Evaluation method, system, equipment and medium for ecological restoration effect of saline-alkali water body

Abstract

The invention provides a method, a system, equipment and a medium for evaluating the ecological restoration effect of a saline-alkali water body, and relates to the technical field of saline-alkali water body restoration evaluation.A double-layer restoration evaluation architecture based on a physical layer and a chemical layer is constructed, environment and biological monitoring data are fused, data-driven principal component analysis and a dynamic time warping algorithm are adopted, and the ecological restoration effect of the saline-alkali water body is evaluated. Effective matching and dynamic weight adjustment of environment and biological index trends are achieved, and scientificity and accuracy of restoration effect evaluation are improved. Time sequence prediction is carried out on the repair process by combining an autoregression integral moving average model, the repair completion time can be quantitatively evaluated, and scientific management and decision making are assisted. According to the whole scheme, multi-dimensional comprehensive evaluation and dynamic closed-loop optimization of the ecological restoration effect of the saline-alkali water body are achieved, the pertinence, real-time performance and sustainability of ecological restoration are remarkably enhanced, and scientific and efficient technical support is provided for saline-alkali soil restoration.

Description

Technical Field

[0001] The present invention relates to the technical field of saline-alkali water body restoration evaluation, and specifically to an evaluation method, system, device and medium for 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 problem of the ecological environment of saline-alkali land has become increasingly severe, seriously affecting farmland productivity, ecosystem health and regional sustainable development. Existing saline-alkali water body ecological restoration methods mostly focus on the monitoring of single physical or chemical indicators, lacking a systematic comprehensive evaluation of multi-dimensional environmental elements, and it is difficult to comprehensively reflect the dynamic changes of the restoration effect and the overall health status of the ecosystem. In addition, the biological response of the ecosystem has hysteresis, and traditional evaluation means are difficult to achieve effective synchronous analysis of environmental indicators and biological indicators, resulting in untimely and inaccurate judgment of the restoration effect. The lack of a scientific, dynamic and closed-loop restoration effect evaluation system makes it difficult to adjust the restoration plan targeted, inhibiting the improvement of the efficiency and effect of ecological restoration.

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

[0004] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present disclosure, and thus it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0005] The purpose of the present invention is to provide an evaluation method, system, device and medium for the ecological restoration effect of saline-alkali water bodies to solve the problems raised in the above background art.

[0006] To achieve the above purpose, the present invention provides the following technical solutions: Assessment method for the ecological restoration effect of saline-alkali water bodies, the specific steps include: S1: Based on the ecological restoration goal of the saline-alkali water body, construct a two-layer restoration evaluation framework, and set it as the physical layer and the chemical layer respectively; S2: Collect the environmental detection data of the saline-alkali water body, construct physical layer indicators and chemical layer indicators respectively to quantify the restoration effect of the saline-alkali water body, and generate standardized data of the physical layer indicators and the chemical layer indicators respectively; S3: Based on the principal component analysis method, determine the weights of the physical layer indicators and the chemical layer indicators respectively, and generate an environmental evaluation score according to 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 the biological detection data of the saline-alkali water body, generate a biological evaluation score according to the biological detection data, and visually display the change curves of the environmental evaluation score and the biological evaluation score over time respectively; S5: Generate a similarity index between the two according to the change curves of the environmental evaluation score and the biological evaluation score over time, and consider the environmental evaluation score reasonable when the similarity index exceeds the preset threshold; S6: Conduct a time series analysis on the environmental evaluation score to generate a predicted value of the time required to complete the ecological restoration of the saline-alkali water body.

[0007] Preferably, the physical layer indicators in the environmental detection data include: water level change rate, soil porosity, salt concentration, conductivity; The chemical layer indicators in the environmental detection data include: available sodium content, pH value, eutrophic element content; The biological detection data includes: population quantity, vegetation coverage rate, key population abundance; Both the environmental detection data and the biological detection data are standardized using the min-max normalization method.

[0008] Preferably, in step S3, the principal component analysis method is used to reduce the dimension of the standardized environmental detection data, extract the main component contribution rate, 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 satisfy the following normalization conditions: ; ; In the formula represents the weight of the th physical layer indicator, represents the weight of the th chemical layer indicator, the subscripts 、 represent the indexes of the physical layer indicators and the chemical layer indicators respectively, 、 They respectively represent the number of types of physical layer indicators and chemical layer indicators.

