A model method for estimating soil organic carbon density in a watershed using optical characteristic parameters of water bodies

Abstract

The invention relates to a model method for estimating the soil organic carbon density of a watershed using optical characteristic parameters of water bodies, and relates to a method for estimating the soil organic carbon density of a watershed, and belongs to the field of water body and soil environmental parameter evaluation. The invention aims to solve the problem that the current method for measuring soil organic carbon density is time-consuming and costly. The method is as follows: 1. Obtain water sample data; 2. Obtain soil sample data; 3. Based on the boundary vector data of China's nine major watersheds, the water sample data and the soil sample data are matched, and the linear regression model of the soil organic carbon density SOCD and the water absorption coefficient a is constructed using SPSS software. CDOM (355), the final model SOCD = 1.22*a CDOM (355) + 0.087. By monitoring the concentration changes of CDOM in water bodies, the present invention can understand the migration and transformation patterns of soil organic carbon density in surrounding watersheds. This is of great significance for understanding the Earth's carbon cycle, protecting the ecological environment, and guiding agricultural production.

Description

Technical Field

[0001] The present invention relates to a method for estimating soil organic carbon density in a watershed, and belongs to the field of water body and soil environmental parameter evaluation. Background Art

[0002] Soil erosion is a major factor contributing to the loss of soil organic carbon (SOC) and soil degradation. Soil organic carbon (SOC) refers to various positively charged carbon-containing organic compounds in soil and is a crucial component of soil. Colored dissolved organic matter (CDOM), the colored portion of DOM, is a key absorber of ultraviolet and visible blue light in water. SOC is a significant source of CDOM. When organic matter in soil dissolves and releases into water, the colored portion forms CDOM. Therefore, the content and composition of SOC directly influence the concentration and properties of CDOM in water. Furthermore, CDOM in water can also affect the dynamic balance of SOC. Microbial decomposition and transformation of SOC also influence the concentration and composition of CDOM in water. For example, the decomposition of SOC produces a series of intermediate products, which may include colored substances, thereby increasing the concentration of CDOM in water. The absorption and fluorescence properties of CDOM can reveal the sources and transformation processes of organic matter in water, providing important information for studying the migration and transformation of soil organic carbon. Furthermore, CDOM in water can also return to the soil through processes such as sedimentation and adsorption, interacting with soil organic carbon.

[0003] Currently, soil organic carbon (SOC) and its density are primarily measured using instruments such as elemental analyzers to determine the carbon content in soil samples. Soil samples are burned at high temperatures and the amount of carbon dioxide released is measured, allowing the soil's carbon content to be inferred. Soil bulk density is a key factor influencing soil carbon density. Therefore, accurate soil bulk density measurement is necessary before determining soil carbon density. This can be achieved through field measurements using tools such as ring cutters, followed by further processing and analysis in the laboratory. This process is cumbersome and complex, with high economic costs and a long experimental data acquisition cycle. The absorption coefficient of optically active substances (CDOM) in water bodies is primarily measured using ultraviolet spectrophotometry, which allows for rapid acquisition of relevant CDOM data. Soil organic carbon can be measured by measuring the absorption coefficient of CDOM in water, allowing the source and composition of SOC and its density to be inferred. However, currently, no numerical method for estimating SOC density in surrounding watersheds based on the optical properties of CDOM has been developed in China or in the Northeast Black Soil Region. Summary of the Invention

[0004] The purpose of the present invention is to solve the problem that the current method of measuring soil organic carbon density is time-consuming and costly, and to provide a model method for estimating the soil organic carbon density in a watershed by using optical characteristic parameters of water bodies.

