Degenerated grassland ecological restoration method and system based on ecological water demand inside and outside rivers and lakes

Abstract

The invention discloses a degraded grassland ecological restoration method and system based on ecological water demand inside and outside rivers and lakes, and the method comprises the steps: carrying out field investigation, analyzing main characteristics of a degraded grassland, and carrying out degradation grade region division, the main characteristics including but not limited to vegetation coverage, species diversity index and soil bulk density; grid division of ecological units is carried out based on terrain self-adaption; according to water resource allocation, grassland restoration, grazing management and economic benefits, constructing a degraded grassland ecological restoration multi-objective function and constraint conditions based on ecological water demands inside and outside rivers and lakes; on the basis of ecological water demand inside and outside rivers and lakes, in combination with a specific grassland degradation level of a degradation area, according to a multi-objective function and constraint conditions, carrying out restoration priority ranking, dynamic adjustment strategy and water resource dynamic adjustment to obtain an optimal degraded grassland ecological restoration scheme; the method is a comprehensive ecological restoration scheme combining water resource utilization, ecological water demand, grazing management and economic benefits, and sustainable restoration of the grassland is promoted.

Description

Technical Field

[0001] The present invention relates to the field of ecological restoration technology, in particular to the field of degraded grassland ecological restoration, and more specifically to a degraded grassland ecological restoration method and system based on ecological water demand inside and outside rivers and lakes. Background Art

[0002] Grassland ecosystems are important carbon sinks and water conservation areas globally, but due to factors such as overgrazing and climate change, grasslands around the world are facing varying degrees of degradation. The ecological functions of degraded grasslands have been severely lost, leading to a series of problems such as soil erosion, reduced species diversity, and degradation of ecosystem service functions. Severely degraded grasslands are especially difficult to restore and require a large amount of resource investment.

[0003] At present, grassland ecological restoration technology mostly relies on a single restoration method, ignoring the optimal allocation of water resources, the scientific design of grazing systems and the long-term stability of the ecosystem.

[0004] Therefore, how to propose a comprehensive ecological restoration plan that combines water resource utilization, ecological water demand, grazing management and economic benefits to help promote the sustainable restoration of grasslands is an urgent problem that technicians in this field need to solve. Summary of the Invention

[0005] In view of this, the present invention provides a method and system for ecological restoration of degraded grasslands based on the ecological water demand inside and outside rivers and lakes to solve some of the technical problems mentioned in the background technology.

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

[0007] A method for ecological restoration of degraded grasslands based on ecological water demand inside and outside rivers and lakes, comprising the following steps:

[0008] S1. Conduct field surveys and classify degraded grasslands into different degradation levels by analyzing their main characteristics, including but not limited to vegetation cover, species diversity index, and soil bulk density;

[0009] S2. Divide the divided area into ecological units based on terrain adaptation;

[0010] S3. Construct a multi-objective function and constraints for degraded grassland ecological restoration based on the ecological water requirements within and outside rivers and lakes, based on the needs of water resource allocation, grassland restoration, grazing management, and economic benefits.

[0011] S4. Based on the ecological water demand inside and outside rivers and lakes, combined with the specific grassland degradation level in the degraded area, based on the constructed multi-objective function and constraints, carry out restoration priority sorting, and formulate dynamic adjustment strategies and dynamic water resource allocation plans, and finally form a sustainable degraded grassland ecological restoration plan based on the ecological water demand inside and outside rivers and lakes.

[0012] Preferably, in step S1, the degraded grassland is divided into severely degraded areas, moderately degraded areas and slightly degraded areas according to degradation levels.

[0013] Preferably, step S1 further comprises using K-means clustering to analyze historical degradation data, and calibrating the cutoff point in combination with the regional background value.

[0014] Preferably, the specific contents of step S2 include:

[0015] S21. Extract watershed boundaries, slopes, and soil types using GIS to generate irregular ecological units;

[0016] S22. Make dynamic adjustments based on drone aerial survey data to ensure the integrity of ecological processes within the unit;

[0017] S23. Divide irregular ecological units into grid units and customize independent management strategies for each grid.

