Evaluation methods, systems, equipment and media for ecological restoration effects of saline-alkali water bodies

Abstract

The present invention provides an evaluation method, system, equipment and medium for the ecological restoration effect of saline-alkali water bodies, and relates to the technical field of saline-alkali water body restoration evaluation. The present invention constructs a two-layer restoration evaluation architecture based on the physical layer and the chemical layer, integrates environmental and biological monitoring data, and adopts data-driven principal component analysis and dynamic time warping algorithms to achieve effective matching of environmental and biological indicator trends and dynamic weight adjustment, thereby improving the scientific nature and accuracy of restoration effect evaluation. The restoration process is predicted in time series by combining the autoregressive integral sliding average model, which can quantitatively evaluate the restoration completion time and assist in scientific management and decision-making. The overall solution realizes multi-dimensional comprehensive evaluation and dynamic closed-loop optimization of the ecological restoration effect of saline-alkali water bodies, significantly enhancing the pertinence, real-time nature and sustainability of ecological restoration, and providing scientific and efficient technical support for saline-alkali land restoration.

Description

Technical Field

[0001] The present invention relates to the technical field of saline-alkali water body restoration assessment, and in particular to a method, system, equipment and medium for assessing the ecological restoration effect of saline-alkali water bodies. Background Art

[0002] With the continuous expansion of the area of ​​saline-alkali water bodies, the degradation of the saline-alkali ecological environment is becoming increasingly serious, seriously affecting farmland productivity, ecosystem health and regional sustainable development. Existing methods for ecological restoration of saline-alkali water bodies mostly focus on the monitoring of single physical or chemical indicators, lacking a systematic and comprehensive evaluation of multidimensional environmental factors, making it difficult to fully reflect the dynamic changes in restoration effects and the overall health of the ecosystem. In addition, the biological response of the ecosystem has a lag, and traditional assessment methods cannot achieve effective synchronous analysis of environmental indicators and biological indicators, resulting in the judgment of restoration effects not being timely and accurate enough. The lack of a scientific, dynamic, closed-loop restoration effect evaluation system makes it difficult to adjust restoration plans in a targeted manner, inhibiting the efficiency and effectiveness of ecological restoration.

[0003] In the prior art, publication number CN117035463A discloses a method, device, equipment, and storage medium for evaluating the effects of lake ecological restoration. The method includes: constructing a lake model based on the state variables of the target lake and the restoration measures; adjusting the nutrient load parameters of the lake model until the lake model is in a steady state, thereby obtaining a bifurcation analysis diagram; determining the first nutrient threshold of the lake model before restoration and the second nutrient threshold after restoration based on the bifurcation analysis diagram; determining the self-purification capacity improvement effect of the lake model based on the first and second nutrient thresholds; performing scenario simulations on the lake model under various scenarios to obtain simulation results for various target scenarios; and evaluating the lake ecological restoration effect based on the self-purification capacity improvement effect and the simulation results for various target scenarios. Although it can evaluate the effects of lake ecological restoration, it focuses on model bifurcation and threshold analysis, lacks a comprehensive evaluation of multi-level environmental and biological indicators, and does not explicitly combine dynamic verification with actual monitoring data. As a result, the evaluation results may be single and have a limited scope of application.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0005] The purpose of the present invention is to provide a method, system, equipment and medium for evaluating the ecological restoration effect of saline-alkali water bodies, so as to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The evaluation method for the ecological restoration effect of saline-alkali water bodies includes the following specific steps:

[0008] S1: Based on the ecological restoration goals of saline-alkali water bodies, a two-layer restoration assessment framework is constructed, which is set as the physical layer and the chemical layer respectively;

[0009] S2: Collect environmental monitoring data of saline-alkali water bodies, construct physical layer indicators and chemical layer indicators to quantify the restoration effect of saline-alkali water bodies, and generate standardized data for physical layer indicators and chemical layer indicators respectively;

[0010] S3: Determine the weights of the physical layer indicators and the chemical layer indicators based on the principal component analysis method, and generate an environmental assessment score based on the weights of the physical layer indicators and the chemical layer indicators and the standardized data of the physical layer indicators and the chemical layer indicators;

[0011] S4: Collect biological detection data of saline-alkali water bodies, generate biological assessment scores based on the biological detection data, and visualize the change curves of environmental assessment scores and biological assessment scores over time;

[0012] S5: Generate a similarity index between the environmental assessment score and the biological assessment score based on their change curves over time. When the similarity index exceeds a preset threshold, the environmental assessment score is considered reasonable.

