Basin ecological restoration measure configuration optimization method based on multi-target cooperation

Abstract

The invention discloses a multi-target cooperation-based drainage basin ecological restoration measure configuration optimization method. The method comprises the following steps: respectively calculating water storage benefits, ecological restoration measure corrosion reduction benefits and drainage basin different ecological restoration measure pollution reduction benefits of different drainage basin ecological restoration measures according to basic data; then constructing a multi-objective function and constraint conditions thereof; and solving and optimizing the multi-target constraint condition by using an NSGA-II optimization algorithm to obtain a Pareto leading edge of an optimized solution. According to the optimization method, the calculation stability of a mature optimization algorithm is reserved, the simulation efficiency and the result precision are remarkably improved, and the problems of large simulation deviation and low convergence speed in a traditional method can be effectively solved through verification of actual drainage basin data; meanwhile, the water storage capacity, the corrosion reduction capacity and the non-point source pollution reduction capacity serve as core optimization targets, the synergistic effect of different remediation measures can be accurately quantified, scientific optimization of the measure configuration mode is achieved, and high-precision numerical model support is provided for formulating a watershed ecological remediation scheme.

Description

Technical Field

[0001] This invention belongs to the field of watershed ecological restoration technology, and relates to a method for optimizing the configuration of watershed ecological restoration measures based on multi-objective collaboration. Background Technology

[0002] The Qinling-Bashan Mountains are the dividing line between northern and southern climates in my country and an important water source conservation area for the Yangtze and Yellow River basins. Known as the "Central Water Tower" and "Biological Gene Bank," they are a core area for maintaining national ecological security. In recent years, affected by agricultural expansion, mining development, and urbanization, the region's watershed ecology has suffered significant degradation: its terrain is predominantly mountainous and hilly, with a high proportion of steep slopes between 10° and 30°. Unreasonable land use, such as reclamation on steep slopes, has exacerbated soil erosion; agricultural non-point source pollution combined with domestic sewage has resulted in substantial nitrogen and phosphorus loss from the watershed, threatening downstream water quality; and inadequate ecological restoration measures have further weakened the watershed's water storage and flood control capacity, making it prone to flash floods during the rainy season, severely hindering regional ecological security and rural revitalization.

[0003] In current ecological restoration practices in the Qinba Mountains watershed, although measures such as afforestation, shrub planting, grassland restoration, and terrace construction have been applied, existing configuration schemes have obvious limitations: First, they rely heavily on traditional experience or single-objective orientation. For example, based solely on the SCS model to calculate water storage benefits, large-scale afforestation is planted in gentle slope areas, or terraces are blindly constructed in steep slope areas based on the RUSLE model to assess erosion reduction effects, neglecting the synergistic effect of multiple objectives such as "water storage-erosion reduction-pollution reduction." Second, existing multi-objective optimization methods often use weighted summation to transform single-objective solutions, which easily leads to the loss of key optimal solutions. Furthermore, they do not incorporate constraints based on the slope differentiation characteristics of the Qinba Mountains, resulting in poor adaptability of measures to the terrain. For instance, planting grassland in areas with a slope greater than 25° not only has limited erosion reduction effects but also easily triggers secondary ecological problems.

[0004] Furthermore, existing technologies are not sufficiently applicable to the Qinba Mountains: most schemes fail to optimize model parameters such as SCS, RUSLE, and SWAT, taking into account the region's concentrated rainfall (annual average rainfall of 750-1100 mm, with frequent rainstorms) and complex soil types (significant differences in sand and clay content), resulting in low accuracy in benefit assessments. Moreover, the optimization algorithms mostly employ traditional genetic algorithms, which suffer from slow convergence and uneven distribution of Pareto front solutions, failing to provide diverse optimal configuration schemes for the Qinba Mountains watershed. In summary, current ecological restoration measures in the Qinba Mountains watershed lack regional specificity and multi-objective collaborative mechanisms, urgently requiring a scientific optimization method adapted to regional characteristics. Summary of the Invention

[0005] The purpose of this invention is to provide a method for optimizing the configuration of watershed ecological restoration measures based on multi-objective collaboration, which solves the problems of lack of regional specificity and multi-objective collaboration in the configuration of watershed ecological restoration measures in the prior art.

[0006] The technical solution adopted in this invention is a method for optimizing the configuration of watershed ecological restoration measures based on multi-objective synergy, which specifically includes the following steps: Step 1: Collect and organize basic data for the study area; Step 2: Calculate the water storage benefits, erosion reduction benefits, and pollution reduction benefits of different ecological restoration measures in the watershed based on the basic data. Step 3: Construct a multi-objective function and its constraints for the watershed's water storage benefits, erosion reduction benefits, and pollution reduction benefits; Step 4: Use the NSGA-II optimization algorithm to solve the multi-objective constraints and obtain the Pareto front of the optimized solution.

