Small watershed multi-dimensional restoration method oriented to composite ecological characteristics

Abstract

The invention discloses a small watershed multi-dimensional restoration method for composite ecological characteristics, and relates to the technical field of small watershed ecological restoration, and the method comprises the steps: dividing space units through remote sensing images, a digital elevation model (DEM), a laser radar LiDAR and geographic information system (GIS) data, constructing an ecological evaluation system, and recognizing an ecological degradation risk; based on the pollution conduction and symbiotic effect network, analyzing a pollution coupling risk, and setting an ecological interference blocking zone to implement a first blocking strategy; in combination with landform regulation and storage monitoring, calculating a landform regulation and storage capacity index, comparing the landform regulation and storage capacity index with a buffer threshold value Z, and judging the ecological buffer capacity; for the area with insufficient buffering capacity, a second restoration strategy is formulated and comprises flood detention depression construction, ecological percolation ditch arrangement and local moisture-proof plant planting, and ecological buffering function restoration is promoted; a graded early warning and dynamic monitoring mechanism is adopted, continuous optimization of multi-dimensional ecological indexes is achieved, and the ecological environment quality of the small watershed is improved.

Description

Technical Field

[0001] This invention relates to the field of small watershed ecological restoration technology, specifically a multidimensional restoration method for small watersheds with complex ecological characteristics. Background Technology

[0002] Small watersheds, as crucial components of terrestrial ecosystems, bear multiple ecological functions, including water conservation, biodiversity maintenance, soil retention, and landscape provision, playing a fundamental role in maintaining regional ecological security and ecosystem service capacity. However, against the backdrop of continuously increasing watershed development and utilization intensity and rapid evolution of land use structure, small watersheds are facing increasingly severe ecological and environmental problems, such as non-point source pollution diffusion, hydrological process disturbance, ecological buffer zone degradation, and declining geomorphic regulation capacity. These problems often intertwine, forming a complex, multi-pathway ecological risk transmission process, further weakening the ecological stability and resilience of small watersheds.

[0003] Existing methods for small watershed restoration and ecological design have several shortcomings in practical applications. On the one hand, some methods focus on the restoration of single ecological elements such as water bodies, water quality, or green spaces, neglecting the coupling relationships between geographical, ecological, and social factors, and lacking systematic identification and integrated analysis of the multidimensional ecological characteristics of small watersheds. On the other hand, current restoration schemes largely rely on empirical judgment, lacking data-driven risk identification and response mechanisms, making it difficult to dynamically adapt to the ecological state and pollution transmission patterns of different spatial units. This results in low efficiency in the deployment of restoration strategies, poor timeliness of ecological interventions, and limited overall restoration effectiveness. Therefore, a comprehensive, scientific, and targeted small watershed restoration scheme is urgently needed. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a multi-dimensional restoration method for small watersheds with complex ecological characteristics, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a multi-dimensional restoration method for small watersheds with complex ecological characteristics, comprising the following steps:

[0006] S1. Based on remote sensing imagery and digital elevation data, the target small watershed is divided into several spatial units. A three-category evaluation index system is constructed for each spatial unit. An ecological monitoring network is set up in several spatial units to obtain a multi-factor ecological risk layer set, identifying geographical, social, and ecological indicators, and combining them to construct a comprehensive ecological evaluation index Zh. i A preset grading threshold X is set when Zh i <X indicates that the current space unit is at risk of ecological degradation, triggering the first warning instruction;

[0007] S2. Several spatial units that receive the first early warning command are aggregated to generate the first degradation risk area. A pollution transmission and symbiotic effect network between the i-th spatial unit and its adjacent spatial units is constructed. A weighted pollution flow path simulation algorithm is used to construct the pollution symbiotic index Gs between the i-th spatial unit and its j-th adjacent spatial unit. i,j To identify high-pollution linkage areas that cause hydrological process disturbances, a disturbance impact threshold Y is preset, when Gs i,j >Y indicates that the i-th spatial unit poses a risk of pollution transmission to the adjacent j-th spatial unit, which will trigger a pollution symbiotic effect. This is marked as a "hydrologically disordered area". A second risk area is generated by summarizing the data. For the spatial units in the second risk area, a first blocking strategy is generated and implemented.

[0008] S3. After implementing the first blocking strategy, for the second risk area, identify the distribution of flood retention depressions, infiltration ditches, slope areas, and stepped ecological wetlands in the i-th spatial unit, and calculate the geomorphic storage capacity index Tx of the i-th spatial unit. i The preset buffer capacity threshold Z is when Tx i If <Z, then the ecological buffering capacity of the i-th spatial unit is determined to be insufficient, the output is the priority ecological intervention sub-unit, and a second restoration strategy is generated and executed.

[0009] Preferably, S1 includes:

[0010] S11. Obtain the geographic base map of the target small watershed using remote sensing images, digital elevation model (DEM) data, lidar (LiDAR) measurement data, and geographic information system (GIS) data.

[0011] S12. On the two-dimensional small watershed geographic base map, the target small watershed is divided into several spatial units with equal areas.

[0012] Preferably, step S1 further includes:

[0013] S13. Construct three types of evaluation index systems based on each spatial unit, set up a multi-point ecological monitoring network within several spatial units, and obtain multi-factor ecological risk layer set data, including a set of geographical index data, a set of social index data, and a set of ecological index data.

[0014] The set of geographic indicators G includes: slope g1, altitude g2, and land use type code g3 for spatial units;

[0015] The social index set S data includes: s1, s2, and s3, which are the length of the walking path accessible to residents in the spatial unit; s3, the ratio of visible spatial area;

[0016] The set of ecological indicators E includes: the average concentration of nitrogen and phosphorus in water in the spatial unit e1, the amount of soil erosion per unit area e2, and the depth of surface runoff per unit time e3.

[0017] Preferably, step S13 includes:

[0018] S131. Based on the multi-factor ecological risk layer set, after dimensionless processing, a comprehensive ecological evaluation index Zh is constructed. i .

[0019] Preferably, step S13 further includes:

[0020] S132. By pre-setting the grading threshold X, the comprehensive ecological evaluation index Zh i The results of the first evaluation are obtained by comparing the results with the grading threshold X:

[0021] When the comprehensive ecological evaluation index Zh i When the value is ≥ the grading threshold X, it indicates that there is no risk of ecological degradation in the current spatial unit, and continuous monitoring is required.