[0013] S6: Conduct time series analysis on the environmental assessment scores to generate a predicted value for the time required to complete the ecological restoration of saline-alkali water bodies.

[0014] Preferably, the physical layer indicators in the environmental detection data include: water level change rate, soil porosity, salt concentration, and electrical conductivity;

[0015] The chemical layer indicators in the environmental testing data include: effective sodium content, pH value, and nutrient content;

[0016] The biological detection data include: population size, vegetation coverage, and abundance of key populations;

[0017] The environmental detection data and biological detection data are both standardized using the maximum and minimum normalization method.

[0018] Preferably, in step S3, principal component analysis is used to reduce the dimension of the standardized environmental detection data, extract the contribution rate of the main components, and determine the weight distribution of the physical layer indicators and the chemical layer indicators respectively according to the contribution rate, and the weights all meet the following normalization conditions:

[0019]

[0020]

[0021] In the formula Indicates the The weights of the physical layer indicators, Indicates the The weight of chemical layer indicators, subscript 、 Represents the index of physical layer index and chemical layer index respectively, 、 Respectively represents the number of types of physical layer indicators and chemical layer indicators.

[0022] Preferably, the environmental assessment score is calculated as follows:

[0023]

[0024] In the formula represents the environmental assessment score, represents the physical layer weight, Indicates the Standardized data of physical layer indicators, Indicates the Standardized data for various chemical layer indicators.

[0025] Preferably, in step S4, before generating the biological evaluation score, the principal component analysis method is also used to reduce the dimension of the standardized biological detection data, and then the main component contribution rate is extracted, and the weight distribution in the biological detection data is determined according to the contribution rate. The biological evaluation score is calculated as follows:

[0026]

[0027] In the formula represents the biological assessment score, Indicates the The weight of biological detection data, Indicates the Standardized data of biological detection data, subscript Represents the index of biological detection data, Indicates the number of types of biological detection data;

[0028] The weight of the biological detection data also satisfies the following normalization conditions:

[0029] .

[0030] Preferably, in step S5, a dynamic time warping algorithm is used to calculate the similarity index of the curves of the environmental assessment score and the biological assessment score changing over time, and the calculation method is:

[0031]

[0032] In the formula represents the similarity index, 、 They represent the environmental assessment score and biological assessment score over time under the dynamic time warping algorithm. The time series of changes, The dynamic time warping distance represents the curve of environmental assessment score and biological assessment score changing with time, 、 Respectively 、 length;

[0033] when When the environmental assessment score is considered reasonable;

[0034] when When the environmental assessment score is considered unreasonable, the reverse gradient method is used to update the weight distribution of physical layer indicators, chemical layer indicators, and biological detection data;

[0035] In the formula represents the similarity threshold, and .

[0036] Preferably, in step S6, an autoregressive integrated moving average model is used to perform time series analysis on the environmental assessment score, when:

[0037]

[0038] Think At this moment, the ecological restoration of saline-alkali water bodies is completed;

[0039] In the formula Indicates the environmental assessment score under the autoregressive integrated moving average model The predicted value at time, Indicates the preset threshold value of the environmental assessment score.

[0040] An evaluation system for the ecological restoration effect of saline-alkali water bodies, wherein the evaluation system is used to implement the above-mentioned evaluation method, specifically includes:

[0041] A data acquisition module, wherein the data acquisition module is used to collect environmental detection data and biological detection data of saline-alkali water bodies;

[0042] A weight distribution module, wherein the weight distribution module is pre-installed with a principal component analysis algorithm for weight distribution of environmental detection data and biological detection data;

[0043] A data analysis module, configured to generate an environmental assessment score and a biological assessment score based on the environmental detection data and the biological detection data, respectively;

[0044] A data correction module is used to calculate the similarity index of the environmental assessment score and the biological assessment score change curve, and update the weight distribution according to the similarity index;

[0045] A time series analysis module is used to perform time series analysis on the environmental assessment scores and predict the time required to complete the restoration of saline-alkali water bodies.

