Vegetation configuration adjustment method applicable to hilly and gully area

Abstract

The present invention relates to the technical field of soil and water conservation. Disclosed is a vegetation configuration adjustment method applicable to a hilly and gully area. The method comprises: on the basis of a digital elevation model and remote sensing image data of a target watershed, dividing the target watershed into a plurality of afforestation areas, wherein each afforestation area corresponds to one site type; conducting surveying and sampling on existing vegetation in the target watershed, and determining ecological service functions of the afforestation areas, wherein the ecological service functions comprise biodiversity, a water resource conservation function and a soil improvement function; on the basis of a soil loss amount of each area in the target watershed, determining the priority degree of water and soil loss control in each area; and for areas where ecological service functions of the existing vegetation in the target watershed do not match site types, using an analytic hierarchy process to adjust vegetation in the afforestation area in view of the priority degree of current water and soil loss control in the watershed. The present invention improves the efficiency of vegetation configuration.

Description

A method for adjusting vegetation configuration in hilly and gully areas Technical Field

[0001] This invention relates to the field of soil and water conservation technology, and in particular to a method for adjusting vegetation configuration in hilly and gully areas. Background Technology

[0002] The hilly and gully regions are characterized by undulating, fragmented terrain and severe soil erosion, heavily influenced by topographical factors. However, existing methods for determining the critical range of suitability have not adequately considered the interaction between soil moisture and vegetation. Forestry and grassland engineering designs and construction are often conducted on a small watershed basis. At the watershed scale, there is often more than one type of vegetation; in fact, it is often a composite of different systems such as forests, grasslands, and farmland. The spatial variability of vegetation, soil, and climate results in different runoff generation and confluence processes in different combinations of watersheds or regions, leading to significant differences in water balance, water quality, and water cycle patterns. Therefore, in the design and optimization of the vegetation pattern, it is necessary to determine the optimal combination ratio of forests and grasslands within the watershed while ensuring a certain vegetation cover and rationally utilizing soil moisture resources. It is essential to consider the quantitative allocation of water-appropriate vegetation patterns at the watershed scale under changing environments. However, simply considering water suitability is insufficient in vegetation construction schemes.

[0003] Summary of the Invention

[0004] The purpose of this invention is to provide a vegetation configuration adjustment method suitable for hilly and gully areas, reduce the error in artificial forest and grassland layout, and improve the efficiency of vegetation configuration.

[0005] To achieve the above objectives, the present invention provides the following solution:

[0006] A method for adjusting vegetation configuration in hilly and gully areas, comprising:

[0007] Based on the digital elevation model and remote sensing image data of the target watershed, the target watershed is divided into multiple afforestation areas, each corresponding to a site type;

[0008] The existing vegetation in each afforestation area within the target watershed was investigated and sampled to determine the ecosystem service functions of each afforestation area; the ecosystem service functions include biodiversity, water conservation, and soil improvement.

[0009] Based on the amount of soil loss in each afforestation area within the target watershed, the priority of soil and water conservation in each afforestation area is determined.

[0010] Based on the priority of soil and water conservation in each afforestation area, the vegetation in the afforestation areas within the target watershed where the ecological service function of the existing vegetation does not match the site type is adjusted using the analytic hierarchy process.

[0011] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0012] Based on the priority of soil and water conservation in each afforestation area, this invention sequentially adjusts the vegetation in afforestation areas where the ecological service function of existing vegetation does not match the site type within the target watershed using the analytic hierarchy process (AHP), thereby reducing errors in artificial forest and grassland layout and improving the efficiency of vegetation configuration. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 is a schematic flowchart of a vegetation configuration adjustment method applicable to hilly and gully areas provided by an embodiment of the present invention.

[0015] Figure 2 is a schematic diagram of the principle of a vegetation configuration adjustment method applicable to hilly and gully areas provided by an embodiment of the present invention;

[0016] Figure 3 is a schematic diagram of elevation classification provided in an embodiment of the present invention;

[0017] Figure 4 is a schematic diagram of slope grading provided in an embodiment of the present invention;

[0018] Figure 5 is a schematic diagram of slope aspect classification provided in an embodiment of the present invention;

[0019] Figure 6 is a schematic diagram of slope classification provided in an embodiment of the present invention;

[0020] Figure 7 is a schematic diagram of vegetation coverage grading provided in an embodiment of the present invention;

[0021] Figure 8 is a schematic diagram of soil erosion classification provided in an embodiment of the present invention;

[0022] Figure 9 is a schematic diagram of site type classification provided in an embodiment of the present invention;

[0023] Figure 10 is a schematic diagram of the water holding capacity of the semi-decomposition layer provided in an embodiment of the present invention;

[0024] Figure 11 is a schematic diagram of the water absorption rate of the semi-decomposition layer provided in an embodiment of the present invention;

[0025] Figure 12 is a schematic diagram of the water holding capacity of the decomposition layer provided in an embodiment of the present invention;

[0026] Figure 13 is a schematic diagram of the water absorption rate of the decomposition layer provided in an embodiment of the present invention;

[0027] Figure 14 is a schematic diagram of the available phosphorus content in the soil of an artificial forest provided in an embodiment of the present invention;

[0028] Figure 15 is a schematic diagram of the available potassium content in the soil of an artificial forest provided in an embodiment of the present invention;

[0029] Figure 16 is a schematic diagram of the available nitrogen content in the soil of an artificial forest provided in an embodiment of the present invention;

[0030] Figure 17 is a schematic diagram of the organic content of plantation soil provided in an embodiment of the present invention;

[0031] Figure 18 is a schematic diagram of the hierarchical structure model for adjusting the structure of plantations provided in an embodiment of the present invention;

[0032] Figure 19 is a schematic diagram of the artificial forest structure before adjustment according to an embodiment of the present invention;

[0033] Figure 20 is a schematic diagram of the adjusted structure of the plantation forest provided in an embodiment of the present invention. Detailed Implementation

[0034] 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.