[0022] When the comprehensive ecological evaluation index Zh i When the threshold value is less than X, it indicates that there is a risk of ecological degradation in the current spatial unit, triggering the first early warning instruction and initiating the monitoring mechanism for pollution transmission and symbiotic effects between spatial units.

[0023] Preferably, step S2 includes:

[0024] S21. Upon receiving the first early warning instruction, several spatial units with ecological degradation risk are aggregated to generate a first degradation risk area. Within the first degradation risk area, a pollution monitoring network is set up to obtain a multi-factor pollution flow layer set, specifically including: the pollution intensity value P in the i-th spatial unit. i The pollution intensity value P in the j-th spatial unit j The number of bidirectional surface runoff connectivity paths W i,j and W j,i The average elevation h of the i-th spatial unit i The average elevation h of the j-th spatial unit j The Euclidean distance d between the centers of mass of the two spatial units i,j .

[0025] Preferably, S21 includes:

[0026] S211. Based on the acquired multi-factor pollution flow layer set, the pollution coupling risk characteristics between the i-th spatial unit and its adjacent j-th spatial unit are identified. A pollution transmission and symbiotic effect network between the i-th spatial unit and its adjacent spatial units is constructed. A weighted pollution flow path simulation algorithm is used, and after dimensionless processing, a pollution symbiotic index Gs between the i-th spatial unit and its j-th adjacent spatial unit is constructed. i,j ;

[0027] S212. By pre-setting the disturbance impact threshold Y, and setting the pollution co-existence index Gs between the i-th spatial unit and the j-th adjacent spatial unit. i,j A comparative analysis was conducted with the disturbance impact threshold Y to obtain the second evaluation results, including:

[0028] When the pollution coexistence index Gs of the i-th spatial unit and the j-th adjacent spatial unit i,j When the value is less than or equal to the disturbance impact threshold Y, it means that the i-th spatial unit does not pose a risk of transmitting pollution to the adjacent j-th spatial unit, and will not cause a pollution symbiotic effect; continuous monitoring is required.

[0029] When the pollution coexistence index Gs of the i-th spatial unit and the j-th adjacent spatial unit i,j When the disturbance impact threshold Y is reached, it indicates that the i-th spatial unit poses a risk of transmissive pollution to the adjacent j-th spatial unit, which will trigger a pollution symbiotic effect, thus triggering a second early warning instruction. The current spatial unit is marked as a "hydrologically disturbed area," a second risk area is generated, and a first blocking strategy is generated and executed for the spatial units within the second risk area. The first blocking strategy includes:

[0030] Ecological disturbance blocking zones are set up in the downstream or lateral connecting spatial units of the pollution path, and spatial units with gentle terrain and slopes of less than 5° are selected. The total number of such zones shall not be less than 60% of the total number of high-risk spatial units.

[0031] Within all barrier zones, bioretention zones, filter ditches, or sustainable vegetation buffer zones should be provided, and their deployment density should cover more than 30% of the spatial unit area of ​​the barrier zone.

[0032] In spatial units with strong continuity of the original pollution pathway, micro-terraced wetlands should be deployed, and their total deployment area should reach more than 20% of the area of ​​the spatial units involved in the dominant pathway.

[0033] At least 50% of the dominant pathway spatial units will undergo micro-modification of the surface structure by setting up intercepting dikes, shallow ditches or diversion barriers to change the runoff direction and guide it to areas with stronger ecological carrying capacity.

[0034] In each spatial unit identified as a critical pollution channel, at least one runoff guidance facility, such as a surface vegetation groove or a lateral drainage channel, is embedded to achieve local interception and deceleration.

[0035] Monitoring points are simultaneously deployed along all spatial units along the blocking path, with a deployment density of no less than 10% of the total number of target spatial units. Changes in the pollution coexistence index before and after the strategy deployment are recorded. A cycle of 15 days is defined. After one cycle, monitoring and calculation are repeated until the pollution coexistence index Gs between the i-th spatial unit and its j-th adjacent spatial unit is reached. i,j Until the disturbance effect threshold Y is reached.

[0036] Preferably, step S3 includes:

[0037] S31. After implementing the first blocking strategy, a geomorphic regulation and storage monitoring network is set up for the second risk area. Based on remote sensing imagery and DEM elevation data, the distribution of flood detention depressions, infiltration ditches, slope areas, and stepped ecological wetlands in the i-th spatial unit is identified, and a multi-factor geomorphic regulation and storage layer set is obtained, including: the area proportion ZA of flood detention depressions in the i-th spatial unit. i The ecological proportion of ecological wetlands in the i-th spatial unit STb i The total length of the infiltration trench in the i-th spatial unit.

[0038] Preferably, step S31 includes:

[0039] S311. Based on the acquired multi-factor geomorphic water storage layer set, identify the natural water storage capacity characteristics of each spatial unit. After dimensionless processing, calculate the geomorphic water storage capacity index Tx of the i-th spatial unit. i .

[0040] Preferably, step S31 further includes:

[0041] S312. By pre-setting the buffer capacity threshold Z, the geomorphic storage capacity index Tx of the i-th spatial unit is... i A comparative analysis with the buffer capacity threshold Z yielded the following third evaluation results:

[0042] When the geomorphic storage capacity index Tx of the i-th spatial unit i If the ecological buffer capacity is greater than or equal to the buffer capacity threshold Z, then the ecological buffer capacity of the i-th spatial unit is deemed qualified and will be continuously monitored.

[0043] When the geomorphic storage capacity index Tx of the i-th spatial unit i When the buffer capacity threshold Z is less than 1, the ecological buffer capacity of the i-th spatial unit is deemed unqualified, triggering a third early warning instruction. The output is designated as a priority ecological intervention sub-unit, and a second restoration strategy is generated and executed. The second restoration strategy includes:

[0044] In all identified spatial units with insufficient water storage capacity, small flood detention depressions, rainwater storage ponds, or surface depressions should be systematically deployed, and the number of such deployments should not be less than 10% of the total number of weak buffer spatial units.

[0045] Ecological infiltration ditches should be laid out within the spatial unit along the main pollution runoff path. The total length of the ditches should not be less than 40% of the original length of the path, and they should form a network with the existing water flow nodes.