[0007] The invention is further characterized by: The water storage benefits of the ecological restoration measures in step 2 are calculated using the SCS equation in the SWAT model. The equation for the water storage benefits of the ecological restoration measures is as follows: (1), In formula (1), The water storage benefits of ecological restoration measures are expressed in meters (m). 3 / yr; Watershed runoff depth in mm when land use is in the absence of ecological restoration measures; For ecological restoration measures; Watershed runoff depth in mm when the land use is sloping farmland; The area for soil and water conservation is expressed in m². 2 .

[0008] The calculation process for the water storage benefit equation of ecological restoration measures is as follows: (2), In formula (2), Potential infiltration rate, in mm; Rainfall amount, in mm; (3), In formula (3), This represents the number of runoff curves.

[0009] In step 2, the erosion reduction benefits of ecological restoration measures were calculated using the RUSLE model. The erosion reduction equation for ecological restoration measures is as follows: (4), Formula (4), To reduce erosion through ecological restoration measures, This represents the amount of soil erosion without ecological restoration measures. The data represents soil erosion with ecological restoration measures, all expressed in t / yr.

[0010] The calculation process for the erosion reduction of ecological restoration measures is as follows: (5), (6), In formulas (5) and (6), Soil erosion without ecological restoration measures, expressed in t / yr; The erosivity factor is the rainfall erosivity factor, expressed in MJ•mm / (ha•h•yr). Slope length factor; Slope factor; It represents the soil erodibility factor, with units of t•h / (MJ•mm). As engineering measure factors, As biological action factors, For cultivation measures factors; (7), In formula (7), Annual rainfall, in mm; (8), In formula (8), The slope length is in meters (m). The slope length index, (9); (10) In formulas (9) and (10), Slope, in degrees; (11), In formula (11), (12) In formula (12), This represents the sand content, expressed as % . Particle content, in percentage (%) Clay content, in percentages (%) Soil organic carbon content, in percentages.

[0011] In step 2, the pollution reduction benefits of different ecological restoration measures in the watershed are calculated using a SWAT model. The pollution reduction equation for the ecological restoration measures is as follows: (13) In formula (13), The pollution reduction benefits of ecological restoration measures are expressed in kg / yr. This refers to the bulk density of sediment, expressed in kg / m³. 3 ; Total nitrogen content in runoff, mg / L; Total phosphorus content in runoff, mg / L; Total nitrogen content in sediment, mg / kg; The total phosphorus content in the sediment is expressed in mg / kg.

[0012] The specific calculation method for the pollution reduction equation of ecological restoration measures is as follows: The surface water flow process is represented by a two-dimensional diffusion wave equation, neglecting inertial forces, and the expression is: (14) In formula (14), Surface velocity, in m / s; For source and sink items; Soil moisture infiltration, in meters (m³) 3 ; The average height of the surface micro-topography, in meters; The water saturation level is expressed as % (%). The depth of flowing water on the Earth's surface, expressed in meters (m). Surface water saturation, in percentages.

[0013] The sediment transport process is represented by the motion equation of sediment along the depth integral, which is expressed in the model as follows: (15) In formula (15), Volumetric sediment concentration, unit: m³ 3 / m 3 ; The total number of boundaries; The runoff velocity flowing into the system at the boundary location is expressed in m / s. For corresponding Volumetric sediment concentration, in m³ 3 / m 3 ; The volume of water is expressed in cubic meters (m³). 3 ; Soil erosion or deposition rate, in meters (m). 3 / s.

[0014] The multi-objective function in step 3 is: (16).

[0015] The constraints in step 3 are: (17) In formula (17), , , , These represent the areas of woodland, shrubland, grassland, and terraced fields, respectively, in ha. The area of ​​the catchment with a slope of less than 25° is expressed in ha. The area of ​​the catchment with a slope of 25°~30° is expressed in ha. The area of ​​a watershed with a slope of 10° to 25° is expressed in ha. The watershed area is expressed in ha.

[0016] The specific steps of step 4 are as follows: Step 4-1: Obtain the area of ​​each type of ecological restoration measure as a constraint. Step 4-2: Construct the optimization solution space based on the preset multiple objectives and constraints; The preset multiple objectives are to maximize water storage benefits, maximize corrosion reduction benefits, and maximize pollution reduction benefits; Step 4-3: Use the multi-objective optimization algorithm NSGA-II to perform iterative search to obtain the Pareto optimal solution set.