[0009] Preferably, the calculation method of the environmental assessment score is as follows: ; In the formula represents the environmental assessment score, represents the physical layer weight, represents the th standardized data of the physical layer indicators, represents the th standardized data of the chemical layer indicators.

[0010] Preferably, in step S4, before generating the biological assessment score, the principal component analysis method is also used to reduce the dimension of the standardized biological detection data, 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 calculation method of the biological assessment score is as follows: ; In the formula represents the biological assessment score, represents the weight of the th biological detection data, represents the th standardized data of the biological detection data, and the subscript represents the index of the biological detection data, represents the number of types of biological detection data; The weight of the biological detection data also satisfies the following normalization condition: .

[0011] Preferably, in step S5, the 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 with time. The calculation method is as follows: ; In the formula represents the similarity index, , respectively represent the time series of the environmental assessment score and the biological assessment score changing with time under the dynamic time warping algorithm , represents the dynamic time warping distance of the curves of the environmental assessment score and the biological assessment score changing with time, , respectively represent , 's lengths; When , it is considered that the environmental assessment score is reasonable; When it is considered that the environmental assessment score is unreasonable, and the backpropagation 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 .

[0012] Preferably, in step S6, when performing time series analysis on the environmental assessment score, an autoregressive integrated moving average model is used. When the following conditions are met: ; it is considered that at the moment of the ecological restoration of saline-alkali water bodies is completed; In the formula represents the predicted value of the environmental assessment score at the moment of under the autoregressive integrated moving average model, represents the preset threshold of the environmental assessment score.

[0013] An evaluation system for the ecological restoration effect of saline-alkali water bodies. The evaluation system is used to execute the above evaluation method, and specifically includes: A data acquisition module, which is used to collect environmental detection data and biological detection data of saline-alkali water bodies; A weight distribution module, in which a principal component analysis algorithm is preset, and is used to distribute weights to environmental detection data and biological detection data; A data analysis module, which is used to generate an environmental assessment score and a biological assessment score respectively according to environmental detection data and biological detection data; A data correction module, which is used to calculate the similarity index of the change curves of the environmental assessment score and the biological assessment score, and update the weight distribution according to the similarity index; A time series analysis module, which is used to perform time series analysis on the environmental assessment score and predict the time required for the restoration of saline-alkali water bodies to be completed.

[0014] An evaluation device for the ecological restoration effect of saline-alkali water bodies. The evaluation device includes: A medium for storing computer programs; A processor for executing the computer program to implement the above evaluation method.

[0015] A medium for the ecological restoration effect of saline-alkali water bodies, which is used to store a computer program, and the computer program realizes the above evaluation method when executed by a processor.

[0016] Compared with the prior art, the beneficial effects of the present invention are: The present invention constructs a double-layer repair 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 effectively match the trends of environmental and biological indicators and adjust dynamic weights, thereby improving the scientificity and accuracy of the evaluation of the repair effect. Combining with the autoregressive integrated moving average model to conduct time series prediction on the repair process can quantitatively evaluate the completion time of the repair 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 repair effect of saline-alkali water bodies, significantly enhances the pertinence, real-time nature, and sustainability of ecological repair, and provides scientific and efficient technical support for the repair of saline-alkali land. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the overall method flow of the present invention; Figure 2 It is a schematic diagram of the module structure of the present invention; Figure 3 It is a schematic diagram of the change curves of the environmental evaluation score and the biological evaluation score of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] To make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with specific embodiments.

[0019] It should be noted that unless otherwise defined, the technical terms or scientific terms used in the present invention should have the ordinary meanings understood by those with ordinary skills in the field to which the present invention belongs. The "first", "second", and similar terms used in the present invention do not indicate any order, quantity, or importance, but are only used to distinguish different components. The terms such as "including" or "comprising" mean that the elements or objects appearing before this word cover the elements or objects listed after this word and their equivalents, without excluding other elements or objects. The terms such as "connected" or "linked" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left", "right", etc. are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0020] Embodiment: Please refer to Figures 1 to 3 The present invention provides a technical solution: A method for evaluating the ecological repair effect of saline-alkali water bodies, the specific steps include: S1: Based on the ecological restoration objectives of saline-alkali water bodies, a two-layer restoration evaluation framework is constructed and set as the physical layer and the chemical layer respectively. The physical layer indicators in the environmental detection data include: water level change rate, soil porosity, salt concentration, and conductivity; the chemical layer indicators in the environmental detection data include: available sodium content, pH value, and eutrophic element content.