[0018] Preferably, in step S3, the objective function includes an ecological benefit maximization objective function, a water resource consumption minimization objective function, a dynamic grazing management objective function, and an economic cost minimization objective function; and the constraint conditions include water resource constraints, vegetation community constraints, space continuity constraints, measure mutual exclusion constraints, and seasonal grazing carrying capacity constraints.

[0019] Preferably, the ecological benefit maximization objective function is:

[0020]

[0021] Among them, F1 is the ecological benefit index, F evg，ij is the vegetation restoration potential index, E soil，ij is the soil improvement index, x ij The jth strategy implemented for the i-th grid;

[0022] The objective function for minimizing water resource consumption is:

[0023]

[0024] Among them, F2 is water resource consumption, W irr，ij is the irrigation water demand of measure j in grid i, W rain，i is the amount of rainwater collected at grid i, W river，iAllocate water for ecological replenishment of rivers and lakes;

[0025] The objective function of dynamic grazing management is:

[0026]

[0027] Among them, D graze，i is the degradation degree of grid i, NDVI i is the normalized vegetation index of grid i, D i is the degradation degree of grid i, P i is the rainfall in grid i, P total is the average annual precipitation of the entire region, k is the slope adjustment parameter;

[0028] The objective function of minimizing economic cost is:

[0029]

[0030] Among them, F3 is the economic cost incurred during the ecological restoration process, x i，graze is the grazing intensity coefficient of grid i. When it is 0, grazing is strictly prohibited. When it is 1, grazing is carried out according to the maximum carrying capacity allowed by grassland productivity. The intermediate value controls the number of livestock or grazing time proportionally. con，ij is the engineering cost of measure j in grid i, C lab，ij is the labor cost of measure j in grid i, L i is the labor demand coefficient, C comp，i is the compensation cost for grazing ban in grid i.

[0031] Preferably, water resource constraints are river and lake ecological water level protection and soil moisture safety range:

[0032]

[0033] Among them, Q max is the maximum water supply of rivers and lakes, Q eco To maintain the minimum water storage capacity for ecological functions, θ initial，i is the initial soil moisture content of grid i, Δθ ij is the vegetation area at the groundwater depth h, and k is the change in water content caused by measure j;

[0034] Vegetation community constraints prohibit species replacement across stages:

[0035] xi j =0, when S j ∈Φ(D i )

[0036] Among them, S j is the plant species corresponding to the measure, Φ(D i) is the set of species allowed by the grid degradation level;

[0037] The continuity constraint between space numbers is the difference threshold of adjacent grid measures:

[0038] |x ij -x kj |≤Δx max ( k∈neighboring grids, )

[0039] Where Δx max is the maximum permissible difference;

[0040] The mutual exclusion constraint of measures means that some measures cannot coexist in the same grid:

[0041] x ij +x ik ≤1( When measures j and k are mutually exclusive)

[0042]

[0043] Among them, x i，reveg The intensity of vegetation reseeding measures is that grazing is prohibited for at least 3 years after reseeding. graze，i Maximum grazing intensity allowed for the grid;

[0044] The seasonal grazing carrying capacity constraint is:

[0045]

[0046] Among them, A is the same grazing management area, K season is the seasonal stocking capacity coefficient, NDVI mean，A is the mean value of the vegetation index in the subregion.

[0047] Preferably, the specific contents of step S4 include:

[0048] S41. Transform the established multi-objective function into an executable decision-making basis, comprehensively consider the restoration urgency score and implementation cost-benefit ratio of each grid unit, and establish a restoration priority ranking strategy through grid management;

[0049] S42. During the remediation implementation process, specific measures will be further developed based on the prioritization results, and the strategy will be continuously adjusted through dynamic strategy optimization and closed-loop management.

[0050] S43. Dynamically allocate water resources through dynamic allocation rules, priority allocation strategies, and dynamic adjustment mechanisms.