[0017] The beneficial effects of this invention are: The multi-objective collaborative watershed ecological restoration measure configuration optimization method of this invention, through targeted algorithm optimization, retains the computational stability of mature optimization algorithms while significantly improving simulation efficiency and result accuracy. Validated by actual watershed data, it effectively avoids the problems of large simulation deviations and slow convergence speeds in traditional methods. Furthermore, this method, with water storage capacity, erosion reduction capacity, and non-point source pollution reduction capacity as core optimization objectives, can accurately quantify the synergistic effects of different restoration measures, achieving scientific optimization of measure configuration. It provides high-precision numerical model support for the formulation of watershed ecological restoration schemes, contributing to the systematic improvement of watershed ecosystem functions, and possesses both theoretical innovation and engineering practicality. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the optimization method of the present invention; Figure 2 This is a flowchart illustrating the process of solving and optimizing multi-objective constraints using the NSGA-II optimization algorithm in this invention. Figure 3 This is the watershed elevation map in Embodiment 1 of the present invention; Figure 4 This is a slope distribution diagram from Embodiment 1 of the present invention; Figure 5 This is the optimized solution calculated in Example 1 of the present invention. Detailed Implementation

[0019] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0020] This invention provides a method for optimizing the configuration of watershed ecological restoration measures based on multi-objective collaboration, applicable to the ecological restoration of watersheds in the Qinling-Bashan Mountains. The method is implemented according to the following steps: Step 1: Collect and organize basic data for the study area; The basic data includes topography, hydrology and meteorology, water quality, and soil texture data.

[0021] Step 2: Calculate the water storage benefits, erosion reduction benefits, and pollution reduction benefits of different ecological restoration measures in the watershed based on the basic data.

[0022] The water storage benefits of different ecological restoration measures in the watershed were calculated using the SCS equation in the SWAT model: Watershed runoff depth when land use is without ecological restoration measures As shown in formula (2), the unit is mm. (2), In formula (2), Potential infiltration rate, in mm; Rainfall amount, in mm; (3), In formula (3), Number of runoff curves; From formulas (2) and (3), the water storage benefit equation of the ecological restoration measures is: (1), In formula (1), The water storage benefits of ecological restoration measures are expressed in meters (m). 3 / yr; For ecological restoration measures; Watershed runoff depth in mm when the land use is sloping farmland; The area for soil and water conservation is expressed in m². 2 .

[0023] The erosion reduction benefits of ecological restoration measures were calculated using the RUSLE model. The specific calculation process is as follows: The Rusle equation is: (5), In formula (5), Soil erosion without ecological restoration measures, expressed in t / yr; The erosivity factor is the rainfall erosivity factor, expressed in MJ•mm / (ha•h•yr). Slope length factor; Slope factor; It represents the soil erodibility factor, with units of t•h / (MJ•mm). (6), In formula (6), Soil erosion with ecological restoration measures, all in t / yr; As engineering measure factors, As biological action factors, Factors related to farming practices.

[0024] In formulas (5) and (6) They are respectively: (7), In formula (7), Annual rainfall, in mm; (8), In formula (8), The slope length is in meters (m). The slope length index, (9); (10) In formulas (9) and (10), Slope, in degrees; (11), In formula (11), (12) In formula (12), This represents the sand content, expressed as % . Particle content, in percentage (%) Clay content, in percentages (%) Soil organic carbon content, in percentages.

[0025] Therefore, the erosion reduction equation for ecological restoration measures is: (4), The pollution reduction benefits of different ecological restoration measures in the watershed were calculated using a SWAT model. The specific calculation method is as follows: The surface water flow process is represented by a two-dimensional diffusion wave equation, neglecting inertial forces, and the expression is: (14) In formula (14), Surface velocity, in m / s; For source and sink items; Soil moisture infiltration, in meters (m³) 3 ; The average height of the surface micro-topography, in meters; The water saturation level is expressed as % (%). The depth of flowing water on the Earth's surface, expressed in meters (m). Surface water saturation, in percentages.

[0026] The sediment transport process is represented by the motion equation of sediment along the depth integral, which is expressed in the model as follows: (15) In formula (15), Volumetric sediment concentration, unit: m³ 3 / m 3 ; The total number of boundaries; The runoff velocity flowing into the system at the boundary location is expressed in m / s. For corresponding Volumetric sediment concentration, in m³ 3 / m 3 ; The volume of water is expressed in cubic meters (m³). 3 ; Soil erosion or deposition rate, in meters (m). 3 / s.

[0027] Combining formulas (14) and (15), the pollution reduction equation for ecological restoration measures is obtained as follows: (13) In formula (13), The pollution reduction benefits of ecological restoration measures are expressed in kg / yr. This refers to the bulk density of sediment, expressed in kg / m³. 3 ; Total nitrogen content in runoff, mg / L; Total phosphorus content in runoff, mg / L; Total nitrogen content in sediment, mg / kg; The total phosphorus content in the sediment is expressed in mg / kg.

[0028] Step 3: Construct a multi-objective function and its constraints for the watershed's water storage benefits, erosion reduction benefits, and pollution reduction benefits.

