from regional observations. To indicate surface runoff input, automatic monitoring stations are set up in major water catchment channels to continuously monitor flow. Water samples were collected regularly to determine the concentration of organic carbon. , This represents groundwater input, with recharge estimated based on a hydrogeological model. Combined with sampling from nearby groundwater wells , This represents sediment resuspension input, which is related to wind and wave energy and water depth. For wind speed, The average water depth, This is an empirical coefficient;

[0115] ;

[0116] ;

[0117] ;

[0118] ;

[0119] in, This indicates surface outflow, with flow rate monitored at the outlet. The average organic carbon density of water bodies calculated by the model , Greenhouse gas emissions are represented by in-situ measured CO2 flux using the floating box method or concentration gradient method (thin boundary layer model). and CH4 flux , The equivalent factor for the global warming potential of methane. This indicates sedimentary burial, achieved through sediment core sampling, using²¹ 0 Pb or ¹³ 7 Cs dating method to obtain sedimentation rate And analyze the organic carbon content of the sediments. , The bulk density of the sediment;

[0120] ;

[0121] ;

[0122] in, The concentration of chlorophyll a in water is a key indicator of phytoplankton biomass. It can be obtained through two complementary methods: first, on-site sampling: water samples are collected periodically (e.g., monthly) at representative locations in the waterlogged area, and measured in the laboratory using acetone extraction-spectrophotometry or fluorescence methods; second, remote sensing inversion: using multispectral or hyperspectral remote sensing images (e.g., Sentinel-2) from around the sampling time, a spatial distribution map of chlorophyll a concentration over a large area of ​​water is inverted using band combination algorithms (e.g., empirical algorithms like OC2 and OC3, or semi-analytical algorithms based on bio-optical models). The remote sensing inversion results are then corrected with synchronous on-site measurements to obtain a spatiotemporally continuous image. Distribution data, and calculation of the area-weighted average of the study area. This represents the maximum photosynthetic rate per unit of chlorophyll a under optimal light conditions. The light attenuation coefficient of water determines the vertical distribution of photosynthetically active radiation (PAR) in a water column. , The water column light utilization efficiency factor describes the ratio of the average light intensity of the entire water column to the light intensity of the water surface under given attenuation coefficient and water depth conditions. It is a dimensionless parameter (between 0 and 1). This represents the daily average irradiance of photosynthetically active radiation (PAR) received by the water surface. This represents the proportion of photosynthetically active radiation to total solar radiation, typically taken as an empirical value of 0.45. Indicates the duration of sunshine;

[0123] in, It is usually exponentially related to water temperature (Q) 10 (Model), and is related to the concentration of degradable organic matter, which can be determined on-site by dark bottle culture method, or using the formula: Make an estimate. This represents the baseline respiratory rate coefficient at 20°C.

[0124] Step 700: Based on the carbon storage change rate and the water carbon storage at a set time, generate the dynamic water carbon storage at the set time.

[0125] It should be noted that the calculation of the carbon storage in the water body of the coal mining subsidence and water accumulation area is based on the surface subsidence and water accumulation area of ​​a certain mine working face as an example.

[0126] Step 1: This working face adopts the strike-longwall caving method of fully mechanized mining. The strike length of the working face is 442m, the dip length is 68m, the average mining depth is 320m, the average mining thickness is m=4m, the coal seam dip angle is α=8°, the subsidence coefficient of the mining area is q=1.1, the main influence angle tangent tanβ=2.16, the horizontal movement coefficient is b=0.31, the upper inflection point offset distance is 0m, and the influence propagation angle is 86.3°. The surface subsidence basin contour lines are predicted using the probability integral method, as shown in the attached figure. Figure 2 As shown;

[0127] The second step is to acquire Landsat 8 remote sensing images of the subsidence and waterlogged area and extract the boundaries of the waterlogged area as shown in the attached image. Figure 3 As shown;

[0128] The third step involves matching and overlaying the extracted water accumulation boundary onto the subsided terrain to calculate the water level subsidence value. The location of the water accumulation boundary within the subsided basin terrain is shown in the attached figure. Figure 4 ;

[0129] The fourth step is to determine the water surface elevation and use the formula to calculate the water volume of the coal mining subsidence water accumulation area to be 101735 m³. 3 ;