[0035] The purpose of this invention is to provide a vegetation configuration adjustment method suitable for hilly and gully areas, reduce the error in artificial forest and grassland layout, and improve the efficiency of vegetation configuration.

[0036] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0037] Example 1

[0038] As shown in Figure 1, a vegetation configuration adjustment method applicable to hilly and gully areas in this embodiment includes the following steps.

[0039] Step 101: Based on the digital elevation model and remote sensing image data of the target watershed, the target watershed is divided into multiple afforestation areas, each afforestation area corresponding to a site type.

[0040] Step 102: Investigate and sample the existing vegetation in each afforestation area within the target watershed to determine the ecological service functions of each afforestation area; the ecological service functions include biodiversity, water conservation, and soil improvement.

[0041] Step 103: Determine the priority of soil and water conservation in each afforestation area based on the amount of soil loss in each afforestation area within the target watershed.

[0042] Step 104: Based on the priority of soil and water conservation in each afforestation area, the vegetation in the afforestation areas within the target watershed where the ecological service function of the existing vegetation does not match the site type is adjusted using the analytic hierarchy process.

[0043] As shown in Figure 2, the vegetation configuration adjustment method applicable to hilly and gully areas of the present invention is summarized into 4 calculation modules.

[0044] One module is for constructing a typical small watershed topographic database. By inputting Digital Elevation Model (DEM) data, remote sensing image data, etc., it is possible to perform topographic analysis and processing of typical small watersheds and classify site conditions.

[0045] The second module analyzes the current status of soil erosion in typical small watersheds and determines the space for remediation. Through a soil erosion estimation model, the current status of soil erosion in the region can be determined, and the current remediation needs can be determined based on the soil erosion intensity.

[0046] The three modules are for estimating the current forest and grassland pattern's ecosystem service functions. Through simple field surveys, sampling, and analysis, the current forest and grassland pattern's ecosystem service functions can be quantitatively estimated.

[0047] The fourth module focuses on the spatial pattern optimization of forestry and grassland projects in small watersheds. Based on the previous modules, the adjustment direction and governance objectives are determined, and then a hierarchical analysis model is constructed to determine the optimization scheme.

[0048] In step 101, the target watershed is a typical small watershed.

[0049] Step 101 includes constructing a topographic database for the target watershed, which includes topographic factors and land use and vegetation cover factors.

[0050] ① Classification of topographic factors

[0051] Based on a 1:10,000 topographic map of a small watershed, vectorization was performed using ArcGIS software to generate DEM data for the watershed. Alternatively, aerial surveys using unmanned aerial vehicles (UAVs) could be employed to obtain the topographic map. The elevation, aspect, and slope information of the watershed were extracted and classified using ArcGIS's analysis functions. Using ArcGIS's raster reclassification function, elevation was classified into 50m units. Slope was divided into the following levels: flat slope <5°, gentle slope 5°~15°, sloping slope 15°~25°, and steep slope >25°. Aspect was divided into 22.5° units, and clockwise from 0° (due north) to 360° (back to due north), a total of 16 levels were established. Based on the aspect classification standard, these 16 levels were divided into two aspect ranges: shady slope: North (337.5°~22.5°), Northeast (22.5°~67.5°), East (67.5°~22.5°), and Northwest (337.5°~22.5°). 5°~112.5°), Northwest (292.5°~337.5°); Sunny slopes: Southeast (112.5°~157.5°), West (247.5°~292.5°), South (157.5°~202.5°), Southwest (202.5°~247.5°); Based on the positive and negative topography of the watershed, the ridgeline of the watershed is divided, and eight site types are divided according to the topographic location, slope grade, and slope aspect conditions. Specifically, it is understood that the slope and slope aspect are first combined by permutation and combination, such as steep sunny slope, gentle sunny slope, sloping sunny slope, etc. After combination, the cases that do not actually exist are eliminated to obtain eight site types.

[0052] Site types include ridge tops, valleys, sunny gentle slopes, sunny sloping slopes, sunny steep slopes, shady gentle slopes, shady sloping slopes, and shady steep slopes.

[0053] ②Land use and vegetation cover factor acquisition

[0054] The land use map was generated using LANDSAT8 imagery (July 1, 2015, cloud cover 0.51, satellite has 11 bands, bands 1-7 and 9-11 have a spatial resolution of 30 meters, band 8 is a panchromatic band with a resolution of 15 meters, GCS_WGS_1984, datum D_WGS_1984, projection coordinate system Transverse_Mercator). After projection transformation, mosaic clipping, and raster registration, it was generated through unsupervised classification and visual interpretation. It was further supplemented by second-class survey data provided by the local forestry department and field surveys to conduct a change survey of land use data. Land use data refers to what is currently on the land, such as houses, farmland, or forest. For vegetation cover data, the Normalized Difference Vegetation Index (NDVI) was first calculated using the Transforms function in ENVI software. Then, the cumulative probability distribution of NDVI values ​​was calculated using the statistical function of ENVI software. The NDVI values ​​with cumulative probabilities of 5% and 90% were taken as the minimum vegetation index (NDVI). min) and maximum vegetation index (NDVI) max The vegetation cover map was calculated using the grid calculation function and formula (1). The calculated vegetation cover map was then reclassified. The classification criteria were <10% bare land, 10-35% low cover, 35-40% medium-low cover, 45-60% medium cover, and >60% high cover.