[0021] For the physical layer indicators selected in the physical layer: The water level is an important physical parameter of the saline-alkali water body ecological environment, reflecting the dynamic hydrological conditions of the water body. The water level change in saline-alkali land refers to the change rate 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 hydrological dynamics. A positive change rate indicates a rising water level, and a negative value indicates a falling water level, which directly affects the processes of soil salt dissolution, migration, and leaching. By monitoring the water level change rate, it is possible to determine whether the water body has good water circulation and self-purification capabilities. A stable or moderately fluctuating water level is conducive to salt migration and dilution, promoting the improvement of soil saline-alkali conditions. An increasing or more stable fluctuation trend of the water level often represents the effectiveness of restoration measures such as ecological water replenishment and salt removal; Porosity reflects the looseness of the soil structure and is an important indicator of soil physical properties. An increase in porosity indicates an improvement in the soil structure, which is crucial for the effective transport of water and nutrients, promoting microbial activities and plant root respiration for ecological restoration; The salt concentration is the core indicator of saline-alkali water bodies, directly reflecting the accumulation degree of salts in the soil and water body. By monitoring the change in salt concentration in real time, it is possible to evaluate the salt leaching and migration conditions, which is an important basis for judging the restoration effectiveness; Conductivity is a proxy indicator for evaluating the total ion content in soil and water body solutions and can be used as a supplementary indicator for salt concentration.

[0022] For the chemical layer indicators selected in the chemical layer: Sodium ion is one of the main causes of soil alkalization and hardening. Excessive sodium ions will damage the soil structure. The available sodium content refers to the concentration or content of sodium ions present in an exchangeable form in the soil or water body and is a key chemical indicator affecting the degree of soil salinization and the suitability of plant growth. Monitoring the available sodium content helps to judge the degree of soil salinization and the risk of hardening. A high available sodium content will cause the destruction of soil aggregates, soil hardening, affect the circulation of water and gas, thus poisoning plant roots and reducing the plant's water absorption capacity; The soil of saline-alkali water bodies is mostly alkaline, and the pH value reflects the soil acidity and alkalinity, which can evaluate the changing trend of the soil acid-base environment; Eutrophic elements (such as nitrogen, phosphorus, potassium) are the 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 soil fertility in saline-alkali land and reflect the enhancement of the ecological system's support capacity for plant growth.

[0023] The above physical and chemical layer indicators comprehensively reflect the hydro-physical conditions, soil structure status, salinization degree, and soil chemical characteristics of the saline-alkali water environment. The changes in these indicators directly or indirectly affect the plant growth environment and microbial ecosystem of saline-alkali land, and are important parameters for evaluating the ecological restoration effect of saline-alkali water bodies. Through systematic monitoring and quantitative analysis of these indicators, it is possible to scientifically guide the adjustment and optimization of restoration plans, and improve the pertinence and effectiveness of restoration.

[0024] S2: Collect environmental detection data of saline-alkali water bodies, respectively construct physical layer indicators and chemical layer indicators to quantify the restoration effect of saline-alkali water bodies, and generate standardized data of physical layer indicators and chemical layer indicators respectively. Here, both environmental detection data and subsequent biological detection data are standardized using the min-max normalization method.

[0025] Specifically, the calculation method of the min-max normalization method is: ; In the formula represents the standardized data, represents the input data, and represent the maximum and minimum values of the input data respectively. Using the min-max normalization method for standardization can eliminate the differences in the dimensions and dimension ranges of different indicators, and ensure the comparability of indicator data. It can be understood that during the restoration process of saline-alkali water bodies, the changes in various parameters are not infinite, but fluctuate within a certain range. For example, the pH value usually fluctuates between 8.5 and 7.5, indicating that the alkalinity of the saline-alkali water body weakens, but will not drop below 7, which 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. Each parameter in the environmental detection data can be further divided into positive indicators and negative indicators according to its function. Positive indicators, such as the water level change rate, soil porosity, and content of eutrophic elements, are positively correlated with the ecological restoration effect, so the directly output is the standardized data that can be used subsequently; while negative indicators, such as salt concentration, conductivity, available sodium content, and pH value, are negatively correlated with the ecological restoration effect, so the output standardized data needs to be corrected, that is: ; Here represents the corrected standardized data, which is used to reflect the different effects of different function indicators on the restoration effect of saline-alkali water bodies.

