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

Abstract

The application discloses a degraded grassland ecological restoration method and system based on ecological water demand inside and outside rivers and lakes, and comprises the following steps: conducting field investigation, analyzing the main characteristics of the degraded grassland to divide the degradation grade area, wherein the main characteristics include but are not limited to vegetation coverage, species diversity index and soil bulk density; carrying out ecological unit grid division based on terrain self-adaption; constructing a multi-objective function and constraint condition of the degraded grassland ecological restoration based on the ecological water demand inside and outside rivers and lakes according to water resource allocation, grassland restoration, grazing management and economic benefits; on the basis of the ecological water demand inside and outside rivers and lakes and in combination with the specific grassland degradation grade of the degraded area, the multi-objective function and the constraint condition are used to carry out restoration priority ranking, dynamic adjustment strategy and water resource dynamic adjustment, so that an optimal degraded grassland ecological restoration scheme is obtained; the application is a comprehensive ecological restoration scheme combining water resource utilization, ecological water demand, grazing management and economic benefits, and is helpful to promoting sustainable restoration of the grassland.

Description

Technical Field

[0001] This invention relates to the field of ecological restoration technology, particularly to the field of degraded grassland ecological restoration, and more specifically to a method and system for degraded grassland ecological restoration based on the ecological water demand inside and outside rivers and lakes. Background Technology

[0002] Grassland ecosystems are important global carbon sinks and water conservation areas, but due to factors such as overgrazing and climate change, grasslands around the world are facing varying degrees of degradation. Degraded grasslands suffer severe loss of ecological functions, leading to a series of problems such as soil erosion, reduced biodiversity, and degradation of ecosystem services. In particular, severely degraded grasslands are difficult to restore and require a large amount of resources.

[0003] Currently, grassland ecological restoration technologies mostly rely on single restoration methods, neglecting 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 a problem that urgently needs to be solved by those skilled in the art. 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 art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

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

[0008] S1. Conduct field surveys and classify degraded grasslands into degradation level zones by analyzing the main characteristics of the degraded grasslands. The main characteristics include, but are not limited to, vegetation cover, species diversity index and soil bulk density.

[0009] S2. For the divided areas, ecological unit grids are generated based on terrain adaptation.

[0010] S3. Based on the needs of water resource allocation, grassland restoration, grazing management and economic benefits, construct a multi-objective function and constraints for the ecological restoration of degraded grasslands based on the ecological water demand inside and outside rivers and lakes;

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

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

[0014] Preferably, step S2 includes the following:

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

[0016] S22. Dynamic adjustments are made based on UAV aerial survey data to ensure the integrity of ecological processes within the unit;

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

[0018] Preferably, in step S3, the objective functions include an objective function for maximizing ecological benefits, an objective function for minimizing water resource consumption, an objective function for dynamic grazing management, and an objective function for minimizing economic costs; the constraints include water resource constraints, vegetation community constraints, continuity constraints between empty numbers, mutual exclusion constraints of measures, and seasonal grazing carrying capacity constraints.

[0019] The preferred objective function for maximizing ecological benefits is:

[0020]

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

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

[0023]

[0024] Where F2 represents water consumption, W irr，ij To measure the irrigation water demand in grid i, W rain，i W represents the amount of rainwater collected in grid i. river，iAllocation of water for ecological replenishment of rivers and lakes;

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

[0026]

[0027] Among them, D graze，i NDVI represents the degree of degradation of mesh i. i Let D be the normalized vegetation index for grid i. i P represents the degree of degradation of grid i. i Let P be the rainfall at grid i. total denoted as the multi-year average precipitation for the entire region, and k is the slope adjustment parameter.

[0028] The objective function for minimizing economic costs is:

[0029]

[0030] Where F3 represents the economic costs incurred during the ecological restoration process, x i，graze C represents the grazing intensity coefficient for grid i. A value of 0 indicates strict grazing prohibition, a value of 1 indicates grazing at the maximum carrying capacity allowed by grassland productivity, and an intermediate value indicates proportional control of livestock numbers or grazing duration. con，ij To reduce the engineering cost of measure j in grid i, C lab，ij To reduce labor costs in grid i for measure j, L i C is the labor demand coefficient. comp，i To compensate for the cost of grazing bans in grid i.

