Stable and suitable coordination method of river basin mountains, water, forests, farmland, lakes and grasses

Abstract

The application discloses a kind of basin mountain and water forest lake grass sand stable suitable coordination method, it is related to the technical field of ecological environment protection and management, including the following steps: step 1: collecting basin ecological background data, and constructing ecological hydrology database;Step 2: according to ecological hydrology database, construct landscape pattern-ecosystem coupling model, and carry out ecological function zoning;Step 3: according to ecological function zoning, construct integrated coupling relationship framework in basin, and identify key ecological hydrology problem;Step 4: according to key ecological hydrology problem, construct nonlinear-multi-objective dynamic programming model;Step 5: solving nonlinear-multi-objective dynamic programming model, obtain parameter optimal solution;Step 6: according to parameter optimal solution, construct coordination strategy.Collaborative optimization of basin ecological hydrology function is taken as core target, the model of basin ecosystem collaborative regulation is established, the optimal parameter is determined by optimizing the model, and coordination strategy is formulated.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ecological environment protection and management, more specifically to a stable and suitable coordination method for mountain-water-forest-river-lake-grass-sand in a river basin. BACKGROUND

[0002] A river basin ecosystem is composed of various elements such as mountains, water, forests, farmland, lakes, grass, and sand. These elements interact with each other in complex ways. However, due to climate change and human activities, many river basins are facing ecological problems such as soil erosion, vegetation degradation, water scarcity, wetland shrinkage, and soil desertification. These problems not only reduce the stability and service function of the river basin ecosystem, but also exacerbate the risk of ecological environment degradation. Therefore, a systematic method is needed to optimize the spatial configuration and ecological function of each element at the river basin scale, coordinate water and soil resource utilization, and improve the adaptability and sustainability of the river basin ecosystem.

[0003] Current river basin ecological restoration techniques mostly focus on a single element, such as water resource regulation or vegetation restoration, without fully considering the coordinated management of the overall ecological system. For example, certain engineering measures may improve water supply in a local area, but if the water flow between mountains, rivers, wetlands, farmland, and grassland is not reasonably coordinated, it may exacerbate the ecological water demand contradiction and lead to unstable restoration results. In addition, traditional restoration techniques lack systematic analysis in terms of water resource carrying capacity, soil moisture dynamic balance, and vegetation structure optimization, making it difficult to achieve long-term stable ecological system restoration.

[0004] The elements of a river basin, such as mountains, water, forests, farmland, lakes, grass, and sand, interact in complex ways. Optimizing their configuration is crucial for maintaining hydrological cycle, soil moisture retention, and ecological diversity protection. Therefore, a comprehensive technique is needed to coordinate water supply and demand, optimize vegetation configuration, improve soil conservation capacity, and enhance the stability and adaptability of the ecological system.

[0005] Therefore, how to achieve the optimal configuration of the elements of the river basin ecosystem and improve the stability and adaptability of the system is a problem that needs to be solved by those skilled in the art. SUMMARY

[0006] Therefore, the present application provides a stable and suitable coordination method for mountain-water-forest-river-lake-grass-sand in a river basin, which takes the coordinated optimization of river basin ecological hydrological function as the core target and establishes a stable and suitable coordination model for the coordinated regulation of the river basin ecosystem. By optimizing the model, the positive maintenance of water cycle, material cycle, and energy flow in the river basin is achieved, thereby improving the overall ecological stability of the river basin and providing theoretical and technical support for the ecological environment protection and sustainable development of society and economy in the river basin.