[0055] VFC = (NDVI - NDVI) min ) / (NDVI max -NDVI min (1)

[0056] In the formula: VFC represents vegetation cover; NDVI represents the vegetation cover percentage. min and NDVI max These are the maximum and minimum NDVI values, respectively.

[0057] Soil types were determined by collecting soil type maps and verifying them by consulting regional soil records and conducting on-site sampling; meteorological data were obtained from the China Meteorological Data Sharing Network and determined by combining real-time monitoring data from existing climate monitoring equipment within the basin.

[0058] Step 103 specifically includes determining the current status of soil erosion and the need for remediation.

[0059] Soil erosion data were calculated using the RUSLE model based on extracted vegetation cover, slope and slope length factors, and actual rainfall and soil physicochemical properties in the study area. The calculations were primarily performed using the raster calculator function in ArcGIS software. The calculated soil erosion was then reclassified, with the hydraulic erosion grading standards as follows: <1000 - slight erosion, 1000–2500 - mild erosion, 2500–5000 - moderate erosion, 5000–8000 - severe erosion, and 8000–15000 - extremely severe erosion.

[0060] The formulas for calculating soil loss in each region are as follows:

[0061] A = R × K × LS × C × P (2)

[0062] Where A is the average annual soil loss; R is the rainfall erosivity factor; K is the soil erodibility factor; LS is the slope length and slope factor; C is the vegetation cover and management factor; and P is the soil and water conservation measures factor.

[0063] Soil erodibility factor is expressed as:

[0064] K=[0.2+0.3exp[0.0256SAN(1-SIL / 100)]]×(SIL / (CLA+SIL))^0.3×

[0065] [1.0-0.25C / (C+exp(3.72-2.59C))]× (3)

[0066] [1.0-0.7SNI / (SNI+exp(-5.51+22.9SNI))]

[0067] Wherein, SAN represents sand content; SIL represents silt content; CLA represents clay content; C represents soil organic matter content; and SNI represents sand particle size index. Soil physicochemical property data were obtained through field sampling and laboratory testing.

[0068] Step 102 specifically includes estimating the current forest and grassland pattern's ecosystem service functions.

[0069] ①Biodiversity estimation

[0070] Field survey: A comprehensive survey of the natural conditions within the watershed, including climate, soil, and vegetation, was conducted. Based on the topographic features and vegetation configuration of the watershed, 20 standard plots were established within the small watershed. Each plot consisted of 30m×30m trees, 15m×15m shrubs, and 5 herbaceous plots (1m×1m) at the four corners and center of each standard plot. Stand factors such as tree height and crown width were measured for the trees within each standard plot. Detailed records were kept of tree species, stand age, canopy closure / coverage, density, soil thickness, slope, aspect, slope position, tree species composition, and geographical location. Herbaceous plant height, cover, frequency, and dominance were recorded separately for each species. All herbaceous material was harvested and brought back to the laboratory. Litter was harvested in layers, separating the undecomposed and semi-decomposed layers.

[0071] Biodiversity includes diversity index, dominance index, and evenness index.

[0072] Biodiversity calculation:

[0073] Importance value = (relative density + relative coverage + relative frequency) / 3.

[0074] Vegetation community diversity indices were analyzed using the Shannon-Wiener diversity index, Simpson dominance index, and Pielou evenness index, with the following formulas:

[0075] The diversity index is expressed as: H = ∑P i InP i (4)

[0076] The dominance index is expressed as: SP = 1 - ∑P i 2 (5)

[0077] The uniformity index is represented by J sw =H / InS (6)

[0078] Patrick Index: S (7)

[0079] Where H is the diversity index, P i P is an intermediate parameter. i =N i / N,N i is the importance value of the i-th plant in the quadrat; N is the sum of the importance values ​​of all plants in the quadrat; SP is the dominance index; J sw The evenness index is represented by S, where S is the number of species.

[0080] ②Estimation of water conservation function

[0081] Water conservation functions include effective water retention capacity and soil water holding capacity, which includes maximum soil water holding capacity and non-capillary soil water holding capacity.

[0082] The volume of litter was determined by the drying method; the water holding capacity was determined by the soaking method; the formulas for calculating the maximum water holding capacity and effective water retention capacity are as follows:

[0083] W = (0.85R) m -R0)×M (8)

[0084] Wsv=(R M -R0)×0.85 (9)

[0085] S M =10000hP j S f =10000hP f (10)

[0086] Where W represents the effective water retention capacity, Wsv represents the water storage capacity, R0 represents the natural moisture content (%), and R m M represents the maximum water holding capacity (%), and M represents the litter layer volume (t·hm). -2 ), S M Soil maximum water holding capacity (t / hm) 2 );S f Soil noncapillary water holding capacity (t / hm) 2 h is the soil layer thickness (m); P j Total soil porosity (%); P f The value represents the non-capillary porosity of the soil (%).

[0087] ③Estimation of soil improvement function

[0088] Soil profiles were excavated within the study area, and soil samples were collected in layers of 0–20 cm, 20–40 cm, and 40–60 cm. These samples were then brought back to the laboratory and air-dried for later use. Laboratory experiments included: soil moisture content was determined using the oven-drying method; soil bulk density was determined using the ring sampler method; soil mechanical composition was determined using a hydrometer rapid measurement method; and particle size classification was performed using the Karl von Willebrand system. Simultaneously, soil physical properties such as bulk density were determined using the ring sampler method; organic carbon was determined using the potassium dichromate-concentrated sulfuric acid external heating method; total nitrogen was determined using the semi-micro Kjeldahl distillation method; available phosphorus was determined using the sodium bicarbonate extraction molybdenum-antimony colorimetric method; available potassium was determined using the ammonium acetate extraction flame photometric method; pH was determined using a pH meter potentiometric method; and litter was determined using the immersion method.