[0046] For spatial units with a slope greater than 8%, stepped gentle slope wetlands or vegetation slope protection strips should be configured, and their coverage should be no less than 50% of the total area of ​​the spatial unit.

[0047] In areas lacking water storage capacity, based on a 500m*500m standard grid, each standard grid should be equipped with at least one set of ecological retention facilities, such as artificial wetland plots or underground infiltration modules, and the facility density should reach more than 4 per square kilometer.

[0048] In the buffer zone, the local moisture-tolerant herbaceous plant community should be fully restored, and its vegetation coverage should be increased to 150% of the original level. Planting vegetation types with well-developed root systems and strong purification capabilities is recommended.

[0049] Record the geomorphic storage capacity index Tx of the i-th spatial unit before and after strategy deployment. i The changes; 15 days constitute one cycle, and after two cycles, monitoring and calculation are repeated until the geomorphic storage capacity index Tx of the i-th spatial unit is reached. i Until the buffer capacity threshold Z is reached.

[0050] Beneficial effects:

[0051] By constructing a multi-factor comprehensive evaluation index system that integrates geographical, social, and ecological factors, and combining remote sensing imagery and geographic information system data, a high-resolution ecological monitoring network can be established within a small watershed. This enables dynamic monitoring and accurate identification of ecological degradation risks in spatial units. The method effectively improves the spatial resolution and classification accuracy of ecological degradation risk identification, providing a scientific basis for subsequent zoned governance.

[0052] By proposing a pollution coexistence index, a pollution transmission and coupling mechanism between spatial units is established to identify high-pollution linkage areas that may trigger hydrological disturbances. Furthermore, a disturbance impact threshold is preset to achieve dynamic monitoring of pollution diffusion paths and key transmission nodes. Simultaneously, spatial blocking measures such as "ecological disturbance blocking zones" are used to cut off the main pollution channels, achieving the goal of precise, tiered, and sustainable intervention.

[0053] The geomorphic storage capacity index is calculated by factors such as the proportion of flood retention depressions, the proportion of wetland ecology, and the length of infiltration ditches. The ecological buffer capacity of each spatial unit is systematically evaluated, and a buffer capacity threshold Z is set for dynamic judgment. This effectively identifies areas with weak storage capacity of the ecosystem under external disturbances such as rainstorms and pollution impacts, and provides targeted decision support for ecological restoration intervention.

[0054] By employing a triple early warning system—first, an ecological degradation warning; second, a hydrological disturbance warning; and third, a buffer failure warning—in conjunction with a first blocking strategy and a second restoration strategy, a closed-loop control system with periodic monitoring, strategy iteration, and indicator feedback has been constructed. The ecological restoration effect can be quantitatively assessed through the periodic updates of the pollution symbiosis index and the storage capacity index, achieving full-process regulation of "trigger-intervention-evaluation-correction," and demonstrating significant adaptive management and intelligent evolution capabilities. Attached Figure Description

[0055] Figure 1 This is a schematic diagram illustrating the steps of the multi-dimensional restoration method for small watersheds with complex ecological characteristics provided by the present invention. Detailed Implementation

[0056] 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.

[0057] Example 1

[0058] Please see Figure 1 This invention provides a multidimensional restoration method for small watersheds with complex ecological characteristics, comprising the following steps:

[0059] S1. Based on remote sensing imagery and digital elevation data, the target small watershed is divided into several spatial units. A three-category evaluation index system is constructed for each spatial unit. An ecological monitoring network is set up in several spatial units to obtain a multi-factor ecological risk layer set, identifying geographical, social, and ecological indicators, and combining them to construct a comprehensive ecological evaluation index Zh. i A preset grading threshold X is set when Zh i <X indicates that the current space unit is at risk of ecological degradation, triggering the first warning instruction;

[0060] S2. Several spatial units that receive the first early warning command are aggregated to generate the first degradation risk area. A pollution transmission and symbiotic effect network between the i-th spatial unit and its adjacent spatial units is constructed. A weighted pollution flow path simulation algorithm is used to construct the pollution symbiotic index Gs between the i-th spatial unit and its j-th adjacent spatial unit. i,j To identify high-pollution linkage areas that cause hydrological process disturbances, a disturbance impact threshold Y is preset, when Gs i,j >Y indicates that the i-th spatial unit poses a risk of pollution transmission to the adjacent j-th spatial unit, which will trigger a pollution symbiotic effect. This is marked as a "hydrologically disordered area". A second risk area is generated by summarizing the data. For the spatial units in the second risk area, a first blocking strategy is generated and implemented.

[0061] S3. After implementing the first blocking strategy, for the second risk area, identify the distribution of flood retention depressions, infiltration ditches, slope areas, and stepped ecological wetlands in the i-th spatial unit, and calculate the geomorphic storage capacity index Tx of the i-th spatial unit. i The preset buffer capacity threshold Z is when Tx i If <Z, then the ecological buffering capacity of the i-th spatial unit is determined to be insufficient, the output is the priority ecological intervention sub-unit, and a second restoration strategy is generated and executed.

[0062] In this embodiment, by constructing a three-stage progressive multidimensional restoration process of ecological degradation early warning, pollution symbiosis identification, and ecological buffer assessment, dynamic identification and response to complex ecological risks in small watersheds can be achieved. Among them, the pollution symbiosis index is used to identify high-linkage risk areas and deploy "ecological disturbance blocking zones" to effectively cut off the dominant path of pollution runoff, enhance the hydrological process regulation capacity, and improve the spatial accuracy of restoration strategies and the effectiveness of ecological intervention.

[0063] Example 2

[0064] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, S1 includes:

[0065] S11. Obtain the geographic base map of the target small watershed using remote sensing images, digital elevation model (DEM) data, lidar (LiDAR) measurement data, and geographic information system (GIS) data.

[0066] S12. On the two-dimensional small watershed geographic base map, the target small watershed is divided into several spatial units with equal areas.

[0067] In this embodiment, a high-precision two-dimensional geographic base map is constructed by integrating remote sensing images, DEM data, LiDAR measurements, and GIS geographic information. The target small watershed is divided into spatial units of equal area, providing a unified spatial analysis unit basis for subsequent multi-factor ecological assessment and regional risk identification. This significantly improves the spatial resolution and operational accuracy of ecological risk identification and intervention strategy deployment.