[0007] To achieve the above purpose, the present application adopts the following technical solutions:

[0008] The basin mountain-water-forest-river-lake-grass-sand stable and suitable coordination method comprises the following steps:

[0009] Step 1: Collecting the ecological background data of the basin and constructing an ecological hydrology database;

[0010] Step 2: Constructing a landscape pattern-ecosystem coupling model according to the ecological hydrology database, obtaining the coupling mechanism of the mountain-water-forest-river-lake-grass-sand life community and the ecological function zoning of the basin;

[0011] Step 3: Constructing a comprehensive coupling relationship framework between different ecosystems, ecological functions and social economies in the basin according to the coupling mechanism of the mountain-water-forest-river-lake-grass-sand life community and the ecological function zoning, obtaining the coupling degree of the basin and the key ecological hydrology problems;

[0012] Step 4: Constructing a non-linear-multi-objective dynamic programming model according to the coupling degree of the basin and the key ecological hydrology problems;

[0013] Step 5: Solving the non-linear-multi-objective dynamic programming model to obtain the optimal solution of the parameters;

[0014] Step 6: Constructing a coordination strategy according to the optimal solution of the parameters.

[0015] Preferably, the ecological background data of the basin includes long-term observation data of meteorological stations, rainfall stations, hydrological stations, underground water monitoring stations and ecosystem flux stations around the basin, remote sensing image data, field investigation data, 10-meter resolution sentinel satellite images and 30-meter resolution digital elevation models (DEM) generated after multi-source data integration; hydrological and meteorological data, soil and vegetation ecological data and topographic and geomorphic data are extracted from the ecological background data of the basin, the sentinel satellite images and the digital elevation model to construct the ecological hydrology database, which provides data support for subsequent ecosystem coupling modeling.

[0016] Preferably, the specific steps of step 2 include:

[0017] Step 21: Using a variable screening method to screen out key ecological factors affecting a single ecosystem in the ecological hydrology database;

[0018] Step 22: Statistically analyzing the action paths between the key ecological factors, performing landscape pattern-ecological process interaction analysis and ecological service change and driving force analysis, and obtaining the key ecological processes corresponding to the landscape pattern;

[0019] Step 23: according to the terrain features, land change model and land surface process model are used for simulation, and land change and land surface process are output, a landscape pattern-ecological process coupling model is constructed according to the land change and land surface process, and the interaction relationship between the distribution pattern of different ecosystems and ecological processes is determined according to the landscape pattern-ecological process coupling model;

[0020] Step 24: according to the interaction relationship between the distribution pattern and the ecological process, a subject-based modeling method is used, different factors in the social system are set, the influence of the social system on the natural ecosystem is simulated, and a natural-social system two-way coupling integrated model is constructed by combining the coupling coordination degree model and the correlation model method;

[0021] Step 25: running the natural-social system two-way coupling integrated model, reasonably analyzing the output simulation results, obtaining the mountain-water-forest-river-lake-grass-sand life community coupling mechanism, and dividing the basin to obtain the ecological function zoning.

[0022] Preferably, the specific steps of step 3 include:

[0023] S31: According to the mountain-water-forest-river-lake-grass-sand life community coupling mechanism and the ecological function zoning, combining the state-stress, pressure-stress interaction relationship between the social system and the economic system, a comprehensive coupling relationship framework between different ecosystems, ecological functions, social systems and economic systems in the basin is constructed, the basin element coupling degree is obtained, and the key ecological and hydrological problems are identified;

[0024] S32: According to the basin element coupling degree and the key ecological and hydrological problems, a nonlinear-multi-objective dynamic programming model is constructed.

[0025] Preferably, the objective function of the nonlinear-multi-objective dynamic programming model includes the optimal target of weighing the basin ecosystem and hydrological function, the maximum target of livestock feeding amount, the maximum target of food production, the minimum target of environmental remediation cost, the minimum target of social change, and the optimal target of environmental quality.

[0026] Preferably, the constraint conditions of the nonlinear-multi-objective dynamic programming model include water resource constraint, area constraint, social constraint, irrigation water quantity constraint, canal system water conveyance efficiency constraint, surface and groundwater availability constraint, water balance constraint, hydrological function target constraint, ecological function target constraint, and non-negative constraint.