[0089] Soil improvement functions include capillary porosity, soil layer thickness, silt content, organic matter content, total nitrogen content, electrical conductivity, moisture content, and available phosphorus content.

[0090] Step 104 involves optimizing the spatial pattern of forestry and grassland projects in the target watershed.

[0091] For determining whether the ecological service functions of existing vegetation in the afforestation area within the target watershed match the site type: the range of ecological service functions that match the site type is stored in advance. If the ecological service functions of the existing vegetation in the afforestation area are within the range of ecological service functions that match the corresponding site type, then they match; otherwise, they do not match.

[0092] For example, sunny slopes are sunny but windy and dry, making them suitable for planting shrubs. However, in reality, trees are planted instead. Although the trees survive, they do not grow well and do not form a forest, thus failing to fulfill their ecological functions.

[0093] For example, if a shady slope is suitable for planting coniferous trees but is instead planted with economic forests, the economic forests will not receive enough sunlight and will not generate economic benefits.

[0094] This involves comparing the ecological functions of the same tree species under different site conditions. For example, the ecological function of Pinus tabuliformis should be 1 in a suitable area, but only 0.5 in an unsuitable area, so adjustments are needed.

[0095] The hierarchical structure for adjusting the vegetation in this region using the Analytic Hierarchy Process (AHP) includes a target layer, a strategy layer, an intermediate layer, and a measure layer. The target layer represents the aligned allocation of soil and water conservation vegetation in the target area. The strategy layer includes ecological function, economic benefits, and spatial requirements. The intermediate layer includes multiple vegetation zones, and the measure layer includes multiple vegetation types. The aligned allocation of soil and water conservation vegetation in the target area represents its ranking among multiple regions. In the strategy layer, ecological function, economic benefits, and spatial requirements represent the weights of vegetation allocation in terms of ecological function, economic benefits, and spatial requirements, respectively (initial values ​​are known), and subsequent optimization is performed using the AHP.

[0096] The relative weights of the current layer elements to each element in the previous layer are known in advance.

[0097] Based on data obtained from field experiments and the establishment of a small watershed attribute database, site types were classified in the small watersheds using spatial analysis and overlay functions of GIS software. The current vegetation status was evaluated, identifying unreasonable aspects of the existing configuration. The Analytic Hierarchy Process (AHP) was used to determine the appropriate proportion of plantations. The inputs to the AHP included the current proportions or weights of various forest land areas in the afforestation area, and the output was the optimized forest land area or weights for the afforestation area. The steps of the AHP are as follows.

[0098] Based on the hierarchical structure, a pairwise comparison judgment matrix is ​​constructed. For a given unit in the upper level, the relative importance of related units in the current level is compared. Let the upper level be A and the current level be B. Using the Delphi method, relevant experts are invited to conduct pairwise comparisons of the importance of indicators according to the importance scale in Table 2 and its corresponding meanings to determine the importance of this level to the upper level. The degree of influence of this element on the upper level is then ranked to construct the judgment matrix. The form of the AB judgment matrix is ​​shown in Table 1.

[0099] Table 1. Judgment Matrix Form Table

[0100] Among them, B1, B2, B i b represents the 1st, 2nd, and ith elements in the hierarchy, respectively. 12 This indicates the relative importance of B2 compared to B1. For example, if a certain site type requires soil erosion control more than economic development, then soil erosion control is more important. 1i b 21 Category b (meaning) 12 .

[0101] Table 2 Importance Scale and Meaning

[0102] For the judgment matrices completed by experts, a hierarchical single-ranking method is used to assign the relative weights of each factor in each judgment matrix to its respective criterion. However, during the hierarchical ranking, a consistency check must be performed on the judgment matrices. Only after passing the check can it be concluded that the judgment matrices are logically reasonable, and only then can the results be further analyzed.

[0103] The formula for calculating the consistency index (CI) is:

[0104] CI=(λ max -n) / (n-1) (11)

[0105] Where, λ max Let n denote the largest eigenvalue, and n be the order of the square matrix.

[0106] The corresponding average random consistency index RI is determined by looking up the table, based on the different orders of the judgment matrix, where n is the number of sample indices.

[0107] Table 3. Random Consistency Index Values

[0108] Finally, the consistency ratio is calculated using the formula.

[0109] CR = CI / RI (12)

[0110] When CR < 0.1, the consistency of the judgment matrix is ​​considered acceptable. When CR > 0.1, the judgment matrix is ​​considered not to meet the consistency requirements and needs to be revised.

[0111] The following specific example illustrates a vegetation configuration adjustment method applicable to hilly and gully areas according to the present invention.

[0112] The vegetation configuration adjustment method of the present invention, applicable to hilly and gully areas, was applied to a small watershed in the sandstone area of ​​Inner Mongolia to verify its effectiveness.

[0113] 1. Construction of Small Watershed Attribute Database

[0114] ①Topographic factor classification

[0115] The study area is characterized by hilly and gully topography. The selected typical watershed is long and narrow, sloping from northwest to southeast. As shown in Figure 3, the watershed elevation ranges from 1145 to 1324.63 m. Dividing the elevation into four levels at 50 m intervals, the total elevation of the watershed is 2.07 km². 2 The area is located in a zone with an altitude between 1145 and 1195 meters, spanning 5.76 km. 2 The area is distributed in the range of 1195–1245 m, with a total length of 4.37 km. 2 The area is distributed in the range of 1245–1295 m, with a length of 0.43 km. 2 The area is distributed within a range of 1295–1345 m. As shown in Figure 4, the slope of the watershed ranges from 0 to 35°, with gentle slopes (5–15°) dominating the terrain, covering an area of ​​6.47 km². 2 Secondly, the area of ​​sloping terrain (15-25°) is 3.97 km². 2 The area with relatively few flat slopes (<5°) is 1.60 km². 2 The area of ​​steep slopes (25-35°) is at least 0.59 km². 2 .