[0051] Preferably, in step S41, the repair urgency score is specifically:

[0052] Urgency i =αD i +β(1-FVC i )+γBD i +δWdist i +εR 侵蚀

[0053] Among them, D i is the degradation level of grid i, FVC i is the vegetation coverage of grid i, BD i is the soil bulk density of the grid, Wdisti i is the water source distance of the grid, R 侵蚀 is the erosion risk of the grid, α, β, γ, δ, ∈ are the weight coefficients of each factor;

[0054] The cost-benefit ratio of implementation is:

[0055]

[0056] In step S42, the dynamic strategy is optimized to update the drone monitoring data every quarter, and the reinforcement learning algorithm Q-learning is used to adjust the strategy:

[0057] Q(s,a)←Q(s,a)+α[r+γmaxa'Q(s',a′)-Q(s,a)]

[0058] In the formula, the Q-learning algorithm takes the ecological index of the grid as the state s and selects the action a according to the current state;

[0059] Pareto optimal solution set generation: Based on a multi-objective optimization model, a Pareto optimal solution set is generated to achieve the optimal balance between ecological benefits, costs, and resource consumption. Combined with constraints, an implementable dynamic restoration plan is formed;

[0060] In step S43, the dynamic allocation rule of water resources is:

[0061]

[0062] Among them, W i is the amount of water distributed to the grid, W irr，i is the theoretical irrigation water requirement of grid i, Q total is the total water supply of the river and lake system, and the remaining water = Q total -∑ 重+中度区 W i .

[0063] A degraded grassland ecological restoration system based on the ecological water demand inside and outside rivers and lakes, based on the above-mentioned degraded grassland ecological restoration method based on the ecological water demand inside and outside rivers and lakes, including a degradation level area division module, an ecological unit grid division module, a multi-objective function and constraint condition construction module, a decision optimization module and a restoration plan output module;

[0064] The degradation grade regionalization module is used to conduct field surveys and classify degraded grasslands into degradation grade regions by analyzing their main characteristics, including but not limited to vegetation cover, species diversity index, and soil bulk density;

[0065] The ecological unit grid division module is used to divide the divided area into ecological units based on terrain adaptation;

[0066] A multi-objective function and constraint construction module is used to construct multi-objective functions and constraint conditions for degraded grassland ecological restoration based on the ecological water demand inside and outside rivers and lakes according to the needs of water resource allocation, grassland restoration, grazing management and economic benefits;

[0067] The decision-making optimization module is used to solve the ecological restoration implementation algorithm based on the ecological water demand inside and outside the rivers and lakes and the specific conditions of the degraded areas, so as to carry out restoration priority sorting, dynamic adjustment strategy and dynamic adjustment of water resources;

[0068] The restoration plan output module is used to refer to the recommended restoration implementation plans for grasslands of different degradation levels, solve the multi-objective function of degraded grassland ecological restoration based on the ecological water demand inside and outside rivers and lakes according to the specific grassland degradation level, and obtain the optimal degraded grassland ecological restoration plan based on the ecological water demand inside and outside rivers and lakes.

[0069] It can be seen from the above technical solution that compared with the existing technology, the present invention discloses a method and system for ecological restoration of degraded grasslands based on the ecological water demand inside and outside rivers and lakes. It combines water resource optimization allocation, multi-objective optimization management and grazing system design, and realizes precise restoration of degraded grasslands through grid management, thereby improving the ecological restoration effect and optimizing the utilization of water resources and economic costs, thereby promoting the sustainable development of grassland ecology. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0071] Figure 1A schematic diagram of a method for ecological restoration of degraded grasslands based on ecological water demand inside and outside rivers and lakes provided by the present invention;

[0072] Figure 2 This is a schematic diagram of the regional division of degradation levels for the degraded grassland provided by the present invention. DETAILED DESCRIPTION

[0073] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0074] The embodiment of the present invention discloses a method for ecological restoration of degraded grassland based on ecological water demand inside and outside rivers and lakes, such as Figure 1 , including the following steps:

[0075] S1. Conduct field surveys and classify degraded grasslands into different degradation levels by analyzing their main characteristics, including but not limited to vegetation cover, species diversity index, and soil bulk density;

[0076] S2. Divide the divided area into ecological units based on terrain adaptation;

[0077] S3. Construct a multi-objective function and constraints for degraded grassland ecological restoration based on the ecological water requirements within and outside rivers and lakes, based on the needs of water resource allocation, grassland restoration, grazing management, and economic benefits.