[0027] Preferably, a multi-objective optimization algorithm is used to solve the nonlinear-multi-objective dynamic programming model, including gradient algorithm, genetic algorithm, annealing algorithm or particle swarm algorithm.

[0028] Preferably, the nonlinear-multi-objective dynamic programming model is solved to obtain the landscape type j that matches the basin land i, so that the objective function is optimal under the condition of meeting all constraint conditions.

[0029] Compared with the prior art, the application provides a stable and suitable coordination method for watersheds, which is suitable for the fields of watershed ecological protection, ecological restoration, sustainable utilization and climate change adaptive regulation, considers the characteristics of watershed multiplicity, complex relationship, structural heterogeneity, functional diversity and system integrity, is based on the scientific principles of watershed suitable water-soil resource carrying capacity and man-land relationship, water resource balance theory, biodiversity maintenance theory and landscape ecology theory, is based on the change law of ecological elements such as mountains, water, forests, fields, lakes, grasses and sands and the research results of ecological hydrological processes, and constructs a stable and suitable coordination model based on the maintenance of the good relationship of ecological hydrology (a nonlinear-multi-objective dynamic programming model), covers constraint conditions such as water resources, area, social, hydrological function target and ecological function target, is a multi-objective optimization with the optimal ecological hydrological function, the best economic and social benefit and the maximum resources and environment, and combines the high correlation of natural and artificial elements to coordinate the ecological elements such as mountains, water, forests, fields, lakes, grasses and sands, further coordinates the supply, regulation, culture and support service functions of the watershed, establishes a three-in-one protection and management mode and countermeasures of the watershed from the perspective of balancing and coordinating the relationship among the protection and restoration target, social economic cost and ecological environmental benefit, and jointly integrates the ecological construction protection and management technology with the characteristics of the mountain-water-forest-field-lake-grass-sand life community. The application aims to optimize the spatial pattern of watershed ecological elements, enhance the ecological functions such as hydrological regulation, soil conservation, vegetation restoration and biodiversity maintenance, and improve the stability and sustainable development ability of the whole watershed, so as to solve the problems of watershed system regulation and protection in the prior art. BRIEF DESCRIPTION OF DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute the embodiments of the application, and those skilled in the art can obtain other drawings according to the provided drawings without any creative effort.

[0031] Figure 1 A stable and suitable coordination method for watersheds provided by the application is shown in the flowchart.

[0032] Figure 2 An embodiment coordination result diagram provided by the application is shown. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0034] The embodiment of the present application discloses a basin water, forest, farmland, lake and grass and sand stable and suitable coordination method, as shown in the figure, comprising the following steps: Figure 1

[0035] S1: Collecting basin ecological background data and constructing an ecological hydrology database;

[0036] S2: Constructing a landscape pattern-ecosystem coupling model according to the ecological hydrology database, obtaining the coupling mechanism of the water, forest, farmland, lake and grass and sand life community and the ecological function zoning of the basin;

[0037] S3: Constructing a comprehensive coupling relationship framework between different ecological systems-ecological functions-social systems-economic systems in the basin according to the coupling mechanism of the water, forest, farmland, lake and grass and sand life community and the ecological function zoning, analyzing the coupling degree of the basin elements, and identifying key ecological hydrology problems;

[0038] S4: Constructing a nonlinear-multi-objective dynamic programming model according to the coupling degree of the basin elements and the key ecological hydrology problems; constructing the objective function of the nonlinear-multi-objective dynamic programming model with the optimal trade-off of the ecological and hydrological functions of the basin, the maximum livestock feeding amount, the maximum food yield, the minimum social change and the optimal environmental quality as the objective function, and constructing the constraint condition of the nonlinear-multi-objective dynamic programming model;

[0039] S5: Solving the objective function by using a multi-objective optimization algorithm according to the constraint condition to obtain the optimal solution of the parameters of the objective function;

[0040] S6: Constructing a coordination strategy according to the optimal solution of the parameters.