[0116] As shown in Figure 5, based on the slope aspect classification, the topography of the studied watershed runs from northwest to southeast, with the eastern half of the watershed slightly smaller than the western half. Therefore, the area of ​​its shady slope is relatively small, at 5.49 km². 2 The sunny slope has a larger area of ​​7.18 km². 2 The slope position of the watershed can be simplified into slope surface, valley, and ridge crest. As shown in Figure 6, the maximum slope area of ​​the watershed is 12.02 km². 2 The relative areas of the valleys and ridge tops are relatively small, at 0.39 km². 2 and 0.26km 2 .

[0117] ②Land use and vegetation cover factor acquisition

[0118] Figure 7 shows the vegetation cover classification map of the watershed, indicating that the bare land area is 0.54 km². 2 This accounts for only 4% of the watershed area. The area of ​​low-coverage land is 2.37 km². 2 This accounts for 18.7% of the drainage area. The area with medium to low water coverage is 2.94 km². 2 It accounts for 23.20% of the drainage area. The medium coverage area is 3.00 km². 2 It accounts for 23.68% of the drainage area. The high-coverage area is 3.80 km². 2 It accounts for 30% of the watershed area.

[0119] 2. Determination of the current status of soil erosion and the need for remediation

[0120] Figure 8 shows the soil erosion classification of the watershed. It can be seen that the soil erosion intensity in the studied watershed is mainly mild, primarily distributed on gently sloping areas with high vegetation cover, covering an area of ​​10.62 km². 2 This area accounts for 83.8% of the watershed area; the slightly eroded zone is mainly distributed in the moderately vegetated area of ​​the slope, covering an area of ​​1.49 km². 2 This accounts for 11.76% of the watershed area; the moderately eroded area is mainly distributed in the low to medium vegetation cover area of ​​the slope, covering an area of ​​0.37 km². 2 This accounts for 3.20% of the drainage area; the area of ​​severe erosion is mainly concentrated in the low-coverage area, covering 0.04 km². 2 This accounts for 0.32% of the drainage area; extremely severe erosion is mainly concentrated on steep slopes and bare land, covering an area of ​​0.01 km². 2 It accounts for 0.01% of the drainage area.

[0121] The typical small watersheds in the study area can be classified into eight types according to topographic location, slope grade, and slope aspect: ridge top, gully, sunny gentle slope, sunny sloping slope, sunny steep slope, shady gentle slope, shady sloping slope, and shady steep slope, as shown in Figure 9. The area of ​​the ridge top type is 0.28 km². 2 The valley area is 0.42 km² 2 The area of ​​the sunny, gentle slope is 4.35 km². 2 The area of ​​the sunny slope is 1.80 km². 2 The area of ​​the sunny, steep slope is 0.12 km². 2 The area of ​​the shady, gentle slope is 3.37 km². 2 The area of ​​the shady slope is 2.01 km². 2 The area of ​​the shady, steep slope is 0.26 km². 2 Due to severe bedrock exposure in the sandstone region, the overlying soil layer is uneven in thickness, and beneath the overlying soil layer lies a weathered bedrock layer. This layer possesses the physical and chemical properties of soil and can provide a substrate environment and hydrothermal conditions for vegetation growth. Therefore, based on the different soil layer thicknesses, the site types in typical watersheds of the sandstone region should be subclassified according to soil layer thickness. Within each site type, three subclasses are further divided: shallow soil (<30cm), medium soil (30–80cm), and thick soil (>80cm). The scale of Figures 3-9 is 1:50,000.

[0122] From the perspective of slopes and gullies within the watershed, severe soil erosion occurs primarily on steep slopes, exposed bedrock areas, and gully slopes. These areas are key zones for soil and water conservation, with the focus on preventing soil erosion and controlling gully bank expansion and channel erosion. Soil erosion is relatively weaker on sloping and gentle slopes, where soil water and fertilizer conditions are better. Economic forests can be appropriately developed while ensuring controllable soil and water loss. Although the slopes of ridges and hilltops are gentle, they face severe wind erosion, and the soil-vegetation ecosystem is fragile and at high risk of destruction. Therefore, the focus of conservation efforts is on controlling wind and water erosion and improving the stability of the vegetation ecosystem. Gully areas have better soil water and heat conditions than ridges and hilltops, but due to exposed bedrock in the upstream gullies, wind, water, freeze-thaw, and gravity erosion occur frequently, resulting in severe gully erosion. During heavy rains, large amounts of high-sediment-laden water flow are generated in the gullies, exerting a strong scouring effect on the gully bottom. Therefore, the focus of conservation efforts should be on preventing gully bottom scouring and reducing flood velocity and sediment content.