[0046] Evaluation equipment for the ecological restoration effect of saline-alkali water bodies, the evaluation equipment comprising:

[0047] medium for storing computer programs;

[0048] A processor is configured to execute the computer program to implement the above-mentioned evaluation method.

[0049] A medium for evaluating the ecological restoration effect of saline-alkali water bodies, wherein the medium is used to store a computer program, and the computer program implements the above-mentioned evaluation method when executed by a processor.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] The present invention constructs a two-layer restoration evaluation framework based on the physical layer and the chemical layer, integrates environmental and biological monitoring data, and adopts data-driven principal component analysis and dynamic time warping algorithms to achieve effective matching of environmental and biological indicator trends and dynamic weight adjustment, thereby improving the scientific nature and accuracy of restoration effect evaluation. Combining the autoregressive integral moving average model to perform time series prediction of the restoration process, it is possible to quantitatively evaluate the restoration completion time and assist in scientific management and decision-making. The overall solution realizes the multi-dimensional comprehensive evaluation and dynamic closed-loop optimization of the ecological restoration effect of saline-alkali water bodies, significantly enhancing the pertinence, real-time nature and sustainability of ecological restoration, and providing scientific and efficient technical support for saline-alkali land restoration. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 Schematic diagram of the overall method flow of the present invention;

[0053] Figure 2 This is a schematic diagram of the module structure of the present invention;

[0054] Figure 3 Schematic diagram of the change curve of the environmental assessment score and the biological assessment score of the present invention. DETAILED DESCRIPTION

[0055] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments.

[0056] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0057] Example:

[0058] See also Figures 1 to 3 , the present invention provides a technical solution:

[0059] The evaluation method for the ecological restoration effect of saline-alkali water bodies includes the following specific steps:

[0060] S1: Based on the ecological restoration goals of saline-alkali water bodies, a two-layer restoration assessment framework is constructed, with physical and chemical layers set up separately. Physical layer indicators from environmental monitoring data include: water level change rate, soil porosity, salt concentration, and electrical conductivity; chemical layer indicators from environmental monitoring data include: available sodium content, pH value, and eutrophic element content.

[0061] For the physical layer indicators selected in the physical layer: water level is an important physical parameter of the ecological environment of saline-alkali water bodies, reflecting the dynamic hydrological conditions of the water bodies. The water level change of saline-alkali land refers to the rate of change of the water level height of a specific water body (water level monitoring point) within a certain time interval, reflecting the speed and amplitude of the hydrological dynamics. A positive rate of change indicates a rise in the water level, and a negative value indicates a drop, which directly affects the dissolution, migration and leaching of soil salt. By monitoring the water level change rate, it can be determined whether the water body has good water circulation and self-purification capabilities. Stable or moderate fluctuations in water level are conducive to salt migration and dilution, and promote the improvement of soil saline-alkali conditions. The increase in water level or a more stable fluctuation trend often represents the effectiveness of restoration measures such as ecological water replenishment and salt withdrawal; pores Porosity reflects the looseness of soil structure and is an important indicator of soil physical properties. The increase in porosity indicates that the soil structure has been improved, which is conducive to the effective transport of water and nutrients, and the promotion of microbial activity and plant root respiration is crucial to ecological restoration; salt concentration is the core indicator of saline-alkali water bodies, which directly reflects the degree of salt accumulation in soil and water bodies. By real-time monitoring of changes in salt concentration, salt leaching and migration can be evaluated, which is an important basis for judging the effectiveness of restoration; electrical conductivity is a proxy indicator for evaluating the total ion content in soil and water solutions, and can be used as a supplementary indicator of salt concentration.