[0029] Based on formulas (1), (4), and (13), the multi-objective function is obtained as follows: (16) Its constraints are: (17) In formula (17), , , , These represent the areas of woodland, shrubland, grassland, and terraced fields, respectively, in ha. The area of ​​the catchment with a slope of less than 25° is expressed in ha. The area of ​​the catchment with a slope of 25°~30° is expressed in ha. The area of ​​a watershed with a slope of 10° to 25° is expressed in ha. The watershed area is expressed in ha.

[0030] Step 4: Use the NSGA-II optimization algorithm to solve the multi-objective constraints and obtain the Pareto front of the optimized solution.

[0031] The specific steps are as follows: Step 4-1: Obtain the area of ​​each type of ecological restoration measure as a constraint. Step 4-2: Construct the optimization solution space based on the preset multiple objectives and constraints; The preset multiple objectives are to maximize water storage benefits, maximize corrosion reduction benefits, and maximize pollution reduction benefits; like Figure 2 As shown, 200 4-dimensional vector individuals are first randomly generated based on the upper and lower bounds of the variables, and then the three objective function values ​​and constraint violation values ​​of each individual are calculated.

[0032] Step 4-3: Use the multi-objective optimization algorithm NSGA-II to perform iterative search to obtain the Pareto optimal solution set; Based on the multi-objective optimization algorithm NSGA-II, individuals in the population are stratified according to Pareto dominance. The first layer is the Pareto front, the second layer is the front after removing the first layer, and so on. Within the same non-dominated layer, the crowding degree (the sum of distances between adjacent points) of each individual in the objective space is calculated to measure the diversity of solutions. First, the parent generation is selected using the comparison rules of a binary tournament; that is, the non-dominated layer is compared first, and the one with the smaller layer number wins; within the same layer, the crowding degree is compared, and the one with the larger crowding degree wins; then, the selected parent generation is subjected to crossover and mutation operations to generate offspring; the parent generation and offspring generation are merged to form a new population (size 400), and non-dominated sorting and crowding degree calculation are performed to select the top 200 individuals as the next generation population; finally, the non-dominated solution (first layer) in the population is the approximate Pareto optimal solution set.

[0033] Multi-objective optimization algorithms can not only weigh different objectives to form a Pareto optimal solution set, but also effectively explore the diversity and adaptability of ecological restoration measures, thereby avoiding the one-sided optimization problem caused by the single objective orientation in traditional schemes.

[0034] Example 1 This embodiment uses a multi-objective collaborative watershed ecological restoration measure configuration optimization method, applied to the Shijiahe small watershed located in Hanbin District, Ankang City, Shaanxi Province, at longitudes 108°40′7″~108°42′47″E and latitudes 32°40′48″~32°42′20″N. The annual rainfall is 750mm-1100mm, and the average annual temperature is 12℃~15℃. The watershed area is 7.35km². 2 ,like Figure 3 As shown, the elevation ranges from 659 to 1311 meters.

[0035] The specific steps are as follows: Step 1: Collect and organize basic data for the study area; basic data includes topography, hydrology and meteorology, water quality, and soil texture data.

[0036] Step 2: Calculate the water storage benefits, erosion reduction benefits, and pollution reduction benefits of different ecological restoration measures in the watershed based on the basic data. Hydrological and meteorological data of the study area were collected, and a water storage benefit equation for ecological restoration measures in the watershed was constructed. Based on the DEM elevation of the study area, slope was calculated using ArcGIS software, and the area of ​​different slope units in the watershed was divided, such as... Figure 4 As shown; by combining hydrological, meteorological, and soil texture data, an equation for the erosion reduction benefits of watershed ecological restoration measures is constructed. Based on land use type and water quality data of the study area, the pollution reduction benefit equations of different ecological restoration measures in the watershed were constructed using the SWAT model.

[0037] Step 3: Construct a multi-objective function and its constraints for the watershed's water storage benefits, erosion reduction benefits, and pollution reduction benefits; By solving the equations for water storage, erosion reduction, and pollution reduction simultaneously, and using slope as a constraint, the area is obtained as a condition. The objective is to maximize the water storage benefit, erosion reduction benefit, and pollution reduction benefit of the watershed.

[0038] Step 4: Use the NSGA-II optimization algorithm to calculate the multi-objective constraints by inputting relevant code in Python, and finally output the Pareto front of the optimized solution; the objective equation is optimized and solved using the NSGA-II optimization algorithm, resulting in 74 ecological restoration measure configuration patterns, such as... Figure 5 As shown.

[0039] The model with the largest water storage capacity, erosion reduction, and pollution reduction was selected, as shown in Table 1. The maximum water storage capacity of the basin was 962,849.45 m³. 3 At this point, the watershed's erosion reduction was 1181.71 t / yr, pollution reduction was 4.49 t / yr, forest area was 1.02 ha, shrubland 447.86 ha, grassland 0.16 ha, and terraced fields 303.75 ha, with shrubland accounting for the largest proportion. The highest erosion reduction was 1413.81 t / yr, the highest pollution reduction was 4.98 t / yr, and the water storage capacity was 912156.68 m³. 3 The area of ​​forest land is 294.61 ha, shrubland is 456.64 ha, grassland is 0.86 ha, and terraced fields is 0.51 ha, with shrubland accounting for the largest proportion.