[0123] 3. Estimation of the ecological service functions of the current forest and grassland pattern

[0124] ①Biodiversity estimation

[0125] Table 4 shows the species importance values ​​of the herbaceous layer under different types of plantations. From the perspective of biodiversity restoration, the *Prunus armeniaca* forest has the richest species, followed by *Caragana korshinskii* forest, while *Pinus tabuliformis* forest has the fewest species. However, the herbaceous species community structure under *Pinus tabuliformis* forest is more uniform and stable, with less uncertainty in individual occurrence. The herbaceous species community structure under *Caragana korshinskii* forest exhibits a higher overall dominance. Topography has a significant impact on herbaceous species under plantations. The hydrothermal conditions on shady slopes are more conducive to the growth and development of herbaceous plants and the restoration of biodiversity. Mixed forests can regulate the growth and development of herbaceous plants under the forest canopy by improving canopy closure, indirectly mitigating the impact of slope aspect differences to some extent. In typical watersheds of the sandstone region, the biodiversity of the herbaceous layer in plantations decreases with increasing slope, limiting the biodiversity restoration function of plantations. Therefore, in the initial stage of afforestation and land preparation on steep slopes, disturbance to the surface should be minimized to avoid damaging the original vegetation.

[0126] Table 4. Species importance values ​​(partial) of the understory herbaceous layer in different types of plantations.

[0127] ②Estimation of water conservation function

[0128] From the perspective of forest land's water conservation function, arbor forests have a stronger litter accumulation capacity than shrub forests, with Pinus tabuliformis forests exhibiting the strongest water retention capacity. Furthermore, the soil under Pinus tabuliformis forests have a lower bulk density and higher total porosity compared to other forest stands, indicating that Pinus tabuliformis has a superior soil improvement ability compared to other tree species. This results in a looser soil structure that can hold more capillary water, which is beneficial for vegetation growth and development. Mixing Pinus tabuliformis with Hippophae rhamnoides and Prunus armeniaca can improve the internal structure and composition of the litter layer, increasing the water retention capacity of the litter. The water retention capacity of litter is influenced not only by tree species but also by topography and the configuration of the plantation. The average litter accumulation of plantations on shady slopes is significantly higher than that on sunny slopes, with the water retention capacity of litter in shady slope plantations being approximately 1.33 times that of sunny slopes. The litter accumulation of plantations on level slopes is significantly higher than that on other slope grades, with no significant difference between gentle and sloping slopes. However, the litter accumulation of plantations on steep slopes is significantly lower than that on other slope grades, with a water retention capacity reduced by 35% compared to plantations on level slopes. The water holding capacity and water absorption rate of the semi-decomposition layer and the decomposition layer are shown in Figures 10-13.

[0129] ③Estimation of soil improvement function

[0130] From the perspective of soil quality improvement, the soil nutrients in all plantations in the study watershed were generally low, and the soil fertility conditions were poor. Eight indicators selected using principal component analysis and the minimum dataset method—capillary porosity, soil layer thickness, silt content, organic matter content, total nitrogen content, electrical conductivity, moisture content, and available phosphorus content—can be used as the minimum dataset for evaluating soil quality in typical small watershed plantations in the sandstone region. Overall, soil quality showed a pattern of shrubland being better than tree forest, which was better than mixed forest. The soil quality ranking for each forest type was as follows: sea buckthorn forest, Caragana korshinskii forest, Prunus armeniaca forest, Pinus tabuliformis forest, Pinus tabuliformis × Prunus armeniaca forest, and Pinus tabuliformis × sea buckthorn forest. With increasing slope, the overall soil quality of all plantations in the study area showed a decreasing trend. The available phosphorus, available potassium, available nitrogen, and organic matter contents of the plantation soils are shown in Figures 14-17.

[0131] 4. Optimization of the spatial pattern of forestry and grassland projects in small watersheds

[0132] ① Construction of the indicator system

[0133] This invention, taking into account the unique geographical conditions of small watersheds in the sandstone region, establishes a hierarchical structure. The target layer A is the symmetrical configuration of soil and water conservation vegetation in typical small watersheds of the sandstone region. The strategy layer B is selected based on economic, social, and ecological benefits. The intermediate layer C is composed of steep slope shelterbelts, gully edge shelterbelts, gully bottom shelterbelts, gentle slope economic forests, and gentle slope grazing forests suitable for vegetation configuration in the sandstone region. The corresponding measure layer D is composed of six tree species configuration patterns: sea buckthorn, caragana, pine, apricot, pine × apricot, and pine × sea buckthorn. The specific hierarchical structure is shown in Figure 18.

[0134] ② Determining Evaluation Weights

[0135] Based on the establishment of a hierarchical structure of vegetation alignment for soil and water conservation in typical small watersheds of the sandstone region, relevant experts were invited to fill out a questionnaire to establish a judgment matrix. Then, the maximum eigenvector of the matrix was calculated using the sum-product method, and a consistency test was performed to determine the weight of each evaluation index.

[0136] (1) Determining the weights of strategy-level indicators

[0137] Relative importance of strategy layer to target layer

[0138] Table 5 AB Judgment Matrix

[0139] Table 5 shows the A / B layer judgment matrix. The consistency ratio CR = 0.9789 < 0.1, indicating that the consistency of the target layer A is acceptable. The final target layer weights are determined as A = (B1, B2, B3) = [0.4062, 0.3403, 0.2534]. These weights are determined through pairwise comparison of the importance of each indicator. The main objective of the artificial forest structure adjustment in the typical small watershed of the sandstone area remains soil and water conservation. With the improvement of the watershed's ecological environment, the vegetation configuration objectives are shifting towards enhancing economic and social benefits. Therefore, the economic benefits after this artificial forest structure adjustment are second only to ecological benefits.

[0140] (2) Determining the weights of strategy-level indicators

[0141] Relative importance of strategy layer to target layer

[0142] Table 6 C-B1 Judgment Matrix

[0143] Table 6 shows the judgment matrix for layer C-B1. The consistency ratio CR = 0.2259 < 0.1, indicating that the consistency of strategy layer B is acceptable. The final target layer weights are determined as B1 = (C1, C2, C3, C4, C5) = [0.3490, 0.0914, 0.1818, 0.2638, 0.1139]. The comparative results of the ecological benefits of each forest type are as follows: steep slope shelterbelt, gully bottom shelterbelt, gully edge shelterbelt, gentle slope grazing forest, and gentle slope economic forest. CR is the same as CR.

