Ecological restoration system for hydro-fluctuation belt in plateau arid valley area

Abstract

The invention provides a plateau arid valley region hydro-fluctuation belt ecological restoration system which comprises an acquisition module, a data analysis module, a data extraction module, a model establishment and analysis module, a model output module, an ecological restoration module and a feedback module. According to the ecological restoration system for the water-level-fluctuating zone in the plateau arid valley area, the calculation model of the water-level-fluctuating zone re-wild opportunity index UROI is constructed by using the entropy weight method, and spatial analysis is performed in combination with GIS software, so that re-wild opportunities of different areas in the water-level-fluctuating zone can be visually displayed, a one-step restoration strategy can be avoided, classified restoration is performed, and the restoration efficiency of the water-level-fluctuating zone in the plateau arid valley area is improved. And through a real-time monitoring and feedback mechanism, continuous optimization and improvement of a repair strategy are realized, and the repair efficiency and quality are improved.

Description

Technical Field

[0001] The invention relates to the field of ecological restoration, and in particular to an ecological restoration system for a water-fluctuation zone in arid river valleys of a plateau. Background Art

[0002] The scouring of river floods, the natural rise and fall of water levels in lakes or rivers, etc. will cause the land on the edge of the water to be periodically flooded and exposed. In the arid river valley areas of the plateau, due to the steep terrain and dry climate, the water level fluctuations may be more dramatic, thus forming a distinct drawdown zone.

[0003] The drawdown zone refers to a unique wetland ecosystem formed by the alternating process of periodic inundation and exposure of land at the edge of the water due to seasonal or periodic fluctuations in water levels. This phenomenon is particularly prominent in the plateau arid river valley areas, where water resources are relatively scarce and are affected by multiple factors such as topography and climate.

[0004] In the arid river valley areas of the plateau, human activities such as irrigation and power generation will have a significant impact on water resources, which in turn has an indirect effect on the formation of the drawdown zone.

[0005] When ecological restoration is carried out in the existing drawdown zone of the plateau arid river valley area, water quality monitoring stations, soil monitoring stations, meteorological monitoring stations and biodiversity monitoring stations are usually established in the drawdown zone to conduct water quality, soil, meteorological and biodiversity detection in the drawdown zone. Although the existing monitoring stations can collect a large amount of data, these data are often for the entire drawdown zone area. There is a lack of targeted monitoring of areas with different ecological types or different degrees of damage, which makes it difficult to make precise adjustments according to the actual conditions of specific areas when formulating restoration strategies, that is, there is a lack of classified restoration. The restoration strategy adopts a "one-size-fits-all" approach, that is, the same restoration measures are adopted for the entire drawdown zone area, resulting in poor restoration effects in some areas within the drawdown zone, and even further damage to the ecosystem. In addition, due to the lack of classified restoration, restoration resources cannot be reasonably allocated. Some areas in the drawdown zone will waste resources due to excessive restoration, while other areas will not be effectively restored due to insufficient restoration, which not only leads to waste of resources but also reduces restoration efficiency.

[0006] Therefore, it is necessary to provide a new ecological restoration system for the drawdown zone in the plateau arid river valley area to solve the above technical problems. Summary of the invention

[0007] In order to solve the above technical problems, the present invention provides an ecological restoration system for the drawdown zone in arid river valley areas of the plateau.

[0008] The ecological restoration system of the water-fluctuation zone in the plateau arid river valley area provided by the present invention comprises a collection module for acquiring multi-source data of the water-fluctuation zone in the plateau arid river valley area;

[0009] The data analysis module uses GIS software to analyze the spatial heterogeneity factors of the water-fluctuation zone based on the multi-source data collected in the plateau arid river valley area, uses remote sensing technology to assess the biodiversity level of the water-fluctuation zone, and analyzes the degree of human interference in the water-fluctuation zone;

[0010] The data extraction module extracts the key factors affecting the rewilding process of the watershed zone based on the results of the data analysis module;

[0011] The model building and analysis module uses the entropy weight method to construct a calculation model for the rewilding opportunity index of the watershed zone based on the extracted key factors, and combines GIS software for spatial analysis;

[0012] The model output module produces a spatial distribution map of the rewilding opportunities in the water-fluctuating zone based on the calculation results of the rewilding opportunities index model. The distribution range includes the distribution range of high value, relatively high value, medium value, relatively low value and low value space.