[0062] For the chemical layer indicators selected in the chemical layer: sodium ions are one of the main causes of soil alkalinization and compaction. Excessive sodium ions will destroy the soil structure. The effective sodium content refers to the concentration or content of sodium ions in exchangeable form in the soil or water body. It is a key chemical indicator affecting the degree of soil salinization and suitability for plant growth. Monitoring the effective sodium content is helpful to judge the degree of soil salinization and the risk of compaction. High effective sodium content will lead to the destruction of soil aggregates, soil compaction, and affect water and gas circulation, thereby poisoning plant roots and reducing the plant's water absorption capacity; saline-alkali water body soil is mostly alkaline, and the pH value reflects the soil acidity and alkalinity, which can evaluate the changing trend of the soil acidity and alkalinity environment; nutrient elements (such as nitrogen, phosphorus, and potassium) are basic nutrients required for plant growth and are also important indicators for measuring soil fertility. Monitoring the content of nutrient elements can evaluate the improvement of saline-alkali soil fertility and reflect the enhancement of the ecosystem's ability to support plant growth.

[0063] The above physical and chemical layer indicators comprehensively reflect the hydrophysical conditions, soil structure, salinization degree and soil chemical properties of the saline-alkali water environment. Changes in these indicators directly or indirectly affect the plant growth environment and microbial ecosystem in saline-alkali land, and are important parameters for evaluating the ecological restoration effects of saline-alkali water bodies. Through systematic monitoring and quantitative analysis of these indicators, we can scientifically guide the adjustment and optimization of restoration plans and improve the pertinence and effectiveness of restoration.

[0064] S2: Collect environmental monitoring data from saline-alkali water bodies, construct physical and chemical layer indicators to quantify the remediation effects of saline-alkali water bodies, and generate standardized data for the physical and chemical layer indicators. Both the environmental monitoring data and subsequent biological monitoring data are standardized using the minimax normalization method.

[0065] Specifically, the calculation method of the maximum and minimum normalization method is:

[0066]

[0067] In the formula represents normalized data, Represents input data, 、 Represent the maximum and minimum values ​​of the input data respectively. The use of the maximum and minimum normalization method for standardization can eliminate the differences in the dimensions and dimensional ranges of different indicators and ensure the comparability of indicator data. It is understandable that in the process of saline-alkali water body restoration, the changes in various parameters are not infinite, but fluctuate within a range. For example, the pH value usually fluctuates between 8.5 and 7.5, indicating that the alkalinity of the saline-alkali water body has weakened, but will not drop below 7. This is also determined by the actual physical environment of the saline-alkali water body. The input data here refers to the original measurement values ​​of environmental detection data and biological detection data. The various parameters in the environmental detection data can be divided into positive indicators and negative indicators according to their functions. Positive indicators, such as water level change rate, soil porosity, and eutrophic element content, are positively correlated with the ecological restoration effect. Therefore, the output is directly standardized data that can be used later. Negative indicators, such as salt concentration, conductivity, effective sodium content, and pH value, are negatively correlated with the ecological restoration effect. Therefore, the output standardized data needs to be corrected, that is:

[0068]

[0069] here It represents the corrected standardized data, which is used to reflect the different effects of different indicators on the restoration of saline-alkali water bodies.

[0070] S3: Determine the weights of the physical layer indicators and the chemical layer indicators respectively based on the principal component analysis method, and generate an environmental assessment score based on the weights of the physical layer indicators and the chemical layer indicators and the standardized data of the physical layer indicators and the chemical layer indicators.

[0071] In step S3, principal component analysis is used to reduce the dimension of the standardized environmental monitoring data, extract the contribution rate of the main components, and determine the weight distribution of the physical layer indicators and the chemical layer indicators respectively according to the contribution rate, and the weights all meet the following normalization conditions:

[0072]

[0073]

[0074] In the formula Indicates the The weights of the physical layer indicators, Indicates the The weight of chemical layer indicators, subscript 、 Represents the index of physical layer index and chemical layer index respectively, 、 Respectively represents the number of types of physical layer indicators and chemical layer indicators.

[0075] Specifically, the logic of principal component analysis (PCA) is:

[0076] Obtain the index data of the physical layer and chemical layer in the saline-alkali water environment detection data, and form two data matrices after standardization;

[0077] Calculate the covariance matrix or correlation matrix for the two data matrices respectively. This matrix reflects the correlation between the indicators and is the basis of PCA dimensionality reduction.

