Design method of pollution load grading buffer zone based on DEM

Abstract

The application discloses a design method of pollution load grading buffer zone based on DEM, and relates to the technical field of environmental protection and ecological engineering, and the method comprises the following steps: obtaining a high-precision digital elevation model of a target region and extracting topographic and hydrological characteristic parameters; calculating the pollution load index of each spatial unit through a built composite pollution load index model, and dividing the target region into high, medium and low pollution load areas; according to a preset mapping rule library, matching different ecological zone design schemes for different pollution load areas, wherein the scheme comprises an ecological zone width, a vegetation configuration structure and engineering structure parameters; and based on a hydrological and water quality model, simulating the efficiency of the design scheme and iteratively optimizing the parameters to generate final engineering drawings. The application realizes dynamic division of pollution load inflow grade areas according to terrain parameters, and matching of different ecological zone types, widths, vegetation structures and engineering parameters.

Description

Technical Field

[0001] This invention relates to the field of environmental protection and ecological engineering technology, and in particular to a method for designing pollution load classification buffer zones based on DEM. Background Technology

[0002] Agricultural non-point source pollution has become one of the main causes of the current deterioration of water quality. While point source pollution has been gradually brought under control, non-point source pollution, caused by rainfall runoff eroding the surface and carrying sediment, nitrogen, phosphorus, and other nutrients, as well as pesticides, into water bodies, is becoming increasingly prominent. Ecological buffer zones, as key transitional zones connecting land and water, can effectively reduce the pollutant load entering rivers and lakes through various mechanisms such as vegetation interception, soil filtration, and microbial degradation, making them an important means of controlling agricultural non-point source pollution. However, the purification efficiency of ecological buffer zones is highly dependent on the rationality of their spatial layout, structural type, vegetation configuration, and width design parameters. In areas with complex topography, variable runoff paths, and significant spatial heterogeneity of pollution loads, how to achieve precise, efficient, and economical design of buffer zones has become a core technical challenge facing the field of ecological engineering.

[0003] The construction of existing ecological buffer zones largely relies on empirical rules and static design patterns. For example, the "fixed-width" riparian vegetation belts recommended by the U.S. Department of Agriculture are still widely used in engineering practices both domestically and internationally. In recent years, some studies have begun to attempt to combine geographic information systems and hydrological analysis tools to identify key pollution source areas or runoff paths based on digital elevation models, thereby achieving differentiated adjustments to the width of the buffer zone. Existing technologies use a method to set the width of the buffer zone based on catchment area and slope gradation. However, most existing technologies remain at the preliminary optimization level of "key area identification + width variation," failing to systematically integrate and parameterize topographic parameters with quantitative simulation of pollution loads and multi-level structural design of ecological zones, nor have they established an iterative optimization mechanism based on hydrological and water quality models. Furthermore, existing technologies generally lack adaptive design for dynamic hydrological scenarios such as areas with fluctuating water levels, and often employ a single vegetation structure, making it difficult to achieve targeted enhanced purification in areas with high pollutant loads, while potentially leading to over-construction in areas with low loads.

[0004] To address the above problems, this invention proposes a pollution load classification buffer zone design method based on DEM. Summary of the Invention

[0005] The purpose of this invention is to provide a design method for pollution load classification buffer zones based on DEM, so as to solve the technical problems of existing ecological buffer zone designs that ignore topographic spatial heterogeneity, mismatch between function and pollution load, and simple structure.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: The design method for pollution load classification buffer zones based on DEM includes: Step S1: Obtain high-resolution digital elevation model data of the target area, simulate surface runoff paths and catchment area division based on the hydrological analysis model, and extract topographic and hydrological feature parameters; the topographic and hydrological feature parameters include slope and aspect vectors, upstream catchment area, curvature, and topographic humidity index; Step S2: Based on the topographic and hydrological characteristic parameters and combined with land use type data, calculate the pollution load index of each catchment unit through the composite pollution load index model, and divide the target area into three levels of pollution load: high, medium and low, according to the index. Step S3: Establish a mapping rule library between pollution load levels and ecological zone design parameters, and match ecological zone design schemes for high, medium and low pollution load areas respectively. The design schemes include ecological zone width, vegetation configuration structure, engineering structure parameters and wavy terrain morphology parameters. Step S4: Couple the hydrological analysis model with the pollutant migration equation to simulate the purification efficiency under different ecological zone design schemes, and perform parameter iterative optimization with cost-benefit as the objective function; Step S5: Generate engineering drawings based on the optimized design scheme, and deploy monitoring sensors at key nodes to dynamically adjust vegetation management strategies and local engineering structures based on real-time monitoring data.

[0007] In a preferred embodiment, in step S1, the data accuracy of the high-resolution digital elevation model data is ≥1m; the vector composition of the topographic and hydrological feature parameters is as follows;

[0008] in, This is a slope and aspect vector, representing the degree and orientation of the land surface tilt; Curvature is used to distinguish between convex and concave slopes, reflecting the convergence and dispersion trends of runoff; The upstream catchment area is a direct measure of the amount of water flowing through that location; The topographic moisture index is used to predict soil saturation zones, and its calculation formula is as follows:

[0009] In a preferred embodiment, in step S2, the composite pollution load index model is composed of the sum of four weighted components, and its calculation formula is as follows:

[0010] in, For position The original composite pollution load index at the location was linearly normalized to the range of 0-10 to obtain the final pollution load index. ; The upstream catchment area, It has the largest catchment area in the entire region. The contribution of water catchment is used to quantify the potential of upstream water to transport pollution load; For slope, This is the steepest slope in the entire area. The topographically driven component is used to characterize the impact of topographic steepness on runoff scouring capacity and pollutant migration efficiency. The pollution source indicator function is assigned different pollution output coefficients according to different land use types, with farmland assigned a value of 1 and forest land assigned a value of 0.2, which is used to reflect the potential for pollutant generation at that location and is represented as the source strength indicator component. The topographic humidity index is used to characterize the degree of soil saturation and the likelihood of surface runoff; it is a humidity conditional component. The weighting coefficients were obtained through literature review and calibration using local monitoring data.