[0026] S3: Based on the principal component analysis method, determine the weights of the physical layer indicators and the chemical layer indicators respectively, and generate an environmental assessment score according to 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.

[0027] In step S3, the principal component analysis method is used to reduce the dimension of the standardized environmental detection data, extract the main component contribution rate, 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 satisfy the following normalization conditions: ; ; In the formula represents the weight of the th physical layer indicator, represents the weight of the th chemical layer indicator. The subscripts and represent the indexes of the physical layer indicators and the chemical layer indicators respectively. and represent the types of the physical layer indicators and the chemical layer indicators respectively.

[0028] Specifically, the logic of the principal component analysis method (i.e., PCA) is as follows: Obtain the index data of the physical layer and the chemical layer in the saline-alkali water body environmental detection data, and respectively form two data matrices after standardization processing; 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 for PCA dimension reduction; Perform eigenvalue decomposition on the correlation matrix respectively, solve the eigenvalues and the corresponding eigenvectors. Each eigenvalue represents the variance contribution size of the corresponding principal component, and the eigenvector represents the linear combination coefficient of the principal component; According to the cumulative contribution rate principle, select the first several principal components so that the cumulative contribution rate reaches a preset threshold (usually more than 90%), ensuring that the main information is retained. In this way, both dimension reduction and information loss reduction are achieved; Reflect the weight of each indicator in the principal component through the eigenvector coefficient (i.e., loading amount) of the principal component. The loading reflects the correlation between the indicator and the principal component. The larger the absolute value of the loading, the greater the contribution of the indicator to the principal component; Combined with the variance contribution rate of the principal component, normalize the weighted variance contribution rate of the absolute loading values on each principal component, and calculate the comprehensive weight of each indicator.

[0029] Since the principal component analysis method is an existing technology, its specific calculation formula will not be elaborated here. By introducing the principal component analysis method to determine the weight distribution, it can be directly obtained by mathematical methods from the data itself, avoiding subjective human setting deviations. Moreover, by extracting the principal components, the relevant redundant information between indicators can also be removed, enhancing the stability and interpretability of the model.

[0030] The calculation method of the environmental assessment score is as follows: ; In the formula represents the environmental assessment score, represents the weight of the physical layer, which can be specifically determined by expert experience. represents the th standardized data of the physical layer indicators, represents the th standardized data of the chemical layer indicators.

[0031] It can be seen from the calculation formula of the environmental assessment score that it represents the comprehensive evaluation result of the environmental state in the process of saline-alkali water body ecological restoration, which is a comprehensive score aggregated from the physical layer and chemical layer indicators; among them, the physical layer and chemical layer represent different aspects of the saline-alkali water body environment, such as the physical and chemical properties of hydrology and soil. By introducing the weight of the physical layer, the relative weights of the two layers can be flexibly adjusted to reflect the importance ratio of the two in the actual restoration process.

[0032] Specifically, when the environmental assessment score is relatively large, it means that the physical layer indicators (such as water level change rate, soil porosity, conductivity, etc.) are in an ideal or relatively stable state, indicating good hydrology and soil structure, and the chemical layer indicators (such as available sodium content, pH value, eutrophic element content) are controlled within a reasonable range conducive to the restoration of the ecosystem, with moderate salinity and sufficient nutrient supply. Therefore, it also means that the ecological environment state of the saline-alkali water body is relatively healthy, which is conducive to plant growth and the restoration of ecosystem functions.

[0033] S4: Collect the biological detection data of the saline-alkali water body, generate a biological assessment score according to the biological detection data. The biological detection data includes: population quantity, vegetation coverage rate, key population abundance, and visually display the change curves of the environmental assessment score and the biological assessment score over time respectively. These parameters are used to reflect the biodiversity and ecological health status of the saline-alkali water body ecosystem, and intuitively display the restoration effect of the saline-alkali water body.

[0034] In step S4, before generating the biological assessment score, the principal component analysis method is also used to reduce the dimension of the standardized biological detection data, then extract the main component contribution rate, and determine the weight distribution in the biological detection data according to the contribution rate. The calculation method of the biological assessment score is as follows: ; In the formula represents the biological assessment score, represents the weight of the th biological detection data, represents the th standardized data of biological detection data, and the subscript represents the index of biological detection data, represents the number of types of biological detection data.