[0040] Table 1

[0041] Example 2 The watershed ecological restoration measure configuration optimization method based on multi-objective collaboration in this embodiment is implemented according to the following steps: Step 1: Collect and organize basic data for the study area.

[0042] Step 2: Calculate the water storage benefits, erosion reduction benefits, and pollution reduction benefits of different ecological restoration measures in the watershed based on the basic data.

[0043] The water storage benefits of ecological restoration measures are calculated using the SCS equation in the SWAT model. The equation for the water storage benefits of ecological restoration measures is as follows: (1), In formula (1), The water storage benefits of ecological restoration measures are expressed in meters (m). 3 / yr; Watershed runoff depth in mm when land use is in the absence of ecological restoration measures; For ecological restoration measures; Watershed runoff depth in mm when the land use is sloping farmland; The area for soil and water conservation is expressed in m². 2 ; The calculation process for the water storage benefit equation of ecological restoration measures is as follows: (2), In formula (2), Potential infiltration rate, in mm; Rainfall amount, in mm; (3), In formula (3), This represents the number of runoff curves.

[0044] Step 3: Construct a multi-objective function and its constraints for the watershed's water storage benefits, erosion reduction benefits, and pollution reduction benefits.

[0045] Step 4: Use the NSGA-II optimization algorithm to solve the multi-objective constraints and obtain the Pareto front of the optimized solution.

[0046] Example 3 The watershed ecological restoration measure configuration optimization method based on multi-objective collaboration in this embodiment is implemented according to the following steps: Step 1: Collect and organize basic data for the study area.

[0047] Step 2: Calculate the water storage benefits, erosion reduction benefits, and pollution reduction benefits of different ecological restoration measures in the watershed based on the basic data.

[0048] The water storage benefits of ecological restoration measures are calculated using the SCS equation in the SWAT model. The equation for the water storage benefits of ecological restoration measures is as follows: (1), In formula (1), The water storage benefits of ecological restoration measures are expressed in meters (m). 3 / yr; Watershed runoff depth in mm when land use is in the absence of ecological restoration measures; For ecological restoration measures; Watershed runoff depth in mm when the land use is sloping farmland; The area for soil and water conservation is expressed in m². 2 ; The calculation process for the water storage benefit equation of ecological restoration measures is as follows: (2), In formula (2), Potential infiltration rate, in mm; Rainfall amount, in mm; (3), In formula (3), This represents the number of runoff curves.

[0049] The erosion reduction benefits of ecological restoration measures were calculated using the RUSLE model. The erosion reduction equation for ecological restoration measures is as follows: (4), Formula (4), To reduce erosion through ecological restoration measures, This represents the amount of soil erosion without ecological restoration measures. The data represents soil erosion with ecological restoration measures implemented, all expressed in t / yr. The calculation process for the erosion reduction of ecological restoration measures is as follows: (5), (6), In formulas (5) and (6), Soil erosion without ecological restoration measures, expressed in t / yr; The erosivity factor is the rainfall erosivity factor, expressed in MJ•mm / (ha•h•yr). Slope length factor; Slope factor; It represents the soil erodibility factor, with units of t•h / (MJ•mm). As engineering measure factors, As biological action factors, For cultivation measures factors; (7), In formula (7), Annual rainfall, in mm; (8), In formula (8), The slope length is in meters (m). The slope length index, (9); (10) In formulas (9) and (10), Slope, in degrees; (11), In formula (11), (12) In formula (12), This represents the sand content, expressed as % . Particle content, in percentage (%) Clay content, in percentages (%) Soil organic carbon content, in percentage.

[0050] Step 3: Construct a multi-objective function and its constraints for the watershed's water storage benefits, erosion reduction benefits, and pollution reduction benefits.

[0051] Step 4: Use the NSGA-II optimization algorithm to solve the multi-objective constraints and obtain the Pareto front of the optimized solution.

[0052] Example 4 The watershed ecological restoration measure configuration optimization method based on multi-objective collaboration in this embodiment is implemented according to the following steps: Step 1: Collect and organize basic data for the study area.

[0053] Step 2: Calculate the water storage benefits, erosion reduction benefits, and pollution reduction benefits of different ecological restoration measures in the watershed based on the basic data.