[0011] Then, based on the calculated final pollution load index Based on the numerical range, the target area is divided into high, medium, and low pollution load zones according to the following classification function:

[0012] in, These represent high, medium, and low pollution load levels, respectively. and These are the lower and upper limits of the load index corresponding to this level, respectively.

[0013] In a preferred embodiment, step S3 involves establishing a mapping rule base between pollution load levels and ecological zone design parameters, for each design type. From a multidimensional design vector Full definition:

[0014] in, The parameter for the width of the ecological zone in a Class K pollution area. Configure parameters for the tree layer in the K-level pollution area. Configure parameters for the shrub layer in the K-level pollution area. Configure parameters for the herbaceous layer in the K-level pollution area. For engineering structural parameters of the K-level pollution zone, The parameters represent the wave-like topographic morphology of the K-level pollution area.

[0015] The mapping rule base is specifically as follows: The ecological belt design scheme for high pollution load areas is configured as follows: the ecological belt width is ≥15 meters, adopts a multi-layered vegetation structure of trees, shrubs and herbaceous plants, and is equipped with engineering reinforcement structures; The ecological zone design scheme for medium pollution load areas is configured as follows: the ecological zone is 8 to 15 meters wide and adopts a shrub and herbaceous vegetation structure; The ecological belt design scheme for low pollution load areas is configured as follows: the ecological belt width is ≤8 meters, and it is mainly composed of herbaceous vegetation.

[0016] Width parameter: The width of the ecozone is configured to match the local slope. Dynamically dependent, the width function is:

[0017] in, The dynamic design width for the K-level pollution zone, This is the baseline width for a Class K pollution zone. Here, S represents the slope coefficient, and S represents the local slope. Specifically: The formula for calculating the width of the ecological zone in a high-pollution-load area is: ; The formula for calculating the width of the ecological zone in the medium pollution load area is: ; The width of the ecological zone in the low pollution load area is a fixed value. It does not change with local slope.

[0018] Vegetation configuration structure: The vegetation configuration structure is defined by the three-dimensional vegetation configuration vector, which includes tree layer configuration parameters. Shrub layer configuration parameters Herbaceous layer configuration parameters :

[0019]

[0020]

[0021] in, These are species combinations representing the tree layer, shrub layer, and herbaceous layer, respectively. This refers to the width and diameter range of the tree layer plants. The height range of the shrub layer, This refers to the depth of the herbaceous root system. , , These refer to the planting densities for the tree layer, shrub layer, and herbaceous layer, respectively. , , The coverage rates of the tree layer, shrub layer, and herbaceous layer are respectively, and they meet the following requirements. ; Specifically: In the ecological zone design scheme for high pollution load areas, the coverage ratio of the tree layer, shrub layer, and herb layer is 0.2:0.3:0.5; In the ecological zone design scheme for medium pollution load areas, the coverage ratio of shrub layer to herb layer is 0.4:0.6, and no tree layer is set ( ); In the ecological zone design scheme of low pollution load area, the herbaceous layer coverage rate is ≥0.9, the shrub layer coverage rate is ≤0.1, and no tree layer is set ( ).

[0022] The engineering structural parameters are specifically: engineering structural parameters This includes filter bed thickness, filter media particle size distribution, and trench dimensions:

[0023] Specifically: The ecological zone design scheme for high pollution load areas includes a zeolite filter media layer and a crushed stone infiltration ditch. The zeolite filter media layer has a thickness of 0.3 to 0.5 meters and a particle size distribution of D50 = 2 to 5 mm, meaning that 50% of the filter media particles by weight are no larger than 2 to 5 mm. The crushed stone infiltration ditch has a width of 0.5 meters and a depth of 0.6 meters, filled with 20 to 40 mm graded crushed stone, and is set every 20 to 30 meters along the direction of the ecological zone. The ecological zone design scheme for the medium pollution load area is equipped with a simple filter soil layer with a thickness of 0.1~0.2 meters, using coarse sand or fine gravel as filter media, with a particle size distribution of D50=0.5~1mm; The ecological zone design scheme for low pollution load areas does not include engineering reinforcement structures. ).

[0024] The wave-shaped terrain morphology parameters It is expressed by a cross-sectional profile function along the direction of the ecological zone, which is a distance perpendicular to the river channel. The design elevation of the ground at that distance is the independent variable. The dependent variable is the pollution level. The cross-sectional profile function of the wavy terrain is:

[0025] in, Distance The ground design elevation at the location, As the reference elevation; The main wave amplitude controls the height of wave undulations, with larger amplitudes in high-load areas to create more storage space. The wavelength is used to control the width of the concave-convex unit, which is related to the width of the ecosystem. Related (e.g.) ); Phase angle; is the amplitude of the secondary wave, used to create more complex micro-topography, promoting local water accumulation and infiltration; k is the pollution level.

[0026] The parameters for wavy terrain are set differently based on the pollution load level: In the ecological zone design scheme of high pollution load area, the main wave amplitude The wavelength is 0.5 to 1.0 meters. It is 4 to 8 meters; In the ecological zone design scheme of medium pollution load area, the main wave amplitude The wavelength is 0.2 to 0.5 meters. It is 3 to 5 meters; In the ecological zone design scheme of low pollution load area, the main wave amplitude 0.2 meters.

[0027] Specifically, in step S4, the cost-benefit objective function is composed of a weighted average of purification efficiency and soil stabilization efficiency, wherein: The objective function of the purification and interception function is:

[0028] in, The objective function is the purification efficiency. and These represent the inflow and outflow pollutant concentrations at position p at time t, respectively.

[0029] pollutant concentration Changes are linked to the convection-diffusion-reaction equation and ecozone parameters. Coupled simulation.

[0030] The objective function for soil stabilization is:

[0031] in, The objective function for soil stabilization is... For effective soil cohesion, The internal friction angle of the soil. The root reinforcement effect coefficient is a factor in vegetation configuration. The function.

[0032] The comprehensive benefit function is:

[0033] Here, α and β are weighting coefficients that satisfy α+β=1, obtained through literature review or field experiment calibration.