[0068] Example 3

[0069] This embodiment is an explanation based on Embodiment 2. Please refer to it. Figure 1 Specifically, step S1 also includes:

[0070] S13. Construct three types of evaluation index systems based on each spatial unit, set up a multi-point ecological monitoring network within several spatial units, and obtain multi-factor ecological risk layer set data, including a set of geographical index data, a set of social index data, and a set of ecological index data.

[0071] The set of geographic indicators G includes: slope g1, altitude g2, and land use type code g3 for spatial units;

[0072] The social index set S data includes: s1, s2, and s3, which are the length of the walking path accessible to residents in the spatial unit; s3, the ratio of visible spatial area;

[0073] The set of ecological indicators E includes: the average concentration of nitrogen and phosphorus in water in the spatial unit e1, the amount of soil erosion per unit area e2, and the depth of surface runoff per unit time e3.

[0074] In this embodiment, by constructing a comprehensive evaluation index system that includes three categories of indicators: geographical, social, and ecological, and by combining it with a multi-point ecological monitoring network to obtain a multi-factor ecological risk layer set, a multi-dimensional and accurate characterization of the ecological status of small watershed spatial units is achieved, effectively improving the ability to identify complex ecological characteristics and the scientific and comprehensive nature of degradation risk assessment.

[0075] Example 4

[0076] This embodiment is an explanation based on Embodiment 3. Please refer to it. Figure 1 Specifically, step S13 includes:

[0077] S131. Based on the multi-factor ecological risk layer set, after dimensionless processing, a comprehensive ecological evaluation index Zh is constructed. i The formula is as follows:

[0078] Zh i =w1*f(G i )+w2*f(S i )+w3*f(Ei );

[0079] In the formula, G i S represents the set of geographical indicators for the i-th spatial unit. i E represents the set of social indicators for the i-th spatial unit. i Let f(.) represent the set of ecological indicators for the i-th spatial unit, f(.) represent the feature set weighting function, w1, w2 and w3 represent the weight coefficients, 0 < w1 < 1, 0 < w2 < 1 and 0 < w3 < 1, and w1 + w2 + w3 = 1;

[0080] G i ={g1 i g2 i g3 i};

[0081] In the formula, g1 i G2 represents the slope of the i-th spatial unit. i G3 represents the altitude of the i-th spatial unit. i This represents the land use type code for the i-th spatial unit;

[0082] S i ={s1 i ,s2 i ,s3 i};

[0083] In the formula, s1 i s2 represents the walking path length accessible to residents of the i-th spatial unit. i s3 represents the visible area ratio of the i-th spatial unit. i The i-th spatial unit represents the landscape aesthetics score. Residents, tourists, and landscape planning experts are organized to score the target area in terms of landscape aesthetics, ecological diversity, and visual accessibility. The comprehensive score is formed by combining the opinions of all parties.

[0084] E i ={e1 i e2 i e3 i};

[0085] In the formula, e1 i e2 represents the average nitrogen and phosphorus concentration in the water of the i-th spatial unit. i This represents the soil erosion per unit area in the i-th spatial unit. Soil erosion plots are established, and lost soil particles are collected periodically using sedimentation pits, troughs, or pans. The actual mass and volume of eroded soil are measured and converted into erosion per unit area, e3. i This represents the surface runoff depth per unit time in the i-th spatial unit;

[0086] The methods for obtaining w1, w2, and w3 are as follows: By comprehensively analyzing historical monitoring data from various types of ecological restoration projects and ecological evolution samples from typical small watersheds, a weighted method combining principal component analysis (PCA) and entropy weighting was used to extract the weights of the dominant factors influencing changes in the ecological quality of small watersheds. Based on this, the Expert Hierarchy Process (AHP) was introduced to adjust the relative importance of geographical, social, and ecological indicators, as well as spatial visibility factors, to construct a multidimensional weighted decision matrix. Finally, the weighting coefficients w1, w2, and w3 were determined to reflect the influence of various indicators on the comprehensive ecological evaluation index Zh. i This will enhance the scientific rigor and regional adaptability of the evaluation results, and provide data support for subsequent remediation priority ranking and strategy generation.

[0087] In this embodiment, by performing dimensionless processing on the multi-factor ecological risk layer set and introducing a weighted function to construct a comprehensive ecological evaluation index, the fusion and quantification of different types of indicators under a unified scale are realized, which effectively improves the comparability and credibility of the ecological evaluation results and provides a scientific basis for the accurate identification of ecological degradation risks in small watersheds.

[0088] Example 5

[0089] This embodiment is an explanation based on Embodiment 4. Please refer to it. Figure 1 Specifically, step S13 also includes:

[0090] S132. By pre-setting the grading threshold X, the comprehensive ecological evaluation index Zh i The results of the first evaluation are obtained by comparing the results with the grading threshold X:

[0091] When the comprehensive ecological evaluation index Zh i When the value is ≥ the grading threshold X, it indicates that there is no risk of ecological degradation in the current spatial unit, and continuous monitoring is required.

[0092] When the comprehensive ecological evaluation index Zh i When the threshold value is less than X, it indicates that there is a risk of ecological degradation in the current spatial unit, triggering the first early warning instruction and initiating the monitoring mechanism for pollution transmission and symbiotic effects between spatial units.

[0093] The grading threshold X was obtained by conducting large-sample statistical analysis of the historical evolution process, ecological degradation cases, and restoration intervention effects of multiple typical small watersheds, combined with the comprehensive ecological evaluation index Zh of spatial units at different periods. iBased on the changing trends, a degradation response database was constructed. On this basis, referencing industry standards such as the "Technical Specifications for Ecological Environment Status Assessment" and the "Guidelines for Watershed Water Ecological Environment Monitoring and Assessment," and in conjunction with the opinions of an ecological expert group, the boundaries of ecological degradation risk levels were scientifically delineated, and a warning threshold X for the comprehensive ecological evaluation index was set. This threshold is used to distinguish between three typical states: mild degradation, potential degradation, and severe degradation, enabling rapid identification and priority marking of highly sensitive areas in small watersheds, thereby improving the efficiency and accuracy of ecological intervention.

[0094] In this embodiment, by comparing the comprehensive ecological evaluation index with a preset grading threshold X, the system can dynamically identify and grade the ecological degradation risk of each spatial unit, effectively avoiding the "homogeneous treatment" problem in traditional restoration methods. Based on risk identification, the system can automatically trigger early warning commands and link pollution transmission mechanisms to establish an early response mechanism for highly sensitive areas, improving the timeliness and accuracy of inter-spatial unit linkage monitoring and intervention, and significantly enhancing the initiative and intelligence level of small watershed ecological management.