[0041] The present application comprehensively considers the interaction of water, forest, farmland, lake, grass and sand, realizes overall optimization, improves the scientificity and accuracy of the scheme through comprehensive GIS, remote sensing, big data and other basin ecological background data and ecological modeling technology, has a wide application prospect, can be customized according to different geographical environment, climate conditions and social and economic needs of the basin, realizes long-term stable ecological and economic benefits through ecological regulation and restoration measures.

[0042] ​Further, the basin ecological background data includes long-term observation data of meteorological stations, rainfall stations, hydrological stations, groundwater monitoring stations and ecosystem flux stations around the basin, remote sensing image data, field investigation data, 10-meter resolution sentinel satellite images and 30-meter resolution digital elevation model (DEM) generated through multi-source data integration; the ecological hydrological database includes hydro-meteorological data, soil and vegetation ecological data and topographic data, providing data support for subsequent ecosystem coupling modeling.

[0043] Further, the hydro-meteorological data is extracted from long-term observation data and remote sensing data, including historical precipitation data (including monthly, quarterly and annual precipitation), evaporation, transpiration, groundwater level, runoff, lake and wetland hydrology, air temperature and other data of the basin, and water, heat, carbon and nitrogen fluxes calculated based on the above data.

[0044] Further, the soil and vegetation ecological data is extracted from field investigation data and 10-meter resolution sentinel satellite images, including soil structure, water and heat conditions, and vegetation community dominant species, height, coverage, and other key ecological indicators such as vegetation index (NDVI), leaf area index (LAI) and net primary productivity (NPP) calculated using 10-meter resolution sentinel satellite images.

[0045] Further, the topographic data is extracted from 30-meter resolution digital elevation model (DEM) combined with 10-meter resolution sentinel satellite images, including basin boundaries and topographic features.

[0046] Further, the landscape pattern of the basin includes mountain, water body, forest, farmland, lake, grassland and sand, each landscape pattern includes multiple ecosystems, and each ecosystem includes multiple ecological processes.

[0047] Further, the specific steps of S2 include:

[0048] S21: using variable screening method to screen out key ecological factors affecting single ecosystem in ecological hydrological database; the variable screening method includes principal component analysis method or feature engineering, etc.;

[0049] S22: statistical analysis of the action path between each key ecological factor, landscape pattern-ecological process interaction analysis and ecological service change and its driving force analysis, obtaining the key ecological process corresponding to the landscape pattern; the statistical analysis method includes structural equation model (SEM) or path analysis method, through statistical analysis to quantitatively evaluate the action path between each key ecological factor, and identify the key ecological process formed by specific landscape pattern;

[0050] S23: According to the topographic features, land change model and land surface process model are used for simulation, and land change and land surface process are output. A landscape pattern-ecological process coupling model is constructed according to the land change and land surface process, and the distribution pattern of different ecosystems and the interaction relationship between ecological processes are determined according to the landscape pattern-ecological process coupling model;

[0051] S24: According to the interaction relationship between the distribution pattern and the ecological process, an agent-based modeling method (ABM) is used. By setting different policy changes, human behavior changes and technological progress in the social system, the influence of these factors on the natural ecosystem is simulated. Through the coupling coordination degree model and the correlation model method, the bidirectional feedback mechanism between the social system and the natural ecosystem is analyzed, and an integrated model reflecting the bidirectional coupling of the natural-social system is constructed;

[0052] S25: The integrated model is run, and the simulation results are reasonably analyzed to realize application test, reveal the mountain-water-forest-river-lake-grass-sand life community coupling mechanism, and carry out ecological function zoning of the basin.

