Isotopic assessment method of the effect of land use pattern on nitrogen pollution in a watershed

Abstract

The embodiment of the application provides an isotope evaluation method for the influence of land use pattern on nitrogen pollution in a basin, which comprises the following steps: field sampling in the basin, determination of the content of nitrate nitrogen in water samples and the nitrogen oxygen isotope value in nitrate; processing of remote sensing images, spatial analysis, division of sub-basins, classification of each sub-basin according to the land use mode of the sub-basin, and division of the region; and calculation of the contribution rate of different sources of nitrogen under different land use modes. The embodiment of the application maximally reduces the influence of time change of individual plots, avoids the limitation of sunlight irradiation and cloud cover; divides the whole basin into corresponding sub-basins, and then merges and classifies the sub-basins according to the land use type, divides the region under different land use modes, can more accurately calculate the contribution rate of different sources of nitrate nitrogen in water, and thus realizes quantitative evaluation of the influence of land use pattern on nitrogen pollution in the basin.

Description

Technical Field

[0001] The embodiments of this application belong to the fields of remote sensing applications and ecological environment impact assessment technology, and in particular involve isotope assessment methods for the impact of land use patterns on watershed nitrogen pollution. Background Technology

[0002] Changes in land use patterns significantly impact river (lake) water quality by altering the natural appearance of the watershed ecosystem landscape, material cycling, and energy distribution. Nitrogen pollution in rivers (lakes) is primarily driven by land use change, which alters runoff, the generation of non-point source pollution, and nutrient transport. Generally, nitrogen input into rivers (lakes) is closely related to the extensive use of nitrogen fertilizers in agricultural land within the watershed. The expansion of construction land, including industrial and urban land, also leads to the discharge of nitrogen-containing wastewater into rivers or lakes, resulting in an increase in nitrogen levels in the water. Forests can fix and absorb nutrients, thus mitigating and eliminating the impact of nitrogen on water bodies.

[0003] Previous studies on the impact of land use patterns on watershed nitrogen pollution have mainly focused on correlation and regression analysis between land use pattern variables and water nitrogen variables within the watershed, and then used land use pattern variables to predict the nitrogen content in the water. Most of these methods focus on the analysis of the relationship between the two, lacking the quantification of the impact of land use patterns on watershed nitrogen pollution, and cannot accurately calculate the contribution rate of land use patterns to the impact of watershed nitrogen pollution.

[0004] Based on the above, this invention discloses an isotopic assessment method for the impact of land use patterns on nitrogen pollution in river (lake) basins. Summary of the Invention

[0005] The purpose of this application is to provide an isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution. It is the first to propose using remote sensing technology combined with nitrate natural abundance isotope values ​​and a hybrid model to assess the impact of land use patterns on river (lake) nitrogen pollution. This method calculates the contribution rate of different nitrogen sources in different land use patterns, applies multi-time-period remote sensing interpretation datasets to improve the accuracy of land use classification, minimizes the impact of temporal variations in individual plots, and avoids limitations imposed by sunlight exposure and cloud cover. By using each sampling point as a water flow outlet, the entire watershed is divided into corresponding sub-watersheds. Furthermore, based on land use type, these sub-watersheds are merged and classified into regions under different land use patterns. This allows for a more accurate calculation of the contribution rate of different sources of nitrate nitrogen in the water body, thereby achieving a quantitative assessment of the impact of land use patterns on watershed nitrogen pollution and solving the problems in the background technology.

[0006] To address the aforementioned technical problems, the technical solution for the isotopic assessment method of the impact of land use patterns on watershed nitrogen pollution provided in this application is as follows:

[0007] An isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution, the method comprising the following steps:

[0008] Step 1: Sampling in the watershed to determine the nitrate nitrogen content and nitrogen oxygen isotope values ​​in the nitrate;

[0009] Step 2: Process remote sensing images, perform spatial analysis, divide into sub-basins, classify each sub-basin according to its land use pattern, and divide the region;

[0010] Step 3: Calculate the contribution rate of each source of nitrogen under different land use patterns in each region.

[0011] In a preferred embodiment of any of the above solutions, step 1 specifically includes:

[0012] Step 11: Set up sampling points from upstream to downstream and along each tributary within the watershed, and collect water samples at each sampling point;

[0013] Step 12: Determine the nitrate nitrogen content in the water at each sampling point in the laboratory;

[0014] Step 13: After pretreatment, the stable isotope δ-nitrate in the water was determined using a VG253 mass spectrometer in the physicochemical center laboratory. 15 N-NO3 and δ 18 The value of O-NO3.