[0078] S4. Based on the ecological water demand inside and outside rivers and lakes, combined with the specific grassland degradation level in the degraded area, based on the constructed multi-objective function and constraints, carry out restoration priority sorting, and formulate dynamic adjustment strategies and dynamic water resource allocation plans, and finally form a sustainable degraded grassland ecological restoration plan based on the ecological water demand inside and outside rivers and lakes.

[0079] In order to further implement the above technical solution, in step S1, the degraded grassland is divided into severe degradation area, moderate degradation area and light degradation area according to the degradation level. Figure 2 .

[0080] In order to further implement the above technical solution, step S1 also includes using K-means clustering to analyze historical degradation data and calibrating the demarcation point in combination with the regional background value.

[0081] In this embodiment, the species diversity index is calculated using the Shannon index:

[0082] H=-∑(p kln p k )

[0083] Among them, p k The proportion of species.

[0084] In order to further implement the above technical solution, the specific contents of step S2 include:

[0085] S21. Use GIS to extract watershed boundaries, slope (<5° is flat area), and soil type to generate irregular ecological units;

[0086] S22. Make dynamic adjustments based on drone-based aerial survey data to ensure the integrity of ecological processes within the unit (e.g., runoff, species dispersal);

[0087] S23. Divide irregular ecological units into grid units and customize independent management strategies for each grid.

[0088] In practical applications, irregular ecological units can be divided into 1-10 hectare grid units (100m×100m is recommended), with each unit (grid) having an independent management strategy. Through grid management, customized restoration can be precisely targeted at factors such as the degree of degradation, grass species distribution, and soil conditions in each area, improving restoration efficiency and effectiveness.

[0089] Regional gridding: Divide the region into n small units, set x ij represents the jth strategy implemented by the i-th grid, x ij ∈[0, 1], where x ij =0 means not to adopt this measure, x ij =1 indicates that the measure is fully adopted, and the intermediate value indicates partial implementation (such as proportional control of grazing intensity). i represents the number of the grassland grid, i=1, 2, 3...n, j represents the number of the relevant attributes or management strategies of the i-th grid. For each grid i, it can contain multiple management dimensions, such as vegetation restoration strategies, soil improvement measures, grazing intensity, etc. Therefore, j can represent the specific management measures or attributes of the i-th grid.

[0090] In order to further implement the above technical solution, in step S3, the objective functions include the ecological benefit maximization objective function, the water resource consumption minimization objective function, the dynamic grazing management objective function and the economic cost minimization objective function; the constraints include water resource constraints, vegetation community constraints, space continuity constraints, measure mutual exclusion constraints and seasonal grazing carrying capacity constraints.

[0091] To further implement the above technical solutions, the ecological benefit maximization objective function is developed, integrating vegetation restoration potential and soil improvement effects, with the goal of maximizing grassland vegetation restoration and improving the grassland's ecological function and soil and water conservation capacity. Specifically:

[0092]

[0093] Among them, F1 is the ecological benefit index, E veg，ij is the vegetation restoration potential index, which is related to species selection and coverage improvement rate. soil，ij is the soil improvement index, which is related to the bulk density reduction rate and organic matter increment, x ij The jth strategy implemented for the i-th grid;

[0094] The objective function of minimizing water resource consumption is to balance irrigation demand with rainwater / river and lake recharge. The purpose is to optimize the allocation and utilization of water resources, maximize the ecological water needs inside and outside rivers and lakes, and promote grassland recovery and ecological restoration. Specifically:

[0095]

[0096] Among them, F2 is water resource consumption, W irr，ij is the irrigation water demand of measure j in grid i, W rain，i is the amount of rainwater collected in grid i, which is related to the volume of the reservoir and the infiltration efficiency, W river，i The amount of water allocated for ecological replenishment of rivers and lakes is constrained by the ecological water level threshold;

[0097] The dynamic grazing management objective function aims to improve the dynamic adjustment of grazing intensity according to grassland degradation and precipitation, and ensure scientific management of grazing during grassland restoration. Specifically:

[0098]

[0099] Among them, D graze，i is the degradation degree of grid i, NDVI i is the normalized vegetation index of grid i, D i is the degradation degree of grid i, P i is the rainfall in grid i, P total is the average annual precipitation of the entire region, k is the slope adjustment parameter, and the default value k=5;