[0095] Example 6

[0096] This embodiment is an explanation based on Embodiment 5. Please refer to it. Figure 1 Specifically, step S2 includes:

[0097] S21. Upon receiving the first early warning instruction, several spatial units with ecological degradation risk are aggregated to generate a first degradation risk area. Within the first degradation risk area, a pollution monitoring network is set up to obtain a multi-factor pollution flow layer set, specifically including: the pollution intensity value P in the i-th spatial unit. i The pollution intensity value P in the j-th spatial unit j The number of bidirectional surface runoff connectivity paths W i,j and W j,i The average elevation h of the i-th spatial unit i The average elevation h of the j-th spatial unit j The Euclidean distance d between the centers of mass of the two spatial units i,j .

[0098] In this embodiment, by setting up a pollution monitoring network in the first degradation risk area and collecting a multi-factor pollution flow layer set, it is possible to accurately model the differences in pollution intensity and runoff connectivity between spatial units. In particular, considering the elevation difference and spatial distance, it improves the simulation accuracy of pollution migration paths and transmission trends, providing high-resolution and dynamic data support for subsequent identification of symbiotic pollution and formulation of blocking strategies, thereby enhancing the scientific nature of small watershed pollution control and the pertinence of regional response.

[0099] Example 7

[0100] This embodiment is an explanation based on Embodiment 6. Please refer to it. Figure 1 Specifically, S21 includes:

[0101] S211. Based on the acquired multi-factor pollution flow layer set, the pollution coupling risk characteristics between the i-th spatial unit and its adjacent j-th spatial unit are identified. A pollution transmission and symbiotic effect network between the i-th spatial unit and its adjacent spatial units is constructed. A weighted pollution flow path simulation algorithm is used, and after dimensionless processing, a pollution symbiotic index Gs between the i-th spatial unit and its j-th adjacent spatial unit is constructed. i,j The formula is as follows:

[0102]

[0103] In the formula, P i P represents the pollution intensity value within the i-th spatial unit. j W represents the pollution intensity value within the j-th spatial unit. i,j W represents the number of surface runoff connectivity paths from spatial unit i to spatial unit j. j,i d represents the number of surface runoff connectivity paths from spatial unit j to spatial unit i. i,j H represents the Euclidean distance between the centroids of two spatial units. i,j This represents the relative elevation difference in slope between spatial unit i and spatial unit j;

[0104]

[0105] In the formula, h i h represents the average elevation of the i-th spatial unit. j Let h represent the average elevation of the j-th spatial unit; i ≤h j At that time, H i,j =0 indicates no gradient conduction;

[0106] S212. By pre-setting the disturbance impact threshold Y, and setting the pollution co-existence index Gs between the i-th spatial unit and the j-th adjacent spatial unit. i,j A comparative analysis was conducted with the disturbance impact threshold Y to obtain the second evaluation results, including:

[0107] When the pollution coexistence index Gs of the i-th spatial unit and the j-th adjacent spatial unit i,j When the value is less than or equal to the disturbance impact threshold Y, it means that the i-th spatial unit does not pose a risk of transmitting pollution to the adjacent j-th spatial unit, and will not cause a pollution symbiotic effect; continuous monitoring is required.

[0108] When the pollution coexistence index Gs of the i-th spatial unit and the j-th adjacent spatial uniti,j When the disturbance impact threshold Y is reached, it indicates that the i-th spatial unit poses a risk of transmissive pollution to the adjacent j-th spatial unit, which will trigger a pollution symbiotic effect, thus triggering a second early warning instruction. The current spatial unit is marked as a "hydrologically disturbed area," a second risk area is generated, and a first blocking strategy is generated and executed for the spatial units within the second risk area. The first blocking strategy includes:

[0109] Ecological disturbance blocking zones are set up in the downstream or lateral connecting spatial units of the pollution path, and spatial units with gentle terrain and slopes of less than 5° are selected. The total number of such zones shall not be less than 60% of the total number of high-risk spatial units.

[0110] Within all barrier zones, bioretention zones, filter ditches, or sustainable vegetation buffer zones should be provided, and their deployment density should cover more than 30% of the spatial unit area of ​​the barrier zone.

[0111] In spatial units with strong continuity of the original pollution pathway, micro-terraced wetlands should be deployed, and their total deployment area should reach more than 20% of the area of ​​the spatial units involved in the dominant pathway.

[0112] At least 50% of the dominant pathway spatial units will undergo micro-modification of the surface structure by setting up intercepting dikes, shallow ditches or diversion barriers to change the runoff direction and guide it to areas with stronger ecological carrying capacity.

[0113] In each spatial unit identified as a critical pollution channel, at least one runoff guidance facility, such as a surface vegetation groove or a lateral drainage channel, is embedded to achieve local interception and deceleration.

[0114] Monitoring points are simultaneously deployed along all spatial units along the blocking path, with a deployment density of no less than 10% of the total number of target spatial units. Changes in the pollution coexistence index before and after the strategy deployment are recorded. A cycle of 15 days is defined. After one cycle, monitoring and calculation are repeated until the pollution coexistence index Gs between the i-th spatial unit and its j-th adjacent spatial unit is reached. i,j Until the disturbance effect threshold Y is reached.

[0115] The method for obtaining the disturbance impact threshold Y: Statistical analysis of pollution symbiosis index data from various spatial units within a large number of small watersheds under diverse ecological environments and pollution conditions was conducted. This analysis, combined with pollutant diffusion mechanisms and hydrological process response characteristics, extracted the distribution range and typical variation patterns of the total pollution symbiosis index. Referring to relevant environmental protection standards, water pollution risk assessment specifications, and the experience of experts in ecological restoration, a reasonable threshold Y was comprehensively determined to scientifically reflect the ecological risk level caused by pollution transmission. This threshold can accurately distinguish the severity of pollution symbiosis effects, guide the identification of key pollution units and the formulation of targeted intervention measures, and ensure the dynamic monitoring and effective control of the pollution transmission network.