[0015] In a preferred embodiment of any of the above solutions, step 2 specifically includes:

[0016] Step 21: Use high temporal and high spatial resolution satellite imagery to acquire multispectral imagery data from different time periods as the basic data source;

[0017] Step 22: Preprocess the image data within the watershed;

[0018] Step 23: Use unsupervised classification technology to classify the land use types of the preprocessed multispectral image data in the watershed, and merge similar land types among the classified land use types;

[0019] Step 24: Based on the watershed digital elevation and river or lake network map, take each sampling point as the water outlet, divide the entire watershed into corresponding sub-watersheds, and then merge and classify each sub-watershed according to land use type to divide it into several areas.

[0020] In a preferred embodiment of any of the above schemes, the preprocessing process includes at least one of radiometric calibration, atmospheric correction, orthorectification, or geometric correction.

[0021] In a preferred embodiment of any of the above solutions, step 3 specifically includes:

[0022] Step 31: In different regions, based on the δ of nitrate in the water... 15 N-NO3 and δ 18 The magnitude of O-NO3 value indicates its main source;

[0023] Step 32: Calculate δ within each region 15 N-NO3 and δ 18 The O-NO3 value is substituted into the isotopic binary or ternary mixing model, and the contribution rate of various sources of nitrate nitrogen under different land use patterns is calculated using the isotopic mixing model, thereby quantitatively assessing the impact of land use patterns on watershed nitrogen pollution.

[0024] In a preferred embodiment of any of the above solutions, in step 11,

[0025] After undergoing pretreatment such as acidification, the collected water samples were stored at a temperature below 4°C and brought back to the laboratory for testing.

[0026] In a preferred embodiment of any of the above schemes, in step 23, similar land use patterns among the divided land use types are merged and finally divided into eight types, namely: building land, artificial forest land, grassland, dry land, paddy field, mining land, bare land and water area.

[0027] In a preferred embodiment of any of the above schemes, in step 23, the overall accuracy of classification and the kappa coefficient are 86% and 0.79, respectively.

[0028] In a preferred embodiment of any of the above schemes, in step 24, based on the similarity of land use types within each sub-basin, the 30 sub-basins are merged and classified into 6 major regions, namely: mixed forest-farmland area, artificial forest area, mixed farmland-livestock area, farmland area, residential area, and mixed farmland-residential area.

[0029] In a preferred embodiment of any of the above schemes, in step 32, the contribution rate of various sources of nitrate nitrogen under different land use patterns is calculated using an isotopic mixing model. The specific calculation formula is as follows: Isotopic ternary mixing model:

[0030] Isotope binary mixing model: ,

[0031] in, and These represent the average isotopic compositions of N-NO3 and O-NO3, respectively. The subscripts A, B, C, and M represent the three sources of nitrogen pollution and their mixtures, respectively. A f B and f C The ratio of different sources of nitrogen pollution, A, B, and C, in M.

[0032] Compared with existing technologies, the isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution in this application proposes for the first time to apply remote sensing technology combined with nitrate natural abundance isotope values ​​and a hybrid model to assess the impact of land use patterns on river (lake) nitrogen pollution, calculate the contribution rate of different nitrogen sources in different land use patterns, and improve the accuracy of land use classification by applying multi-time period remote sensing interpretation datasets, minimizing the impact of temporal changes in individual plots and avoiding the limitations of sunlight exposure and cloud cover. By using each sampling point as a water flow outlet, the entire watershed is divided into corresponding sub-watersheds, and then the sub-watersheds are merged and classified according to land use type, dividing them into regions under different land use patterns. This allows for a more accurate calculation of the contribution rate of different sources of nitrate nitrogen in the water body, thereby achieving a quantitative assessment of the impact of land use patterns on watershed nitrogen pollution. Attached Figure Description

[0033] The accompanying drawings, which are provided to further illustrate this application and constitute a component of it, are used to explain the application and do not constitute an undue limitation thereof. Some specific embodiments of the application will be described in detail below with reference to the accompanying drawings in an exemplary and non-limiting manner. The same reference numerals in the drawings denote the same or similar components or parts. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale.

[0034] Figure 1 This is a schematic diagram illustrating the process of determining the nitrate nitrogen content and nitrogen oxygen isotope values ​​in the isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution in this application embodiment.