[0100] The objective function of minimizing economic costs is to minimize the economic costs incurred during ecological restoration. Specifically,

[0101]

[0102] Among them, F3 is the economic cost incurred during the ecological restoration process, x i，graze is the grazing intensity coefficient of grid i. When it is 0, grazing is strictly prohibited. When it is 1, grazing is carried out according to the maximum carrying capacity allowed by grassland productivity. The intermediate value controls the number of livestock or grazing time proportionally. con，ijis the engineering cost of measure j in grid i, C lab，ij is the labor cost of measure j in grid i, L i is the labor demand coefficient, C comp，i is the compensation cost for grazing ban in grid i.

[0103] To further implement the above technical solutions, water resource constraints are the ecological water level protection of rivers and lakes and the safe range of soil moisture content:

[0104]

[0105] Among them, Q max is the maximum water supply of rivers and lakes, Q eco To maintain the minimum water storage capacity for ecological functions, θ initial，i is the initial soil moisture content of grid i, Δθ ij is the vegetation area at the groundwater depth h, k is the change in water content caused by measure j, and is related to the irrigation amount and permeability coefficient;

[0106] Vegetation community constraints prohibit cross-stage species replacement. For example, top community species cannot be directly planted in severely degraded areas. Specifically:

[0107] xi j =0, when S j ∈Φ(D i )

[0108] Among them, S j is the plant species corresponding to the measure, Φ(D i ) is the set of species allowed by the grid degradation level; the continuity constraint between spaces is the difference threshold of adjacent grid measures:

[0109] |x ij -x kj |≤Δx max ( k∈neighboring grids, )

[0110] Where Δx max is the maximum allowable difference, usually set to 0.3;

[0111] Mutual exclusion constraint means that some measures cannot coexist in the same grid, such as tillage and no-tillage. Specifically:

[0112] x ij +x ik ≤1( When measures j and k are mutually exclusive)

[0113]

[0114] Among them, x i，revegis the intensity of vegetation reseeding measures, and grazing is prohibited for at least 3 years after reseeding (achieved through the time variable expansion model), D graze，i Maximum grazing intensity allowed for the grid;

[0115] The seasonal grazing carrying capacity constraint is:

[0116]

[0117] Among them, A is the same grazing management area, K season is the seasonal stocking coefficient (0.8 in summer and 0.3 in winter), NDVI mean，A is the mean value of the vegetation index in the subregion.

[0118] In order to further implement the above technical solution, the specific contents of step S4 include:

[0119] S41. Transform the established multi-objective function into an executable decision-making basis, comprehensively consider the restoration urgency score and implementation cost-benefit ratio of each grid unit, and establish a restoration priority ranking strategy through grid management;

[0120] S42. During the remediation implementation process, specific measures will be further developed based on the prioritization results, and the strategy will be continuously adjusted through dynamic strategy optimization and closed-loop management.

[0121] S43. Dynamically allocate water resources through dynamic allocation rules, priority allocation strategies, and dynamic adjustment mechanisms.

[0122] To further implement the above technical solution, in step S41, the repair urgency score is used to quantify the repair urgency of each grid cell, specifically:

[0123] Urgency i =αD i +β(1-FVC i )+γBD i +δWdist i +εR 侵蚀

[0124] Among them, D i is the degradation level of grid i (severe = 1.0, moderate = 0.6, mild = 0.3), FVC i is the vegetation coverage of grid i (0-1), BD i is the soil bulk density of the grid, Wdisti i is the distance of the grid to the water source (0-1, the farther the distance, the larger the value), R 侵蚀 is the erosion risk of the grid (calculated by gully density from remote sensing images), α, β, γ, δ, and v are the weight coefficients of each factor;

[0125] In this embodiment, the repair priority determination rule is: if Urgency>0.7, the grid is a first-level priority repair area and repair measures need to be implemented as soon as possible; if Urgency is lower, natural recovery or delayed repair can be considered;

[0126] The cost-benefit ratio of implementation is:

[0127]

[0128] In this embodiment, the restoration priority decision is as follows: select the grid with the highest ecological benefit per unit cost (e.g., prioritize the grid with the largest CE value), prioritize the restoration of grids with high urgency and high CE (e.g., severely degraded areas close to water sources), and postpone the restoration of grids with low urgency, with natural recovery as the main method.