[0034] With the dual objectives of maximizing overall benefits and minimizing engineering costs, a genetic algorithm or a multi-objective particle swarm optimization algorithm is used for iterative parameter optimization, with the ratio of overall benefits to engineering costs serving as the fitness function.

[0035] In the optimization process, the ratio of comprehensive benefits to engineering costs is used as the optimization objective. When the number of consecutive iterations reaches a preset upper limit, or the rate of change of the fitness function value in a preset number of consecutive iterations is less than a preset threshold, it is determined that the convergence condition is met, the iteration is stopped, and the current optimal solution set is output.

[0036] Preferably, in step S5, the specific method for generating engineering drawings based on the optimized design scheme is as follows: the optimized ecological zone width, vegetation configuration zoning, engineering structure parameters, and wavy terrain parameters are automatically converted into vector layers based on the GIS platform, and a preset engineering drawing template is called to generate construction drawings; the monitoring sensors include water quality sensors and soil moisture meters; the dynamic adjustment of vegetation management strategies and local engineering structures based on real-time monitoring data includes: when the monitoring data shows that the pollutant concentration exceeds a preset threshold, increasing the vegetation density, thickening the filter layer, or adding infiltration ditches.

[0037] As a preferred embodiment, in step S5, flood-tolerant and drought-resistant amphibian plant communities are configured in the water level fluctuation zone, and stepped ecological retention dams are added at the abrupt slope changes to form a dynamic adaptive ecological belt. Specifically, in step S5, the method for determining the key nodes is as follows: based on the pollution load classification map generated in step S2, the runoff outlets of each catchment unit in the high pollution load area are taken as primary key nodes; based on the surface runoff paths extracted in step S1, secondary key nodes are set at the intersection of two or more runoff paths; and tertiary key nodes are set at the boundary between high and medium pollution load areas, as well as at the cross-section where the width of the ecological zone changes.

[0038] As a simplified implementation, when data acquisition or computing resources are limited, the above method can be simplified as follows: Simplified pollution load classification: The upstream catchment area of ​​each watershed is directly used as the pollution load classification index, with an upstream catchment area set at 2.0. The area is a high pollution load zone, with a concentration of 1.0 to 2.0. The area is classified as a medium pollution load zone, with a load less than 1.0. The area is a low pollution load zone, and there is no need to calculate the composite pollution load index; Width simplification: The dynamic functional relationship between width and slope is eliminated, and a fixed width design is adopted, that is, the width of high pollution load area is 18 meters, the width of medium pollution load area is 10 meters, and the width of low pollution load area is 5 meters. Simplification of terrain morphology: The wavy terrain parameter setting is cancelled, and the surface of the ecological zone adopts a natural and gentle terrain; Simplification of engineering structure: Elimination of engineering reinforcement structures such as zeolite filter media layer and crushed stone infiltration trench.

[0039] This simplified solution is suitable for application scenarios that do not have high-precision DEM data, soil permeability data, or rainfall intensity data. Although the purification efficiency is lower than that of the complete solution, the design process is faster and still better than the traditional homogenization design solution.

[0040] Compared with the prior art, the beneficial technical effects of the present invention are as follows: This invention establishes a calculable and hierarchical technical chain from "topographic features → hydrological path → spatial distribution of pollution load" through high-precision DEM hydrological analysis, realizing the paradigm shift of ecological buffer zones from static experience design to dynamic topographic response design, and solving the spatial decision-making problem of "where to build" in traditional methods.

[0041] This invention constructs a mapping rule library of "load classification - structure type - parameter set" to match differentiated ecological belt widths, vegetation configuration structures and engineering reinforcement measures for high, medium and low pollution load areas, thereby achieving "precise pollution control" and avoiding the problems of insufficient purification in high load areas and excessive construction in low load areas.

[0042] This invention uses a sine function to express the wavy terrain morphology parameters, elevating the ecological zone from a planar design to a three-dimensional design with specific terrain undulations. This significantly increases surface roughness and runoff contact time, thereby improving interception and purification efficiency. Verification by examples shows that the method of this invention can increase the total phosphorus removal rate by about 40 percentage points, the suspended solids interception rate by about 22 percentage points, and the purification efficiency per unit investment by about 1.5 to 1.8 times.

[0043] This invention optimizes parameters iteratively by coupling a hydrological and water quality model, forming a closed-loop feedback process of "preliminary design → simulation verification → parameter optimization → final design". It also configures flood-tolerant and drought-resistant amphibious plant communities in the water level fluctuation zone, realizing the adaptive adjustment of the ecological zone to dynamic hydrological conditions. Attached Figure Description

[0044] Figure 1 This is a flowchart of the pollution load classification buffer zone design method based on DEM provided in the embodiments of the present invention; Figure 2 These are actual engineering site images provided in the embodiments of the present invention; Figure 3 This is a high-resolution digital elevation model data map provided in an embodiment of the present invention. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] Example 1: Differentiated Design Scheme for Pollution Load Classification Based on DEM Location: Ximinbianhe Ecological Buffer Zone Project, Sucheng District, Jiangsu Province like Figure 2 As shown, Figure 2 This is an image of the actual engineering site. This embodiment is based on actual data from the Ximinbian River basin in Sucheng District, Jiangsu Province, and uses the SWAT (a specific form of moisture analysis model, a distributed hydrological model) model for scenario simulation. The simulation period is one complete hydrological year. The suspended solids interception rate and total phosphorus removal rate are calculated based on the pollutant concentration difference between the inlet and outlet output by the model. The comprehensive project cost is calculated based on local engineering cost quotas. Figure 1 As shown, the specific steps are as follows: Step S1: Topographic Data Acquisition and Hydrological Analysis. High-resolution digital elevation model (DEM) data of the target area is acquired, with a data accuracy of 0.5 meters. Based on this DEM data, the D8 single-flow-direction algorithm (a well-known method for calculating flow direction in DEMs) is used to sequentially perform depression filling, flow direction analysis, and runoff accumulation calculation, simulating surface runoff paths and dividing the catchment area. The 27.6222 square kilometer area is divided into 12 catchment sub-areas, numbered WS-01 to WS-12.