[0035] Figure 2 This is a schematic diagram illustrating the process of extracting sub-basins and dividing regions based on land use patterns within a watershed in the isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution in this application embodiment.

[0036] Figure 3 This is a schematic diagram illustrating the calculation process of the contribution rate of different nitrogen sources under different land use patterns in the isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution in this application embodiment.

[0037] Figure 4 This is a flowchart illustrating the isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution, as described in this application.

[0038] Figure 5 The isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution in this application embodiment is based on the land use pattern, which classifies 30 sub-watersheds into six regions.

[0039] Figure 6 The isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution in the embodiments of this application uses δ¹⁸ nitrates in each region. 15 N-NO3 and δ 18 A schematic diagram showing the range and location of O-NO3 values. Detailed Implementation

[0040] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely embodiments of one component of the present application, and not embodiments of the entire application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative effort should fall within the scope of protection of the present application.

[0041] The following embodiments of this application use the isotope assessment method for the impact of land use patterns on watershed nitrogen pollution as an example to illustrate the scheme of this application. However, this embodiment does not limit the scope of protection of this application. Example

[0042] This application provides an isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution, the method comprising the following steps:

[0043] Step 1: Field sampling of the watershed to determine the nitrate nitrogen content and nitrogen and oxygen isotope values ​​in the water samples; Step 1 specifically includes: Step 11: Setting up sampling points from upstream to downstream and along each tributary within the watershed, collecting water samples at each sampling point, pre-treating the collected water samples by acidification, storing them below 4°C, and bringing them back to the laboratory for analysis; Step 12: Determining the nitrate nitrogen content in the water at each sampling point in the laboratory; Step 13: After pre-treatment, determining the stable isotope δ-nitrate in the water using a VG253 mass spectrometer in the physicochemical center laboratory. 15 N-NO3 and δ 18 The value of O-NO3;

[0044] Step 2: Process remote sensing images, perform spatial analysis, divide sub-basins, and classify each sub-basin according to its land use patterns, thus dividing the area. Specifically, Step 2 includes: Step 21: Acquire multispectral image data from different time periods using high temporal and spatial resolution satellite imagery as the basic data source; Step 22: Preprocess the image data within the basin; Step 23: Use unsupervised classification technology to classify the land use types of the preprocessed multispectral image data within the basin, merging similar land use patterns among the identified land use types, ultimately dividing it into eight major types: built-up land, artificial forest land, grassland, dry land, paddy fields, mining land, and bare land. For water bodies, the overall accuracy and kappa coefficient of the classification are 86% and 0.79, respectively; Step 24: Based on the watershed digital elevation and river or lake network map, the entire watershed is divided into corresponding sub-watersheds, with each sampling point as the water outlet. Then, the sub-watersheds are merged and classified according to land use type, and divided into several regions; The preprocessing process includes at least one of radiometric calibration, atmospheric correction, orthorectification, or geometric correction; In step 24, based on the similarity of land use types in each sub-watershed, the 30 sub-watersheds are merged and classified into 6 major regions, namely: forest-farmland mixed area, artificial forest area, farmland-aquaculture mixed area, farmland area, residential area, and farmland-residential mixed area.

[0045] Step 3: Calculate the contribution rate of different nitrogen sources under different land use patterns in each region; Step 3 specifically includes: Step 31: In different regions, based on the δ of nitrate in water bodies... 15 N-NO3 and δ 18 The magnitude of the O-NO3 value determines its main source; Step 32: Calculate the δ value for each region. 15 N-NO3 and δ 18 The O-NO3 value is substituted into a binary or ternary isotopic mixing model, and the contribution rate of various sources of nitrate nitrogen under different land use patterns is calculated using the isotopic mixing model, thereby quantitatively assessing the impact of land use patterns on watershed nitrogen pollution; in step 32, the contribution rate of various sources of nitrate nitrogen under different land use patterns in each region is calculated using the isotopic mixing model, and the specific calculation formula is as follows:

[0046] Isotope ternary mixing model: Isotope binary mixing model: ,in, and These represent the average isotopic compositions of N-NO3 and O-NO3, respectively. The subscripts A, B, C, and M represent the three sources of nitrogen pollution and their mixtures, respectively. A f B and f CThe ratio of different sources of nitrogen pollution, A, B, and C, in M.