[0035] The weights of biological detection data also satisfy the following normalization conditions: .

[0036] It can be seen from the calculation formula of the biological assessment score that it represents the comprehensive health status of the saline-alkali water ecosystem based on biological indicators, and it is a quantitative indicator that reflects the overall biological environmental quality with a single value. When the biological assessment score is relatively large, it indicates that the biological indicators of the saline-alkali water body perform well, the population quantity is rich, the vegetation coverage rate is high, the abundance of key populations is sufficient, the biological health of the ecosystem is good and the diversity is good, and the restoration effect is significant; on the contrary, when the biological assessment score is relatively small, it indicates that the biological indicators perform poorly, and problems such as population reduction, sparse vegetation, and lack of key populations may occur, the ecological function is damaged, and the restoration still needs to be strengthened. It is an indicator that can intuitively judge the restoration effect of the saline-alkali water body.

[0037] S5: Generate the similarity index of the environmental assessment score and the biological assessment score according to their change curves over time, and consider the environmental assessment score reasonable when the similarity index exceeds the preset threshold.

[0038] Although the biological assessment score can directly reflect the ecological restoration effect of the saline-alkali water body, the growth of organisms requires a certain amount of time, which will cause the change of the biological assessment score to be later than that of the environmental assessment score. In other words, the biological assessment score is more intuitive but has hysteresis. Therefore, using the more immediate environmental assessment score 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. They play the same role and have the same change trend. The only difference is the time point of change on the time axis, and the parameters in the calculation of the biological assessment score can all be directly measured. Therefore, the calculation model of the environmental assessment score can be corrected according to the change trend of the biological assessment score to make their change trends similar, and then use the more immediate environmental assessment score to inversely reflect the change trend of the biological assessment score, so as to predict the restoration status of the saline-alkali water body.

[0039] In step S5, the dynamic time warping (DTW) algorithm is used to calculate the similarity index of the curves of the environmental assessment score and the biological assessment score over time. The DTW algorithm can effectively handle the situation where the lengths of two time series are different and there is a non-linear deformation on the time axis, accurately measure the morphological similarity between the curves, and overcome the deficiencies of the traditional Euclidean distance calculation. Its calculation method is as follows: ; In the formula represents the similarity index, and the value range is from 0 to 1, indicating the morphological similarity of 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; 、 respectively represent the time series of the environmental assessment score and the biological assessment score over time under the dynamic time warping algorithm changes, represents the dynamic time warping distance of the curves of the environmental assessment score and the biological assessment score over time. The smaller the distance, the more similar the curves are, 、 respectively represent 、 the lengths of, which are used to normalize the DTW distance to make the similarity index dimensionless and the value within a reasonable range; When , it is considered that the environmental assessment score is reasonable; When , it is considered that the environmental assessment score is unreasonable, and the backpropagation gradient method is used to update the weight distribution of the physical layer index, the chemical layer index, and the biological detection data; In the formula represents the similarity threshold, and , and its specific value can be adjusted according to actual needs or expert experience.

[0040] Here, by introducing the dynamic time warping algorithm to calculate the similarity index between time series, the quantitative determination of the trend matching degree between the environmental assessment score and the biological assessment score is realized, and the weights are feedback-adjusted according to the similarity threshold. Not only the high consistency verification of the environment and ecological biological response is completed, but also the dynamic self-adaptation and closed-loop optimization of the environmental assessment system are realized, which helps to improve the scientificity and accuracy of the assessment results.

[0041] S6: Conduct a time series analysis on the environmental assessment score to generate a predicted value for the time required to complete the ecological restoration of saline-alkali water bodies.

[0042] In step S6, when performing time series analysis on the environmental assessment score, the autoregressive integrated moving average model (i.e., ARIMA model) is adopted. The ARIMA model simultaneously considers the self-lag effect (autoregressive AR), differencing process (integration I), and random noise (moving average MA) of the sequence, and is suitable for processing non-stationary ecological environment data with random perturbations, improving the prediction accuracy. When the following conditions are met: ; It is considered that at time, the ecological restoration of the saline-alkali water body is completed; In the formula represents the predicted value of the environmental assessment score under the autoregressive integrated moving average model at time. The larger the value, the better the expected ecological environment state, the overall physical and chemical indicators tend to be excellent, and the ecological system function gradually recovers. represents the preset threshold of the environmental assessment score. As a quantitative indicator for reaching the repair standard, it combines the prediction results to judge the time point when this threshold is reached, which is the ecological restoration completion time.