[0047] Extracting topographic and hydrological feature parameter vectors :

[0048] in, This is a slope and aspect vector, representing the degree and orientation of the land surface tilt; Curvature is used to distinguish between convex and concave slopes, reflecting the convergence and dispersion trends of runoff; The upstream catchment area is a direct measure of the amount of water flowing through that location; The topographic moisture index is used to predict soil saturation areas. The calculation formula is:

[0049] It should be noted that the slope ∇z(p), upstream catchment area A(p), and topographic humidity index TWI(p) are all grid-scale parameters. For a catchment sub-region, the slope value is the arithmetic mean of the slopes of all grids within the sub-region, and the TWI value is the arithmetic mean of the TWI values ​​of all grids within the sub-region.

[0050] Taking a grid cell in the WS-03 sub-region as an example, the final calculated average slope is 1.5°, the average slope length is 60m, the total upstream catchment area is 2.85 square kilometers, and the average topographic humidity index TWI is 7.0.

[0051] The flow accumulation is calculated using the D8 algorithm and represents the number of upstream grid cells flowing through each grid cell. In this embodiment, the grading criteria for the flow accumulation are as follows: Extremely high: Upstream catchment area > 2.5 ; High: Upstream catchment area 1.0-2.5 ; Middle: Upstream catchment area 0.2-1.0 ; Low: Upstream catchment area ≤ 0.2 ; The topographic factors of each catchment area are shown in the table below: ; Step S2: Pollution load index calculation and spatial classification. For example... Figure 3 As shown, based on the topographic and hydrological characteristic parameters and combined with land use type data, the pollution load index of each catchment unit is calculated through a composite pollution load index model, and the target area is divided into high, medium and low pollution load zones according to the pollution load index. Based on the extracted topographic and hydrological feature parameters and combined with land use type data, a composite pollution load index model is constructed.

[0052] The formula for calculating the composite pollution load index is:

[0053] in, For position The composite pollution load index at the location; The upstream catchment area, It has the largest catchment area in the entire region. The contribution of water catchment is used to quantify the potential of upstream water to transport pollution load; For slope, This is the steepest slope in the entire area. The topographically driven component is used to characterize the impact of topographic steepness on runoff scouring capacity and pollutant migration efficiency. The pollution source indicator function is assigned different pollution output coefficients according to different land use types, with farmland assigned a value of 1 and forest land assigned a value of 0.2, which is used to reflect the potential for pollutant generation at that location and is represented as the source strength indicator component. The topographic humidity index is used to characterize the degree of soil saturation and the likelihood of surface runoff; it is a humidity conditional component. These are the weighting coefficients, which were obtained through literature review and calibration using local monitoring data.

[0054] The formula above calculates the original composite pollution load index L(p). To facilitate subsequent classification and comparison, it is further linearly normalized to the range of 0-10 to obtain the final pollution load index. : Taking WS-05 sub-zone as an example: the largest catchment area in the entire region square kilometers, the steepest slope in the entire area .

[0055] Taking the WS-03 sub-region as an example, , The land use in this sub-region is mainly farmland, and the pollution source indicator function... , Substitute into the formula:

[0056] After normalization, the pollution load index is 8.1.

[0057] The hierarchical function is:

[0058] in, These represent high, medium, and low pollution load levels, respectively. In this embodiment, the following settings are used: High pollution load areas: Medium pollution load area: Low pollution load area: .

[0059] The pollution load index of sub-zone WS-03 is 8.1 > 7.5, thus it is classified as a high pollution load zone. The calculation results for each sub-zone are as follows: ; Sub-zones WS-03, WS-05, and WS-07 were identified as high-pollution-load areas, WS-06 and WS-10 as low-pollution-load areas, and the rest as medium-pollution-load areas.

[0060] Step S3: Differentiated Multi-Level Ecosystem Design. Establish a rule base for mapping pollution load levels to ecosystem design parameters. For each design type... From a multidimensional design vector Full definition:

[0061] in, The parameter for the width of the ecological zone in a Class K pollution area. Configure parameters for the tree layer in the K-level pollution area. Configure parameters for the shrub layer in the K-level pollution area. Configure parameters for the herbaceous layer in the K-level pollution area. For engineering structural parameters of the K-level pollution zone, The parameters represent the wave-like topographic morphology of the K-level pollution area.

[0062] (1) Width parameter The width of the ecological zone is configured to match the local slope. (Unit: degrees) Dynamically dependent, width function is:

[0063] in, The dynamic design width for the K-level pollution zone, This is the baseline width for a Class K pollution zone. Here, S is the slope coefficient, and S is the local slope. Specifically: High pollution load areas (WS-03, WS-05, WS-07): Width calculation formula is as follows .

[0064] The WS-03 has a local slope of 1.5°. Meters, that is, the deployment of a 18-meter-wide high-strength purification belt.

[0065] Medium pollution load zone: The formula for calculating the width is as follows .

[0066] Taking WS-04 as an example, the average slope is 1.0°. Meters, that is, to deploy a 9-meter-wide medium-strength interception strip.

[0067] Low pollution load zone (WS-06, WS-10): Width is a fixed value The term "meter" refers to the establishment of a 5-meter-wide ecological conservation belt.

[0068] (2) Vegetation configuration structure The vegetation configuration structure is defined by a three-dimensional vegetation configuration vector, which includes tree layer configuration parameters. Shrub layer configuration parameters Herbaceous layer configuration parameters :

[0069]

[0070]

[0071] in, These are species combinations representing the tree layer, shrub layer, and herbaceous layer, respectively. This refers to the width and diameter range of the tree layer plants. The height range of the shrub layer, This refers to the depth of the herbaceous root system. , , These refer to the planting densities for the tree layer, shrub layer, and herbaceous layer, respectively. , , The coverage rates of the tree layer, shrub layer, and herbaceous layer are respectively, and they meet the following requirements. ; Specifically: In the ecological zone design scheme for high-pollution areas, a multi-layered vegetation structure of trees, shrubs, and grasses is adopted. The tree layer coverage rate is... The planting density is 200 trees per hectare, the species is dawn redwood, and the trees are 2.5 meters wide; the shrub layer coverage is... The planting density is 4000 clumps per hectare, the species is *Salix matsudana*, and the height is 1.5 meters; the herbaceous layer coverage is... The planting density is 100%, and the species are reeds and cattails. The coverage rate meets [the requirements]. .

