Ecological sustainable measurement and analysis method for promoting ecological restoration of inland river basin

Abstract

The invention discloses an ecological sustainable measurement analysis method for promoting ecological restoration of an inland river basin, which comprises the steps of inland river basin ecological system function and sustainable development target evaluation and spatial pattern feature analysis. And the ecological system and the sustainable development target are subjected to tradeoff collaborative analysis, and ecological sustainable differential zoning is realized and adjustment measures are put forward by constructing an inland river basin ecological sustainable development cluster. The method is simple, can assist in quickly realizing coupling analysis of an ecological system and sustainable development, and provides a scientific basis for fully exploring a sustainable development link relationship coupled with ecological system service in an inland river basin; and a technical support is provided for making an environmental resource utilization plan for realizing the goals of ecological restoration and sustainable development in the inland river basin.

Description

Technical Field

[0001] The present invention relates to the technical fields of geography and ecology, in particular to an ecological sustainability measurement and analysis method for promoting ecological restoration of inland river basins. Background Art

[0002] Inland river basins, due to their unique geographical location, severe ecological environment, and conflicts between human activities and ecological protection, have become a hot topic for studying the contradictions between ecosystem and socioeconomic development. However, due to the prevalence of ecological degradation, the interaction between human social development and the environment in inland river basins has been neglected. To achieve the mutually beneficial development of the ecological environment and human society, a systematic analysis of ecosystem services and sustainable development goals is necessary. This will identify the ecological-sustainable development nexus, assist in the development of ecological-sustainable functional zoning in arid regions, and identify the key factors affecting the ecological environment and sustainable development in each zoning. This will provide a scientific basis and technical support for planning measures to restore ecosystem functions and achieve sustainable development goals.

[0003] Existing ecological sustainability measurement and analysis mainly focuses on ecosystem service functions, using correlation analysis, structural equation models, and machine learning methods to analyze the trade-offs and synergies between each ecosystem service function and their changing characteristics. At the same time, cellular automata or the Future Land Use Change Model (FLUS) are used to further simulate and analyze the land use in the study area, and based on this, the optimization direction of future ecosystem services is proposed.

[0004] The above methods only focus on the impact between ecosystem service functions, and pay less attention to the relationship between ecological functions and the sustainable development goals of human society. They cannot provide analytical basis and decision-making support for achieving the coordinated development of ecological restoration and sustainable development goals. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide an ecological sustainability measurement and analysis method to promote the ecological restoration of inland river basins. By calculating the ecosystem service functions and sustainable development goals of inland river basins, the ecological-sustainable ties that dominate regional development are identified, and based on this, regional ecological-sustainable development clusters are identified and divided. Based on the calculation of the key influencing factors of ecological-sustainable development that dominate each partition, ecological-sustainable development optimization measures for each partition are proposed; this method provides an analytical basis and decision-making support for coordinating the conflict between ecological protection and social development.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention provides an ecological sustainability measurement and analysis method for promoting ecological restoration of inland river basins, comprising the following steps:

[0008] S1. Identify and extract inland river basins from topographic and geomorphological data, and build a basic inland river database;

[0009] S2. Construct ecosystem service data for inland river basins to evaluate ecosystem functions; the ecosystem service data include wind and sand erosion, water yield, habitat quality, food production, carbon storage, and soil conservation data;

[0010] S3. Construct Sustainable Development Goal data for inland river basins to evaluate sustainable development; the Sustainable Development Goal data include SDG1-No Poverty, SDG2-Zero Hunger, SDG3-Good Health and Well-being, SDG6-Clean Water and Sanitation, SDG7-Clean Energy, SDG9-Industry, Innovation and Infrastructure, SDG11-Sustainable Cities and Communities, SDG13-Climate Action, SDG15-Life on Land, SDG16-Peace, Justice and Strong Institutions, and SDG17-Partnerships;

[0011] S4. Based on ecosystem service data and sustainable development goal data, identify the ecological-sustainable development nexus of inland river basins, extract ecological-sustainable development zoning clusters of inland river basins, and zoning them;

[0012] S5. Calculate the key driving factors of ecological and sustainable development in each region based on the ecological zoning data, and propose resource planning measures to achieve ecological and sustainable goals.

[0013] Furthermore, the basic database includes hydrological data, socio-economic data, meteorological data, topographic data, land use data, ecological environment data and remote sensing data; the steps for establishing the basic database are as follows:

[0014] S11. Inland River Basin Extraction

[0015] Based on digital elevation data, the boundaries of inland river basins are extracted after completing depression calculation, flow direction analysis, flow calculation, and slope point capture;

[0016] S12. Construction of basic database of inland river basins

[0017] Based on the concept of multi-source heterogeneous data fusion, relying on the geographic spatiotemporal intelligent platform, using data cleaning algorithms and spatial registration technology, we unify the coordinate benchmarks and reconstruct the spatiotemporal attributes of multi-dimensional data, and build a basic spatiotemporal database for inland river basins, providing a full-factor digital foundation for ecological monitoring and sustainable development.