[0116] In this embodiment, a pollution transmission and symbiotic effect network is constructed, and a weighted pollution flow path simulation algorithm is used to accurately calculate the pollution symbiotic index between spatial units. Based on a preset disturbance impact threshold Y, hydrological disturbance areas are dynamically identified, effectively revealing key pathways and high-risk nodes of pollution transmission. Based on this, a scientifically sound first-line blocking strategy is formulated, and ecological disturbance blocking zones and ecological buffer facilities are deployed. This can effectively cut off pollution runoff channels, reduce pollutant migration, alleviate hydrological process disturbances, and significantly improve the accuracy and sustainable effectiveness of small watershed ecological restoration through periodic monitoring and dynamic adjustment of intervention measures.

[0117] Example 8

[0118] This embodiment is an explanation based on Embodiment 7. Please refer to it. Figure 1 Specifically, step S3 includes:

[0119] S31. After implementing the first blocking strategy, a geomorphic regulation and storage monitoring network is set up for the second risk area. Based on remote sensing imagery and DEM elevation data, the distribution of flood detention depressions, infiltration ditches, slope areas, and stepped ecological wetlands in the i-th spatial unit is identified, and a multi-factor geomorphic regulation and storage layer set is obtained, including: the area proportion ZA of flood detention depressions in the i-th spatial unit. i The ecological proportion of ecological wetlands in the i-th spatial unit STb i The total length of the infiltration trench in the i-th spatial unit.

[0120] In this embodiment, by setting up a geomorphic regulation and storage monitoring network and combining remote sensing images and DEM elevation data, the distribution characteristics of flood retention depressions, infiltration ditches, slope areas and stepped ecological wetlands in each spatial unit within the second risk area are accurately identified. A multi-factor geomorphic regulation and storage layer set is also obtained, which effectively reflects the regulation and storage capacity and ecological structure status of the spatial units. This provides a scientific basis for subsequent ecological buffer capacity assessment and targeted restoration strategies, and enhances the hydrological regulation and pollution slow release functions of the small watershed ecosystem.

[0121] Example 9

[0122] This embodiment is an explanation based on Embodiment 8. Please refer to it. Figure 1 Specifically, step S31 includes:

[0123] S311. Based on the acquired multi-factor geomorphic water storage layer set, identify the natural water storage capacity characteristics of each spatial unit. After dimensionless processing, calculate the geomorphic water storage capacity index Tx of the i-th spatial unit. i The formula is as follows:

[0124] Tx i =a1*ZA i +a2*STbi +a3*CLG i ;

[0125] In the formula, ZA i STb represents the area proportion of the flood detention depression in the i-th spatial unit. i CLG represents the ecological proportion of wetlands in the i-th spatial unit. i The total length of the infiltration trench is represented by a1, a2, and a3, which are weighting coefficients, 0 < a1 < 1, 0 < a2 < 1, and 0 < a3 < 1, and a1 + a2 + a3 = 1.

[0126] The methods for obtaining a1, a2, and a3 are as follows: Statistical analysis of field survey data and remote sensing monitoring data from a large number of typical small watersheds, combined with the measured contribution rates of flood detention depressions, ecological wetlands, and infiltration ditches in different geomorphic units to hydrological regulation and their ecological function impacts. Through multi-factor regression analysis and expert review, combined with relevant eco-hydrological models and regional ecological restoration needs, the relative weight coefficients of each regulation factor are scientifically determined. Referring to domestic and international research results on water conservancy and ecological regulation, ecological wetland protection standards, and geomorphic regulation efficiency assessment standards, a reasonable weight coefficient system is formulated to ensure that the geomorphic regulation capacity index accurately reflects the comprehensive contribution of different regulation factors, guiding the optimization design and implementation of subsequent ecological restoration strategies. In this embodiment, a multi-factor geomorphic storage capacity index is constructed, which includes the proportion of flood retention depression area, the ecological proportion of ecological wetland and the total length of infiltration ditch space. This index is used to quantitatively assess the natural storage capacity of each spatial unit, realize the scientific identification and dimensionless unified processing of geomorphic storage characteristics, provide a quantitative basis for accurately determining the strength of ecological buffer capacity and formulating differentiated restoration strategies, and improve the overall storage and protection efficiency of small watershed ecosystems.

[0127] In this embodiment, a multi-factor geomorphic storage capacity index is constructed, which includes the proportion of flood retention depression area, the ecological proportion of ecological wetland and the total length of infiltration ditch space. This index is used to quantitatively assess the natural storage capacity of each spatial unit, realize the scientific identification and dimensionless unified processing of geomorphic storage characteristics, provide a quantitative basis for accurately determining the strength of ecological buffer capacity and formulating differentiated restoration strategies, and improve the overall storage and protection efficiency of small watershed ecosystems.

[0128] Example 10

[0129] This embodiment is an explanation based on Embodiment 9. Please refer to it. Figure 1 Specifically, step S31 also includes:

[0130] S312. By pre-setting the buffer capacity threshold Z, the geomorphic storage capacity index Tx of the i-th spatial unit is... i A comparative analysis with the buffer capacity threshold Z yielded the following third evaluation results:

[0131] When the geomorphic storage capacity index Tx of the i-th spatial unit i If the ecological buffer capacity is greater than or equal to the buffer capacity threshold Z, then the ecological buffer capacity of the i-th spatial unit is deemed qualified and will be continuously monitored.

[0132] When the geomorphic storage capacity index Tx of the i-th spatial unit i When the buffer capacity threshold Z is less than 1, the ecological buffer capacity of the i-th spatial unit is deemed unqualified, triggering a third early warning instruction. The output is designated as a priority ecological intervention sub-unit, and a second restoration strategy is generated and executed. The second restoration strategy includes:

[0133] In all identified spatial units with insufficient water storage capacity, small flood detention depressions, rainwater storage ponds, or surface depressions should be systematically deployed, and the number of such deployments should not be less than 10% of the total number of weak buffer spatial units.

[0134] Ecological infiltration ditches should be laid out within the spatial unit along the main pollution runoff path. The total length of the ditches should not be less than 40% of the original length of the path, and they should form a network with the existing water flow nodes.

[0135] For spatial units with a slope greater than 8%, stepped gentle slope wetlands or vegetation slope protection strips should be configured, and their coverage should be no less than 50% of the total area of ​​the spatial unit.