[0130] Step 5: Organic carbon content was tested through on-site sampling, and the organic carbon density of the water in the coal mining subsidence area was calculated to be 4.33 mg / L using a formula;

[0131] Step 6: Combining the water body capacity and the organic carbon density of the water body, the carbon storage of the surface water accumulation area of ​​the working face in this mining area is calculated to be 440,512.55t;

[0132] Step 7: Establish small automatic meteorological and hydrological stations in waterlogged areas and major catchment paths to monitor rainfall, wind speed, water temperature, water level, and inflow / outflow. Collect runoff, groundwater, and rainwater samples quarterly to analyze carbon concentration. Measure gas flux monthly using the floating box method. Use a drone equipped with a multispectral sensor quarterly to retrieve chlorophyll a concentration. Combine the data obtained from the above monitoring... , , , Equal throughput data, along with and By inputting a carbon dynamics model, the dynamic carbon storage of the water body at the current moment can be output, and the dynamic carbon storage of the water body at subsequent moments can also be predicted.

[0133] The introduction of carbon dynamics models can continuously simulate the trajectory of carbon storage changes over time, revealing its seasonal patterns (such as high carbon sequestration capacity in summer and potential conversion to carbon source in winter) and interannual trends. More importantly, it has the ability to predict future scenarios and assess changes in carbon sequestration function under different climate conditions and management measures, providing a basis for forward-looking planning.

[0134] The above description of this embodiment is not limited to the specific implementation described above. The specific implementation described above is merely illustrative and not restrictive. Those skilled in the art can make many other forms based on the guidance of this embodiment, all of which are within the protection scope of this embodiment.

Claims

1. A method for calculating the carbon storage in water bodies of subsidence and waterlogged areas, characterized in that, Includes the following steps: Step 100: Obtain geological and mining condition data of the mining area where the subsidence and water accumulation area is located, and calculate the subsidence data set of the subsidence and water accumulation area based on the geological and mining condition data. Step 200: Obtain the remote sensing image data sequence of the subsidence water accumulation area and perform preprocessing. Use the water index method to extract the water accumulation boundary data sequence of the subsidence water accumulation area, and generate the water accumulation area data sequence based on the water accumulation boundary data sequence. Step 300: Overlay the water accumulation area data sequence and the subsidence data in a unified coordinate system to obtain the reservoir capacity time series; Step 400: Using the grid method, multiple sampling points are systematically deployed in the subsidence and water accumulation area to collect multiple water sample data. Based on the multiple water sample data, the organic carbon density data of the water body in the subsidence and water accumulation area at a set time is obtained. Step 500: Calculate the water carbon storage at the set time based on the reservoir capacity time series and the water organic carbon density data of the subsidence water area at the set time.

2. The method for calculating the carbon storage in water bodies of subsidence and waterlogged areas according to claim 1, characterized in that, It also includes the following steps: Step 600: Construct a carbon dynamics model, input the water carbon storage at the set time in step 500 into the carbon dynamics model, and output the carbon storage change rate. Step 700: Based on the carbon storage change rate and the water carbon storage at a set time, generate the dynamic water carbon storage at the set time.

3. The method for calculating the carbon storage in water bodies of subsidence and waterlogged areas according to claim 2, characterized in that, The geological and mining condition data includes average mining depth H, mining thickness m, and coal seam dip angle. Expected working face strike length L, dip length l, subsidence coefficient q, horizontal movement coefficient b, main influence radius r, and mining influence propagation angle. And the inflection point offset s; The formula for calculating the sinking data is: ； ； in, Representing surface points The subsidence value at that location, D represents the maximum surface subsidence value, and D represents the projected range of the mining area on the coordinate plane. All of these are coordinate variables derived from the mining unit. This represents the variable in a double integral.