[0005] The model method for estimating the soil organic carbon density in a watershed using water body optical characteristic parameters is carried out in the following steps:

[0006] 1. Obtain water sample data: Taking typical lakes in Northeast China as sampling points, 593 sampling points of CDOM concentration in 279 lakes in Northeast China were obtained. Surface water of the lakes was collected. 2L water samples were collected at each sampling point and immediately placed in a refrigerator for dark storage. All water samples were filtered within two days. The filtered samples were refrigerated and stored at 4℃. Optical absorption parameters were tested using the water absorption coefficient a. CDOM (355) represents the CDOM concentration of the water sample;

[0007] 2. Obtain soil sample data: Soil samples were collected from the 0-10 cm surface layer within a 5-kilometer buffer zone around 279 lakes. Five to eight soil samples were collected from each lake and placed in sealed containers, for a total of 720 surface soil samples. Soil bulk density was measured using the knife ring method, and soil organic carbon content was measured using external heating-potassium dichromate titration. Soil organic carbon density (SOCD) is equal to soil organic carbon content (TOC) multiplied by soil bulk density (BD). The average soil organic carbon density for the 279 lakes was calculated.

[0008] Third, based on the boundary vector data of China's nine major river basins, all samples were divided into 279 sub-basins, and the water sample data and soil sample data were matched. That is, there were 279 pairs of water and soil sample data, of which 175 sample points were used for model construction, and 104 sample points were used for model verification;

[0009] The linear regression model of soil organic carbon density SOCD and water absorption coefficient a was constructed using SPSS software. CDOM (355), the final model SOCD = 1.22*a CDOM (355)+0.087.

[0010] The optical absorption parameter testing method described in step 1 is as follows:

[0011] First, the water sample was filtered using a 47 μm glass fiber microporous filter membrane to obtain a primary filtered water sample;

[0012] The primary filtered water sample was then filtered through a 0.22 μm polycarbonate membrane to obtain the water sample for CDOM testing;

[0013] The water sample used for CDOM test was placed in a cuvette, ultrapure water was used as a reference, and the absorbance of the water sample used for CDOM test at 200nm–800nm ​​was measured using a Shimadzu UV spectrophotometer UV-2660. CDOM The absorption coefficient of (355) represents the CDOM concentration.

[0014] By monitoring the concentration changes of CDOM in water bodies, the present invention can understand the migration and transformation patterns of soil organic carbon density in surrounding watersheds. This is of great significance for understanding the earth's carbon cycle, protecting the ecological environment, and guiding agricultural production. According to the model method of the present invention, water samples were collected in the black soil area of ​​Northeast China, and CDOM samples were filtered and the absorption coefficient a was measured by ultraviolet spectrophotometer in the laboratory. CDOM (355) measured using SOC = 1.22*a CDOM The average soil organic carbon density within a 5-km buffer zone around a water body can be estimated by adding (355) to 0.087, without measuring soil organic carbon and soil bulk density. This method can quickly obtain soil organic carbon density around a water body. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is the location map of water bodies in Northeast China in the present invention;

[0016] Figure 2 is the relationship between the water CDOM absorption coefficient and the surrounding soil organic carbon density in Experiment 1;

[0017] Figure 3 This is a comparison chart of the measured values ​​of soil organic carbon density in Experiment 1 and the model-estimated values. DETAILED DESCRIPTION

[0018] The technical solution of the present invention is not limited to the specific embodiments listed below, but also includes any combination of the specific embodiments.

[0019] Specific embodiment 1: This embodiment uses the optical characteristic parameters of water bodies to estimate the soil organic carbon density in the watershed model method according to the following steps:

[0020] 1. Obtain water sample data: Taking typical lakes in Northeast China as sampling points, 593 sampling points of CDOM concentration in 279 lakes in Northeast China were obtained. Surface water of the lakes was collected. 2L water samples were collected at each sampling point and immediately placed in a refrigerator for dark storage. All water samples were filtered within two days. The filtered samples were refrigerated and stored at 4℃. Optical absorption parameters were tested using the water absorption coefficient a. CDOM (355) represents the CDOM concentration of the water sample;

[0021] 2. Obtain soil sample data: Soil samples were collected from the 0-10 cm surface layer within a 5-kilometer buffer zone around 279 lakes. Five to eight soil samples were collected from each lake and placed in sealed containers, for a total of 720 surface soil samples. Soil bulk density was measured using the knife ring method, and soil organic carbon content was measured using external heating-potassium dichromate titration. Soil organic carbon density (SOCD) is equal to soil organic carbon content (TOC) multiplied by soil bulk density (BD). The average soil organic carbon density for the 279 lakes was calculated.