[0018] Furthermore, the inland river basin ecosystem service assessment in step S2 is performed in the following manner:

[0019] Based on the water balance principle, the Budyko curve and the average annual rainfall are used to calculate the water yield value of the basin and each grid within the basin;

[0020] In the InVEST model, the habitat quality is calculated by integrating parameters such as habitat suitability of land use types, spatial distribution and attenuation patterns of threat sources, and sensitivity of habitats to threats, and using a spatial superposition algorithm.

[0021] Based on the statistical data of grain production, the grain productivity was calculated by combining the LRPM grid allocation model and NDVI to represent the value of grain supply services.

[0022] In the InVEST model, carbon density data from different land use types are integrated to quantitatively assess the carbon storage of ecosystems in carbon pools such as surface vegetation, soil, and dead organic matter. Spatial overlay analysis methods are used to calculate and quantify the distribution pattern of carbon storage in ecosystems.

[0023] Soil conservation was calculated based on the modified universal soil erosion equation (RUSLE).

[0024] Furthermore, the assessment of sustainable development goals for inland river basins in step S3 is performed according to the following steps:

[0025] S31. Calculate the proportion of the population living below the national poverty line and the proportion of households with access to basic services from the available statistical data, and thus calculate the indicator value for SDG 1 - No Poverty.

[0026] S32. Use food production data to calculate the agricultural output per labor unit to represent the indicator value of SDG2-Zero Hunger.

[0027] S33. Use indicators such as disease incidence and mortality to represent the indicator value of SDG3 - Good Health and Well-being.

[0028] S34. Use water resource utilization efficiency and water stress to calculate the indicator value of SDG6 - Clean drinking water and sanitation facilities.

[0029] S35. The proportion of the population with access to electricity and the proportion of the population relying on clean fuels and technologies are used to calculate the indicator value for SDG7 - Clean Energy.

[0030] S36. The proportion of the rural population living within two kilometers of a road accessible all year round is used to represent the indicator value of SDG9 - Industry, Innovation and Infrastructure.

[0031] S37. Use the proportion of the population with convenient access to public transportation to represent the indicator value of SDG-11 Sustainable Cities and Communities.

[0032] S38. Use annual greenhouse gas emissions to represent the indicator value of SDG-13 climate action.

[0033] S39. Use the ratio of forest area to total land area and the ratio of mountain green cover index to calculate the indicator value of SDG15 - Terrestrial Life.

[0034] S310: Use the proportion of victims of intentional homicide to represent the indicator value of S16 - Peace, Justice and Strong Institutions.

[0035] S311. Use the proportion of the population using the Internet to represent the indicator value of S17-Partnership.

[0036] S312. Standardize all SDGs and then calculate the total score of all SDGs.

[0037] Further, step S4 is performed according to the following steps:

[0038] S41. Extraction of Ecological-Sustainable Development Links

[0039] The Min-Max normalization method was used to standardize the six ecosystem service functions, and Rstudio software was used to conduct Pearson correlation analysis between ecosystem service functions and sustainable development goals to characterize the direction and intensity of the interaction between ecosystems and sustainable development goals, extract sustainable development goals with a strong correlation with ecosystem services, and identify the ecological-sustainable development link.

[0040] S42. Identification of Ecological-Sustainable Development Clusters

[0041] Based on the extracted ecological-sustainable development links, the self-organizing map neural network model was used in combination with the random forest algorithm to screen key features, and hierarchical cluster analysis was applied to reveal the inherent hierarchical structure of the data. The spatial morphology of ecological-sustainable development clusters was identified through cluster analysis.

[0042] Further, step S5 is performed according to the following steps:

[0043] S51. Use the geographic detector method to identify the key driving factors within each ecological-sustainable development cluster, and use the factor detection and interaction detection functions to calculate the main factors affecting each ecological-sustainable development cluster, and then propose targeted suggestions and measures.

[0044] Furthermore, the wind and sand erosion is calculated as follows:

[0045]

[0046] Where S Lis the actual amount of wind and sand erosion (t / km 2 / a), which is the amount of soil lost per unit area due to wind in a certain period of time; z is the distance from the top of the wind field to the ground surface (m), Q max It represents the maximum conveying capacity (kg / m); s is the critical field length (m).

[0047] Furthermore, the water production is calculated as follows:

[0048]

[0049] Where Y(X) represents the water production on grid x, P x represents the annual rainfall on grid x, and AET(X) represents the actual evapotranspiration on grid X.