[0078] Perform eigenvalue decomposition on the correlation matrix to obtain the eigenvalues ​​and corresponding eigenvectors. Each eigenvalue represents the variance contribution of the corresponding principal component, and the eigenvector represents the linear combination coefficient of the principal component.

[0079] According to the cumulative contribution rate principle, the first several principal components are selected so that the cumulative contribution rate reaches the preset threshold (usually above 90%) to ensure that the main information is retained, thus achieving dimensionality reduction and reducing information loss;

[0080] The weight of each indicator in the principal component is reflected by the eigenvector coefficient (i.e., the load). The load reflects the correlation between the indicator and the principal component. The larger the absolute value of the load, the greater the contribution of the indicator to the principal component.

[0081] Combined with the variance contribution rate of the principal component, the absolute load value on each principal component is weighted by the variance contribution rate and normalized to calculate the comprehensive weight of each indicator.

[0082] Because principal component analysis is an existing technology, its specific calculation formula will not be elaborated here. By introducing principal component analysis to determine weight distribution, it can be directly derived from the data itself through mathematical methods, avoiding subjective bias in setting. Moreover, by extracting the principal components, it can also remove relevant redundant information between indicators, enhancing the stability and explanatory power of the model.

[0083] The environmental assessment score is calculated as follows:

[0084]

[0085] In the formula represents the environmental assessment score, Represents the physical layer weight, which can be determined by expert experience. Indicates the Standardized data of physical layer indicators, Indicates the Standardized data for various chemical layer indicators.

[0086] It can be seen from the calculation formula of the environmental assessment score that it represents the comprehensive evaluation result of the environmental status during the ecological restoration of saline-alkali water bodies. It is a comprehensive score that is a summary of the physical layer and chemical layer indicators. The physical layer and chemical layer represent different aspects of the saline-alkali water environment, such as the physical and chemical properties of hydrological soil. By introducing the physical layer weight , the relative weights of the two levels can be flexibly adjusted to reflect the importance ratio of the two in the actual repair process.

[0087] Specifically, when the environmental assessment score is large, it means that the physical layer indicators (such as water level change rate, soil porosity, electrical conductivity, etc.) are in an ideal or relatively stable state, indicating that the hydrology and soil structure are good, and the chemical layer indicators (such as effective sodium content, pH value, eutrophic element content) are controlled within a reasonable range that is conducive to ecosystem recovery. The salinity is moderate and the nutrient supply is sufficient. Therefore, it also means that the ecological environment of saline-alkali water bodies is relatively healthy, which is conducive to plant growth and ecosystem function recovery.

[0088] S4: Collect biological detection data of saline-alkali water bodies and generate biological assessment scores based on the biological detection data. The biological detection data include: population size, vegetation coverage, and abundance of key populations. Visualize the change curves of environmental assessment scores and biological assessment scores over time. These parameters are used to reflect the biodiversity and ecological health status of saline-alkali water ecosystems, and intuitively demonstrate the restoration effect of saline-alkali water bodies.

[0089] In step S4, before generating the biological evaluation score, the principal component analysis method is also used to reduce the dimension of the standardized biological test data, and then the main component contribution rate is extracted. The weight distribution in the biological test data is determined based on the contribution rate. The biological evaluation score is calculated as follows:

[0090]

[0091] In the formula represents the biological assessment score, Indicates the The weight of biological detection data, Indicates the Standardized data of biological detection data, subscript Represents the index of biological detection data, Indicates the number of types of biological detection data.

[0092] The weight of biological detection data also meets the following normalization conditions:

[0093] .

[0094] The biological assessment score, as calculated using the formula, represents the comprehensive health of saline-alkali water ecosystems based on biological indicators. It is a quantitative indicator that uses a single value to reflect the overall quality of the biological environment. A high biological assessment score indicates good biological indicators in saline-alkali water bodies, abundant species, high vegetation coverage, sufficient abundance of key species, healthy ecosystems with good biological diversity, and significant restoration results. Conversely, a low biological assessment score indicates poor biological indicator performance, possible population decline, sparse vegetation, and a lack of key species. Ecological functions are impaired, and restoration efforts require further improvement. This score is an indicator that can be used to intuitively assess the effectiveness of saline-alkali water body restoration.