[0047] Example 1

[0048] Step 1: Determination of nitrate nitrogen content and nitrogen and oxygen isotope values ​​in water samples. Thirty sampling points were established from upstream to downstream and along tributaries in a river basin in Northeast China. Water samples were collected at each point. After pretreatment such as acidification, the collected water samples were stored below 4°C and brought back to the laboratory for analysis. In the laboratory, the nitrate nitrogen content at each sampling point was determined using a spectrophotometer. The nitrate content in the water was pretreated using the silver nitrate method, and the stable isotope δ¹⁸O was determined using a VG253 mass spectrometer in the physicochemical center laboratory. 15 N-NO3 and δ 18 The value of O-NO3.

[0049] Step 2: Spatial analysis using remote sensing imagery to divide the watershed into sub-basins. Based on differences in land use patterns, each sub-basin is categorized and divided into regions. High-resolution (2.5-meter resolution) multispectral SPOT imagery from 2009 is used as the basic data source for image preprocessing of the sampled watershed. Unsupervised classification techniques are employed to classify land use types within the preprocessed multispectral imagery data of the watershed. Similar land use patterns within the identified land use types are merged, ultimately resulting in eight major types: built-up land, artificial forest, grassland, dry land, paddy fields, mining land, bare land, and water area. The overall accuracy and kappa coefficient of the classification are 86% and 0.79, respectively. Based on the watershed digital elevation and river network map, using 30 sampling points as water outlets, the entire watershed is divided into 30 corresponding sub-basins. Based on the similarity of land use types within each sub-basin, the 30 sub-basins are merged and classified into 6 major regions (…). Figure 5 The zones are: mixed forest-farmland zone (Z1), plantation forest zone (Z2), mixed farmland-livestock zone (Z3), farmland zone (Z4), residential zone (Z5), and mixed farmland-residential zone (Z6).

[0050] Step 3: Calculate the contribution rate of different nitrogen sources under different land use patterns in each region, i.e., the contribution of different land use patterns to nitrogen pollution. The stable isotope δ¹⁸O in the six regions... 15 N-NO3 and δ 18 Integrate O-NO3 values ​​( Figure 6 Based on the δ of nitrate in the water bodies of the six sub-basins. 15 N-NO3 and δ 18 The magnitude of O-NO3 values ​​indicates the main sources of nitrate nitrogen in each sub-basin (synthetic fertilizers, domestic sewage / feces, soil organic matter, and atmospheric deposition); the δ values ​​for each region are used to determine the main sources of nitrate nitrogen (synthetic fertilizers, domestic sewage / feces, soil organic matter, and atmospheric deposition). 15 N-NO3 and δ18 The O-NO3 value is substituted into the isotopic binary or ternary mixture model (Formula 1 or 2), and the contribution rate of various sources of nitrate nitrogen under different land use patterns in each region is calculated using the isotopic mixture model (Table 1), thereby quantitatively assessing the impact of land use patterns on watershed nitrogen pollution.

[0051] Isotope ternary mixing model: (Formula 1)

[0052] Isotope binary mixing model: (Formula 2)

[0053] in, and These represent the average values ​​of the isotopic composition of N-NO3 and O-NO3, respectively.

[0054] The subscripts A, B, C, and M represent the three sources of nitrogen pollution and their mixtures, respectively.

[0055] f A f B and f C The ratio of different sources of nitrogen pollution, A, B, and C, in M.

[0056]

[0057] The present invention provides an experimental method for assessing the impact of land use patterns on nitrogen pollution in river (lake) basins, and an evaluation method combining isotope technology. This method utilizes multi-time-period remote sensing interpretation datasets to improve the accuracy of land use classification, minimizing the impact of temporal variations in individual plots and avoiding limitations imposed by sunlight exposure and cloud cover. By using each sampling point as a water outlet, the entire basin is divided into corresponding sub-basins. These sub-basins are then merged and categorized according to land use type, classifying them into regions under different land use patterns. This allows for more accurate calculation of the contribution rate of different sources of nitrate nitrogen in the water, thereby achieving a quantitative assessment of the impact of land use patterns on watershed nitrogen pollution.