[0050] Furthermore, the habitat quality is calculated as follows:

[0051]

[0052] Where Q xj is the habitat quality index of grid x in land use type j; H j is the habitat suitability of land use type j; D xj For land use

[0053] The degree of habitat degradation for grid x in type j; z is the normalization constant; and k is the half-saturation constant.

[0054] Furthermore, the food production is calculated as follows:

[0055]

[0056] Where S GP is the estimated grain production, GP sum is the total grain production statistics within the study area, NDVI i is the NDVI value of the cultivated land pixel in the grid, NDVI sum It is the sum of the NDVI of all cultivated land pixels at the corresponding scale.

[0057] Furthermore, the carbon reserves are calculated as follows:

[0058]

[0059] Where i is different types of land use, C sum is the total carbon storage in the study area (t / hm2), C i-above is the aboveground carbon storage (t / hm2), C i-below is the underground carbon storage (t / hm2), Ci-soil is soil carbon storage (t / hm2), C i-dead is the dead organic carbon storage (t / hm2). The larger the calculated value is, the higher the carbon storage is.

[0060] Furthermore, the carbon reserves are calculated as follows:

[0061] SC=R×K×LS×(1-C×P)

[0062] Where SC is the annual soil conservation capacity (t / km 2 / a); R is the rainfall erosivity coefficient (MJ·mm / hm2·h·a); K is the soil erodibility factor (t·ha·h / ha·MJ·mm); LS refers to topographic factors, including steepness and slope length; C is the surface vegetation cover factor; and P is the soil and water conservation measures factor.

[0063] Furthermore, the SDG-6 Clean Water and Sanitation is calculated as follows:

[0064] The calculation method for water resource utilization efficiency is:

[0065] WUE=A we ×P A +M we ×P M +S we ×P S

[0066] Where WUE is water resource utilization efficiency (USD / m 3 ), A we is the agricultural water resource utilization efficiency (USD / m 3 ), M we is the water resource utilization efficiency of the industrial sector (USD / m 3 ), S we Water resource utilization efficiency of the service sector (USD / m 3 ), P A , P M and P S These are the proportions of total water use occupied by agriculture, industry and services respectively.

[0067] The calculation method for water stress is:

[0068]

[0069] Where WS is the water resource utilization efficiency (%), TFWW is the total annual freshwater withdrawal; TRWR is the total available freshwater resources in the region, and EFR is the minimum water resources required to maintain the normal operation of the ecosystem in the region.

[0070] Furthermore, the SDG-15 terrestrial organisms are calculated as follows:

[0071] The ratio of forest area to total land area is calculated as follows:

[0072]

[0073] Where FR is the proportion of forest area to the total area of ​​the watershed (%), FA is the forest area in the watershed (km 2 ); TA is the total area of ​​the study area (km 2 ).

[0074] The calculation method of mountain green coverage index is:

[0075]

[0076] Where MGCI is the mountain green coverage index, AC is the cultivated land area in mountainous areas (km 2 ), AF is the forest coverage area in mountainous areas (km 2 ), AG is the grassland coverage area in mountainous areas (km 2 ), TMA (km 2 ) is the total mountainous area.

[0077] Further, calculations for other Sustainable Development Goals based on statistical data (SDG1, SDG2, SDG3, SDG7, SDG9, SDG11, SDG13, SDG16 and SDG17):

[0078]

[0079] Where SDGV is the value of a sustainable development goal in the Aral Sea Basin, i is the seven countries where the Aral Sea Basin is located, PA i is the population / nighttime light / GDP value of country i in the Aral Sea basin, IV i is the performance of a certain sustainable development goal of country i, and TPA is the total population of the Aral Sea basin / night lights / GDP.

[0080] Furthermore, the standardized processing process for all SDGs is:

[0081]

[0082] In the formula, x is the raw data value of each SDGs indicator, min(x) and max(x) are the values ​​corresponding to the worst and best performance of the raw data of the positive and negative indicators, respectively. ′ It is the standardized score of SDGs indicators.

[0083] The beneficial effects of the present invention are:

[0084] The ecological sustainability measurement and analysis method provided by this invention to promote ecological restoration in inland river basins includes evaluation of ecosystem service functions in inland river basins and analysis of trends in sustainable development goals, correlation analysis between ecosystem services and sustainable development goals, spatial clustering and zoning through the construction of ecological-sustainable development clusters, analysis of the driving factors within each zone, and the proposed differentiated optimization measures based on these factors. This simple, direct, and logical method can assist in the rapid implementation of ecological-sustainable functional zoning in inland river basins, provide a basis for scientifically determining priority measures to promote the coordinated optimization of ecological restoration and sustainable development under different environmental conditions, and provide technical support for the development of environmental resource utilization plans for inland river basins to achieve ecological restoration and sustainable development goals.