[0129] In step S42, the dynamic strategy is optimized to update the drone monitoring data every quarter, and the reinforcement learning algorithm Q-learning is used to adjust the strategy:

[0130] Q(s,a)←Q(s,a)++α[r+γmaxa'Q(s',a')-Q(s,a)]

[0131] In the formula, the Q-learning algorithm uses the ecological indicators of the grid (such as vegetation status, soil moisture, etc.) as the state s, and selects action a according to the current state, such as adjusting grazing intensity or irrigation amount, to optimize the restoration effect;

[0132] Pareto optimal solution set generation: Based on a multi-objective optimization model, a Pareto optimal solution set is generated to achieve the optimal balance between ecological benefits, costs, and resource consumption. Combined with constraints, an implementable dynamic restoration plan is formed;

[0133] In step S43, the dynamic allocation rule of water resources is:

[0134]

[0135] Among them, W i is the amount of water allocated to grid i, W irr，i is the theoretical irrigation water requirement of grid i, Q total is the total water supply of the river and lake system, and the remaining water = Q total -∑ 重＋中度区 W i ;

[0136] Priority assignment strategy:

[0137] Severely degraded areas: Prioritize meeting water resource demands, allocating no more than 30% of the total water volume to prevent excessive encroachment on ecological water use; Moderately degraded areas: Conduct secondary allocation after the demands of severely degraded areas are met; Slightly degraded areas: Mainly rely on natural recovery, with the least water demand.

[0138] Dynamic adjustment mechanism:

[0139] Monitor the soil moisture content of a grid θ i <12%:W i ←W i +ΔW, ΔW=0.05·Q total ;

[0140] Monitor the soil moisture content of a grid θ i >18%:W i ←W i -0.5·(W i -W irr，i );

[0141] Based on real-time monitoring of soil moisture, water resource allocation is dynamically adjusted. For example, when the soil moisture content falls below a predetermined threshold (such as 12%), emergency water replenishment is initiated.

[0142] A degraded grassland ecological restoration system based on the ecological water demand inside and outside rivers and lakes, based on a degraded grassland ecological restoration method based on the ecological water demand inside and outside rivers and lakes, including a degradation level area division module, an ecological unit grid division module, a multi-objective function and constraint condition construction module, a decision optimization module and a restoration plan output module;

[0143] The degradation grade regionalization module is used to conduct field surveys and classify degraded grasslands into degradation grade regions by analyzing their main characteristics, including but not limited to vegetation cover, species diversity index, and soil bulk density;

[0144] The ecological unit grid division module is used to divide the divided area into ecological units based on terrain adaptation;

[0145] A multi-objective function and constraint construction module is used to construct multi-objective functions and constraint conditions for degraded grassland ecological restoration based on the ecological water demand inside and outside rivers and lakes according to the needs of water resource allocation, grassland restoration, grazing management and economic benefits;

[0146] The decision-making optimization module is used to solve the ecological restoration implementation algorithm based on the ecological water demand inside and outside the rivers and lakes and the specific conditions of the degraded areas, so as to carry out restoration priority sorting, dynamic adjustment strategy and dynamic adjustment of water resources;

[0147] The restoration plan output module is used to refer to the recommended restoration implementation plans for grasslands of different degradation levels, solve the multi-objective function of degraded grassland ecological restoration based on the ecological water demand inside and outside rivers and lakes according to the specific grassland degradation level, and obtain the optimal degraded grassland ecological restoration plan based on the ecological water demand inside and outside rivers and lakes.