[0013] Ecological restoration module, based on the spatial distribution map of rewilding opportunities in the watershed zone, establishes a rewilding restoration strategy for the watershed zone;

[0014] The feedback module optimizes the strategy based on the rewilding and restoration strategy of the drawdown zone using real-time monitoring data.

[0015] Furthermore, in the acquisition module, multi-source data include land use, topography, climate, hydrology, biodiversity, and human activities in the drawdown zone of the plateau arid river valley area.

[0016] Furthermore, in the data analysis module, spatial heterogeneity factors include the terrain undulation, slope and aspect parameters of the water-drawing zone. The assessment of the biodiversity of the water-drawing zone includes the assessment of the plant species, animal populations and ecosystem service functions of the water-drawing zone. The degree of human interference in the water-drawing zone is analyzed, including human changes in land use, water resource development and pollution emissions.

[0017] Furthermore, in the data extraction module, key factors include soil quality, water source conditions and vegetation coverage.

[0018] Furthermore, the entropy weight method was used to construct a rewilding opportunity index model for the watershed zone, which included the following steps:

[0019] Step 1: Data preprocessing: Use the normalization method of positive indicators to normalize the data within the extracted key factors;

[0020] Step 2: Construct a judgment matrix: Construct a judgment matrix based on the normalized data by indicators and samples, including different regions or time periods, where each row represents a sample and each column represents an indicator;

[0021] Step 3: Calculate information entropy, redundancy and determine weight: Calculate the information entropy and redundancy of each indicator according to the judgment matrix, and calculate the weight of each indicator according to the redundancy;

[0022] Step 4: Construct a UROI calculation model: Calculate the weighted sum of each sample based on the weight of each indicator and the normalized data, and use GIS software to perform spatial visualization analysis on the calculated UROI value. According to the UROI value, divide the watershed zone into different rewilding opportunity levels, where the rewilding opportunity levels include high value, relatively high value, medium value, relatively low value, and low value space.

[0023] Step 5: Model verification: Based on the constructed UROI calculation model, the cross-validation method is used to verify the UROI calculation model, compare the differences between the model prediction results and the actual situation, and optimize the model.

[0024] Furthermore, the rewilding restoration strategy includes the following stages:

[0025] S1. Preparation stage: First, conduct on-site survey of the drawdown zone to understand the water flow speed, type and quantity of floating objects;

[0026] S2, interception stage: according to the results of on-site investigation, interception nets and buoys are installed upstream of the drawdown zone or at key locations;

[0027] S3, maintenance stage: regularly check the status of the interception net and buoys, and clear the blockages in time;

[0028] S4, collection stage: collecting garbage and floating objects intercepted by interception nets and buoys, and classifying and processing the collected garbage;

[0029] S5, purification stage: according to the water quality, set up purification areas and use plants and microorganisms to purify water;

[0030] S6, Monitoring and evaluation stage: Regularly monitor the quality of purified water, evaluate the purification effect, and adjust the purification method or add purification facilities based on the monitoring results;

[0031] S7, Improvement stage: Improve the soil around the area where the water quality is purified in the drawdown zone, and remove weeds and stones;

[0032] S8, vegetation selection stage: after clearing weeds and rocks, select appropriate vegetation types for planting according to local climate, soil conditions and ecological needs;

[0033] S9, vegetation maintenance stage: continue to regularly water and fertilize the newly planted vegetation;

[0034] S10, vegetation monitoring phase: continue to test newly planted vegetation and establish long-term monitoring points.

[0035] Furthermore, in the feedback module, the following steps are included:

[0036] Step 1. Arrange monitoring sites: First, arrange monitoring sites in the drawdown zone;

[0037] Step 2, data collection and processing: After the deployment is completed, use sensors or telemetry equipment to monitor water quality, soil, meteorological and biodiversity indicators in real time;

[0038] Step 3, data analysis and evaluation: compare the real-time monitoring data with the baseline data before the implementation of the restoration strategy, analyze the impact of the restoration measures on the ecological environment, and use statistical analysis and data mining techniques to explore the correlation and regularity between the data;

[0039] Step 4, Strategy optimization: Based on the data obtained from monitoring, evaluate the vegetation recovery, soil quality improvement, water purification effect and biodiversity.