[0085] The present invention uses data from remote sensing images, official statistics from the United Nations and the Food and Agriculture Organization of the United Nations, etc., and ultimately completes the assessment of ecosystem service functions of inland river basins, calculation of sustainable development goals, correlation analysis, extraction of ecological-sustainable ties, identification and zoning of ecological-sustainable clusters, and identification of major influencing factors.

[0086] This study leverages a variety of open-source data and specialized algorithmic models to quantitatively analyze the ecosystem services and sustainable development goals of inland river basins. Geospatial analysis software is then used to analyze and optimize the ecosystem's ecosystem structure. The model's computational steps are clear, and specific parameters (such as total water resources, carbon density under different soil types, soil and water conservation factors, and land cover factors) can be adjusted based on the characteristics of each study area to meet the planning needs of different regions, achieving strong adaptability to migration.

[0087] Other advantages, objectives, and features of the present invention will be partially described in the subsequent description, and those skilled in the art will naturally understand this content through the following research and analysis or verification of specific embodiments. The objectives, related advantages, and beneficial effects of the present invention can be achieved and verified through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] In order to make the purpose, technical solution and effect of the present invention clearer, the present invention provides the following drawings for illustration:

[0089] Figure 1 It is a schematic diagram of the overall process of an embodiment of the present invention.

[0090] Figure 2 4 is a spatial distribution map of ecosystem services according to an embodiment of the present invention.

[0091] Figure 3 This is a graph showing the changing trend of sustainable development goals according to an embodiment of the present invention.

[0092] Figure 4This is an ecological-sustainable linkage diagram according to an embodiment of the present invention.

[0093] Figure 5 1 is an ecologically sustainable cluster distribution pattern and spatial distribution diagram of an embodiment of the present invention.

[0094] Figure 6 4 is a diagram of driving factors for ecological-sustainable zoning according to an embodiment of the present invention.

[0095] Figure 7 1 is a diagram of various ecological-sustainable zoning measures according to an embodiment of the present invention. DETAILED DESCRIPTION

[0096] In order to further illustrate the technical methods and effects adopted by the present invention to achieve the intended purpose of the invention, the following is a detailed description of the specific implementation methods, structures, features and effects of the present invention in combination with the accompanying drawings and preferred embodiments.

[0097] like Figure 1 As shown, the ecological sustainability measurement and analysis method provided in this embodiment to promote ecological restoration in inland river basins quantitatively analyzes the development trends of ecosystem services and sustainable development goals in inland river basins, deconstructs the correlation between the two over time, extracts the links that can characterize ecology and sustainability, clusters and zons based on ecosystem services and sustainable development goals in arid areas, and proposes an optimization strategy for achieving two-way improvement in ecology and sustainability in the region. It includes the following steps:

[0098] S1. Inland river basin extraction and database construction

[0099] S1.1. Inland River Basin Extraction

[0100] Based on the digital elevation data, after completing the filling calculation, flow direction analysis, flow calculation and slope point capture, the inland river basin boundary is extracted, and the DEM elevation data and basic geographic information such as rivers are imported into the inland river basin.

[0101] S1.2. Construction of the basic database of inland river basins

[0102] Through open-source data platforms such as PIE or GEE, we collected multi-source remote sensing data (land use, environmental data, meteorological data, etc.), and collected publicly available statistical data from the United Nations, the Food and Agriculture Organization of the United Nations, or other government agencies. Using tools such as resampling and projection correction in the ArcGIS geographic information platform, we set all spatial data to a unified coordinate system and resolution (coordinate system 1: WGS_1984, pixel resolution: 1 km x 1 km), completing the construction of a basic inland river basin database.

[0103] S2. Assessment of ecosystem service functions in inland river basins

[0104] The inland river ecosystem service assessment in this example includes the following:

[0105] Six modules, namely wind and sand erosion, water yield, habitat quality, food production, carbon storage and soil conservation, were selected to evaluate ecosystem service functions. Figure 2 shown.

[0106] (1) Wind and sand erosion

[0107] The amount of wind-blown sand erosion is calculated based on the modified wind-blown sand erosion equation RWEQ;

[0108]

[0109] Where S L is the actual amount of wind and sand erosion (t / km 2 / a), which is the amount of soil lost per unit area due to wind in a certain period of time; z is the distance from the top of the wind field to the ground surface (m), Q max It represents the maximum conveying capacity (kg / m); s is the critical field length (m).

[0110] (2) Water production

[0111] Based on the water balance principle, the Budyko curve and the average annual rainfall are used to calculate the water yield value of the basin and each grid within the basin;

[0112]

[0113] Where Y(X) represents the water production on grid x, P x represents the annual rainfall on grid x, and AET(X) represents the actual evapotranspiration on grid X.