[0148] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0149] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for ecological restoration of degraded grasslands based on ecological water demand inside and outside rivers and lakes, characterized in that: The following steps are involved: S1. Conduct field surveys and classify degraded grasslands into different degradation levels by analyzing their main characteristics, including but not limited to vegetation cover, species diversity index, and soil bulk density; S2. Divide the divided area into ecological units based on terrain adaptation; S3. Construct a multi-objective function and constraints for degraded grassland ecological restoration based on the ecological water requirements within and outside rivers and lakes, based on the needs of water resource allocation, grassland restoration, grazing management, and economic benefits. S4. Based on the ecological water demand inside and outside rivers and lakes, combined with the specific grassland degradation level in the degraded area, based on the constructed multi-objective function and constraints, carry out restoration priority sorting, and formulate dynamic adjustment strategies and dynamic water resource allocation plans, and finally form a sustainable degraded grassland ecological restoration plan based on the ecological water demand inside and outside rivers and lakes.

2. The method for ecological restoration of degraded grasslands based on ecological water demand inside and outside rivers and lakes according to claim 1, characterized in that: In step S1, the degraded grassland is divided into severe degradation areas, moderate degradation areas and light degradation areas according to degradation level.

3. The method for ecological restoration of degraded grasslands based on ecological water demand inside and outside rivers and lakes according to claim 1, characterized in that: Step S1 also includes using K-means clustering to analyze historical degradation data and calibrating the cutoff point in combination with regional background values.

4. The method for ecological restoration of degraded grasslands based on ecological water demand inside and outside rivers and lakes according to claim 1, characterized in that: The specific contents of step S2 include: S21. Extract watershed boundaries, slopes, and soil types using GIS to generate irregular ecological units. S22. Make dynamic adjustments based on drone aerial survey data to ensure the integrity of ecological processes within the unit; S23. Divide irregular ecological units into grid units and customize independent management strategies for each grid.

5. The method for ecological restoration of degraded grassland based on ecological water demand inside and outside rivers and lakes according to claim 1, characterized in that: In step S3, the objective functions include the ecological benefit maximization objective function, the water resource consumption minimization objective function, the dynamic grazing management objective function and the economic cost minimization objective function; the constraints include water resource constraints, vegetation community constraints, space continuity constraints, measure mutual exclusion constraints and seasonal grazing carrying capacity constraints.

6. The method for ecological restoration of degraded grasslands based on ecological water demand inside and outside rivers and lakes according to claim 4, characterized in that: The objective function of maximizing ecological benefits is: Among them, F1 is the ecological benefit index, E veg，ij is the vegetation restoration potential index, E soil，ij is the soil improvement index, x ij The jth strategy implemented for the i-th grid; The objective function for minimizing water resource consumption is: Among them, F2 is water resource consumption, W irr，ij is the irrigation water demand of measure j in grid i, W rain，i is the amount of rainwater collected at grid i, W river，i Allocate water for ecological replenishment of rivers and lakes; The objective function of dynamic grazing management is: Among them, D grazei is the degradation degree of grid i, NDVI i is the normalized vegetation index of grid i, D i is the degradation degree of grid i, P i is the rainfall in grid i, P total is the average annual precipitation of the entire region, k is the slope adjustment parameter; The objective function of minimizing economic cost is: Among them, F3 is the economic cost incurred during the ecological restoration process, x i，graze is the grazing intensity coefficient of grid i. When it is 0, grazing is strictly prohibited. When it is 1, grazing is carried out according to the maximum carrying capacity allowed by grassland productivity. The intermediate value controls the number of livestock or grazing time in proportion. con，ij is the engineering cost of measure j in grid i, C lab，ij is the labor cost of measure j in grid i, L i is the labor demand coefficient, C comp，i is the compensation cost for grazing ban in grid i.

7. The method for ecological restoration of degraded grasslands based on ecological water demand inside and outside rivers and lakes according to claim 5, characterized in that: Water resource constraints are the ecological water level protection of rivers and lakes and the safe range of soil moisture content: Among them, Q max is the maximum water supply of rivers and lakes, Q eco To maintain the minimum water storage capacity for ecological functions, θ initial，i is the initial soil moisture content of grid i, Δθ ij is the vegetation area at the groundwater depth h, and k is the change in water content caused by measure j; Vegetation community constraints prohibit species replacement across stages: xi j =0, when S j ∈Φ(D i ) Among them, S j is the plant species corresponding to the measure, Φ(D i ) is the set of species allowed by the grid degradation level; The continuity constraint between space numbers is the difference threshold of adjacent grid measures: Where Δx max is the maximum permissible difference; The mutual exclusion constraint of measures means that some measures cannot coexist in the same grid: Among them, x i，reveg The intensity of vegetation reseeding measures is that grazing is prohibited for at least 3 years after reseeding. graze，i Maximum grazing intensity allowed for the grid; The seasonal grazing carrying capacity constraint is: Among them, A is the same grazing management area, K season is the seasonal stocking capacity coefficient, NDVI mean,A is the mean value of the vegetation index in the subregion.