[0053] Further, the specific steps of S3 include:

[0054] S31: According to the mountain-water-forest-river-lake-grass-sand life community coupling mechanism and the ecological function zoning, the comprehensive coupling relationship between different ecosystems, ecological functions, social systems and economic systems in the basin is obtained by combining the known "state-stress" and "pressure-stress" interaction relationship between the social system and the economic system. According to the framework analysis of the comprehensive coupling relationship, the basin element coupling degree is obtained, and the key ecological and hydrological problems are identified;

[0055] S32: According to the basin element coupling degree and the key ecological and hydrological problems, a target function is constructed. The target function includes the optimal target of weighing the basin ecosystem and hydrological function, the maximum target of livestock feeding amount, the maximum target of grain yield, the minimum target of environmental restoration cost, the minimum target of social change, and the optimal target of environmental quality. The key ecological and hydrological problems are taken as the parameters of the target function to establish the relationship between the parameters around the basin element coupling degree, so as to obtain the target function.

[0056] Further, the target function OptF is represented as:

[0057] OptF=[MaxOb,MaxSC,MaxGR,MinCOST,MinCH,MinEN]

[0058]

[0059] MinEN=ω1·I wq +ω2·I aq +ω3·Ibio

[0060] wherein, represents the optimal target of trade-off between watershed ecosystem and hydrological function; α k represents the weight coefficient of k hydrological function indicators; α l represents the weight coefficient of l ecological function indicators; Hy k represents k hydrological function indicators, including groundwater level, runoff, precipitation, etc.; Ec l represents l ecological function indicators, including vegetation coverage, biodiversity, primary productivity, etc.; X ij is a binary variable, indicating whether the i-th watershed plot is allocated to the j-th landscape type use, X ij = 1 indicates allocation, X ij = 0 indicates no allocation; n represents the total number of watershed plots; m represents the total number of landscape types;

[0061] represents the maximum target of livestock feeding amount; sc ij is the amount of livestock that can be fed in the j-th landscape type, sc jmax represents the maximum amount of livestock that can be fed in the j-th landscape type;

[0062] represents the maximum target of grain yield; gr ij is the grain yield of the j-th landscape type;

[0063] represents the minimum target of environmental remediation cost; co iw is the unit cost of the w-th environmental remediation in the i-th watershed plot, q iw is the scale or quantity of the w-th environmental remediation in the i-th watershed plot, wherein, Costsum represents the total cost; q min ≤ q iw ≤ q max , wherein qmin represents the feasible scale of ecological remediation, and qmax represents the maximum feasible scale;

[0064] represents the minimum target of social change; β1, β2, β3 are the coefficients of economic change, environmental change, and social change, respectively; P i is the weight of each economic factor, indicating its contribution to the total economic change; GDP i is the GDP of the i-th watershed plot or industry; Q j is the weight of each environmental factor, indicating its contribution to the total environmental change; Q j is the environmental and ecological indicator of the j-th landscape type; R cis the weight of each social factor, representing its contribution to the total social change; Ch c is the cth social indicator;

[0065] MinEN = ω1·I wq + ω2·I aq + ω3·I bio represents the optimal target of environmental quality; I wq , I aq , I bio respectively represent water quality indicators, air quality indicators, and biodiversity indicators, and ω1, ω2, and ω3 are the corresponding indicator weight coefficients, used to balance the importance of different factors.

[0066] Preferably, the constraint conditions include water resource constraints, area constraints, social constraints, irrigation water quantity constraints, canal system water delivery efficiency constraints, surface and groundwater availability constraints, water balance constraints, hydrological function target constraints, ecological function target constraints, and non-negative constraints.

[0067] The water resource constraint MaxQHS is represented as: Q(ij, t) ≥ MaxQ HS , where Q(ij, t) represents the water resource quantity of different basins, is the weight of the jth landscape type unit in the ith basin plot; according to the ecological function zoning, the river runoff simulation results Q(t) are obtained by using the hydrological-economic integrated (WEAP) model under the current mountain-water-forest-river-lake-grass-sand configuration conditions, and the river runoff simulation results Q(t) are discretized to the research units of the economic model by using the geographic spatial interpolation method, and the water resource quantities of different basins are calculated.