[0114] (3) Habitat quality

[0115] In the InVEST model, the habitat quality is calculated by integrating parameters such as habitat suitability of land use types, spatial distribution and attenuation patterns of threat sources, and sensitivity of habitats to threats, and using a spatial superposition algorithm.

[0116]

[0117] Where Q xj is the habitat quality index of grid x in land use type j; H j is the habitat suitability of land use type j; D xj is the degree of habitat degradation of grid x in land use type j; z is the normalization constant; k is the half-saturation constant.

[0118] (4) Grain production

[0119] Based on the statistical data of grain production, the grain productivity was calculated by combining the LRPM grid allocation model and NDVI to represent the value of grain supply services.

[0120]

[0121] Where S GP is the estimated grain production, GP sum is the total grain production statistics within the study area, NDVI i is the NDVI value of the cultivated land pixel in the grid, NDVI sum It is the sum of the NDVI of all cultivated land pixels at the corresponding scale.

[0122] (5) Carbon storage

[0123] In the InVEST model, carbon density data from different land use types are integrated to quantitatively assess the carbon storage of ecosystems in carbon pools such as surface vegetation, soil, and dead organic matter. Spatial overlay analysis methods are used to calculate and quantify the distribution pattern of carbon storage in ecosystems.

[0124]

[0125] Where i is different types of land use, C sum is the total carbon storage in the study area (t / hm 2 ), C i-above is the aboveground carbon storage (t / hm 2 ), C i-below is the underground carbon storage (t / hm 2 ), C i-soil is soil carbon storage (t / hm 2 ), C i-dead is the dead organic carbon stock (t / hm 2 ), the larger the calculated value, the higher the carbon storage.

[0126] (6) Soil conservation

[0127] Soil conservation was calculated based on the modified universal soil erosion equation (RUSLE).

[0128] SC=R×K×LS×(1-C×P)

[0129] Where SC is the annual soil conservation capacity (t / km 2 / a; R is the rainfall erosivity coefficient (MJ·mm / hm 2 ·h·a); K is the soil erodibility factor (t·ha·h / ha·MJ·mm); LS refers to topographic factors, including steepness and slope length; C is the surface vegetation cover factor; and P is the soil and water conservation measures factor.

[0130] S3. Assessment of Sustainable Development Goals for Inland River Basins

[0131] According to the indicator availability and representativeness principles, 11 Sustainable Development Goals, including SDG1-No Poverty, SDG2-Zero Hunger, SDG3-Good Health and Well-being, SDG6-Clean Water and Sanitation, SDG7-Clean Energy, SDG9-Industry, Innovation and Infrastructure, SDG11-Sustainable Cities and Communities, SDG13-Climate Action, SDG15-Life on Land, SDG16-Peace, Justice and Strong Institutions, and SDG17-Partnership, were selected to evaluate the Sustainable Development Goals of inland river basins. Figure 3 shown.

[0132] (1) SDG-6 Clean Water and Sanitation

[0133] The calculation method for water resource utilization efficiency is:

[0134] WUE=A we ×P A +M we ×P M +S we ×P S

[0135] Where WUE is water resource utilization efficiency (USD / m 3 ), A we is the agricultural water resource utilization efficiency (USD / m 3 ), M we is the water resource utilization efficiency of the industrial sector (USD / m 3 ), S we Water resource utilization efficiency of the service sector (USD / m 3 ), P A , P M and P S These are the proportions of total water use occupied by agriculture, industry and services respectively.

[0136] The calculation method for water stress is:

[0137]

[0138] Where WS is the water resource utilization efficiency (%), TFWW is the total annual freshwater withdrawal; TRWR is the total available freshwater resources in the region, and EFR is the minimum water resources required to maintain the normal operation of the ecosystem in the region.

[0139] (2) SDG-15 Terrestrial Organisms

[0140] The ratio of forest area to total land area is calculated as follows:

[0141]

[0142] Where FR is the proportion of forest area to the total area of ​​the watershed (%), FA is the forest area in the watershed (km 2 ); TA is the total area of ​​the study area (km 2 ).

[0143] The calculation method of mountain green coverage index is:

[0144]

[0145] Where MGCI is the mountain green coverage index, AC is the cultivated land area in mountainous areas (km 2 ), AF is the forest coverage area in mountainous areas (km 2 ), AG is the grassland coverage area in mountainous areas (km 2 ), TMA (km 2 ) is the total mountainous area.

[0146] (3) Other Sustainable Development Goals based on statistical data

[0147]

[0148] Where SDGV is the value of a sustainable development goal in the Aral Sea Basin, i is the seven countries where the Aral Sea Basin is located, PA i is the population / nighttime light / GDP value of country i in the Aral Sea basin, IV i is the performance of a certain sustainable development goal of country i, and TPA is the total population of the Aral Sea basin / night lights / GDP.