[0031] Preferably, the water resource constraint is the range between the protection of river and lake ecological water levels and the safe range of soil moisture content:

[0032]

[0033] Among them, Q max Q represents the maximum available water volume of rivers and lakes. eco The minimum water storage required to maintain ecological functions, θ initial，i Let Δθ be the initial soil moisture content of grid i. ij Let be the vegetation area at a groundwater depth of h, and k be the change in water content caused by measure j.

[0034] Vegetation community constraints prohibit cross-stage species replacement:

[0035] xi j =0, when S j ∈Φ(D i )

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

[0037] The continuity constraint between empty numbers is the threshold for the difference in measures between adjacent grids:

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

[0039] Where, Δx max The maximum permissible difference;

[0040] Mutually exclusive constraints on measures mean that some measures within the same grid cannot coexist.

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

[0042]

[0043] Where, x i，reveg To ensure the intensity of vegetation reseeding, grazing should be prohibited for at least 3 years after reseeding. graze，i The maximum grazing intensity allowed by the grid;

[0044] The carrying capacity constraint for seasonal grazing is:

[0045]

[0046] Where A represents the same grazing management zone, and K season NDVI is the seasonal carrying capacity coefficient. mean，A This represents the average vegetation index for each zone.

[0047] Preferably, step S4 includes the following:

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

[0049] S42. During the remediation process, based on the priority ranking results, further specific measures are formulated, and the strategy is continuously adjusted through dynamic strategy optimization and closed-loop management;

[0050] S43. Water resources are dynamically allocated through dynamic allocation rules, priority allocation strategies, and dynamic adjustment mechanisms.

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

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

[0053] Among them, D i FVC is the degradation level of grid i. i Let BD be the vegetation cover of grid i. i For the soil bulk density of the grid, Wdisti i R represents the distance to the water source in the grid. 侵蚀 The erosion risk of the grid is represented by α, β, γ, δ, and ∈, which 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 quarterly, and the strategy is adjusted using the reinforcement learning algorithm Q-learning.

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

[0058] In the formula, the Q-learning algorithm uses the ecological indicators of the grid as the state s and selects the action a based on 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 scheme is formed.

[0060] In step S43, the dynamic allocation rule for water resources is as follows:

[0061]

[0062] Among them, W i For the allocation of water to the grid, W irr，i Let Q be the theoretical irrigation water requirement for grid i. total The total available water volume of the river and lake system, and the surplus water volume = Q total -∑ 重+中度区 W i .

[0063] A degraded grassland ecological restoration system based on ecological water demand inside and outside rivers and lakes, and based on the aforementioned method for degraded grassland ecological restoration based on ecological water demand inside and outside rivers and lakes, includes 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 scheme output module;

[0064] The degradation level zone delineation module is used to conduct field surveys. It divides degraded grasslands into degradation level zones by analyzing the main characteristics of the grasslands. The main characteristics include, but are not limited to, vegetation cover, species diversity index and soil bulk density.

[0065] The ecological unit grid division module is used to perform ecological unit grid division of the divided areas based on terrain adaptation.

[0066] The multi-objective function and constraint construction module is used to construct multi-objective functions and constraints for the ecological restoration of degraded grasslands based on the needs of water resource allocation, grassland restoration, grazing management and economic benefits.

[0067] The decision optimization module is used to solve the ecological restoration implementation algorithm based on the ecological water demand inside and outside the river and lake, combined with the specific situation of the degradation area, so as to prioritize restoration, dynamically adjust strategies, and dynamically adjust water resources.

[0068] The restoration scheme output module is used to refer to the suggested restoration implementation schemes for grasslands with different degradation levels. Based on the specific grassland degradation level, it solves the multi-objective function of ecological restoration of degraded grasslands based on the ecological water demand inside and outside rivers and lakes, and obtains the optimal ecological restoration scheme for degraded grasslands based on the ecological water demand inside and outside rivers and lakes.

[0069] As can be seen from the above technical solution, compared with the prior art, the present invention discloses a method and system for ecological restoration of degraded grassland based on the ecological water demand inside and outside rivers and lakes. By combining optimized allocation of water resources, multi-objective optimized management and grazing system design, and through grid management, it achieves precise restoration of degraded grassland, improves the ecological restoration effect, optimizes the utilization of water resources and economic costs, and promotes the sustainable development of grassland ecology. Attached Figure Description

[0070] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

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

[0072] Figure 2 A schematic diagram illustrating the degraded grassland delineation by level, as provided by this invention. Detailed Implementation

[0073] 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.