[0072] In the ecological zone design scheme for medium pollution load areas: a shrub and grass vegetation structure is adopted, and no tree layer is set. Shrub cover The planting density is 3000 clumps per hectare, and the species is Amorpha fruticosa; the herbaceous layer coverage is... The planting density is 100%, and the species are Bermuda grass and Bahia grass.

[0073] In the ecological zone design scheme for low pollution load areas: herbaceous vegetation is the main component, and no tree layer is set up. Herbaceous layer coverage Shrub cover The planting density is 2000 clumps / hectare, and the species are Zoysia japonica and wild grass.

[0074] (3) Engineering structural parameters Engineering structural parameters This includes filter bed thickness, filter media particle size distribution, and trench dimensions:

[0075] Ecological zone design scheme for high pollution load area: configuration of pre-sedimentation ditch, underground zeolite filter media layer and crushed stone infiltration ditch, wherein the pre-sedimentation ditch is 1 meter wide and 0.5 meters deep, the underground zeolite filter media layer is 0.3 meters thick and the filter media particle size D50=2mm, and the crushed stone infiltration ditch is 0.5 meters wide and 0.6 meters deep.

[0076] Ecological zone design scheme for medium pollution load area: Set up a simple filter soil layer with a thickness of 0.1 meters. The filter material is coarse sand with a particle size distribution of D50=0.5~1mm.

[0077] Ecological zone design scheme for low pollution load areas: No engineering reinforcement structures are required.

[0078] (4) Parameters of wave-shaped terrain Wave-shaped topographic parameters are used to create sinusoidal undulations on the surface of the ecozone. By increasing surface roughness, forming micro-storage spaces, and extending runoff residence time, the ecozone's efficiency in intercepting and purifying pollutants is significantly improved.

[0079] The profile function of the wavy terrain section is:

[0080] in, As the reference elevation, Main wave amplitude, For wavelength, The phase angle is 0 in this embodiment. This represents the amplitude of the secondary wave.

[0081] Ecological zone design scheme for high pollution load areas: benchmark elevation meters, main wave amplitude meters, secondary wave amplitude meters, wavelength Meters. A bioretention pool (0.8 meters deep) is formed at the trough, which intercepts runoff and settles particulate matter; a drought-resistant habitat is formed at the crest.

[0082] Ecological zone design scheme for medium pollution load areas: baseline elevation meters, main wave amplitude meters, wavelength Meters, without secondary waves ( ).

[0083] Ecological zone design scheme for low pollution load areas: benchmark elevation meters, main wave amplitude Meters, without secondary waves ( (), almost natural terrain.

[0084] Step S4: Parameter Optimization and Performance Simulation. In this embodiment, the well-known SWAT model is used as the specific implementation of the hydrological analysis model. This model is a distributed physical mechanism model, and the input data required for its operation include: a 0.5-meter resolution DEM, a soil type and physical property database, daily meteorological data (rainfall, temperature) with a 1km grid, and a land use / cover map. Surface runoff is calculated using the model's built-in SCS runoff curve number method, and the catchment area and river network are automatically extracted using the D8 unidirectional flow algorithm.

[0085] The differentiated design schemes generated in step S3 were input as scenario parameters into the calibrated SWAT model, coupled with its built-in hydrological module and pollutant migration equation, to simulate the pollutant purification efficiency under different design parameters. The Nash efficiency coefficient (NSE) reached 0.68 during the model calibration period and 0.65 during the validation period, indicating that the model has good applicability in this region.

[0086] In the cost-benefit objective function, the benefit function is composed of a weighted average of purification efficiency and soil stabilization efficiency. The objective function of the purification and interception function is:

[0087] in, The objective function is the purification efficiency. and These represent the inflow and outflow pollutant concentrations at position p at time t, respectively.

[0088] pollutant concentration Changes are linked to the convection-diffusion-reaction equation and ecozone parameters. Coupled simulation.

[0089] The objective function for soil stabilization is:

[0090] Among them, soil effective cohesion kPa, soil internal friction angle Root reinforcement effect coefficient , The root reinforcement effect coefficient is a factor in vegetation configuration. The function.

[0091] The comprehensive benefit function is:

[0092] Here, α and β are weighting coefficients that satisfy α+β=1, obtained through literature review or field experiment calibration.

[0093] With the dual objectives of maximizing overall benefits and minimizing engineering costs, a genetic algorithm or a multi-objective particle swarm optimization algorithm is used for iterative parameter optimization. The population size is set to 80, the crossover probability is 0.8, and the mutation probability is 0.05. The ratio of overall benefits to engineering costs is used as the fitness function.

[0094] When the number of consecutive iterations reaches the preset upper limit (500 times in this embodiment), or when the rate of change of the fitness function value is less than 1% in a preset number of consecutive iterations (10 times in this embodiment), it is determined that the convergence condition is met, the iteration stops, and the current optimal solution set is output.

[0095] After iterative optimization, the width of the high pollution load zone was increased from the initial 18 meters to 20 meters, the thickness of the filter layer was increased from 0.3 meters to 0.35 meters, and the vegetation coverage rate remained the same.

[0096] Step S5: Project Implementation and Adaptive Adjustment. Based on the optimized design scheme in Step S4, the ecological zone width boundary, vegetation configuration zoning, engineering structure parameters, and wavy terrain contour lines are automatically converted into vector layers using the GIS platform. Pre-set CAD engineering drawing templates are used to generate construction drawings, and monitoring sensors are deployed at key nodes. Based on real-time monitoring data, vegetation management strategies and local engineering structures are dynamically adjusted.