[0149] (4) Standardization of Sustainable Development Goals

[0150]

[0151] In the formula, x is the raw data value of each SDGs indicator, x+ is the score of the positive indicator, x- is the score of the negative indicator, min(x) and max(x) are the values ​​corresponding to the worst and best performance of the raw data of the positive and negative indicators, respectively. ′ It is the standardized score of SDGs indicators.

[0152] S4. Extraction of Ecological-Sustainable Development Links and Identification and Partitioning of Ecological-Sustainable Development Clusters in Inland River Basins

[0153] S41. Extraction of Ecological-Sustainable Development Links

[0154] In order to eliminate the dimensional differences between different ecosystem service functions, the Min-Max normalization method was used to standardize the six ecosystem service functions. The specific formula is:

[0155]

[0156] Where ES is the standardized value of a certain ecosystem service function, ES x is the observed value of the function, ES min(x) and ES max(x) are the maximum and minimum values ​​of this function.

[0157] Rstudio software was used to conduct Pearson correlation analysis on ecosystem service functions and sustainable development goals, characterize the direction and strength of the interaction between ecosystems and sustainable development goals, extract sustainable development goals with strong correlation with ecosystem services, and identify ecological-sustainable development links, such as Figure 4 shown.

[0158] S42. Identification of Ecological-Sustainable Development Clusters

[0159] Based on the extracted ecological-sustainable development links, the self-organizing map neural network model was used in combination with the random forest algorithm to screen key features, and hierarchical cluster analysis was used to reveal the inherent hierarchical structure of the data. The spatial morphology of ecological-sustainable development clusters was identified through cluster analysis. The optimal number of ecological-sustainable development clusters in the Aral Sea basin was identified as 4 categories, such as Figure 5 As shown in Figure 1. Each cluster is named according to its dominant ecological-sustainable development function. The Aral Sea Basin has formed an ecological restoration zone (I), a major grain production zone (II), an energy adjustment zone (III), and an ecological regulation zone (IV). The spatial distribution is shown in Figure 1. Figure 5 shown.

[0160] S5. Identification of the dominant factors in each partition

[0161] In this embodiment, the identification of dominant factors within a partition is performed in the following manner:

[0162] The geographical detector method was used to identify the key driving factors in each ecological-sustainable development cluster, and the factor detection and interaction detection functions were used to calculate the main factors affecting each ecological-sustainable development cluster, such as Figure 6 As shown; and then put forward targeted suggestions and measures, such as Figure 7 As shown. The geographic detector method can be expressed as:

[0163]

[0164] Where h = 1, ..., L is the stratification of variable Y or factor X; N hand N are the number of units in layer h and the whole area respectively, and σ 2 are the variances of the Y values ​​of layer h and the entire region, q∈[0,1].

[0165] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as above in terms of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can, without departing from the scope of the technical solution of the present invention, make some changes or modifications to equivalent embodiments using the technical contents disclosed above. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. The ecological sustainability measurement and analysis method for promoting ecological restoration in inland river basins includes the following steps: S1. Identify and extract inland river basins from topographic and geomorphological data, and build a basic inland river database; S2. Construct ecosystem service data for inland river basins to evaluate ecosystem functions; the ecosystem service data include wind and sand erosion, water yield, habitat quality, food production, carbon storage, and soil conservation data; S3. Construct Sustainable Development Goal data for inland river basins to evaluate sustainable development; the Sustainable Development Goal data include SDG1-No Poverty, SDG2-Zero Hunger, SDG3-Good Health and Well-being, SDG6-Clean Water and Sanitation, SDG7-Clean Energy, SDG9-Industry, Innovation and Infrastructure, SDG11-Sustainable Cities and Communities, SDG13-Climate Action, SDG15-Life on Land, SDG16-Peace, Justice and Strong Institutions, and SDG17-Partnerships; S4. Based on ecosystem service data and sustainable development goal data, identify the ecological-sustainable development nexus of inland river basins, extract ecological-sustainable development zoning clusters of inland river basins, and zoning them; S5. Calculate the key driving factors of ecological and sustainable development in each region based on the ecological zoning data, and propose resource planning measures to achieve ecological and sustainable goals.

2. The ecological sustainability measurement and analysis method for promoting ecological restoration in inland river basins according to claim 1, wherein the basic database includes hydrological data, socioeconomic data, meteorological data, topographic data, land use data, ecological environment data, and remote sensing data; and the basic database is established as follows: S11. Inland River Basin Extraction Based on digital elevation data, the boundaries of inland river basins are extracted after completing depression calculation, flow direction analysis, flow calculation, and slope point capture; S12. Construction of basic database of inland river basins Based on the concept of multi-source heterogeneous data fusion, relying on the geographic spatiotemporal intelligent platform, using data cleaning algorithms and spatial registration technology, we unify the coordinate benchmarks and reconstruct the spatiotemporal attributes of multi-dimensional data, and build a basic spatiotemporal database for inland river basins, providing a full-factor digital foundation for ecological monitoring and sustainable development.