[0054] The water storage benefits of ecological restoration measures are calculated using the SCS equation in the SWAT model. The equation for the water storage benefits of ecological restoration measures is as follows: (1), In formula (1), The water storage benefits of ecological restoration measures are expressed in meters (m). 3 / yr; Watershed runoff depth in mm when land use is in the absence of ecological restoration measures; For ecological restoration measures; Watershed runoff depth in mm when the land use is sloping farmland; The area for soil and water conservation is expressed in m². 2 ; The calculation process for the water storage benefit equation of ecological restoration measures is as follows: (2), In formula (2), Potential infiltration rate, in mm; Rainfall amount, in mm; (3), In formula (3), This represents the number of runoff curves.

[0055] The erosion reduction benefits of ecological restoration measures were calculated using the RUSLE model. The erosion reduction equation for ecological restoration measures is as follows: (4), Formula (4), To reduce erosion through ecological restoration measures, This represents the amount of soil erosion without ecological restoration measures. The data represents soil erosion with ecological restoration measures implemented, all expressed in t / yr. The calculation process for the erosion reduction of ecological restoration measures is as follows: (5), (6), In formulas (5) and (6), Soil erosion without ecological restoration measures, expressed in t / yr; The erosivity factor is the rainfall erosivity factor, expressed in MJ•mm / (ha•h•yr). Slope length factor; Slope factor; It represents the soil erodibility factor, with units of t•h / (MJ•mm). As engineering measure factors, As biological action factors, For cultivation measures factors; (7), In formula (7), Annual rainfall, in mm; (8), In formula (8), The slope length is in meters (m). The slope length index, (9); (10) In formulas (9) and (10), Slope, in degrees; (11), In formula (11), (12) In formula (12), This represents the sand content, expressed as % . Particle content, in percentage (%) Clay content, in percentages (%) Soil organic carbon content, in percentage.

[0056] The pollution reduction benefits of different ecological restoration measures in the watershed were calculated using a SWAT model. The pollution reduction equation for the ecological restoration measures is as follows: (13) In formula (13), The pollution reduction benefits of ecological restoration measures are expressed in kg / yr. This refers to the bulk density of sediment, expressed in kg / m³. 3 ; Total nitrogen content in runoff, mg / L; Total phosphorus content in runoff, mg / L; Total nitrogen content in sediment, mg / kg; The total phosphorus content in the sediment is expressed in mg / kg.

[0057] The specific calculation method for the pollution reduction equation of ecological restoration measures is as follows: The surface water flow process is represented by a two-dimensional diffusion wave equation, neglecting inertial forces, and the expression is: (14) In formula (14), Surface velocity, in m / s; For source and sink items; Soil moisture infiltration, in meters (m³) 3 ; The average height of the surface micro-topography, in meters; The water saturation level is expressed as % (%). The depth of flowing water on the Earth's surface, expressed in meters (m). Surface water saturation, in percentages.

[0058] The sediment transport process is represented by the motion equation of sediment along the depth integral, which is expressed in the model as follows: (15) In formula (15), Volumetric sediment concentration, unit: m³ 3 / m 3 ; The total number of boundaries; The runoff velocity flowing into the system at the boundary location is expressed in m / s. For corresponding Volumetric sediment concentration, in m³ 3 / m 3 ; The volume of water is expressed in cubic meters (m³). 3 ; Soil erosion or deposition rate, in meters (m). 3 / s.

[0059] Step 3: Construct a multi-objective function and its constraints for the watershed's water storage benefits, erosion reduction benefits, and pollution reduction benefits.

[0060] Step 4: Use the NSGA-II optimization algorithm to solve the multi-objective constraints and obtain the Pareto front of the optimized solution.

[0061] Example 5 The watershed ecological restoration measure configuration optimization method based on multi-objective collaboration in this embodiment is implemented according to the following steps: Step 1: Collect and organize basic data for the study area.

[0062] Step 2: Calculate the water storage benefits, erosion reduction benefits, and pollution reduction benefits of different ecological restoration measures in the watershed based on the basic data.

[0063] The water storage benefits of ecological restoration measures are calculated using the SCS equation in the SWAT model. The equation for the water storage benefits of ecological restoration measures is as follows: (1), In formula (1), The water storage benefits of ecological restoration measures are expressed in meters (m). 3 / yr; Watershed runoff depth in mm when land use is in the absence of ecological restoration measures; For ecological restoration measures; Watershed runoff depth in mm when the land use is sloping farmland; The area for soil and water conservation is expressed in m². 2 ; The erosion reduction benefits of ecological restoration measures were calculated using the RUSLE model. The erosion reduction equation for ecological restoration measures is as follows: (4), Formula (4), To reduce erosion through ecological restoration measures, This represents the amount of soil erosion without ecological restoration measures. Soil erosion with ecological restoration measures, all in t / yr; The pollution reduction benefits of different ecological restoration measures in the watershed were calculated using a SWAT model. The pollution reduction equation for the ecological restoration measures is as follows: (13) In formula (13), The pollution reduction benefits of ecological restoration measures are expressed in kg / yr. This refers to the bulk density of sediment, expressed in kg / m³. 3 ; Total nitrogen content in runoff, mg / L; Total phosphorus content in runoff, mg / L; Total nitrogen content in sediment, mg / kg; The total phosphorus content in the sediment is expressed in mg / kg.