[0040] Furthermore, in step five, model validation, the model is optimized including adjusting the selection of evaluation indicators, improving the normalization method, and optimizing the weight calculation;

[0041] Furthermore, in the data extraction module, it also includes data cleaning of the collected multi-source data;

[0042] Furthermore, in Step 1, arranging the monitoring stations includes arranging water quality monitoring stations, soil monitoring stations, meteorological monitoring stations and biodiversity monitoring stations.

[0043] Compared with the related technologies, the ecological restoration system for the water-fluctuation zone in the plateau arid river valley area provided by the present invention has the following beneficial effects:

[0044] 1. By using the entropy weight method to construct a calculation model for the rewilding opportunity index of the water-fluctuating zone, and combining it with GIS software for spatial analysis, the rewilding opportunities of different areas in the water-fluctuating zone can be intuitively displayed, which helps to avoid a "one-size-fits-all" restoration strategy and conduct classified restoration. In addition, through real-time monitoring and feedback mechanisms, the restoration strategy can be continuously optimized and improved, thereby improving the efficiency and quality of restoration.

[0045] 2. By collecting, analyzing and extracting multi-source data, we can identify the ecological characteristics and degree of damage in different areas of the watershed, implement classified restoration, avoid a "one-size-fits-all" restoration strategy, and reasonably allocate restoration resources based on UROI calculation results and the spatial distribution map of rewilding opportunities to avoid resource waste and insufficient restoration;

[0046] 3. Through classified restoration and real-time monitoring, further damage to the ecosystem can be avoided and the ecological environment of the drawdown zone in the plateau arid river valley areas can be protected. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 The overall flow chart of the ecological restoration system for the plateau arid river valley area provided by the present invention;

[0048] Figure 2 A flowchart for constructing the UROI model of the rewilding opportunity index of the watershed zone;

[0049] Figure 3 A flowchart of the rewilding restoration strategy. DETAILED DESCRIPTION

[0050] The present invention will be further described below in conjunction with the accompanying drawings and implementation modes.

[0051] In the specific implementation process, Figure 1 As shown, the ecological restoration system of the water-drawing zone in the plateau arid river valley area includes a collection module for obtaining multi-source data of the water-drawing zone in the plateau arid river valley area, and the multi-source data includes land use, topography, climate, hydrology, biodiversity and human activities in the water-drawing zone in the plateau arid river valley area;

[0052] The data analysis module uses GIS software to analyze the terrain relief, slope and aspect parameters of the water-fluctuation zone based on the multi-source data collected from the plateau arid river valley area. It also uses remote sensing technology to evaluate the plant species, animal populations and ecosystem service functions of the water-fluctuation zone, and analyzes the degree of human interference in the water-fluctuation zone, including human changes in land use, water resource development and pollution emissions.

[0053] The data extraction module extracts the key factors affecting the rewilding process of the watershed zone based on the results of the data analysis module, including soil quality, water source conditions and vegetation coverage;

[0054] The model building and analysis module uses the entropy weight method to construct a calculation model of the rewilding opportunity index (UROI) of the watershed zone based on the extracted key factors, and combines GIS software for spatial analysis;

[0055] The model output module produces a spatial distribution map of rewilding opportunities in the drawdown zone based on the UROI calculation results, with the distribution ranges including the high value, upper value, middle value, lower value, and low value spaces;

[0056] Ecological restoration module, based on the spatial distribution map of rewilding opportunities in the watershed zone, establishes a rewilding restoration strategy for the watershed zone;

[0057] The feedback module optimizes the strategy based on the rewilding and restoration strategy of the drawdown zone using real-time monitoring data.

[0058] It should be noted that through remote sensing technology, the data analysis module can evaluate the plant species, animal populations and ecosystem service functions in the water-drawing zone, which not only helps to understand the current health of the ecosystem, but also reveals the vulnerability and resilience of the ecosystem in response to environmental changes and interference from human activities.