[0074] This invention discloses a method for ecological restoration of degraded grasslands based on the ecological water demand inside and outside rivers and lakes, such as... Figure 1 This includes the following steps:

[0075] S1. Conduct field surveys and classify degraded grasslands into degradation level zones by analyzing the main characteristics of the degraded grasslands. The main characteristics include, but are not limited to, vegetation cover, species diversity index and soil bulk density.

[0076] S2. For the divided areas, ecological unit grids are generated based on terrain adaptation.

[0077] S3. Based on the needs of water resource allocation, grassland restoration, grazing management and economic benefits, construct a multi-objective function and constraints for the ecological restoration of degraded grasslands based on the ecological water demand inside and outside rivers and lakes;

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

[0079] To further implement the above technical solution, in step S1, the degraded grassland is divided into severely degraded areas, moderately degraded areas, and slightly degraded areas, such as... Figure 2 .

[0080] To further implement the above technical solution, step S1 also includes using K-means clustering analysis to analyze historical degradation data and calibrating the boundary 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] Where, p k The percentage of the species.

[0084] To further implement the above technical solution, step S2 includes the following:

[0085] S21. Irregular ecological units are generated by extracting watershed boundaries, slopes (<5° is considered flat area) and soil types using GIS;

[0086] S22. Make dynamic adjustments based on UAV aerial survey data to ensure the integrity of ecological processes (such as runoff and species dispersal) within the unit;

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

[0088] In practical applications, irregular ecological units can be divided into grid units of 1-10 hectares (100m×100m recommended), and each unit (grid) has an independent management strategy. Through grid management, customized restoration can be carried out precisely for each area based on factors such as the degree of degradation, grass species distribution, and soil conditions, thereby improving restoration efficiency and effectiveness.

[0089] Regional gridding: Dividing a region into n smaller units, let x ij Let x represent the j-th strategy implemented in the i-th grid. ij ∈[0,1], where x ij =0 indicates that this measure will not be adopted, x ij =1 indicates that the measure is fully adopted, and intermediate values ​​indicate partial implementation (such as proportional control of grazing intensity). i represents the grassland grid number, i = 1, 2, 3...n, and j represents the number of the relevant attribute or management strategy of the i-th grid. For each grid i, there may be 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] To further implement the above technical solution, in step S3, the objective functions include the objective function of maximizing ecological benefits, the objective function of minimizing water resource consumption, the objective function of dynamic grazing management, and the objective function of minimizing economic costs; the constraints include water resource constraints, vegetation community constraints, continuity constraints between empty numbers, mutual exclusion constraints of measures, and seasonal grazing carrying capacity constraints.

[0091] To further implement the above technical solutions, the objective function for maximizing ecological benefits integrates vegetation restoration potential and soil improvement effects. The aim is to maximize grassland vegetation restoration and enhance grassland ecological functions and soil and water conservation capabilities, specifically:

[0092]

[0093] Where F1 is the ecological benefit index, E veg，ij E is a vegetation restoration potential index, which is related to species selection and coverage improvement rate. soil，ij The soil improvement index is related to the rate of decrease in bulk density and the increase in organic matter. ij The j-th strategy is implemented for the i-th grid.

[0094] The objective function for minimizing water resource consumption balances irrigation demand with rainwater / river / lake replenishment. Its aim is to optimize water resource allocation and utilization, maximizing the solution of ecological water needs both within and outside rivers and lakes, and promoting grassland restoration and ecological recovery. Specifically:

[0095]

[0096] Where F2 represents water consumption, W irr，ij To measure the irrigation water demand in grid i, W rain，i The amount of rainwater collected in grid i is related to the reservoir volume and infiltration efficiency, W. river，i The allocation of ecological water replenishment for rivers and lakes is constrained by ecological water level thresholds.

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

[0098]

[0099] Among them, D graze，i NDVI represents the degree of degradation of mesh i. i Let D be the normalized vegetation index for grid i. i P represents the degree of degradation of grid i. i Let P be the rainfall at grid i. total The average annual precipitation for the entire region is given by , and k is the slope adjustment parameter with a default value of k = 5.