3. The ecological sustainability measurement and analysis method for promoting ecological restoration of inland river basins according to claim 1, wherein the inland river basin ecosystem service assessment in step S2 is performed in the following manner: The amount of wind-blown sand erosion is calculated based on the modified wind-blown sand erosion equation RWEQ; Based on the water balance principle, the Budyko curve and the average annual rainfall are used to calculate the water yield value of the basin and each grid within the basin; In the InVEST model, the habitat quality is calculated by integrating parameters such as habitat suitability of land use types, spatial distribution and attenuation patterns of threat sources, and sensitivity of habitats to threats, and using a spatial superposition algorithm. Based on the statistical data of grain production, the grain productivity was calculated by combining the LRPM grid allocation model and NDVI to represent the value of grain supply services. In the InVEST model, carbon density data from different land use types are integrated to quantitatively assess the carbon storage of ecosystems in carbon pools such as surface vegetation, soil, and dead organic matter. Spatial overlay analysis methods are used to calculate and quantify the distribution pattern of carbon storage in ecosystems. Soil conservation was calculated based on the modified universal soil erosion equation (RUSLE).

4. The ecological sustainability measurement and analysis method for promoting ecological restoration of inland river basins according to claim 1, wherein the assessment of sustainable development goals of inland river basins in step S3 is performed according to the following method: S31. Calculate the proportion of the population living below the national poverty line and the proportion of households with access to basic services from available statistical data, and thus calculate the indicator value for SDG 1 - No Poverty; S32. Use food production data to calculate agricultural production per labor unit to represent the indicator value of SDG2 - Zero Hunger; S33. Use disease incidence and mortality indicators to represent the indicator value of SDG3 - Good Health and Well-being; S34. Use water resource utilization efficiency and water stress to calculate the indicator value of SDG6 - Clean drinking water and sanitation facilities. S35. Calculate the indicator value for SDG7 - Clean Energy using the proportion of the population with access to electricity and the proportion of the population relying on clean fuels and technologies. S36. Use the proportion of the rural population living within two kilometers of a road accessible all year round to represent the indicator value of SDG 9 - Industry, Innovation, and Infrastructure; S37. Use the proportion of the population with convenient access to public transportation to represent the indicator value of SDG-11 Sustainable Cities and Communities. S38. Use annual greenhouse gas emissions to represent the indicator value of SDG-13 climate action; S39. Use the ratio of forest area to total land area and the ratio of mountain green cover index to calculate the indicator value of SDG15 - Life on Land; S310: Use the proportion of victims of intentional homicide to represent the indicator value of S16 - Peace, Justice and Strong Institutions; S311. Use the proportion of the population using the Internet to represent the indicator value of S17-Partnership. S312. Standardize all SDGs and then calculate the total score of all SDGs.

5. The ecological sustainability measurement and analysis method for promoting ecological restoration in inland river basins according to claim 1 is characterized by: Step S4 is performed as follows: S41. Extraction of Ecological-Sustainable Development Links The Min-Max normalization method was used to standardize the six ecosystem service functions, and Rstudio software was used to conduct Pearson correlation analysis between ecosystem service functions and sustainable development goals to characterize the direction and intensity of the interaction between ecosystems and sustainable development goals, extract sustainable development goals with a strong correlation with ecosystem services, and identify the ecological-sustainable development link. S42. Identification of Eco-Sustainable Development Clusters Based on the extracted ecological-sustainable development links, the self-organizing map neural network model was used in combination with the random forest algorithm to screen key features, and hierarchical cluster analysis was applied to reveal the inherent hierarchical structure of the data. The spatial morphology of ecological-sustainable development clusters was identified through cluster analysis.

6. The ecological sustainability measurement and analysis method for promoting ecological restoration in inland river basins according to claim 1 is characterized by: The step S5 is performed as follows: The geographic detector method is used to identify the key driving factors within each ecological-sustainable development cluster, and the factor detection and interaction detection functions are used to calculate the main factors affecting each ecological-sustainable development cluster, and then targeted recommended measures are proposed.

7. The ecological sustainability measurement and analysis method for promoting ecological restoration in inland river basins according to claim 3, wherein the wind and sand erosion is calculated according to the following method: Where S L is the actual amount of wind and sand erosion (t / km 2 / a), that is, the amount of soil lost per unit area due to wind in a certain period of time; z is the distance from the upper end of the wind field to the ground surface (m); Qmax is the maximum transport capacity (kg / m); s is the critical field length (m).