[0059] refer to Figure 2 As shown in the figure, the entropy weight method is used to construct the UROI model of the watershed zone rewilding opportunity index, which includes the following steps:

[0060] Step 1: Data preprocessing: Use the normalization method of positive indicators to normalize the data within the extracted key factors;

[0061] Among them, the key factors are used as input variables, and the UROI value is calculated through the model. The normalization of the positive indicator is a linear transformation of the original data, so that the result value is mapped to [0,1]. This system uses Min-Max normalization within the normalization of the positive indicator. The specific operation steps are:

[0062] First, find the maximum value (max) and minimum value (min) in the data set;

[0063] Second, use the formula Normalize each data;

[0064] x is the original data, x' is the normalized data

[0065] For example, if the data set in one of the key factors is [2.5, 3.5, 0.5, 1.5], its minimum value is 0.5 and its maximum value is 3.5, according to the Min-Max normalization method, the normalized data set is [0.6667, 1, 0, 0.3333].

[0066] Step 2: Construct a judgment matrix: Construct a judgment matrix based on the normalized data by indicators and samples, including different regions or time periods, where each row represents a sample and each column represents an indicator;

[0067] Each row represents a sample, such as the data of the drawdown zone in different regions or time periods;

[0068] Each column represents an indicator, such as normalized vegetation coverage and soil erosion degree;

[0069] For the judgment matrix, there are the following analyses, for example:

[0070] Select three samples, including area A, area B and area C, and two indicators, including vegetation coverage and water content, and the judgment matrix is ​​as follows:

[0071] area Vegetation coverage Moisture content A 0.5 0.7 B 0.8 0.4 C 0.3 0.6

[0072] Step 3: Calculate information entropy, redundancy and determine weight: Calculate the information entropy and redundancy of each indicator according to the judgment matrix, and calculate the weight of each indicator according to the redundancy;

[0073] The formula for calculating information entropy is:

[0074] in, is the normalized value of the indicator;

[0075] Calculate the redundancy, the calculation formula is: D j =1-E j ;

[0076] The weight is determined according to the redundancy, and the calculation formula is:

[0077] According to the above judgment matrix, there are the following steps:

[0078] First, for vegetation coverage, the information entropy of each indicator is calculated:

[0079] Calculate the ratio of the normalized value of each sample to the total of the indicator:

[0080]

[0081] Calculate information entropy:

[0082] in,

[0083] E1=-0.9102(0.3125log(0.3125)+0.5log(0.5)

[0084] +0.18759log(0.18759))

[0085] log(0.3125)≈-1.1928, log(0.5)≈-0.6931, log(0.18759)≈-1.6788

[0086] E1=-0.9102(0.3125×(-1.1928)+0.5×(-0.6931)+0.18759×(-1.6788))

[0087] E1=-0.9102(-0.3728+(-0.34655)+(-0.3149))=0.9413

[0088] Secondly, for moisture content: calculate the ratio of each sample's normalized value to the total of that indicator:

[0089]

[0090] Calculate information entropy:

[0091] E2=-0.9102(0.4118log(0.4118)+0.2353(0.2353)+0.3529(0.3529))

[0092] log(0.4118)≈-0.8871, log(0.2353)≈-1.4394, log(0.3529)≈-1.0438

[0093] E2=-0.9102(0.4118×(-0.8871)+0.2353×(-1.4394)+0.3529×(-1.0438))

[0094] E2=-0.9102(-0.3653+(-0.3386)+(-0.3683))

[0095] E2=-0.9102×(-1.0722)≈0.9759

[0096] The information entropy obtained from the above vegetation coverage and moisture content is used to calculate the redundancy:

[0097] D1=1-E1=1-0.9413=0.0587

[0098] D2=1-E2=1-0.9759=0.0241

[0099] Get the weight according to the redundancy:

[0100]

[0101] From this we can get: vegetation coverage: information entropy: 0.9413, redundancy: 0.0587, weight: 0.96;

[0102] Moisture content: information entropy: 0.9759, redundancy: 0.0241, weight: 0.39.

[0103] Calculate the contribution rate of each factor. The contribution rate calculation formula is:

[0104] Among them, for vegetation coverage,

[0105] For moisture content,

[0106] According to the contribution rate of each factor multiplied by its weight, the final proportion of each factor is obtained:

[0107] For vegetation coverage, percentage = 0.9376 × 0.96 = 0.9001;

[0108] For moisture content, percentage = 0.9753 × 0.39 = 0.3804

[0109] Therefore, in the ecological restoration system of the water-drawing zone in the plateau arid river valley area, the vegetation coverage rate contributes more in the set of data collected. According to the actual situation of vegetation coverage rate and moisture content, the focus and sequence of restoration measures are adjusted, and the resources required for ecological restoration are reasonably allocated to avoid waste of resources and ensure the efficient progress of restoration work to achieve the best ecological restoration effect. Step four is executed.