[0068] The area constraint is represented as:

[0069]

[0070] where A ij is the land use area of the jth landscape type in the ith basin plot, A total is the total land use area; A sczj is the area of the jth landscape type land use suitable climate zone; A ic is the grassland area of the ith basin plot, A itc is the natural grassland area of the ith basin plot, A irc is the artificial grassland area of the ith basin plot; A il is the forest land area of the ith basin plot, A itl is the natural forest land area of the ith basin plot, A ijl is the artificial forest land area of the ith basin plot; A is is the mountainous area of the ith basin plot, and A ixsA

[0071] Social constraints are expressed as:

[0072]

[0073] The planned area of the i-th watershed land block land use type is greater than or equal to the national protected area;

[0074] The irrigation water quantity constraint is expressed as:

[0075]

[0076] wherein A z is the area occupied by irrigation measure z, Ir z is the irrigation water quantity per unit area, Ir permit is the allowable irrigation water quantity;

[0077] The canal system water delivery efficiency constraint is expressed as:

[0078]

[0079] wherein η z is the canal system water delivery efficiency;

[0080] The surface and groundwater availability constraint is expressed as:

[0081]

[0082] wherein, and are the surface water and groundwater allocated in the i-th watershed land block in the t-th month (mm / hm2); is the precipitation in the i-th watershed land block in the t-th month (mm); represents the evapotranspiration of the i-th watershed land block in the t-th month (mm);

[0083] The water balance constraint is expressed as:

[0084]

[0085] wherein I i is the water input of the system, including precipitation, river input, etc., O j is the water output in the system, including evaporation, runoff, etc.

[0086] For the formulated mountain-water-forest-river-lake-grass-sand configuration results, the basic hydrological service functions of river runoff, sediment, flow velocity, and lake ecological water level need to be met at the watershed scale, so the hydrological function target constraint is set, which is expressed as:

[0087]

[0088] wherein H k' , k = 1, 2, 3, 4, 5, 6, 7, respectively represent the regulation capacity of runoff, sediment content, river flow velocity under the current vegetation configuration; K k' represents the balance threshold or ecological capacity of the k'th type of hydrological service function of the watershed, i.e. the target achievement value or target expectation value, with priority level l, l = 1, 2, 3, 4; K 1' represents the regulation capacity of runoff, which is the annual runoff variation rate; K 2' is the appropriate sediment content of the river, which represents the sediment content of the river at time t; K 3' is the river flow velocity, V d < V < V s ; K d The river flow velocity should be between the river deposition flow velocity V s and the river scouring flow velocity V 4' ; K 5' is the river continuous flow state in the runoff area, V(j, t) ≠ 0, j takes the value range of the grid cells in the runoff area of the watershed, and t is the non-frozen period; K 6' is the river continuous flow state in the runoff area: V(j, t) ≠ 0, j takes the value range of the grid cells in the runoff area of the watershed, and t is the non-frozen period; K 7' is the lake water level, H ≥ H s ; K s ;

[0089] The results of the optimal configuration of mountain-water-forest-river-lake-wetland-grass-sand need to meet the basic ecological functions of different types of ecosystems, so the ecological function target constraints are set, which are represented as:

[0090]

[0091] wherein V k , k = 1, 2, 3, 4, respectively represent the lower limit of biodiversity of healthy ecosystems, the minimum ecological flow of rivers, the minimum ecological water level of lakes, and the minimum ecological water demand of wetlands under the current optimal configuration; K klThe balance threshold or ecological capacity of the kth ecological service function of the watershed, i.e. the target achievement value or target expectation value, has a priority level l, l = 1, 2, 3, 4; K1 is a biodiversity index of the watershed, the first-level target value is 20, the second-level target value is 30, and the third-level target value is 60; K2 is the minimum basic flow of the river: the first-level target value is 10% of the average annual runoff, the second-level target value is 20% of the average annual runoff, and the third-level target value is 30% of the average annual runoff; K3 is the satisfaction degree of the minimum ecological water level of the lake: the first-level target value is that the 7d moving average water level is lower than the minimum ecological water level, the second-level target value is that the 3d moving average water level is lower than the minimum ecological water level, but the 7d moving average water level is not lower than the minimum ecological water level, the third-level target value is that the daily average water level is lower than the minimum ecological water level, but the 3d moving average water level is lower than the minimum ecological water level, and the fourth-level target value is that the daily average water level is higher than the minimum ecological water level in the year; K4 is the minimum ecological water requirement of the wetland: the first-level target value is that the wetland vegetation and water surface account for 60%-70% of the total area, the second-level target value is that the wetland vegetation and water surface account for 70%-80% of the total area, and the third-level target value is that the wetland vegetation and water surface account for more than 80% of the total area;