[0022] Third, based on the boundary vector data of China's nine major river basins, all samples were divided into 279 sub-basins, and the water sample data and soil sample data were matched. That is, there were 279 pairs of water and soil sample data, of which 175 sample points were used for model construction, and 104 sample points were used for model verification;

[0023] The linear regression model of soil organic carbon density SOCD and water absorption coefficient a was constructed using SPSS software. CDOM (355), the final model SOCD = 1.22*a CDOM (355)+0.087.

[0024] Specific embodiment 2: This embodiment differs from specific embodiment 1 in that the optical absorption parameter testing method in step 1 is as follows:

[0025] First, the water sample was filtered using a 47 μm glass fiber microporous filter membrane to obtain a primary filtered water sample;

[0026] The primary filtered water sample was then filtered through a 0.22 μm polycarbonate membrane to obtain the water sample for CDOM testing;

[0027] The water sample used for CDOM test was placed in a cuvette, ultrapure water was used as a reference, and the absorbance of the water sample used for CDOM test at 200nm–800nm ​​was measured using a Shimadzu UV spectrophotometer UV-2660. CDOM The absorption coefficient of (355) represents the CDOM concentration. Other aspects are the same as those in the first embodiment.

[0028] The following experiments were used to verify the effects of the present invention:

[0029] Experiment 1:

[0030] The model method for estimating the soil organic carbon density in a watershed using water body optical characteristic parameters is carried out in the following steps:

[0031] 1. Obtaining water sample data: Taking the Northeast region ( Figure 1) Typical lakes were used as sampling points, and 593 sampling points with measured CDOM concentrations were obtained from 279 lakes in Northeast China. Surface water samples of lakes were collected, and 2L of water samples were collected from each sampling point and immediately placed in a refrigerator for dark storage. All water samples were filtered within two days and stored at 4°C. The optical absorption parameters were tested using the water absorption coefficient a CDOM (355) represents the CDOM concentration of the water sample;

[0032] 2. Obtain soil sample data: Soil samples were collected from the 0-10 cm soil surface within a 5 km buffer zone around 279 lakes. 5-8 soil samples were collected from each lake and placed in sealed containers. A total of 720 surface soil samples were collected. The soil bulk density was measured using the ring knife method (place the ring knife holder on a ring knife of known weight, slightly apply vaseline on the inner wall of the ring knife, and press the ring knife edge vertically downward into the soil until the ring knife tube is filled with the sample. If the soil is hard, the ring knife handle can be gently tapped with a hammer. Use a soil cutter to cut the soil sample around the ring knife, take out the ring knife filled with soil, and carefully cut off the ring knife. Remove excess soil at both ends so that the soil volume is exactly the volume of the ring cutter, and wipe off the soil outside the ring cutter. Immediately cover the ends of the ring cutter to prevent water evaporation. Weigh the wet soil in the ring cutter and the weight of the ring cutter, and record the data. At the same time, use an aluminum box to sample and determine the natural moisture content of the soil. Calculate the soil bulk density according to the formula. ), the soil organic carbon content is measured using the external heating-potassium dichromate titration method (LY / T1237-1999). The soil organic carbon density (SOCD) is equal to the soil organic carbon content (TOC) multiplied by the soil bulk density (BD). The average soil organic carbon density of 279 lakes was calculated;

[0033] Third, based on the boundary vector data of China's nine major river basins, all samples were divided into 279 sub-basins, and the water sample data and soil sample data were matched. That is, there were 279 pairs of water and soil sample data, of which 175 sample points were used for model construction, and 104 sample points were used for model verification;

[0034] The linear regression model of soil organic carbon density SOCD and water absorption coefficient a was constructed using SPSS software. CDOM (355) (In SPSS software, click "Analysis" - "Regression" - "Linear Regression" in sequence to enter the linear regression analysis interface. In the linear regression analysis interface, import the dependent variable (SOCD) and the independent variable (CDOM) into the corresponding boxes respectively. Click the "Statistics" button and select the required statistical options, such as regression coefficient, model fit, and estimated value.), the final model SOCD = 1.22*a CDOM (355)+0.087