[0110] Step 4: Construct a UROI calculation model: Calculate the weighted sum of each sample based on the weight of each indicator and the normalized data, and use GIS software to perform spatial visualization analysis on the calculated UROI value. According to the UROI value, divide the watershed zone into different rewilding opportunity levels, where the rewilding opportunity levels include high value, relatively high value, medium value, relatively low value, and low value space.

[0111] Calculate the UROI value of each sample using the following formula:

[0112] Among them, W j is the weight of the jth indicator, p i,j is the normalized value of the jth indicator of the i-th sample;

[0113] Develop strict protection strategies for areas with high and relatively high UROI values, such as establishing nature reserves and ecological buffer zones, and prohibiting or limiting human interference;

[0114] For the UROI median and lower value spaces, appropriate ecological restoration measures should be taken, such as vegetation restoration, soil improvement, and hydrological regulation, to enhance the self-recovery capacity of the ecosystem.

[0115] According to the three samples selected in step 3, then:

[0116] For Region A: UROI A =W1×P A1 +W2×P A2 =0.96×0.5+0.39×0.7=0.753;

[0117] For Region B: UROI B =W1×P B1 +W2×P B2 =0.96×0.8+0.39×0.4=0.924;

[0118] For Region C: UROI C =W1×P C1 +W2×P C2 =0.96×0.3+0.39×0.6=0.522; summarizing area A, area B, and area C, we get the following table:

[0119] area Vegetation coverage Moisture content UROI Value A 0.5 0.7 0.753 B 0.8 0.4 0.924 C 0.3 0.6 0.522

[0120] Categorize the drawdown zone into different levels of rewilding opportunities:

[0121] Among them, advanced: UROI>0.8;

[0122] High value: 0.6 <UROI≤0.8;

[0123] Median: 0.4 <UROI≤0.6;

[0124] Lower value: 0.2 <UROI≤0.4;

[0125] Low value: UROI ≤ 0.2.

[0126] Therefore, in area B: UROI = 0.924, it belongs to the high value level, and strict protection strategies should be formulated, such as establishing nature reserves and ecological buffer zones, and prohibiting or restricting human activities from interfering;

[0127] Area A: UROI = 0.753, which is a relatively high value level. Appropriate protection measures should be taken to reduce human interference and promote ecological restoration.

[0128] Region C: UROI = 0.522, which is a median level. Appropriate management and protection are being carried out to gradually improve the ecological environment.

[0129] Step 5: Model verification: Based on the constructed UROI calculation model, the cross-validation method is used to verify the UROI calculation model, compare the difference between the model prediction results and the actual situation, and optimize the model;

[0130] Among them, the cross-validation method: divide the data set into a training set and a test set, use the training set to build the UROI calculation model, and use the test set for verification;

[0131] Comparative analysis: compare the differences between the model prediction results and the actual situation, and adjust the model parameters or structure for optimization;

[0132] It should be noted that information entropy indicates the degree of confusion or uncertainty of information. The larger the information entropy, the more chaotic or uncertain the information.

[0133] Redundancy: indicates the degree of repetition of information; the greater the redundancy, the more information is repeated.

[0134] Weight: Indicates the importance of a factor in the whole; the larger the weight, the more important the factor.

[0135] refer to Figure 3 As shown in Figure 1, the rewilding restoration strategy includes the following stages:

[0136] S1. Preparation stage: First, conduct on-site survey of the drawdown zone to understand the water flow speed, type and quantity of floating objects;

[0137] S2, interception stage: according to the results of on-site investigation, interception nets and buoys are installed upstream of the drawdown zone or at key locations to effectively intercept floating objects and prevent them from entering the drawdown zone area, thereby reducing pollution;

[0138] S3, maintenance stage: regularly check the status of the interception net and buoys, and clean up the blockages in time to maintain the interception effect;

[0139] S4, collection stage: collecting garbage and floating objects intercepted by interception nets and buoys, and classifying and processing the collected garbage;

[0140] S5, purification stage: according to the water quality, set up purification areas, use plants and microorganisms to purify water and improve water quality;