[0092] The non-negative constraint is represented as all variables in all constraints ≥ 0.

[0093] Further, the multi-objective optimization algorithm in S5 includes a gradient algorithm, a genetic algorithm, an annealing algorithm, or a particle swarm algorithm. The multi-objective optimization algorithm is used to solve the model, and the optimal solution of the parameters can guide the specified coordination strategy, thereby maintaining a benign relationship between ecological hydrology; the model is solved to obtain the matching landscape type j of the basin land i that satisfies all constraint conditions, so that the target function is optimal, and the process includes:

[0094] S51: initializing parameters of the non-linear-multi-objective dynamic programming model; the parameters include weight coefficients, ecological system dynamics parameters, etc., and initial values are assigned to the parameters according to actual needs;

[0095] S52: using a multi-objective optimization algorithm to solve the optimal solution of the parameters that satisfy the constraint conditions.

[0096] Further, S6 formulates a coordination strategy according to the meaning of each parameter in the optimal solution of the parameters and the constraint conditions according to actual needs.

[0097] In one specific embodiment, a kind of basin mountain-water-forest-river-lake-grass-sand stable suitable coordination method is applied to the middle and lower reaches of a river in the interlaced region of sand dune and meadow in the east of a certain district, and the mountain-water-forest-river-lake-grass-sand stable suitable coordination result is: grassland accounts for 18.64% of the total area of the whole basin, farmland accounts for 10.34%, water body accounts for 1.09%, forest land accounts for 2.82%, sand land accounts for 66.38%, and other accounts for 0.53%, as shown in Figure 2 .

[0098] The various embodiments described in this specification are presented by way of example, and each embodiment is presented with the understanding that it will not limit the scope of the disclosure. Each embodiment is provided to highlight a certain aspect of the disclosure, and the scope of the disclosure is not limited to that embodiment. The same or similar elements are denoted by the same or similar reference numbers throughout the drawings and the specification.

[0099] The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended 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 stable and suitable coordination of watershed landscapes, forests, fields, lakes, grasslands, and sand, characterized in that, Includes the following steps: Step 1: Collect baseline ecological data of the watershed and construct an eco-hydrological database; Step 2: Construct a landscape pattern-ecosystem coupling model based on the eco-hydrological database to obtain the coupling mechanism of the community of life of mountains, rivers, forests, fields, lakes, grasslands and deserts and the ecological functional zoning of the watershed; Step 3: Based on the coupling mechanism of the community of life of mountains, rivers, forests, fields, lakes, grasslands and deserts and the ecological functional zoning, construct a comprehensive coupling relationship framework between different ecosystems, ecological functions and socio-economic factors in the watershed, and obtain the coupling degree of watershed sub-elements and key eco-hydrological issues; Step 4: Construct a nonlinear-multi-objective dynamic programming model based on the coupling degree of watershed sub-elements and key eco-hydrological issues; Step 5: Solve the nonlinear-multi-objective dynamic programming model to obtain the optimal solution for the parameters; Step 6: Construct a coordination strategy based on the optimal parameter solution; Step 2 includes the following specific steps: Step 21: Use variable screening methods to screen out key ecological factors affecting a single ecosystem in the eco-hydrological database; Step 22: Statistically analyze the interaction pathways between key ecological factors, conduct landscape pattern-ecological process interaction analysis and ecosystem service change and its driving force analysis to obtain the key ecological processes corresponding to the landscape pattern. Step 23: Simulate land change and land surface process based on topographic features using land change and land surface process models, output land change and land surface processes, construct a landscape pattern-ecological process coupling model based on land change and land surface processes, and determine the interaction between the distribution patterns of different ecosystems and ecological processes based on the landscape pattern-ecological process coupling model. Step 24: Based on the interaction between distribution patterns and ecological processes, an agent-based modeling method is adopted. By setting different factors in the social system, the impact of the social system on the natural ecosystem is simulated. Combining the coupling coordination degree model and the correlation model method, a two-way coupled integrated model of the natural-social system is constructed. Step 25: Run the natural-social system bidirectional coupling integrated model, conduct a rationality analysis on the output simulation results, obtain the coupling mechanism of the mountain-water-forest-field-lake-grassland-desert community of life, and divide the watershed to obtain ecological function zoning.