[0035] Plot the water absorption coefficient aCDOM In the rectangular coordinate system with (355) as the horizontal axis and soil organic carbon density as the vertical axis, the correlation coefficient can reach 0.73 ( Figure 2 ), and the linear relationship was verified by using the remaining 104 water and soil sample data to verify the measured data. The horizontal axis is the measured value, and the measured value is brought into the above final model. The calculated result is recorded as the estimated value, and the vertical axis is used to compare the measured value with the model estimated value. The verification result shows that the correlation slope is 0.75 and the correlation coefficient is 0.72 ( Figure 3 ).

[0036] Since the sampling points are widely and evenly distributed within the black soil region of Northeast China, the soil organic carbon density calculated according to the method of the present invention has a very high credibility.

[0037] The optical absorption parameter testing method described in step 1 is as follows:

[0038] First, the water sample was filtered using a 47 μm glass fiber microporous filter membrane to obtain a primary filtered water sample;

[0039] The primary filtered water sample was then filtered through a 0.22 μm polycarbonate membrane to obtain the water sample for CDOM testing;

[0040] The water sample for CDOM test was placed in a cuvette, and ultrapure water (Milli-Q IQ 7000 system) was used as a reference. The absorbance of the water sample for CDOM test at 200nm–800nm ​​was measured using a Shimadzu UV spectrophotometer UV-2660. CDOM The absorption coefficient of (355) represents the CDOM concentration.

Claims

1. A model method for estimating soil organic carbon density in a watershed using optical characteristic parameters of water bodies, characterized by The model method for estimating the soil organic carbon density in a watershed using optical characteristic parameters of water bodies is carried out in the following steps:

1. Obtain water sample data: Using typical lakes in Northeast China as sampling points, 593 sampling points with measured CDOM concentrations were obtained from 279 lakes in Northeast China. Surface water samples were collected from lakes. 2L of water samples were collected from each sampling point and immediately placed in a refrigerator for dark storage. All water samples were filtered within two days and stored at 4°C. Optical absorption parameters were tested using the water absorption coefficient a. CDOM (355) represents the CDOM concentration of the water sample; 2. Obtain soil sample data: Soil samples were collected from the 0-10 cm surface layer within a 5-kilometer buffer zone around 279 lakes. Five to eight soil samples were collected from each lake and placed in sealed containers, for a total of 720 surface soil samples. Soil bulk density was measured using the knife ring method, and soil organic carbon content was measured using external heating-potassium dichromate titration. Soil organic carbon density (SOCD) is equal to soil organic carbon content (TOC) multiplied by soil bulk density (BD). The average soil organic carbon density for the 279 lakes was calculated. Third, based on the boundary vector data of China's nine major river basins, all samples were divided into 279 sub-basins, and the water sample data and soil sample data were matched. That is, there were 279 pairs of water and soil sample data, of which 175 sample points were used for model construction, and 104 sample points were used for model verification; The linear regression model of soil organic carbon density SOCD and water absorption coefficient a was constructed using SPSS software. CDOM (355), the final model SOCD = 1.22*a CDOM (355)+0.

087.

2. The model method for estimating soil organic carbon density in a watershed using optical characteristic parameters of water bodies according to claim 1 is characterized in that The optical absorption parameter testing method described in step 1 is as follows: First, the water sample was filtered using a 47 μm glass fiber microporous filter membrane to obtain a primary filtered water sample; The primary filtered water sample was then filtered through a 0.22 μm polycarbonate membrane to obtain the water sample for CDOM testing; The water sample used for CDOM test was placed in a cuvette, ultrapure water was used as a reference, and the absorbance of the water sample used for CDOM test at 200nm–800nm ​​was measured using a Shimadzu UV spectrophotometer UV-2660. CDOM The absorption coefficient of (355) represents the CDOM concentration.

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