[0136] In areas lacking water storage capacity, based on a 500m*500m standard grid, each standard grid should be equipped with at least one set of ecological retention facilities, such as artificial wetland plots or underground infiltration modules, and the facility density should reach more than 4 per square kilometer.

[0137] In the buffer zone, the local moisture-tolerant herbaceous plant community should be fully restored, and its vegetation coverage should be increased to 150% of the original level. Planting vegetation types with well-developed root systems and strong purification capabilities is recommended.

[0138] Record the geomorphic storage capacity index Tx of the i-th spatial unit before and after strategy deployment. i The changes; 15 days constitute one cycle, and after two cycles, monitoring and calculation are repeated until the geomorphic storage capacity index Tx of the i-th spatial unit is reached. i Until the buffer capacity threshold Z is reached.

[0139] The buffer capacity threshold Z is determined based on measured data of the storage capacity of multiple typical small watersheds and long-term tracking studies of ecological restoration effects, combined with simulation results of hydrological storage models and analysis of historical flood control effectiveness. By statistically analyzing the distribution range of storage capacity of different geomorphic units under the configuration of storage elements such as flood detention basins, ecological wetlands, and infiltration ditches, and referring to national water resources management standards, ecological and environmental protection regulations, and watershed flood control design specifications, combined with expert experience and regional ecological restoration goals, a reasonable critical threshold Z for storage capacity is scientifically set. This threshold is used to determine whether a spatial unit possesses sufficient natural storage capacity, thereby guiding the implementation of priority ecological intervention and restoration measures, and improving the overall ecological security and hydrological control capacity of the small watershed.

[0140] In this embodiment, by setting a buffer capacity threshold Z and dynamically comparing the geomorphic regulation capacity index with this threshold, the system can accurately identify spatial units with insufficient ecological buffer capacity, promptly trigger early warning and priority ecological intervention measures, effectively improve the hydrological regulation and ecological restoration capacity of key areas, promote soil and water conservation and pollution slow release within the basin, ensure the continuous stability of the ecological environment, and achieve scientific and refined ecological restoration management.

[0141] The threshold size is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value, it is acceptable.

Claims

1. A multidimensional restoration method for small watersheds with complex ecological characteristics, characterized in that, Includes the following steps: S1. Based on remote sensing imagery and digital elevation data, the target small watershed is divided into several spatial units. A three-category evaluation index system is constructed for each spatial unit. An ecological monitoring network is set up in several spatial units to obtain a multi-factor ecological risk layer set, identifying geographical, social, and ecological indicators, and combining them to construct a comprehensive ecological evaluation index. A preset grading threshold X is set when... This indicates that the current space unit is at risk of ecological degradation, triggering the first early warning instruction; S2. Several spatial units that receive the first early warning command are aggregated to generate the first degradation risk area. A pollution transmission and symbiotic effect network between the i-th spatial unit and its adjacent spatial units is constructed. A weighted pollution flow path simulation algorithm is used to construct the pollution symbiotic index between the i-th spatial unit and its j-th adjacent spatial unit. To identify high-pollution linkage areas that cause hydrological process disturbances, a disturbance impact threshold Y is preset. This indicates that the i-th spatial unit poses a risk of pollution transmission to the adjacent j-th spatial unit, which will trigger a pollution symbiotic effect. This is marked as a "hydrologically disordered area". A second risk area is generated by summarizing these areas. For the spatial units in the second risk area, a first blocking strategy is generated and implemented. S3. After implementing the first blocking strategy, for the second risk area, identify the distribution of flood retention depressions, infiltration ditches, slope areas, and stepped ecological wetlands in the i-th spatial unit, and calculate the geomorphic storage capacity index of the i-th spatial unit. The preset buffer capacity threshold Z is when If the ecological buffering capacity of the i-th spatial unit is insufficient, the output is the priority ecological intervention sub-unit, and a second restoration strategy is generated and executed.

2. The multidimensional restoration method for small watersheds with complex ecological characteristics according to claim 1, characterized in that, S1 includes: S11. Obtain the geographic base map of the target small watershed using remote sensing images, digital elevation model (DEM) data, lidar (LiDAR) measurement data, and geographic information system (GIS) data. S12. On the two-dimensional small watershed geographic base map, the target small watershed is divided into several spatial units with equal areas.

3. The method for multidimensional restoration of small watersheds with complex ecological characteristics according to claim 2, characterized in that, Step S1 also includes: S13. Construct three types of evaluation index systems based on each spatial unit, set up a multi-point ecological monitoring network within several spatial units, and obtain multi-factor ecological risk layer set data, including a set of geographical index data, a set of social index data, and a set of ecological index data. The set of geographic indicators G includes: slope g1, altitude g2, and land use type code g3 for spatial units; The social index set S data includes: s1, s2, and s3, which are the length of the walking path accessible to residents in the spatial unit; s3, the ratio of visible spatial area; The set of ecological indicators E includes: the average concentration of nitrogen and phosphorus in water in the spatial unit e1, the amount of soil erosion per unit area e2, and the depth of surface runoff per unit time e3.

4. The method for multidimensional restoration of small watersheds with complex ecological characteristics according to claim 3, characterized in that, Step S13 includes: S131. Based on the multi-factor ecological risk layer set, after dimensionless processing, a comprehensive ecological evaluation index is constructed. .

5. A multi-dimensional restoration method for small watersheds with complex ecological characteristics according to claim 4, characterized in that, Step S13 also includes: S132. By pre-setting the grading threshold X, the comprehensive ecological evaluation index is... The results of the first evaluation are obtained by comparing the results with the grading threshold X: When the comprehensive ecological evaluation index When the value is ≥ the grading threshold X, it indicates that there is no risk of ecological degradation in the current spatial unit, and continuous monitoring is required. When the comprehensive ecological evaluation index When the threshold value is less than X, it indicates that there is a risk of ecological degradation in the current spatial unit, triggering the first early warning instruction and initiating the monitoring mechanism for pollution transmission and symbiotic effects between spatial units.

6. A multi-dimensional restoration method for small watersheds with complex ecological characteristics according to claim 5, characterized in that, Step S2 includes: S21. Upon receiving the first early warning instruction, several spatial units with ecological degradation risk are aggregated to generate a first degradation risk area. Within the first degradation risk area, a pollution monitoring network is set up to obtain a multi-factor pollution flow layer set, specifically including: the pollution intensity value within the i-th spatial unit. Pollution intensity value within the j-th spatial unit Number of bidirectional surface runoff connectivity paths and The average elevation of the i-th spatial unit The average elevation of the j-th spatial unit Euclidean distance between the centers of gravity of the two spatial units .