2. The method for stable and suitable coordination of watershed mountains, rivers, forests, fields, lakes, grasslands, and sand according to claim 1, characterized in that, The watershed ecological baseline data includes long-term observation data, remote sensing image data, and field survey data from meteorological stations, rain gauges, hydrological stations, groundwater monitoring stations, and ecosystem flux stations around the watershed. After multi-source data integration, 10-meter resolution Sentinel satellite imagery and 30-meter resolution digital elevation models are generated. Based on the watershed ecological baseline data, Sentinel satellite imagery, and digital elevation models, hydrological and meteorological data, soil and vegetation ecological data, and topographic data are extracted to construct an eco-hydrological database.

3. The method for stable and suitable coordination of watershed mountains, rivers, forests, fields, lakes, grasslands, and sand according to claim 1, characterized in that, Step 3 includes the following specific steps: S31: Based on the coupling mechanism of the community of life of mountains, rivers, forests, fields, lakes, grasslands and deserts and the ecological function zoning, combined with the state-stress and pressure-stress interaction relationship between social systems and economic systems, construct a comprehensive coupling relationship framework between different ecosystems, ecological functions, social systems and economic systems in the basin, obtain the coupling degree of basin sub-elements, and identify key eco-hydrological issues; S32: Construct a nonlinear-multi-objective dynamic programming model based on the coupling degree of watershed sub-elements and key eco-hydrological issues.

4. The method for stable and suitable coordination of watershed mountains, rivers, forests, fields, lakes, grasslands, and sand according to claim 1, characterized in that, The objective functions of the nonlinear multi-objective dynamic programming model include the optimal balance between watershed ecosystem and hydrological functions, the maximum livestock population, the maximum grain yield, the minimum environmental restoration cost, the minimum social change, and the optimal environmental quality.

5. The method for stable and suitable coordination of watershed mountains, rivers, forests, fields, lakes, grasslands, and sand according to claim 4, characterized in that, The constraints of the nonlinear multi-objective dynamic programming model include water resource constraints, area constraints, social constraints, irrigation water volume constraints, canal system water conveyance efficiency constraints, surface and groundwater availability constraints, water balance constraints, hydrological function objective constraints, ecological function objective constraints, and non-negativity constraints.

6. The method for stable and suitable coordination of watershed mountains, rivers, forests, fields, lakes, grasslands, and sand according to claim 4, is characterized in that, Multi-objective optimization algorithms are used to solve nonlinear multi-objective dynamic programming models, including gradient algorithms, genetic algorithms, annealing algorithms, or particle swarm optimization algorithms.

7. The method for stable and suitable coordination of watershed mountains, rivers, forests, fields, lakes, grasslands, and sand according to claim 5, characterized in that, Solving the nonlinear-multi-objective dynamic programming model yields the landscape type j that matches watershed plot i when all constraints are satisfied, thus optimizing the objective function.

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