[0097] In this embodiment, the method for determining key nodes is as follows: Based on the pollution load classification map generated in step S2, the runoff outlets of each catchment unit in the high pollution load area are designated as primary critical nodes; based on the surface runoff paths extracted in step S1, secondary critical nodes are set at the intersection of two or more runoff paths; and tertiary critical nodes are set at the boundary between high and medium pollution load areas, as well as at cross-sections where the width of the ecological zone changes.

[0098] Water quality sensors and soil moisture meters are deployed at key nodes of the ecological belt project. In this embodiment, sensors are only deployed at the runoff outlets of the high-pollution-load sub-zones (WS-03, WS-05, WS-07) and at the boundary between the high- and medium-pollution-load zones, totaling 6 water quality sensors and 6 soil moisture meters, with a sampling frequency of once every 30 minutes. When the monitoring data shows that the total phosphorus concentration exceeds 0.2 mg / L, the system automatically triggers the addition of vegetation density (increase by 20%), thickening of the filter layer (increase by 0.1 meters), or the addition of infiltration trenches (one every 50 meters).

[0099] In the water level fluctuation zone, at elevations of 9.5 meters to 10.5 meters, a flood-tolerant and drought-resistant amphibious plant community, including reeds and bermudagrass, is planted to provide flood tolerance and drought resistance, respectively. This is also implemented at locations of abrupt slope changes. A stepped ecological retention dam was added, with each step having a height difference of 0.5 meters, forming a dynamically adaptive ecological belt.

[0100] Example 2: Simplified design scheme based on catchment area threshold grading (simplified version) Location: Agricultural non-point source pollution control project in a hilly area.

[0101] This embodiment provides a simplified implementation scheme applicable to scenarios where data acquisition or computing resources are limited, such as a lack of high-precision DEM data, soil permeability data, rainfall intensity data, or insufficient computing resources to run complex hydrological models. Compared to Embodiment 1, this embodiment simplifies in the following aspects: Pollution load classification: The upstream catchment area is used directly as the classification index, and there is no need to calculate the composite pollution load index; Width design: Use a fixed width and eliminate the dynamic functional relationship with the slope; Terrain morphology: Cancel the wavy micro-terrain setting; Engineering structure: Eliminate engineering reinforcement measures such as filter media layers and seepage trenches.

[0102] Although the purification efficiency of this simplified scheme is lower than that of Example 1 (by about 20% to 30%), the design process is faster and the data requirements are lower, making it still superior to the traditional homogenization design scheme.

[0103] This embodiment is based on actual data (1-meter resolution DEM) from an agricultural non-point source pollution control area in a hilly region. A SWAT model is used for scenario simulation, with a simulation period of one complete hydrological year. The data calculation method is the same as in Embodiment 1.

[0104] Step S1: Topographic Data Acquisition and Hydrological Analysis. High-resolution digital elevation model (DEM) data of the target area is acquired, with a data accuracy of 1 meter. Based on this DEM data, the D8 single-flow direction algorithm is used to sequentially perform depression filling, flow direction analysis, and runoff accumulation calculation to simulate surface runoff paths and delineate catchment areas. The 15.30 square kilometer area is divided into 8 catchment sub-areas, numbered S-01 to S-08.

[0105] Topographic and hydrological characteristic parameters were extracted, including slope, upstream catchment area A, and topographic humidity index TWI. The topographic factors for each sub-region are shown in the table below: ; The formula for calculating the topographic humidity index is:

[0106] Where A is the upstream catchment area and β is the local slope.

[0107] Step S2: Pollution Load Index Calculation and Spatial Classification (Simplified Version). This embodiment uses a simplified classification method: areas with a catchment area greater than a certain threshold are directly defined as high-load zones.

[0108] Set catchment area threshold: High pollution load area ; Medium pollution load area: upstream catchment area ; Low pollution load zone: upstream catchment area ; The hierarchical function is:

[0109] Based on the catchment area of ​​each sub-zone, S-03 was identified ( S-05 The area designated as high pollution load (1) is classified as high pollution load area, while the rest are classified as medium pollution load areas. The risk level classification results for each sub-area are as follows: ; Four sub-zones, S-01, S-03, S-05, and S-08, were identified as high-pollution-load zones, while the rest were identified as medium-pollution-load zones.

[0110] Step S3: Differentiated multi-level ecosystem design.

[0111] (1) Width parameter The width of the ecological zone is set to a fixed value, without setting a dynamic function relationship with the slope.

[0112] High pollution load areas (S-01, S-03, S-05, S-08): Deploy a high-intensity purification belt with a width of 18 meters.

[0113] Medium pollution load areas (S-02, S-04, S-06, S-07): Deploy a medium-strength interception zone with a width of 10 meters.

[0114] If there are low pollution load areas, then ecological conservation interception belts with a width of 5 meters should be laid out.

[0115] (2) Vegetation configuration structure The vegetation configuration structure is defined by the vegetation three-dimensional configuration vector.

[0116] High pollution load areas: A multi-layered vegetation structure of trees, shrubs, and grasses will be adopted. Tree cover rate... =0.2, planting density 200 trees / hectare, species is dawn redwood, tree width 2.5 meters; shrub layer coverage =0.3, planting density 4000 clumps / hectare, species is *Salix matsudana*, height 1.5 meters; herbaceous layer coverage rate =0.5, planting density 100%, species are reeds and cattails. Coverage meets the requirements. + + =1.0≤1.

[0117] Medium pollution load zone: A shrub and grass vegetation structure will be adopted, without a tree layer. =0. Shrub cover =0.4, planting density 3000 clumps / hectare, species is Amorpha fruticosa; herbaceous layer coverage rate =0.6, planting density 100%, species are Bermuda grass and Bahia grass.

[0118] (3) Engineering structural parameters This embodiment does not include any engineering reinforcement measures. Zeolite filter media layers and crushed stone infiltration ditches are not configured in high-pollution-load areas, and filter soil layers are not configured in medium-pollution-load areas.

[0119] (4) Parameters of wave-shaped terrain This embodiment does not feature wavy micro-topography. The surface of the ecological zone is naturally flat, without sinusoidal undulations.