8. The ecological sustainability measurement and analysis method for promoting ecological restoration of inland river basins according to claim 3, wherein the water yield is calculated according to the following method: Where Y(X) represents the water yield on grid x, Px represents the annual rainfall on grid x, and AET(X) represents the actual evapotranspiration on grid x.

9. In the ecological sustainability measurement and analysis method for promoting ecological restoration in inland river basins as claimed in claim 3, the habitat quality is calculated according to the following method: Where Q xj is the habitat quality index of grid x in land use type j; H j is the habitat suitability of land use type j; D xj is the degree of habitat degradation of grid x in land use type j; z is the normalization constant; k is the half-saturation constant.

10. The ecological sustainability measurement and analysis method for promoting ecological restoration of inland river basins according to claim 3, wherein the grain yield is calculated according to the following method: Where S GP is the estimated grain production, GP sum is the total grain production statistics within the study area, NDVI i is the NDVI value of the cultivated land pixel in the grid, NDVI sum It is the sum of the NDVI of all cultivated land pixels at the corresponding scale.

11. The ecological sustainability measurement and analysis method for promoting ecological restoration in inland river basins according to claim 3, wherein the carbon storage is calculated according to the following method: Where i is different types of land use, C sum is the total carbon storage in the study area (t / hm 2 ), C i-above is the aboveground carbon storage (t / hm 2 ), C i-below is the underground carbon storage (t / hm 2 ), C i-soil is soil carbon storage (t / hm 2 ), C i-dead is the dead organic carbon stock (t / hm 2 ), the larger the calculated value, the higher the carbon storage.

12. The ecological sustainability measurement and analysis method for promoting ecological restoration in inland river basins according to claim 3, wherein the carbon storage is calculated according to the following method: SC=R×K×LS×(1-C×P) Where SC is the annual soil conservation capacity (t / km 2 / a; R is the rainfall erosivity coefficient (MJ·mm / hm 2 ·h·a); K is the soil erodibility factor (t·ha·h / ha·MJ·mm); LS refers to topographic factors, including steepness and slope length; C is the surface vegetation cover factor; and P is the soil and water conservation measures factor.

13. The ecological sustainability measurement and analysis method for promoting ecological restoration in inland river basins according to claim 4, wherein the SDG-6 clean drinking water and sanitation facilities are calculated according to the following method: The calculation method for water resource utilization efficiency is: WUE=A we ×P A +M we ×P M +S we ×P S Where WUE is water resource utilization efficiency (USD / m 3 ), A we is the agricultural water resource utilization efficiency (USD / m 3 ), M we is the water resource utilization efficiency of the industrial sector (USD / m 3 ), S we Water resource utilization efficiency of the service sector (USD / m 3 ), P A , P M and P S These are the proportions of total water use occupied by agriculture, industry and services respectively. The calculation method for water stress is: Where WS is the water resource utilization efficiency (%), TFWW is the total annual freshwater withdrawal; TRWR is the total available freshwater resources in the region, and EFR is the minimum water resources required to maintain the normal operation of the ecosystem in the region.

14. The ecological sustainability measurement and analysis method for promoting ecological restoration in inland river basins according to claim 4, wherein the SDG-15 terrestrial organisms are calculated according to the following method: The ratio of forest area to total land area is calculated as follows: Where FR is the proportion of forest area to the total area of ​​the watershed (%), FA is the forest area in the watershed (km 2 ); TA is the total area of ​​the study area (km 2 ). The calculation method of mountain green coverage index is: Where MGCI is the mountain green coverage index, AC is the cultivated land area in mountainous areas (km 2 ), AF is the forest coverage area in mountainous areas (km 2 ), AG is the grassland coverage area in mountainous areas (km 2 ), TMA (km 2 ) is the total mountainous area.

15. The ecological sustainability measurement and analysis method for promoting ecological restoration of inland river basins as claimed in claim 4, and the calculation of other sustainable development goals based on statistical data (SDG1, SDG2, SDG3, SDG7, SDG9, SDG11, SDG13, SDG16 and SDG17): Where SDGV is the value of a sustainable development goal in the Aral Sea Basin, i is the seven countries where the Aral Sea Basin is located, PA i is the population / nighttime light / GDP value of country i in the Aral Sea basin, IV i is the performance of a certain sustainable development goal of country i, and TPA is the total population of the Aral Sea basin / night lights / GDP.

16. The ecological sustainability measurement and analysis method for promoting ecological restoration in inland river basins as claimed in claim 4, wherein the standardized processing method for all sustainable development goals is: Where x is the raw data value of each SDGs indicator, x + is the score of the positive indicator, x - is the score of the negative indicator, min(x) and max(x) are the values ​​corresponding to the worst and best performance of the original data in the positive and negative indicators, respectively.

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