[0095] S5: Generate a similarity index between the environmental assessment score and the biological assessment score based on their change curves over time. When the similarity index exceeds a preset threshold, the environmental assessment score is considered reasonable.

[0096] Although the biological assessment score can directly reflect the ecological restoration effect of saline-alkali water bodies, the growth of organisms requires a certain amount of time, which will cause the change of the biological assessment score to be later than the change of the environmental assessment score. In other words, the biological assessment score is more intuitive, but has a lag. Therefore, the more immediate environmental assessment score is used to judge the ecological restoration effect. It can be understood that the biological assessment score directly reflects the restoration effect of the saline-alkali water body from the result, and the environmental assessment score reflects the restoration effect of the saline-alkali water body from the cause. The two play the same role and have the same change trend. The only difference is the time point when the change occurs on the timeline, and the parameters used in the calculation of the biological assessment score can be directly measured. Therefore, the calculation model of the environmental assessment score can be modified by the change trend of the biological assessment score to make the change trends of the two similar. Then, the more immediate environmental assessment score can be used to reversely reflect the change trend of the biological assessment score, thereby predicting the restoration status of the saline-alkali water body.

[0097] In step S5, the dynamic time warping (DTW) algorithm is used to calculate the similarity index of the time-varying curves of the environmental assessment score and the biological assessment score. The DTW algorithm can effectively handle the situation where the two time series have different lengths and the time axis has nonlinear deformation, accurately measure the morphological similarity between the curves, and overcome the shortcomings of traditional Euclidean distance calculation. Its calculation method is as follows:

[0098]

[0099] In the formula It represents the similarity index, with a value range of 0 to 1, indicating the morphological similarity between the environmental assessment score curve and the biological assessment score curve over time. The closer the value is to 1, the more similar the trends of the two curves are. 、 They represent the environmental assessment score and biological assessment score over time under the dynamic time warping algorithm. The time series of changes, It represents the dynamic time warping distance of the curves of environmental assessment scores and biological assessment scores changing with time. The smaller the distance, the more similar the curves are. 、 Respectively 、 The length of is used to normalize the DTW distance so that the similarity index is dimensionless and the value is within a reasonable range;

[0100] when When the environmental assessment score is considered reasonable;

[0101] when When the environmental assessment score is considered unreasonable, the reverse gradient method is used to update the weight distribution of physical layer indicators, chemical layer indicators, and biological detection data;

[0102] In the formula represents the similarity threshold, and , its specific value can be adjusted according to actual needs or expert experience.

[0103] Here, by introducing a dynamic time warping algorithm to calculate the similarity index between time series, the quantitative determination of the trend matching degree between environmental assessment scores and biological assessment scores is achieved, and the weights are adjusted based on the similarity threshold feedback. This not only completes the verification of the high consistency of environmental and ecological biological responses, but also realizes the dynamic adaptation and closed-loop optimization of the environmental assessment system, which helps to improve the scientificity and accuracy of the assessment results.

[0104] S6: Conduct time series analysis on the environmental assessment scores to generate a predicted value for the time required to complete the ecological restoration of saline-alkali water bodies.

[0105] In step S6, the autoregressive integrated moving average model (ARIMA model) is used to perform time series analysis on the environmental assessment scores. The ARIMA model simultaneously considers the sequence's own lag effect (autoregressive AR), difference processing (integral I), and random noise (moving average MA). It is suitable for processing non-stationary ecological and environmental data with random disturbances to improve prediction accuracy. When the following conditions are met:

[0106]

[0107] Think At this moment, the ecological restoration of saline-alkali water bodies is completed;

[0108] In the formula Indicates the environmental assessment score under the autoregressive integrated moving average model The larger the predicted value at a certain moment, the better the expected ecological environment status is. The overall physical and chemical indicators tend to be excellent, and the ecosystem function gradually recovers. It represents the preset threshold of the environmental assessment score, which serves as a quantitative indicator of whether the restoration has met the standards. The time point when the threshold is reached, determined in combination with the prediction results, is the completion time of ecological restoration.