[0064] Step 3: Construct a multi-objective function and its constraints for the watershed's water storage benefits, erosion reduction benefits, and pollution reduction benefits.

[0065] The multi-objective function is: (16) The constraints are: (17) In formula (17), , , , These represent the areas of woodland, shrubland, grassland, and terraced fields, respectively, in ha. The area of ​​the catchment with a slope of less than 25° is expressed in ha. The area of ​​the catchment with a slope of 25°~30° is expressed in ha. The area of ​​a watershed with a slope of 10° to 25° is expressed in ha. The watershed area is expressed in ha.

[0066] Step 4: Use the NSGA-II optimization algorithm to solve the multi-objective constraints and obtain the Pareto front of the optimized solution.

[0067] Example 6 The watershed ecological restoration measure configuration optimization method based on multi-objective collaboration in this embodiment is implemented according to the following steps: Step 1: Collect and organize basic data for the study area.

[0068] Step 2: Calculate the water storage benefits, erosion reduction benefits, and pollution reduction benefits of different ecological restoration measures in the watershed based on the basic data.

[0069] The water storage benefits of ecological restoration measures are calculated using the SCS equation in the SWAT model. The equation for the water storage benefits of ecological restoration measures is as follows: (1), In formula (1), The water storage benefits of ecological restoration measures are expressed in meters (m). 3 / yr; Watershed runoff depth in mm when land use is in the absence of ecological restoration measures; For ecological restoration measures; Watershed runoff depth in mm when the land use is sloping farmland; The area for soil and water conservation is expressed in m². 2 ; The erosion reduction benefits of ecological restoration measures were calculated using the RUSLE model. The erosion reduction equation for ecological restoration measures is as follows: (4), Formula (4), To reduce erosion through ecological restoration measures, This represents the amount of soil erosion without ecological restoration measures. Soil erosion with ecological restoration measures, all in t / yr; The pollution reduction benefits of different ecological restoration measures in the watershed were calculated using a SWAT model. The pollution reduction equation for the ecological restoration measures is as follows: (13) In formula (13), The pollution reduction benefits of ecological restoration measures are expressed in kg / yr. This refers to the bulk density of sediment, expressed in kg / m³. 3 ; Total nitrogen content in runoff, mg / L; Total phosphorus content in runoff, mg / L; Total nitrogen content in sediment, mg / kg; The total phosphorus content in the sediment is expressed in mg / kg.

[0070] Step 3: Construct a multi-objective function and its constraints for the watershed's water storage benefits, erosion reduction benefits, and pollution reduction benefits.

[0071] The multi-objective function is: (16) The constraints are: (17) In formula (17), , , , These represent the areas of woodland, shrubland, grassland, and terraced fields, respectively, in ha. The area of ​​the catchment with a slope of less than 25° is expressed in ha. The area of ​​the catchment with a slope of 25°~30° is expressed in ha. The area of ​​a watershed with a slope of 10° to 25° is expressed in ha. The watershed area is expressed in ha.

[0072] Step 4: Use the NSGA-II optimization algorithm to solve the multi-objective constraints and obtain the Pareto front of the optimized solution.

[0073] The specific steps are as follows: Step 4-1: Obtain the area of ​​each type of ecological restoration measure as a constraint. Step 4-2: Construct the optimization solution space based on the preset multiple objectives and constraints; The preset multiple objectives are to maximize water storage benefits, maximize corrosion reduction benefits, and maximize pollution reduction benefits; Step 4-3: Use the multi-objective optimization algorithm NSGA-II to perform iterative search to obtain the Pareto optimal solution set.

Claims

1. A method for optimizing allocation of ecological restoration measures in a river basin based on multi-objective coordination, characterized in that, The method is implemented according to the following steps: Step 1, collecting and arranging the basic data of the research area; Step 2, calculating the water storage benefit, erosion reduction benefit and pollution reduction benefit of different ecological restoration measures in the basin according to the basic data; Step 3, constructing a multi-objective function of water storage benefit, erosion reduction benefit and pollution reduction benefit of the basin and its constraint conditions; Step 4, using the NSGA-II optimization algorithm to solve and optimize the multi-objective constraint conditions to obtain the Pareto frontier of the optimization solution.

2. The multi-objective coordination based optimization method for configuring ecological restoration measures in a river basin according to claim 1, characterized in that, The water storage benefit of the ecological restoration measure in step 2 is calculated by using the SCS equation in the SWAT model, and the water storage benefit equation of the ecological restoration measure is: （1）， In formula (1), The water storage benefit of ecological restoration measures, unit: m 3 / yr; The runoff depth of the basin when the land use is no ecological restoration measures, unit: mm; The ecological restoration measures; The runoff depth of the basin when the land use is slope farmland, unit: mm; The water and soil conservation area, unit: m 2 .