4. The method for calculating the carbon storage in water bodies of subsidence and waterlogged areas according to claim 3, characterized in that, Step 200 includes the following specific steps: Step 201: Perform radiometric calibration, atmospheric correction, and geometric fine correction on the remote sensing image data sequence; Step 202: The corrected remote sensing image data sequence is processed using the improved normalized difference water index method to generate an index image data sequence. The calculation formula for the water index method is as follows: ； in, This represents the improved normalized difference water index value. This represents the surface reflectance in the green band of satellite imagery. This indicates the surface reflectance in the shortwave infrared band of satellite imagery; Step 203: Binarize the exponential image of the specified image phase by setting an empirical threshold, extract water body pixels, and then vectorize them to obtain accurate water accumulation boundary vector data. And calculate its area. ,in, Indicates the phase of an image.

5. The method for calculating the carbon storage in water bodies of subsidence and waterlogged areas according to claim 4, characterized in that, Step 300 includes the following specific steps: Step 301: Obtain each time phase Water accumulation boundary vector data Spatial overlay analysis was performed with the subsidence dataset in a unified coordinate system; Step 302: For each time phase, determine the water surface elevation of the water accumulation area. ; Calculate the reservoir capacity for each time phase. The calculation formula is as follows: ； in, Indicates phase The reservoir's water storage capacity Indicates phase The area of ​​the waterlogged area, Indicates phase water surface elevation, Point The projected surface elevation at the location, Represents an area element in Cartesian coordinates; Step 303: Combine the reservoir capacity of each time phase. Obtain the reservoir capacity data sequence .

6. The method for calculating the carbon storage in water bodies of subsidence and waterlogged areas according to claim 5, characterized in that, Step 400 includes the following specific steps: Step 401: Using the grid sampling method, collect several water samples at different water depths and record the coordinates of each sampling point; Step 402: Process the water sample and obtain the total carbon and inorganic carbon content. Calculate the organic carbon content based on the total carbon and inorganic carbon content using the following formula: ； in, This indicates the total organic carbon content of the water sample. This indicates the total carbon content of the water sample. This indicates the inorganic carbon content of the water sample; Step 403: Take the arithmetic mean of the TOC values ​​of all sampling points to obtain... Average organic carbon density of water at any given time .

7. The method for calculating the carbon storage in water bodies of subsidence and waterlogged areas according to claim 6, characterized in that, The formula for calculating the carbon storage in the water body at the set time in step 500 is as follows: ； in, This indicates the carbon storage in the water body at a given time.

8. The method for calculating the carbon storage in water bodies of subsidence and waterlogged areas according to claim 7, characterized in that, The calculation formula for the carbon dynamics model is as follows: ； in, This represents the organic carbon storage in the water body of the water accumulation area at time t. This represents the rate of change in carbon reserves at time t. This represents the total external carbon input flux at time t. This represents the total carbon output flux at time t. This represents the primary carbon sequestration flux within the water body at time t. This represents the carbon emission flux from respiration and decomposition within the water body at time t.

9. The method for calculating the carbon storage in water bodies of subsidence and waterlogged areas according to claim 8, characterized in that, ； ； ； ； ； in, Indicates atmospheric deposition. Indicates precipitation. This indicates the concentration of organic carbon in rainwater. This represents dry sedimentation flux. Indicates surface runoff input, This indicates continuous monitoring of flow rate. This indicates the concentration of organic carbon in the surface runoff input water sample. Indicates groundwater input. This indicates the estimated recharge volume from the hydrogeological model. This indicates the concentration of organic carbon in groundwater. Indicates sediment resuspension input. For wind speed, The average water depth, This is an empirical coefficient; ； ； ； ； in, Indicates surface outflow. Indicates the flow rate monitored at the outlet. Indicates greenhouse gas emissions, This indicates the on-site measured CO2 flux. This indicates the on-site measured CH4 flux. The equivalent factor for the global warming potential of methane. Indicates sedimentation and burial. Indicates the deposition rate, Indicates the organic carbon content of sediments. This refers to the bulk density of the sediment.

10. The method for calculating the carbon storage in water bodies of subsidence and waterlogged areas according to claim 9, characterized in that, ； ； in, This indicates the concentration of chlorophyll a in the water. This represents the maximum photosynthetic rate per unit of chlorophyll a under optimal light conditions. Indicates the light attenuation coefficient of water body. This represents the light utilization efficiency factor of the water column. This represents the daily average irradiance of photosynthetically active radiation received by the water surface. This indicates the proportion of photosynthetically active radiation to total solar radiation. Indicates the duration of sunshine.

Images