[0109] Here, the ARIMA model is used to perform time-series prediction on the environmental assessment score sequence, and the preset threshold is combined to determine the completion time of restoration, thereby achieving scientific quantitative prediction and management control of the saline-alkali water body ecological restoration process, significantly improving the accuracy and practicality of ecological environment assessment and governance.

[0110] In this example, data was collected during the first 20 days of the saline-alkali water body restoration process, and the obtained data are shown in the following table:

[0111] Table 1: Data sheet for saline-alkali water restoration

[0112]

[0113] From the above table data and Figure 3As can be seen, the environmental assessment score comprehensively reflects changes in key environmental indicators at the physical and chemical levels. It gradually increases with the progress of ecological restoration, indicating that ecological restoration measures have effectively alleviated salinity and alkalinity stress in soil and water, improved hydrological conditions, and promoted the transformation of soil chemical properties toward those suitable for biological survival. The biological assessment score showed no significant change in the first two days, but began to show a clear upward trend from the third day, with a gradual increase in population size, vegetation cover, and the abundance of key species. This indicates that the recovery of the biological community is progressing, providing an intuitive assessment of the ecological effectiveness of ecological restoration and ecosystem stability. The improvement in the environmental assessment score preceded the biological assessment score, reflecting that improved environmental conditions provided necessary but not immediate response conditions for biological recovery. This trend is consistent with the classic theory of ecosystem restoration: first, the physical and chemical environment improves, followed by the gradual recovery and stabilization of the biological community.

[0114] This embodiment also provides an evaluation system for the ecological restoration effect of saline-alkali water bodies. The evaluation system is used to implement the above-mentioned evaluation method, specifically including:

[0115] Data acquisition module, which is used to collect environmental detection data and biological detection data of saline-alkali water bodies;

[0116] The weight distribution module has a pre-installed principal component analysis algorithm for weight distribution of environmental detection data and biological detection data;

[0117] A data analysis module is used to generate an environmental assessment score and a biological assessment score based on the environmental detection data and the biological detection data respectively;

[0118] The data correction module is used to calculate the similarity index of the environmental assessment score and the biological assessment score change curve, and update the weight distribution according to the similarity index;

[0119] The time series analysis module is used to perform time series analysis on the environmental assessment scores and predict the time required to complete the restoration of saline-alkali water bodies.

[0120] This embodiment also provides an evaluation device for the ecological restoration effect of saline-alkali water bodies, which includes:

[0121] medium for storing computer programs;

[0122] A processor is configured to execute a computer program to implement the above-mentioned evaluation method.

[0123] This embodiment also provides a medium for the ecological restoration effect of saline-alkali water bodies, where the medium is used to store a computer program, and when the computer program is executed by a processor, the above-mentioned evaluation method is implemented.

[0124] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0125] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software depends on the specific application and design constraints of the technical solution.

[0126] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, and may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment as needed.

[0127] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A method for evaluating the ecological restoration effect of saline-alkali water bodies, characterized in that: The specific steps include: S1: Based on the ecological restoration goals of saline-alkali water bodies, a two-layer restoration assessment framework is constructed, with the framework set as the physical layer and the chemical layer; S2: Collect environmental monitoring data of saline-alkali water bodies, construct physical layer indicators and chemical layer indicators to quantify the restoration effect of saline-alkali water bodies, and generate standardized data for physical layer indicators and chemical layer indicators respectively; S3: Determine the weights of the physical layer indicators and the chemical layer indicators based on the principal component analysis method, and generate an environmental assessment score based on the weights of the physical layer indicators and the chemical layer indicators and the standardized data of the physical layer indicators and the chemical layer indicators; S4: Collect biological detection data of saline-alkali water bodies, generate biological assessment scores based on the biological detection data, and visualize the change curves of environmental assessment scores and biological assessment scores over time; S5: Generate a similarity index between the environmental assessment score and the biological assessment score based on their change curves over time. When the similarity index exceeds a preset threshold, the environmental assessment score is considered reasonable. The dynamic time warping algorithm is used to calculate the similarity index of the curves of environmental assessment scores and biological assessment scores changing over time. The calculation method is: In the formula represents the similarity index, 、 They represent the environmental assessment score and biological assessment score over time under the dynamic time warping algorithm. The time series of changes, The dynamic time warping distance represents the curve of environmental assessment score and biological assessment score changing with time, 、 Respectively 、 length; when When the environmental assessment score is considered reasonable; when When the environmental assessment score is considered unreasonable, the reverse gradient method is used to update the weight distribution of physical layer indicators, chemical layer indicators, and biological detection data; In the formula represents the similarity threshold, and ; S6: Conduct time series analysis on the environmental assessment scores to generate a predicted value for the time required to complete the ecological restoration of saline-alkali water bodies; The autoregressive integrated moving average model is used to conduct time series analysis on environmental assessment scores when: Think At this moment, the ecological restoration of saline-alkali water bodies is completed; In the formula Indicates the environmental assessment score under the autoregressive integrated moving average model The predicted value at time, Indicates the preset threshold value of the environmental assessment score.