[0144] Table 7 C-B2 Judgment Matrix

[0145] Table 7 shows the judgment matrix for the C-B2 layer. The consistency ratio CR = 0.1636 < 0.1, indicating that the consistency of the strategy layer B is acceptable. The final target layer weight is determined as B2 = (C1, C2, C3, C4, C5) = [0.0627, 0.4326, 0.0437, 0.1280, 0.3330]. The comparison results of the economic benefits of each forest type are as follows: economic forest on gentle slopes, grazing forest on gentle slopes, bottom protection forest in gullies, protection forest on steep slopes, and protection forest on the edge of gullies.

[0146] Table 8 C-B3 Judgment Matrix

[0147] Table 8 shows the judgment matrix for the C-B3 layer. The consistency ratio CR = 0.1027 < 0.1, indicating that the consistency of the strategy layer B is acceptable. The final target layer weight is determined as B3 = (C1, C2, C3, C4, C5) = [0.1175, 0.3904, 0.0939, 0.1256, 0.2726]. The comparison results of the social benefits of each forest type are as follows: economic forest on gentle slopes, grazing forest on gentle slopes, bottom protection forest in gullies, protection forest on steep slopes, and protection forest on the edge of gullies.

[0148] (3) Determining the weights of intermediate layer indicators

[0149] The relative importance of the intermediate layer to the strategy layer

[0150] Table 9 D-C1 Judgment Matrix

[0151] Table 9 shows the judgment matrix for layer D-C1. The consistency ratio CR = 0.1164 < 0.1, indicating that the consistency of strategy layer B is acceptable. The final target layer weight is determined as C1 = (D1, D2, D3, D4, D5, D6) = [0.3499, 0.3816, 0.0589, 0.0473, 0.0566, 0.1058]. The comparison results of each tree species configuration for steep slope shelterbelts are as follows: Caragana korshinskii, Hippophae rhamnoides, Pinus tabuliformis × Hippophae rhamnoides, Prunus armeniaca, Pinus tabuliformis × Prunus armeniaca, Pinus tabuliformis.

[0152] Table 10 D-C2 Judgment Matrix

[0153] Table 10 shows the judgment matrix for the D-C2 layer. The consistency ratio CR = 0.1971 < 0.1, indicating that the consistency of strategy layer B is acceptable. The final target layer weight is determined as C2 = (D1, D2, D3, D4, D5, D6) = [0.1232, 0.1636, 0.4041, 0.0287, 0.2196, 0.0608]. The comparison results for each tree species configuration as a gentle slope economic forest are as follows: Prunus armeniaca, Pinus tabuliformis × Prunus armeniaca, Caragana korshinskii, Hippophae rhamnoides, Pinus tabuliformis × Hippophae rhamnoides, Pinus tabuliformis.

[0154] Table 11 D-C3 Judgment Matrix

[0155] Table 11 shows the judgment matrix for layer D-C3. The consistency ratio CR = 0.0496 < 0.1, indicating that the consistency of strategy layer B is acceptable. The final target layer weight is determined as C3 = (D1, D2, D3, D4, D5, D6) = [0.3949, 0.3710, 0.0415, 0.0410, 0.0410, 0.1106]. The comparison results for each tree species configured as gully edge shelterbelts are as follows: Hippophae rhamnoides, Caragana korshinskii, Pinus tabuliformis × Hippophae rhamnoides, Prunus armeniaca, Pinus tabuliformis × Prunus armeniaca, Pinus tabuliformis.

[0156] Table 12 D-C4 Judgment Matrix

[0157] Table 12 shows the judgment matrix for layer D-C4. The consistency ratio CR = 0.1564 < 0.1, indicating that the consistency of strategy layer B is acceptable. The final target layer weight is determined as C4 = (D1, D2, D3, D4, D5, D6) = [0.5283, 0.1607, 0.0654, 0.0608, 0.0590, 0.1259]. The comparison results of each tree species configuration as a bottom shelterbelt are as follows: Hippophae rhamnoides, Caragana korshinskii, Pinus tabuliformis × Hippophae rhamnoides, Prunus armeniaca, Pinus tabuliformis, Pinus tabuliformis × Prunus armeniaca.

[0158] Table 13 D-C5 Judgment Matrix

[0159] Table 13 shows the judgment matrix for layer D-C5. The consistency ratio CR = 0.0715 < 0.1, indicating that the consistency of strategy layer B is acceptable. The final target layer weight is determined as C5 = (D1, D2, D3, D4, D5, D6) = [0.0335, 0.5432, 0.1479, 0.1045, 0.1125, 0.0583]. The comparison results of the tree species configurations for gentle slope grazing forests are as follows: Caragana korshinskii, Prunus armeniaca, Pinus tabuliformis × Prunus armeniaca, Pinus tabuliformis, Pinus tabuliformis × Hippophae rhamnoides, Hippophae rhamnoides.

[0160] ③ Adjustment of plantation structure

[0161] The final plantation structure of a typical small watershed in the sandstone area was calculated using the analytic hierarchy process (AHP). The adjusted weights of each level in the study area are shown in Table 14. The weights of the strategy level were: ecological benefits (0.4062) > economic benefits (0.3403) > social benefits (0.2534). The weights of forest species structure were as follows: steep slope shelterbelt (0.1929), gully edge shelterbelt (0.1125), gully bottom shelterbelt (0.1826), gentle slope economic forest (0.2833), and gentle slope grazing forest (0.2287). The order of tree species structure weights was: Caragana korshinskii (0.3153) > Hippophae rhamnoides (0.2510) > Prunus armeniaca (0.1763) > Pinus tabuliformis × Prunus armeniaca (0.1142) > Pinus tabuliformis × Hippophae rhamnoides (0.0864) > Pinus tabuliformis (0.0569).