[0141] S6, Monitoring and evaluation stage: Regularly monitor the quality of purified water, evaluate the purification effect, and adjust the purification method or add purification facilities based on the monitoring results to ensure continuous improvement of water quality;

[0142] S7, Improvement stage: Improve the soil in the surrounding area of ​​the water quality after purification in the drawdown zone, remove weeds and stones, and provide good conditions for vegetation planting;

[0143] S8, vegetation selection stage: after clearing weeds and rocks, select appropriate vegetation types for planting according to local climate, soil conditions and ecological needs;

[0144] S9, vegetation maintenance stage: continue to regularly water and fertilize the newly planted vegetation to ensure its normal growth, thereby increasing the vegetation coverage rate;

[0145] S10, vegetation monitoring stage: continue to test newly planted vegetation and set up long-term monitoring points to promptly detect and address problems that may arise during vegetation growth.

[0146] It should be noted that the water quality in the drawdown zone can be effectively improved through measures such as intercepting floating objects and setting up purification areas.

[0147] It should be noted that the intercepted garbage and floating objects need to be classified and processed to reduce environmental pollution and improve the utilization of resources.

[0148] In the feedback module, the following steps are included:

[0149] Step 1. Arrange monitoring stations: First, arrange monitoring stations in the drawdown zone, including water quality monitoring stations, soil monitoring stations, meteorological monitoring stations and biodiversity monitoring stations;

[0150] Step 2, data collection and processing: After the deployment is completed, use sensors or telemetry equipment to monitor water quality, soil, meteorological and biodiversity indicators in real time to obtain real-time data to provide a basis for subsequent analysis and evaluation;

[0151] Step 3, data analysis and evaluation: compare the real-time monitoring data with the baseline data before the implementation of the restoration strategy, analyze the impact of the restoration measures on the ecological environment, and use statistical analysis and data mining techniques to explore the correlation and regularity between the data;

[0152] Step 4, Strategy optimization: Based on the data obtained from monitoring, evaluate the vegetation recovery, soil quality improvement, water purification effect and biodiversity, and then optimize the restoration strategy.

[0153] In step five, model verification, model optimization includes adjusting the selection of evaluation indicators, improving the normalization method, and optimizing the weight calculation.

[0154] The data extraction module also includes data cleaning of the collected multi-source data.

[0155] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention, and any figure mark in the claims should not be regarded as limiting the claims involved.

[0156] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. The ecological restoration system of the water-fluctuation zone in the plateau arid river valley area is characterized by: It includes an acquisition module for obtaining multi-source data of the drawdown zone in the plateau arid river valley area; The data analysis module uses GIS software to analyze the spatial heterogeneity factors of the water-fluctuation zone based on the multi-source data collected in the plateau arid river valley area, uses remote sensing technology to assess the biodiversity level of the water-fluctuation zone, and analyzes the degree of human interference in the water-fluctuation zone; The data extraction module extracts the key factors affecting the rewilding process of the watershed zone based on the results of the data analysis module; The model building and analysis module uses the entropy weight method to construct a calculation model for the rewilding opportunity index of the watershed zone based on the extracted key factors, and combines GIS software for spatial analysis; The model output module produces a spatial distribution map of the rewilding opportunities in the water-fluctuating zone based on the calculation results of the rewilding opportunities index model. The distribution range includes the distribution range of high value, relatively high value, medium value, relatively low value and low value space. Ecological restoration module, based on the spatial distribution map of rewilding opportunities in the watershed zone, establishes a rewilding restoration strategy for the watershed zone; The feedback module optimizes the strategy based on the rewilding and restoration strategy of the drawdown zone using real-time monitoring data.

2. The ecological restoration system for the water-fluctuation zone in the plateau arid river valley area according to claim 1 is characterized in that: In the acquisition module, the multi-source data include land use, topography, climate, hydrology, biodiversity and human activities in the drawdown zone of the plateau arid river valley area.

3. The ecological restoration system for the water-fluctuation zone in the plateau arid river valley area according to claim 1 is characterized in that: In the data analysis module, the spatial heterogeneity factors include the terrain undulation, slope and aspect parameters of the water-drawing zone, the assessment of the biodiversity of the water-drawing zone includes the assessment of the plant species, animal populations and ecosystem service functions of the water-drawing zone, and the analysis of the degree of human interference in the water-drawing zone includes human changes in land use, water resource development and pollution emissions.