[0100] The objective function for minimizing economic costs aims to minimize the economic costs incurred during ecological restoration. Specifically:

[0101]

[0102] Where F3 represents the economic costs incurred during the ecological restoration process, x i，graze C represents the grazing intensity coefficient for grid i. A value of 0 indicates strict grazing prohibition, a value of 1 indicates grazing at the maximum carrying capacity allowed by grassland productivity, and an intermediate value indicates proportional control of livestock numbers or grazing duration. con，ijTo reduce the engineering cost of measure j in grid i, C lab，ij To reduce labor costs in grid i for measure j, L i C is the labor demand coefficient. comp，i To compensate for the cost of grazing bans in grid i.

[0103] To further implement the above technical solutions, water resource constraints are defined as the range between river and lake ecological water level protection and safe soil moisture content:

[0104]

[0105] Among them, Q max Q represents the maximum available water volume for rivers and lakes. eco The minimum water storage required to maintain ecological functions, θ initial，i Let Δθ be the initial soil moisture content of grid i. ij denoted as the vegetation area at a groundwater depth of h, and k as the change in water content caused by measure j, which is related to irrigation amount and permeability coefficient.

[0106] Vegetation community constraints prohibit cross-stage species replacement; for example, climax 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 For the plant species corresponding to the measure, Φ(D) i ) represents the set of species allowed for the grid degradation level; the continuity constraint between empty numbers is the threshold for the difference in measures between adjacent grids:

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

[0110] Where, Δx max The maximum permissible difference is typically set to 0.3;

[0111] Mutually exclusive constraints on measures mean that some measures cannot coexist within 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] Where, x i，revegTo determine the intensity of vegetation reseeding, grazing should be prohibited for at least 3 years after reseeding (achieved through a time-variable extended model), D graze，i The maximum grazing intensity allowed by the grid;

[0115] The carrying capacity constraint for seasonal grazing is:

[0116]

[0117] Where A represents the same grazing management zone, and K season The seasonal carrying capacity coefficient (0.8 in summer, 0.3 in winter), NDVI mean，A This represents the average vegetation index for each zone.

[0118] To further implement the above technical solution, step S4 includes the following:

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

[0120] S42. During the remediation process, based on the priority ranking results, further specific measures are formulated, and the strategy is continuously adjusted through dynamic strategy optimization and closed-loop management;

[0121] S43. Water resources are dynamically allocated 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 as follows:

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

[0124] Among them, D i FVC represents the degradation level of grid i (severe = 1.0, moderate = 0.6, mild = 0.3). i Let BD be the vegetation cover (0-1) of grid i. i For the soil bulk density of the grid, Wdisti i R represents the distance to the water source in the grid (0-1, with larger values ​​for greater distances). 侵蚀 The erosion risk of the grid (calculated by the gully density of remote sensing imagery) is represented by α, β, γ, δ, and v, which are the weighting coefficients of each factor.

[0125] In this embodiment, the repair priority determination rule is as follows: if Urgency > 0.7, then the grid is a first-level priority repair area and repair measures should be implemented as soon as possible; if Urgency is low, 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 grids with the highest ecological benefits per unit cost (e.g., prioritize the implementation of grids with high CE values), prioritize the restoration of grids with high Urgency and high CE (e.g., severely degraded areas near water sources), and postpone the restoration of low Urgency grids, allowing them to recover naturally.

[0129] In step S42, the dynamic strategy is optimized to update the drone monitoring data quarterly, and the strategy is adjusted using the reinforcement learning algorithm Q-learning.

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

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

[0133] In step S43, the dynamic allocation rule for water resources is as follows:

[0134]

[0135] Among them, W i For the water allocation of grid i, W irr，i Let Q be the theoretical irrigation water requirement for grid i. total The total available water volume of the river and lake system, and the surplus water volume = Q total -∑ 重＋中度区 W i ;

[0136] Priority allocation strategy:

[0137] Severely degraded areas: Priority will be given to meeting water resource needs, with allocation not exceeding 30% of the total water volume to prevent excessive encroachment on ecological water use; Moderately degraded areas: Secondary allocation will be made after the needs of severely degraded areas are met; Slightly degraded areas: Mainly rely on natural restoration and require the least amount of water.