8. The method for ecological restoration of degraded grassland based on ecological water demand inside and outside rivers and lakes according to claim 1, characterized in that: The specific contents of step S4 include: S41. Transform the established multi-objective function into an executable decision-making basis, comprehensively consider the restoration urgency score and implementation cost-benefit ratio of each grid unit, and establish a restoration priority ranking strategy through grid management; S42. During the remediation implementation process, specific measures will be further developed based on the prioritization results, and the strategy will be continuously adjusted through dynamic strategy optimization and closed-loop management. S43. Dynamically allocate water resources through dynamic allocation rules, priority allocation strategies, and dynamic adjustment mechanisms.

9. The method for ecological restoration of degraded grassland based on ecological water demand inside and outside rivers and lakes according to claim 1, characterized in that: In step S41, the repair urgency score is specifically: Urgency i =αD i +β(1-FVC i )+γBD i +δWdist i +εR 侵蚀 Among them, D i is the degradation level of grid i, FVC i is the vegetation coverage of grid i, BD i is the soil bulk density of the grid, Wdisti i is the water source distance of the grid, R 侵蚀 is the erosion risk of the grid, α, β, γ, δ, ∈ are the weight coefficients of each factor; The cost-benefit ratio of implementation is: In step S42, the dynamic strategy is optimized to update the drone monitoring data every quarter, and the reinforcement learning algorithm Q-learning is used to adjust the strategy: Q(s,a)←Q(s,a)+α[r+γmaxa′Q(s′,a′)-Q(s,a)] In the formula, the Q-learning algorithm takes the ecological index of the grid as the state s and selects the action a according to the current state; Pareto optimal solution set generation: Based on a multi-objective optimization model, a Pareto optimal solution set is generated to achieve the optimal balance between ecological benefits, costs, and resource consumption. Combined with constraints, an implementable dynamic restoration plan is formed; In step S43, the dynamic allocation rule of water resources is: Among them, W i is the amount of water distributed to the grid, W irr，i is the theoretical irrigation water requirement of grid i, Q total is the total water supply of the river and lake system, and the remaining water = Q total -∑ 重+中度区 W i .

10. A degraded grassland ecological restoration system based on ecological water demand inside and outside rivers and lakes, characterized by: A method for ecological restoration of degraded grasslands based on ecological water demand inside and outside rivers and lakes according to any one of claims 1 to 9, comprising a degradation level area division module, an ecological unit grid division module, a multi-objective function and constraint condition construction module, a decision optimization module, and a restoration plan output module; The degradation level regionalization module is used to conduct field surveys and classify degraded grasslands into degradation level regions by analyzing their main characteristics, including but not limited to vegetation cover, species diversity index, and soil bulk density; The ecological unit grid division module is used to divide the divided area into ecological units based on terrain adaptation; A multi-objective function and constraint construction module is used to construct multi-objective functions and constraint conditions for degraded grassland ecological restoration based on the ecological water demand inside and outside rivers and lakes according to the needs of water resource allocation, grassland restoration, grazing management and economic benefits; The decision-making optimization module is used to solve the ecological restoration implementation algorithm based on the ecological water demand inside and outside the rivers and lakes and the specific conditions of the degraded areas, so as to carry out restoration priority sorting, dynamic adjustment strategy and dynamic adjustment of water resources; The restoration plan output module is used to refer to the recommended restoration implementation plans for grasslands of different degradation levels, solve the multi-objective function of degraded grassland ecological restoration based on the ecological water demand inside and outside rivers and lakes according to the specific grassland degradation level, and obtain the optimal degraded grassland ecological restoration plan based on the ecological water demand inside and outside rivers and lakes.

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