[0120] Step S4: Parameter Optimization and Performance Simulation. The differentiated design schemes generated in Step S3 are input into the SWAT hydrological and water quality model. The hydrological model is coupled with the pollutant migration equation to simulate the pollutant purification efficiency under different design parameters. The specific operation is consistent with Example 1.

[0121] Step S5: Project Implementation and Adaptive Adjustment. Based on the optimized design scheme in Step S4, the ecological zone width boundary and vegetation configuration zoning are automatically converted into vector layers using the GIS platform, and construction drawings are generated by calling preset CAD engineering drawing templates.

[0122] Water quality sensors and soil moisture meters are deployed at key nodes of the ecological belt project. The water quality sensors are used to monitor the concentration of total phosphorus and suspended solids, with a sampling frequency of once every 30 minutes. When the monitoring data shows that the total phosphorus concentration exceeds 0.2 mg / L, the vegetation density is automatically increased by 20%.

[0123] In areas with fluctuating water levels, flood-tolerant and drought-resistant amphibious plant communities, including reeds and bermudagrass, are planted to provide both flood tolerance and drought resistance, forming a dynamically adaptive ecological zone.

[0124] Comparative Example 1: Traditional homogenization design scheme Location: Ximinbianhe Ecological Buffer Zone Project, Sucheng District, Jiangsu Province (same area as Example 1).

[0125] This comparative study uses SWAT model scenario simulation based on actual data from the Ximinbian River basin in Sucheng District, Jiangsu Province, with a simulation period of one complete hydrological year. The suspended solids interception rate and total phosphorus removal rate are calculated using the pollutant concentration difference between the inlet and outlet output by the model. The overall project cost is calculated based on local engineering cost quotas.

[0126] Design Methodology: This comparative model adopts traditional empirical design methods, without DEM hydrological analysis, pollution load classification, fixed width and single vegetation structure throughout the watershed, without setting undulating terrain, without setting engineering reinforcement measures, and without parameter optimization.

[0127] The specific design is as follows: A 10-meter-wide composite belt of shrubs and grass is uniformly laid out along the entire line; Vegetation configuration: A uniform shrub-grass structure is adopted, with a shrub layer coverage rate of [missing information]. =0.4, herbaceous layer coverage =0.6, no tree layer is set; no pollution load level is distinguished; no wavy micro-topography is set; no filter media layer and infiltration ditch are set; no hydrological and water quality model optimization is performed.

[0128] Implementation results: Construction was carried out using traditional, experience-based methods, followed by performance monitoring upon completion.

[0129] The suspended solids interception rate is 60% to 65%, the total phosphorus removal rate is 30% to 35%, the comprehensive project cost is 1 million yuan as the benchmark value, and the unit investment purification efficiency is 0.32 as the benchmark value.

[0130] The comparison data with Example 1 are as follows: ; The comparison results between this comparative example and Example 1 show that: First, in terms of purification efficiency, the suspended solids interception rate of Example 1 is about 22 percentage points higher than that of the traditional scheme, and the total phosphorus removal rate is about 38 percentage points higher. This shows that the present invention significantly enhances the interception and purification capacity of the ecological zone for agricultural non-point source pollutants through the comprehensive effects of high-precision DEM hydrological analysis, composite pollution load index classification, differentiated width and vegetation configuration, wavy terrain and engineering reinforcement measures.

[0131] Second, in terms of economic benefits, the overall engineering cost of Example 1 is only 15% higher than that of the traditional solution, but the purification efficiency per unit investment is increased by about 1.9 times. This shows that the present invention, through the "precision pollution control" strategy, accurately directs more than 70% of the enhanced engineering work to high pollution load areas, achieving the optimal balance between cost and benefit.

[0132] Third, based on the above analysis, compared with the traditional uniform design scheme, the present invention significantly improves the removal efficiency of pollutants with a slight increase in cost, verifying the scientific nature and efficiency of the technology chain from "topography quantification" to "load classification" and then to "precision design".

[0133] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for designing pollution load grading buffer zones based on DEM, characterized in that, Includes the following steps: Step S1: Obtain high-resolution digital elevation model data of the target area, simulate surface runoff paths and catchment area division based on the hydrological analysis model, and extract topographic and hydrological feature parameters; the topographic and hydrological feature parameters include slope and aspect vectors, upstream catchment area, curvature, and topographic humidity index; Step S2: Based on the topographic and hydrological characteristic parameters and combined with land use type data, calculate the pollution load index of each catchment unit through the composite pollution load index model, and divide the target area into three levels of pollution load zones: high, medium and low, according to the pollution load index. Step S3: Establish a mapping rule library between pollution load levels and ecological zone design parameters, and match ecological zone design schemes for high, medium and low pollution load areas respectively. The design schemes include ecological zone width, vegetation configuration structure, engineering structure parameters and wavy terrain morphology parameters. Step S4: Couple the hydrological analysis model with the pollutant migration equation to simulate the purification efficiency under different ecological zone design schemes, and perform parameter iterative optimization with cost-benefit as the objective function; Step S5: Generate engineering drawings based on the optimized ecological zone design scheme, and deploy monitoring sensors at key nodes. Adjust vegetation management strategies and local engineering structures dynamically based on real-time monitoring data.

2. The pollution load classification buffer zone design method based on DEM according to claim 1, characterized in that, In step S2, the composite pollution load index model is composed of the sum of four weighted components: The first item is the water catchment contribution component, which is the ratio of the upstream catchment area of ​​the target area to the maximum catchment area of ​​the entire area; the water catchment contribution component is multiplied by the first weighting coefficient to quantify the potential of upstream water to transport pollution load. The second term is the terrain-driven component, which is the ratio of the slope of the target area to the maximum slope of the entire area; The terrain-driven component is multiplied by a second weighting coefficient to characterize the impact of terrain steepness on runoff scouring capacity and pollutant migration efficiency. The third term is the source strength indication component, which is represented by the pollution source indication function value; The source strength indicator component is multiplied by a third weighting coefficient. In the pollution source indicator function, farmland is assigned a value of 1, and forest land is assigned a value of 0.