[0162] Table 14 Weights at Each Level

[0163] Comparing the spatial distribution maps of forest land in the watershed before and after the adjustment (Figures 19 and 20), the original sea buckthorn forest accounted for 34.46% of the total forest area, while the adjusted forest area accounted for 25.1%, a decrease of 9.36%. The original Caragana korshinskii forest accounted for 26.85% of the total forest area, while the adjusted forest area accounted for 31.53%, an increase of 4.68%. The original Pinus tabuliformis forest accounted for 22.24% of the total forest area, while the adjusted forest area accounted for 5.69%, a decrease of 16.55%. The original Prunus armeniaca forest accounted for 11.62% of the total forest area, while the adjusted forest area accounted for 17.63%, an increase of 6.02%. The remainder consisted of two types of mixed tree-shrub forests: the original Pinus tabuliformis × Prunus armeniaca mixed forest accounted for 3.61% of the total forest area, while the adjusted forest area accounted for 11.42%, an increase of 7.81%; and the original Pinus tabuliformis × sea buckthorn mixed forest accounted for 1.28% of the total forest area, while the adjusted forest area accounted for 8.64%, an increase of 7.36%.

[0164] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0165] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for adjusting vegetation configuration in hilly and gully areas, characterized in that, include: Based on the digital elevation model and remote sensing image data of the target watershed, the target watershed is divided into multiple afforestation areas, each corresponding to a site type; The existing vegetation in each afforestation area within the target watershed was investigated and sampled to determine the ecosystem service functions of each afforestation area; the ecosystem service functions include biodiversity, water conservation, and soil improvement. Based on the amount of soil loss in each afforestation area within the target watershed, the priority of soil and water conservation in each afforestation area is determined. Based on the priority of soil and water conservation in each afforestation area, the vegetation in the afforestation areas within the target watershed where the ecological service function of the existing vegetation does not match the site type is adjusted using the analytic hierarchy process.

2. The vegetation configuration adjustment method applicable to hilly and gully areas according to claim 1, characterized in that, The site types include ridge tops, valleys, sunny gentle slopes, sunny sloping slopes, sunny steep slopes, shady gentle slopes, shady sloping slopes, and shady steep slopes.

3. The vegetation configuration adjustment method applicable to hilly and gully areas according to claim 1, characterized in that, The formula for calculating soil loss in each region is: A = R × K × LS × C × P; Where A is the average annual soil loss; R is the rainfall erosivity factor; K is the soil erodibility factor; LS is the slope length and slope factor; C is the vegetation cover and management factor; and P is the soil and water conservation measures factor.

4. The vegetation configuration adjustment method applicable to hilly and gully areas according to claim 3, characterized in that, The soil erodibility factor is expressed as: K=[0.2+0.3exp[0.0256SAN(1-SIL / 100)]]×(SIL / (CLA+SIL))^0.3× [1.0-0.25C / (C+exp(3.72-2.59C))]×[1.0-0.7SNI / (SNI+exp(-5.51+22.9SNI))] Wherein, SAN is the sand content; SIL is the silt content; CLA is the clay content; C is the soil organic matter content; and SNI is the sand particle index.

5. The vegetation configuration adjustment method applicable to hilly and gully areas according to claim 1, characterized in that, The biodiversity includes diversity index, dominance index, and evenness index; The diversity index is expressed as: H = ∑P i InP i ; The dominance index is expressed as: The uniformity index is expressed as: J sw =H / InS; Where H is the diversity index, P i P is an intermediate parameter. i =N i / N,N i is the importance value of the i-th plant in the quadrat; N is the sum of the importance values ​​of all plants in the quadrat; SP is the dominance index; J sw The evenness index is represented by S, where S is the number of species.

6. The vegetation configuration adjustment method applicable to hilly and gully areas according to claim 1, characterized in that, The water conservation function includes effective water retention capacity and soil water holding capacity, and the soil water holding capacity includes maximum soil water holding capacity and non-capillary soil water holding capacity. The effective interception capacity is expressed as: W = (0.85R) m -R0)×M; The maximum water holding capacity of the soil is expressed as: S M =10000hP j ; The soil noncapillary water holding capacity is expressed as: S f =10000hP f ; Where W represents the effective water retention capacity, R0 represents the natural moisture content, and R m M represents the maximum water holding capacity, and S represents the volume of litter layer. M S is the maximum water holding capacity of the soil. f ρ represents noncapillary water holding capacity of the soil; h represents soil layer thickness; P represents... j Total porosity of soil; P f This refers to the non-capillary porosity of the soil.

7. The vegetation configuration adjustment method applicable to hilly and gully areas according to claim 1, characterized in that, The soil improvement functions include capillary porosity, soil layer thickness, silt content, organic matter content, total nitrogen content, electrical conductivity, moisture content, and available phosphorus content.

8. The vegetation configuration adjustment method applicable to hilly and gully areas according to claim 1, characterized in that, The hierarchical structure for adjusting the vegetation in the afforestation area using the analytic hierarchy process includes a target layer, a strategy layer, an intermediate layer, and a measure layer. The target layer is the locational configuration of soil and water conservation vegetation in the target area. The strategy layer includes ecological functions, economic benefits, and spatial requirements. The intermediate layer includes multiple vegetation zones, and the measure layer includes multiple vegetation types.

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