[0058] This invention utilizes high-resolution multispectral imagery as the basic data source to preprocess the watershed imagery, obtaining watershed boundaries and land use maps. Unsupervised classification techniques are employed to classify land use types from the preprocessed multispectral imagery data. Based on the watershed digital elevation and river network map, and using each sampling point as a water outlet, the entire watershed is divided into corresponding sub-watersheds. Based on the similarity of land use patterns within each sub-watershed, the sub-watersheds are merged and categorized into several regions. The stable isotope δ¹⁸ within each region is then analyzed. 15 N-NO3 and δ 18O-NO3 values ​​were integrated to determine the main sources of nitrate nitrogen in each sub-basin. An isotopic mixing model was used to calculate the contribution rates of various nitrogen sources under different land use patterns. The application of multi-time-period remote sensing interpretation data improved the accuracy of land use classification, minimizing the impact of temporal variations in individual plots and avoiding limitations imposed by sunlight exposure and cloud cover. Using each sampling point as a water flow outlet, the entire watershed was divided into corresponding sub-basins. These sub-basins were then merged and categorized according to land use type, resulting in more accurate calculations of the contribution rates of different nitrogen sources under different land use patterns. This enabled a quantitative assessment of the impact of land use patterns on watershed nitrogen pollution.

[0059] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to the component or whole component technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. An isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution, characterized in that, The method includes the following steps: Step 1: Sampling in the watershed to determine the nitrate nitrogen content and nitrogen oxygen isotope values ​​in the nitrate; Step 2: Process remote sensing images, perform spatial analysis, divide into sub-basins, classify each sub-basin according to its land use pattern, and divide the region; Step 3: Calculate the contribution rate of each source of nitrogen under different land use patterns in each region; Step 2 specifically includes: Step 21: Use high temporal and high spatial resolution satellite imagery to acquire multispectral imagery data from different time periods as the basic data source; Step 22: Preprocess the image data within the watershed; Step 23: Use unsupervised classification technology to classify the land use types of the preprocessed multispectral image data in the watershed, and merge similar land types among the classified land use types; Step 24: Based on the watershed digital elevation and river or lake network map, take each sampling point as the water outlet, divide the entire watershed into corresponding sub-watersheds, and then merge and classify each sub-watershed according to land use type to divide it into several areas. Step 3 specifically includes: Step 31: In different regions, based on the δ of nitrate in the water... 15 N-NO3 and δ 18 The magnitude of O-NO3 value indicates its main source; Step 32: Calculate δ within each region 15 N-NO3 and δ 18 The O-NO3 value is substituted into the isotope binary or ternary mixing model, and the contribution rate of various sources of nitrate nitrogen under different land use patterns is calculated using the isotope mixing model, so as to quantitatively assess the impact of land use patterns on watershed nitrogen pollution. In step 23, similar land use patterns among the identified land use types are merged and finally divided into eight types: building land, artificial forest land, grassland, dry land, paddy field, mining land, bare land and water area. In step 24, based on the similarity of land use types within each sub-basin, the 30 sub-basins are merged and classified into 6 major regions, namely: mixed forest-farmland area, artificial forest area, mixed farmland-livestock area, farmland area, residential area, and mixed farmland-residential area; In step 32, the contribution rate of various sources of nitrate nitrogen under different land use patterns in each region is calculated using an isotopic mixing model. The specific calculation formula is as follows: Isotope ternary mixing model: , Isotope binary mixing model: , in, and These represent the average isotopic compositions of N-NO3 and O-NO3, respectively. The subscripts A, B, C, and M represent the three sources of nitrogen pollution and their mixtures, respectively. A f B and f C The ratio of different sources of nitrogen pollution, A, B, and C, in M.

2. The isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution according to claim 1, characterized in that, Step 1 specifically includes: Step 11: Set up sampling points from upstream to downstream and along each tributary within the watershed, and collect water samples at each sampling point; Step 12: Determine the nitrate nitrogen content in the water at each sampling point in the laboratory; Step 13: After pretreatment, the stable isotope δ-nitrate in the water was determined using a VG253 mass spectrometer in the physicochemical center laboratory. 15 N-NO3 and δ 18 The value of O-NO3.

3. The isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution according to claim 1, characterized in that, The preprocessing process includes at least one of radiometric calibration, atmospheric correction, orthorectification, or geometric correction.

4. The isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution according to claim 2, characterized in that, In step 11, the collected water sample is pretreated by acidification and then stored at a temperature below 4°C before being brought back to the laboratory for testing.

5. The isotopic assessment method for the impact of land use patterns on watershed nitrogen pollution according to claim 1, characterized in that, In step 23, the overall accuracy of classification and the kappa coefficient were 86% and 0.79, respectively.

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