2. The pollution source indicator function assigns different pollution output coefficients according to different land use types to reflect the potential for pollutant generation at that location. The fourth component is the humidity condition component, which is represented as the topographic humidity index of the target area; the humidity condition component is multiplied by the fourth weighting coefficient to characterize the soil saturation level and the probability of surface runoff. The first to fourth weighting coefficients were obtained through literature review and calibration using local monitoring data. The original composite pollution load index at that location is obtained by summing the four weighted components. The original composite pollution load index is then linearly normalized to the range of 0 to 10 to obtain the final composite pollution load index.

3. The pollution load classification buffer zone design method based on DEM according to claim 1, characterized in that, In step S3, the mapping rule base specifically refers to: The ecological belt design scheme for high pollution load areas is configured as follows: the ecological belt width is ≥15m, adopts a multi-layered vegetation structure of trees, shrubs and herbaceous plants, and is equipped with engineering reinforcement structures; The ecological zone design scheme for medium pollution load areas is configured as follows: the ecological zone width is 8-15m, and it adopts a shrub and herbaceous vegetation structure; The ecological zone design scheme for low pollution load areas is configured as follows: the ecological zone width is ≤8m, and it is mainly composed of herbaceous vegetation.

4. The pollution load classification buffer zone design method based on DEM according to claim 3, characterized in that, The width of the ecological zone is configured to correspond to the local slope. Dynamic related: The formula for calculating the width of the ecological belt design scheme in the high pollution load area is as follows: ; The formula for calculating the width of the ecological belt design scheme in the medium pollution load zone is as follows: ; The width of the ecological zone in the low-pollution load area is a fixed value. ≤8m, does not change with local slope.

5. The pollution load classification buffer zone design method based on DEM according to claim 1, characterized in that, In step S3, the vegetation configuration structure is defined by a three-dimensional vegetation configuration vector, which includes tree layer configuration parameters, shrub layer configuration parameters, and herb layer configuration parameters; wherein, the configuration parameters of each layer include at least species composition, planting density, and coverage. The sum of the tree layer coverage, shrub layer coverage, and herb layer coverage is ≤1; In the ecological zone design scheme of the high pollution load area, the coverage ratio of the tree layer, shrub layer, and herb layer is 0.2:0.3:0.5; In the ecological zone design scheme for medium pollution load areas, the coverage ratio of shrub layer to herb layer is 0.4:0.6, and no tree layer is set; In the ecological zone design scheme of low pollution load area, the herbaceous layer coverage rate is ≥0.9, the shrub layer coverage rate is ≤0.1, and no tree layer is set.

6. The pollution load classification buffer zone design method based on DEM according to claim 1, characterized in that, In step S3, the wavy terrain morphology parameters are expressed by a cross-sectional profile function along the direction of the ecological zone: in, Distance The ground design elevation at the location, As the reference elevation, Main wave amplitude, For wavelength, The amplitude of the secondary wave is given by k, where k is the pollution level. The phase angle; In the ecological zone design scheme of the high pollution load area , ; In the ecological zone design scheme of the medium pollution load area mentioned above , ; In the ecological zone design scheme of the low pollution load area .

7. The pollution load classification buffer zone design method based on DEM according to claim 1, characterized in that, In step S3, the engineering structural parameters include filter layer thickness, and the dimensions of the seepage trench; The ecological zone design scheme of the high pollution load area is equipped with a zeolite filter media layer and a crushed stone infiltration ditch. The zeolite filter media layer has a thickness of 0.3~0.5 meters and a particle size distribution of D50=2~5mm. The crushed stone infiltration ditch has a width of 0.5 meters and a depth of 0.6 meters, and is set every 20~30 meters along the direction of the ecological zone. The ecological zone design scheme for the medium pollution load area is equipped with a simple filter soil layer with a thickness of 0.1~0.2 meters. The filter material is coarse sand or fine gravel with a particle size distribution of D50=0.5~1mm. The ecological zone design scheme for the low-pollution load area does not include any engineering reinforcement structures.

8. The method for designing pollution load classification buffer zones based on DEM according to claim 1, characterized in that, In step S4, the parameter iterative optimization takes the dual objectives of maximizing comprehensive efficiency and minimizing engineering cost, and uses a genetic algorithm or a multi-objective particle swarm optimization algorithm to optimize the ecological zone width, vegetation coverage and engineering structure parameters; the comprehensive benefits are composed of a weighted average of purification efficiency and soil stabilization efficiency. In the optimization process, the ratio of comprehensive benefits to engineering costs is used as the optimization objective. When the number of consecutive iterations reaches a preset upper limit, or the rate of change of the fitness function value in a preset number of consecutive iterations is less than a preset threshold, it is determined that the convergence condition is met, the iteration is stopped, and the current optimal solution set is output.

9. The method for designing pollution load classification buffer zones based on DEM according to claim 1, characterized in that, In step S5, flood-tolerant and drought-resistant amphibian plant communities are configured in the water level fluctuation zone, and stepped ecological retention dams are added at the abrupt slope changes to form a dynamically adaptive ecological belt. The method for determining the key nodes is as follows: based on the pollution load classification map generated in step S2, the runoff outlets of each water catchment unit in the high pollution load zone are taken as primary key nodes; based on the surface runoff paths extracted in step S1, secondary key nodes are set at the intersection of two or more runoff paths; and tertiary key nodes are set at the boundary between high and medium pollution load zones, and at the cross-section where the width of the ecological belt changes.

10. The method for designing pollution load classification buffer zones based on DEM according to claim 1, characterized in that, In step S5, the specific method for generating engineering drawings based on the optimized design scheme is as follows: the optimized ecological belt width, vegetation configuration zoning, engineering structure parameters and wavy terrain parameters are automatically converted into vector layers based on the GIS platform, and the construction drawings are generated by calling the preset engineering drawing template; the monitoring sensors include water quality sensors and soil moisture meters; the dynamic adjustment of vegetation management strategies or local engineering structures based on real-time monitoring data includes: when the monitoring data shows that the pollutant concentration exceeds the preset threshold, the vegetation density is increased, the filter layer is thickened, or infiltration ditches are added.

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