[0138] Dynamic adjustment mechanism:

[0139] The soil moisture content θ of a certain grid was monitored. i <12%: W i ←W i +ΔW, ΔW=0.05·Q total ;

[0140] The soil moisture content θ of a certain grid was monitored. i >18%: W i ←W i -0.5·(W i -W irr，i );

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

[0142] A degraded grassland ecological restoration system based on ecological water demand inside and outside rivers and lakes, and a degraded grassland ecological restoration method based on 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 scheme output module;

[0143] The degradation level zone delineation module is used to conduct field surveys. It divides degraded grasslands into degradation level zones by analyzing the main characteristics of the grasslands. The main characteristics include, but are not limited to, vegetation cover, species diversity index and soil bulk density.

[0144] The ecological unit grid division module is used to perform ecological unit grid division of the divided areas based on terrain adaptation.

[0145] The multi-objective function and constraint construction module is used to construct multi-objective functions and constraints for the ecological restoration of degraded grasslands based on the needs of water resource allocation, grassland restoration, grazing management and economic benefits.

[0146] The decision optimization module is used to solve the ecological restoration implementation algorithm based on the ecological water demand inside and outside the river and lake, combined with the specific situation of the degradation area, so as to prioritize restoration, dynamically adjust strategies, and dynamically adjust water resources.

[0147] The restoration scheme output module is used to refer to the suggested restoration implementation schemes for grasslands with different degradation levels. Based on the specific grassland degradation level, it solves the multi-objective function of ecological restoration of degraded grasslands based on the ecological water demand inside and outside rivers and lakes, and obtains the optimal ecological restoration scheme for degraded grasslands 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 its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0149] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those 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 invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for ecological restoration of degraded grasslands based on the ecological water demand inside and outside rivers and lakes, characterized in that, Includes the following steps: S1. Conduct field surveys and classify degraded grasslands into degradation level zones by analyzing the main characteristics of the degraded grasslands. The main characteristics include, but are not limited to, vegetation cover, species diversity index and soil bulk density. S2. For the divided areas, ecological unit grids are generated based on terrain adaptation. S3. Based on the needs of water resource allocation, grassland restoration, grazing management and economic benefits, construct a multi-objective function and constraints for the ecological restoration of degraded grasslands based on the ecological water demand inside and outside rivers and lakes; S4. Based on the protection of ecological water demand inside and outside rivers and lakes, and combined with the specific grassland degradation level in the degraded area, based on the constructed multi-objective function and constraints, carry out restoration priority ranking, formulate dynamic adjustment strategies and dynamic water resource allocation schemes, and finally form a sustainable degraded grassland ecological restoration scheme based on ecological water demand inside and outside rivers and lakes. In step S3, the objective functions include the objective function of maximizing ecological benefits, the objective function of minimizing water resource consumption, the objective function of dynamic grazing management, and the objective function of minimizing economic costs; the constraints include water resource constraints, vegetation community constraints, space continuity constraints, mutual exclusion constraints of measures, and seasonal grazing carrying capacity constraints. The objective function for maximizing ecological benefits is: in, For ecological benefit index, As a vegetation restoration potential index, The soil improvement index, The j-th strategy is implemented for the i-th grid. The objective function for minimizing water resource consumption is: in, Water consumption For measure j, the irrigation water demand in grid i, Let i be the amount of rainwater collected. Allocation of water for ecological replenishment of rivers and lakes; The objective function for dynamic grazing management is: in, The degree of degradation of grid i, Let be the normalized vegetation index for grid i. The degree of degradation of grid i, Let i be the rainfall in grid i. denoted as the multi-year average precipitation for the entire region, and k is the slope adjustment parameter. The objective function for minimizing economic costs is: in, The economic costs incurred during the ecological restoration process is the grazing intensity coefficient for grid i. When it is 0, grazing is strictly prohibited. When it is 1, grazing is allowed according to the maximum carrying capacity of the grassland productivity. The intermediate value controls the number of livestock or the grazing time proportionally. To reduce the engineering cost of measure j in grid i, To reduce labor costs in grid i for measure j, This is the labor demand coefficient. To compensate for the cost of grazing bans in grid i.