[0043] Here, by using the ARIMA model to perform time series prediction on the environmental assessment score sequence and combining the preset threshold to determine the repair completion time, the scientific quantitative prediction and management control of the saline-alkali water body ecological restoration process are realized, significantly improving the accuracy and practicality of ecological environment assessment and governance.

[0044] In this embodiment, data is collected for the first 20 days during the saline-alkali water body repair process, and the obtained data is shown in the following table: Table 1: Data table for saline-alkali water body repair ; From the data in the above table and Figure 3 it can be seen that the environmental assessment score comprehensively reflects the changes in key environmental indicators of the physical and chemical layers. As the ecological restoration process progresses, it gradually increases, indicating that the ecological restoration measures effectively reduce the saline-alkali stress on the soil and water body, improve the hydrological environment conditions, and promote the transformation of soil chemical properties towards a direction suitable for the survival of organisms. The biological assessment score does not show an obvious change trend in the first two days, and shows an obvious upward trend starting from the third day. The population quantity, vegetation coverage rate, and key population abundance gradually increase, indicating that the restoration of the biological community is gradually advancing, and the ecological effects and ecosystem stability of ecological restoration can be intuitively judged. The improvement of the environmental assessment score precedes the biological assessment score, reflecting that the improvement of environmental conditions provides necessary but not immediate response conditions for biological restoration, and the trend conforms to the classical theory of ecosystem restoration: first improve the physical and chemical environment, and then the biological community gradually recovers and stabilizes.

[0045] This embodiment also provides an evaluation system for the ecological restoration effect of the saline-alkali water body. The evaluation system is used to execute the above evaluation method, and specifically includes: A data acquisition module, which is used to acquire environmental detection data and biological detection data of saline-alkali water bodies; A weight allocation module, in which a principal component analysis algorithm is preset, and is used to allocate weights to environmental detection data and biological detection data; A data analysis module, which is used to generate environmental evaluation scores and biological evaluation scores according to environmental detection data and biological detection data respectively; A data correction module, which is used to calculate the similarity index of the change curves of environmental evaluation scores and biological evaluation scores, and update the weight allocation according to the similarity index; A time series analysis module, which is used to perform time series analysis on environmental evaluation scores and predict the time required for the completion of saline-alkali water body restoration.

[0046] This embodiment also provides an evaluation device for the ecological restoration effect of saline-alkali water bodies. The evaluation device includes: A medium, which is used to store computer programs; A processor, which is used to execute computer programs to implement the above evaluation method.

[0047] This embodiment also provides a medium for the ecological restoration effect of saline-alkali water bodies. The medium is used to store computer programs, and when the computer programs are executed by a processor, the above evaluation method is implemented.

[0048] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by software simulation of a large amount of collected data to get a formula closest to the real situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0049] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. 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 can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0050] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. They can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0051] As described above, it is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application.

Claims

1. An evaluation method for the ecological restoration effect of saline-alkali water bodies, characterized in that, The specific steps include: S1: Construct a two-layer repair evaluation architecture based on the ecological restoration goal of saline-alkali water bodies, and set the architecture as a physical layer and a chemical layer; S2: Collect the environmental detection data of saline-alkali water bodies, respectively construct physical layer indicators and chemical layer indicators to quantify the repair effect of saline-alkali water bodies, and respectively generate the standardized data of physical layer indicators and chemical layer indicators; S3: Based on the principal component analysis method, respectively determine the weights of physical layer indicators and chemical layer indicators, and generate an environmental evaluation score according to the weights of physical layer indicators and chemical layer indicators and the standardized data of physical layer indicators and chemical layer indicators; S4: Collect the biological detection data of saline-alkali water bodies, generate a biological evaluation score according to the biological detection data, and respectively visualize the change curves of environmental evaluation scores and biological evaluation scores over time; S5: Generate a similarity index between the two according to the change curves of environmental evaluation scores and biological evaluation scores over time, and consider the environmental evaluation score reasonable when the similarity index exceeds a preset threshold; S6: Conduct a time series analysis on the environmental evaluation score to generate a predicted value of the time required to complete the ecological restoration of saline-alkali water bodies.