2. The method for evaluating the ecological restoration effect of saline-alkali water bodies according to claim 1, wherein: The physical layer indicators in the environmental monitoring data include: water level change rate, soil porosity, salt concentration, and electrical conductivity; The chemical layer indicators in the environmental testing data include: effective sodium content, pH value, and nutrient content; The biological detection data include: population size, vegetation coverage, and abundance of key populations; The environmental detection data and biological detection data are both standardized using the maximum and minimum normalization method.

3. The method for evaluating the ecological restoration effect of saline-alkali water bodies according to claim 2, wherein: In step S3, principal component analysis is used to reduce the dimension of the standardized environmental monitoring data, extract the contribution rate of the main components, and determine the weight distribution of the physical layer indicators and the chemical layer indicators respectively according to the contribution rate, and the weights all meet the following normalization conditions: In the formula Indicates the The weights of the physical layer indicators, Indicates the The weight of chemical layer indicators, subscript 、 Respectively represent the index of the physical layer indicator and chemical layer indicator type, 、 Respectively represents the number of types of physical layer indicators and chemical layer indicators.

4. The method for evaluating the ecological restoration effect of saline-alkali water bodies according to claim 3, wherein: The environmental assessment score is calculated as follows: In the formula represents the environmental assessment score, represents the physical layer weight, Indicates the Standardized data of physical layer indicators, Indicates the Standardized data for various chemical layer indicators.

5. The method for evaluating the ecological restoration effect of saline-alkali water bodies according to claim 4, wherein: In step S4, before generating the biological evaluation score, the principal component analysis method is also used to reduce the dimension of the standardized biological detection data, and then the main component contribution rate is extracted. The weight distribution in the biological detection data is determined based on the contribution rate. The biological evaluation score is calculated as follows: In the formula represents the biological assessment score, Indicates the The weight of biological detection data, Indicates the Standardized data of biological detection data, subscript An index representing the type of biological detection data. Indicates the number of types of biological detection data; The weight of the biological detection data also satisfies the following normalization conditions: 。 6. The evaluation system for the ecological restoration effect of saline-alkali water bodies is characterized by: The evaluation system is used to perform the evaluation method according to any one of claims 1 to 5, specifically comprising: A data acquisition module, wherein the data acquisition module is used to collect environmental detection data and biological detection data of saline-alkali water bodies; A weight distribution module, wherein the weight distribution module is pre-installed with a principal component analysis algorithm for weight distribution of environmental detection data and biological detection data; A data analysis module, configured to generate an environmental assessment score and a biological assessment score based on the environmental detection data and the biological detection data, respectively; A data correction module is used to calculate the similarity index of the environmental assessment score and the biological assessment score change curve, and update the weight distribution according to the similarity index; A time series analysis module is used to perform time series analysis on the environmental assessment scores and predict the time required to complete the restoration of saline-alkali water bodies.

7. Equipment for evaluating the ecological restoration effect of saline-alkali water bodies, characterized by: The evaluation equipment includes: medium for storing computer programs; A processor, configured to execute the computer program to implement the evaluation method according to any one of claims 1 to 5.

8. A medium for ecological restoration of saline-alkali water bodies, characterized by: The medium is used to store a computer program, and when the computer program is executed by a processor, the evaluation method according to any one of claims 1 to 5 is implemented.

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