3. The multi-objective coordination based optimization method for configuring ecological restoration measures in a river basin according to claim 2, characterized in that, The calculation process of the water storage benefit equation of the ecological restoration measure is: （2）， In equation (2), is the potential infiltration, in mm; is the rainfall, in mm; （3）， In equation (3), is the runoff curve number.

4. The multi-objective coordination based optimization method for configuring ecological restoration measures in a river basin according to claim 1, characterized in that, The erosion reduction benefit of the ecological restoration measure in step 2 is calculated by using the RUSLE model, and the erosion reduction equation of the ecological restoration measure is: （4）， Equation (4), The soil erosion amount without ecological restoration measures, The soil erosion amount without ecological restoration measures, The soil erosion amount with ecological restoration measures, unit: t / yr.

5. The multi-objective coordination based optimization method for configuring ecological restoration measures in a river basin according to claim 4, characterized in that, The calculation process of the erosion reduction amount of the ecological restoration measure is: （5）， （6）， In formula (5) and formula (6), is the soil erosion amount without ecological restoration measures, and the unit is t / yr; is the rainfall erosion factor, and the unit is MJ•mm / (ha•h•yr); is the slope length factor; is the slope gradient factor; is the soil erodibility factor, and the unit is t•h / (MJ•mm); is the engineering measure factor, is the biological measure factor, is the tillage measure factor; （7）， In equation (7), is the annual rainfall in mm. （8）， In equation (8), is the slope length, in meters; is the slope length exponent, （9）； （10）， In formulas (9) and (10), is the slope, in °; （11）， In formula (11), （12）， In equation (12), is the sand content, in %; is the silt content, in %; is the clay content, in %; is the soil organic carbon content, in %.

6. The multi-objective coordination based optimization method for configuring ecological restoration measures in a river basin according to claim 1, characterized in that, The pollution reduction benefit of different ecological restoration measures in the basin in step 2 is calculated by constructing a SWAT model, and the pollution reduction equation of the ecological restoration measure is: （13）， In formula (13), The pollution reduction benefit of ecological restoration measures is kg / yr. The sediment bulk density is kg / m 3 ; The total nitrogen content in runoff is mg / L. The total phosphorus content in runoff is mg / L. The total nitrogen content in sediment is mg / kg. The total phosphorus content in sediment is mg / kg.

7. The multi-objective coordination based optimization method for configuring ecological restoration measures in a river basin according to claim 6, characterized in that, The calculation method of the pollution reduction equation of the ecological restoration measure is: The process of surface water flow movement uses a two-dimensional diffusion wave equation, without considering inertial force, and the expression is: （14）， In formula (14), is the surface flow velocity, in m / s; is the source-sink term; is the soil water infiltration, in m 3 ; is the average height of the surface micro-topography, in m; is the surface water saturation, in %; is the surface depth of flowable water, in m; is the surface water saturation, in %. The process of sediment transport is embodied by the movement equation of sediment along the depth, and the expression in the model is: （15）， In equation (15), is the volume sediment concentration, with units of m 3 / m 3 ; is the total number of boundaries; is the runoff flow rate at the boundary location into the system, with units of m / s; is the volume sediment concentration corresponding to , with units of m 3 / m 3 ; is the volume of the water body, with units of m 3 ; is the soil erosion or deposition rate, with units of m 3 / s.

8. The multi-objective coordination based optimization method for configuring ecological restoration measures in a river basin according to claim 1, characterized in that, The multi-objective function in step 3 is: （16）。 9. The multi-objective synergy-based optimization method for configuring ecological restoration measures in a river basin according to claim 1, characterized in that, The constraint condition in step 3 is: （17）， In formula (17), , , , are the areas of forest land, shrub, grassland and terrace, respectively, with the unit of ha; is the watershed area with a slope of <25°, with the unit of ha; is the watershed area with a slope of 25°~30°, with the unit of ha; is the watershed area with a slope of 10°~25°, with the unit of ha; is the watershed area, with the unit of ha.

10. The multi-objective synergy-based optimization method for configuring ecological restoration measures in a river basin according to claim 1, characterized in that, The specific steps of step 4 are: Step 4-1, obtaining the area of each type of ecological restoration measure as a constraint condition; Step 4-2, constructing an optimization solution space according to the preset multiple objectives and constraint conditions; The preset multiple objectives are to maximize the water storage benefit, maximize the erosion reduction benefit and maximize the pollution reduction benefit; Step 4-3, iterative search is performed by using the multi-objective optimization algorithm NSGA-II to obtain a Pareto optimal solution set.

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