2. The evaluation method for the ecological restoration effect of saline-alkali water bodies according to claim 1, wherein: The physical layer indicators in the environmental detection data include: water level change rate, soil porosity, salt concentration, conductivity; The chemical layer indicators in the environmental detection data include: available sodium content, pH value, eutrophic element content; The biological detection data includes: population quantity, vegetation coverage rate, key population abundance; Both the environmental detection data and the biological detection data are standardized using the min-max normalization method.

3. The evaluation method for the ecological restoration effect of saline-alkali water bodies according to claim 2, characterized in that: In step S3, the principal component analysis method is used to reduce the dimension of the standardized environmental detection data, extract the main component contribution rate, and respectively determine the weight distribution of physical layer indicators and chemical layer indicators according to the contribution rate, and the weights all meet the following normalization conditions: ； ； where represents the weight of the th physical layer index, represents the weight of the th chemical layer index, and the subscripts and respectively represent the indices of the types of physical layer and chemical layer indices, and respectively represent the number of types of physical layer and chemical layer indices.

4. The evaluation method for the ecological restoration effect of saline-alkali water bodies according to claim 3, characterized in that: The calculation method of the environmental evaluation score is: ； wherein represents the environmental assessment score, represents the physical layer weight, represents the standardized data of the th physical layer index, represents the standardized data of the th chemical layer index.

5. The evaluation method for the ecological restoration effect of saline-alkali water bodies according to claim 4, characterized in that: 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, then extract the main component contribution rate, and determine the weight distribution in the biological detection data according to the contribution rate. The calculation method of the biological evaluation score is: ； where represents the biological assessment score, represents the weight of the th biological detection data, represents the standardized data of the th biological detection data, and the subscript represents the index of the type of biological detection data, represents the number of types of biological detection data; The weights of the biological detection data also meet the following normalization conditions: 。 6. The evaluation method for the ecological restoration effect of saline-alkali water bodies according to claim 5, wherein: In step S5, the dynamic time warping algorithm is used to calculate the similarity index of the change curves of environmental evaluation scores and biological evaluation scores over time. The calculation method is: ； where represents the similarity index, and represent the time series of the environmental assessment score and the biological assessment score over time under the dynamic time warping algorithm, respectively, represents the dynamic time warping distance of the curves of the environmental assessment score and the biological assessment score changing over time, and represent and lengths respectively; When the environmental assessment score is considered reasonable; When it is considered that the environmental assessment score is unreasonable, and the backpropagation gradient method is used to update the weight allocation of physical layer indicators, chemical layer indicators, and biological detection data; wherein represents a similarity threshold, and .

7. The evaluation method for the ecological restoration effect of saline-alkali water bodies according to claim 6, characterized in that: In step S6, when conducting a time series analysis on the environmental evaluation score, an autoregressive integrated moving average model is used. When it satisfies: ； It is considered that the ecological restoration of saline-alkali water bodies is completed at this moment; where represents the predicted value of the environmental assessment score under the autoregressive integrated moving average model at time, represents the preset threshold of the environmental assessment score.

8. An evaluation system for the ecological restoration effect of saline-alkali water bodies, characterized in that: The evaluation system is used to execute the evaluation method described in any one of claims 1-7, and specifically includes: A data acquisition module, which is used to collect the environmental detection data and biological detection data of saline-alkali water bodies; A weight distribution module, which is pre-set with a principal component analysis algorithm and is used to distribute weights to the environmental detection data and biological detection data; A data analysis module, which is used to generate environmental evaluation scores and biological evaluation scores respectively according to the environmental detection data and biological detection data; A data correction module, which is used to calculate the similarity index of the environmental assessment score and the change curve of the biological assessment score, and update the weight assignment according to the similarity index; A timing analysis module, which is used to perform timing analysis on the environmental assessment score and predict the time required for the completion of the saline-alkali water body restoration.

9. An evaluation device for the ecological restoration effect of saline-alkali water bodies, characterized in that: The evaluation device includes: A medium for storing computer programs; A processor for executing the computer program to implement the evaluation method according to any one of claims 1-7.

10. Medium for ecological restoration effect of saline-alkali water body, characterized in that: The medium is used to store a computer program, and when the computer program is executed by the processor, the evaluation method according to any one of claims 1-7 is implemented.

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