4. The ecological restoration system for the water-fluctuation zone in the plateau arid river valley area according to claim 1 is characterized in that: In the data extraction module, the key factors include soil quality, water source conditions and vegetation coverage.

5. The ecological restoration system for the water-fluctuation zone in the plateau arid river valley area according to claim 4 is characterized in that: The entropy weight method is used to construct a rewilding opportunity index model for the water-fluctuation zone, including the following steps: Step 1: Data preprocessing: Use the normalization method of positive indicators to normalize the data within the extracted key factors; Step 2: Construct a judgment matrix: Construct a judgment matrix based on the normalized data by indicators and samples, including different regions or time periods, where each row represents a sample and each column represents an indicator; Step 3: Calculate information entropy, redundancy and determine weight: Calculate the information entropy and redundancy of each indicator according to the judgment matrix, and calculate the weight of each indicator according to the redundancy; Step 4: Construct a UROI calculation model: Calculate the weighted sum of each sample based on the weight of each indicator and the normalized data, and use GIS software to perform spatial visualization analysis on the calculated UROI value. According to the UROI value, divide the watershed zone into different rewilding opportunity levels, where the rewilding opportunity levels include high value, relatively high value, medium value, relatively low value, and low value space. Step 5: Model verification: Based on the constructed UROI calculation model, the cross-validation method is used to verify the UROI calculation model, compare the differences between the model prediction results and the actual situation, and optimize the model.

6. The ecological restoration system for the water-fluctuation zone in the plateau arid river valley area according to claim 5 is characterized in that: The rewilding strategy includes the following stages: S1. Preparation stage: First, conduct on-site survey of the drawdown zone to understand the water flow speed, type and quantity of floating objects; S2, interception stage: according to the results of on-site investigation, interception nets and buoys are installed upstream of the drawdown zone or at key locations; S3, maintenance stage: regularly check the status of the interception net and buoys, and clear the blockages in time; S4, collection stage: collecting garbage and floating objects intercepted by interception nets and buoys, and classifying and processing the collected garbage; S5, purification stage: according to the water quality, set up purification areas and use plants and microorganisms to purify water; S6, Monitoring and evaluation stage: Regularly monitor the quality of purified water, evaluate the purification effect, and adjust the purification method or add purification facilities based on the monitoring results; S7, Improvement stage: Improve the soil around the area where the water quality is purified in the drawdown zone, and remove weeds and stones; S8, vegetation selection stage: after clearing weeds and rocks, select appropriate vegetation types for planting according to local climate, soil conditions and ecological needs; S9, vegetation maintenance stage: continue to regularly water and fertilize the newly planted vegetation; S10, vegetation monitoring phase: continue to test newly planted vegetation and establish long-term monitoring points.

7. The ecological restoration system for the water-fluctuation zone in the plateau arid river valley area according to claim 1 is characterized in that: In the feedback module, the following steps are included: Step 1. Arrange monitoring sites: First, arrange monitoring sites in the drawdown zone; Step 2, data collection and processing: After the deployment is completed, use sensors or telemetry equipment to monitor water quality, soil, meteorological and biodiversity indicators in real time; Step 3, data analysis and evaluation: compare the real-time monitoring data with the baseline data before the implementation of the restoration strategy, analyze the impact of the restoration measures on the ecological environment, and use statistical analysis and data mining techniques to explore the correlation and regularity between the data; Step 4, Strategy optimization: Based on the data obtained from monitoring, evaluate the vegetation recovery, soil quality improvement, water purification effect and biodiversity.

8. The ecological restoration system for the water-fluctuation zone in the plateau arid river valley area according to claim 5 is characterized in that: In the step 5 of model verification, the optimization of the model includes adjusting the selection of evaluation indicators, improving the normalization method and optimizing the weight calculation.

9. The ecological restoration system for the water-fluctuation zone in the plateau arid river valley area according to claim 8 is characterized in that: The data extraction module also includes data cleaning of the collected multi-source data.

10. The ecological restoration system for the water-fluctuation zone in the plateau arid river valley area according to claim 7 is characterized in that: In the Step 1, arranging the monitoring stations includes arranging water quality monitoring stations, soil monitoring stations, meteorological monitoring stations and biodiversity monitoring stations.

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