2. The method for ecological restoration of degraded grassland based on the 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 severely degraded areas, moderately degraded areas, and slightly degraded areas based on the degree of degradation.

3. The method for ecological restoration of degraded grassland based on the ecological water demand inside and outside rivers and lakes according to claim 1, characterized in that, Step S1 also includes using K-means clustering analysis to analyze historical degradation data and calibrating the boundary points in conjunction with the regional baseline values.

4. The method for ecological restoration of degraded grassland based on the ecological water demand inside and outside rivers and lakes according to claim 1, characterized in that, The specific content of step S2 includes: S21. Extract watershed boundaries, slopes, and soil types using GIS to generate irregular ecological units; S22. Dynamic adjustments are made based on UAV aerial survey data to ensure the integrity of ecological processes within the unit; S23. Divide the irregular ecological units into grid units and customize an independent management strategy for each grid.

5. The method for ecological restoration of degraded grassland based on the ecological water demand inside and outside rivers and lakes according to claim 1, characterized in that, Water resource constraints are defined as the protection of river and lake ecological water levels and the safe range of soil moisture content. in, This represents the maximum available water volume for rivers and lakes. The minimum water storage required to maintain ecological functions. Let i be the initial soil moisture content. The vegetation area is defined as the depth of groundwater (h). The change in moisture content caused by measure j; Vegetation community constraints prohibit cross-stage species replacement: in, For the plant species corresponding to the measures, The set of species allowed by the grid degradation level; The continuity constraint between empty numbers is the threshold for the difference in measures between adjacent grids: in, The maximum permissible difference; Mutually exclusive constraints on measures mean that some measures within the same grid cannot coexist. in, To ensure the intensity of vegetation reseeding, grazing should be prohibited for at least three years after reseeding. The maximum grazing intensity allowed by the grid; The carrying capacity constraint for seasonal grazing is: in, For the same grazing management zone, This is the seasonal carrying capacity coefficient. This represents the average vegetation index for each zone.

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

7. The method for ecological restoration of degraded grassland based on the ecological water demand inside and outside rivers and lakes according to claim 1, characterized in that, In step S41, the urgency score for repair is as follows: in, Let i be the degradation level. Let i be the vegetation cover. The soil bulk density of the grid. The distance to the water source in the grid. For the erosion risk of the mesh, α, β, γ, δ, These are the weighting coefficients for each factor; The cost-benefit ratio of implementation is: In step S42, the dynamic strategy is optimized to update the drone monitoring data quarterly, and the strategy is adjusted using the reinforcement learning algorithm Q-learning. In the formula, the Q-learning algorithm uses the ecological indicators of the grid as the state s, and selects action a based on 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 scheme is formed. In step S43, the dynamic allocation rule for water resources is as follows: Among them, W i Distribute water volume to the grid. Let i be the theoretical irrigation water requirement. The total available water volume of the river and lake system, and the remaining water volume = .

8. A degraded grassland ecological restoration system based on the ecological water demand inside and outside rivers and lakes, characterized in that, A method for ecological restoration of degraded grassland based on ecological water demand inside and outside rivers and lakes, according to any one of claims 1-7, includes 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 scheme output module. The degradation level zone delineation module is used to conduct field surveys. It divides degraded grasslands into degradation level zones by analyzing the main characteristics of the grasslands. The main characteristics include, but are not limited to, vegetation cover, species diversity index and soil bulk density. The ecological unit grid division module is used to perform ecological unit grid division of the divided areas based on terrain adaptation. The multi-objective function and constraint construction module is used to construct multi-objective functions and constraints for the ecological restoration of degraded grasslands based on the needs of water resource allocation, grassland restoration, grazing management and economic benefits. The decision optimization module is used to solve the ecological restoration implementation algorithm based on the ecological water demand inside and outside the river and lake, combined with the specific situation of the degradation area, so as to prioritize restoration, dynamically adjust strategies, and dynamically adjust water resources. The restoration scheme output module is used to refer to the suggested restoration implementation schemes for grasslands with different degradation levels. Based on the specific grassland degradation level, it solves the multi-objective function of ecological restoration of degraded grasslands based on the ecological water demand inside and outside rivers and lakes, and obtains the optimal ecological restoration scheme for degraded grasslands based on the ecological water demand inside and outside rivers and lakes.

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