7. A multi-dimensional restoration method for small watersheds with complex ecological characteristics according to claim 6, characterized in that, S21 includes: S211. Based on the acquired multi-factor pollution flow layer set, identify the pollution coupling risk characteristics between the i-th spatial unit and its adjacent j-th spatial unit, construct a pollution transmission and symbiotic effect network between the i-th spatial unit and its adjacent spatial units, and construct a pollution symbiotic index between the i-th spatial unit and its adjacent spatial units after dimensionless processing using a weighted pollution flow path simulation algorithm. ; S212. By pre-setting the disturbance impact threshold Y, and setting the pollution co-existence index between the i-th spatial unit and the j-th adjacent spatial unit. A comparative analysis was conducted with the disturbance impact threshold Y to obtain the second evaluation results, including: When the pollution coexistence index of the i-th spatial unit and the j-th adjacent spatial unit When the value is less than or equal to the disturbance impact threshold Y, it means that the i-th spatial unit does not pose a risk of transmitting pollution to the adjacent j-th spatial unit, and will not cause a pollution symbiotic effect; continuous monitoring is required. When the pollution coexistence index of the i-th spatial unit and the j-th adjacent spatial unit When the disturbance impact threshold Y is reached, it indicates that the i-th spatial unit poses a risk of transmissive pollution to the adjacent j-th spatial unit, which will trigger a pollution symbiotic effect, thus triggering a second early warning instruction. The current spatial unit is marked as a "hydrologically disturbed area," a second risk area is generated, and a first blocking strategy is generated and executed for the spatial units within the second risk area. The first blocking strategy includes: Ecological disturbance blocking zones should be set up downstream of the pollution path or in the horizontally connected spatial units, and the number of such zones should be no less than 60% of the total number of high-risk spatial units. Within all barrier zones, bioretention zones, filter ditches, or sustainable vegetation buffer zones should be provided, and their deployment density should cover more than 30% of the spatial unit area of ​​the barrier zone. In spatial units with strong continuity of the original pollution pathway, micro-terraced wetlands should be deployed, and their total deployment area should reach more than 20% of the area of ​​the spatial units involved in the dominant pathway. At least 50% of the dominant pathway spatial units will undergo micro-modification of the surface structure by setting up intercepting dikes, shallow ditches or diversion barriers to change the direction of runoff and guide it to areas with stronger ecological carrying capacity. In each spatial unit identified as a critical pollution channel, at least one runoff guidance facility, such as a surface vegetation groove or a lateral drainage channel, is embedded to achieve local interception and deceleration. Monitoring points are simultaneously deployed along all spatial units along the blocking path, with a deployment density of no less than 10% of the total number of target spatial units. Changes in the pollution coexistence index before and after the strategy deployment are recorded. A cycle of 15 days is defined. After one cycle, monitoring and calculation are repeated until the pollution coexistence index between the i-th spatial unit and its j-th adjacent spatial unit is reached. Until the disturbance effect threshold Y is reached.

8. A multi-dimensional restoration method for small watersheds with complex ecological characteristics according to claim 7, characterized in that, Step S3 includes: S31. After implementing the first blocking strategy, a geomorphic regulation and storage monitoring network is set up for the second risk area. Based on remote sensing imagery and DEM elevation data, the distribution of flood detention depressions, infiltration ditches, slope areas, and stepped ecological wetlands in the i-th spatial unit is identified, and a multi-factor geomorphic regulation and storage layer set is obtained, including: the area ratio of flood detention depressions in the i-th spatial unit. Ecological proportion of ecological wetlands in the i-th spatial unit The total length of the infiltration trench in the i-th spatial unit.

9. A multi-dimensional restoration method for small watersheds with complex ecological characteristics according to claim 8, characterized in that, Step S31 includes: S311. Based on the acquired multi-factor geomorphic water storage layer set, identify the natural water storage capacity characteristics of each spatial unit. After dimensionless processing, calculate the geomorphic water storage capacity index of the i-th spatial unit. .

10. A multi-dimensional restoration method for small watersheds with complex ecological characteristics according to claim 9, characterized in that, Step S31 also includes: S312. By pre-setting the buffer capacity threshold Z, the geomorphic storage capacity index of the i-th spatial unit is... A comparative analysis with the buffer capacity threshold Z yielded the following third evaluation results: When the geomorphic storage capacity index of the i-th spatial unit If the ecological buffer capacity is greater than or equal to the buffer capacity threshold Z, then the ecological buffer capacity of the i-th spatial unit is deemed qualified and will be continuously monitored. When the geomorphic storage capacity index of the i-th spatial unit When the buffer capacity threshold Z is less than 1, the ecological buffer capacity of the i-th spatial unit is deemed unqualified, triggering a third early warning instruction. The output is designated as a priority ecological intervention sub-unit, and a second restoration strategy is generated and executed. The second restoration strategy includes: In all identified spatial units with insufficient water storage capacity, small flood detention depressions, rainwater storage ponds, or surface depressions should be systematically deployed, and their number should not be less than 10% of the total number of weak buffer spatial units; Ecological infiltration ditches should be laid out within the spatial unit along the main pollution runoff path. The total length of the ditches should not be less than 40% of the original length of the path, and they should form a network with the existing water flow nodes. For spatial units with a slope greater than 8%, stepped gentle slope wetlands or vegetation slope protection strips should be configured, with a coverage rate of not less than 50% of the total area of ​​the spatial unit; In areas lacking water storage capacity, based on a 500m*500m standard grid, each standard grid should be equipped with at least one set of ecological retention facilities, such as artificial wetland plots or underground infiltration modules, and the facility density should reach more than 4 per square kilometer. In the buffer zone, the local moisture-tolerant herbaceous plant community should be fully restored, and its vegetation coverage should be increased to 150% of the original level. Planting vegetation types with well-developed root systems and strong purification capabilities is recommended. Record the geomorphic storage capacity index of the i-th spatial unit before and after the strategy deployment. The changes; a cycle of 15 days, after two cycles, monitoring and calculation are repeated until the geomorphic storage capacity index of the i-th spatial unit is reached. Until the buffer capacity threshold Z is reached.

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