An intelligent evaluation method for the implementation effect of ecological restoration of river, lake and wetland in a river basin

Abstract

The present invention relates to the field of intelligent evaluation technology, and specifically to an intelligent evaluation method for the implementation effect of ecological restoration of river, lake and wetland in a river basin. The method includes: obtaining sampling data of sampling points after experiencing preset ecological restoration measures; determining the data change amplitude of the sampling points at each sampling moment, and then determining the degree of influence of the restoration measures; determining the ecological carrying capacity according to the numerical distribution of the degree of influence of the restoration measures; determining the confidence of the ecological restoration effect according to the degree of influence of the restoration measures and the ecological carrying capacity of the sampling points in the wetland area and its neighboring areas; adjusting the sampling data according to the confidence of the ecological restoration effect to obtain confidence data; and implementing the restoration effect evaluation of the preset ecological restoration measures according to the confidence data of all sampling points to obtain an evaluation result. The embodiment of the present invention can avoid the influence of ecological carrying capacity and the mutual influence between multiple wetland areas, effectively improve the reliability of the evaluation, and enhance the accuracy of the evaluation results.

Description

Technical Field

[0001] The present invention relates to the field of intelligent evaluation technology, and in particular to an intelligent evaluation method for the implementation effect of ecological restoration of river, lake and wetland in a river basin. Background Art

[0002] Ecological restoration of river and lake wetlands in the basin mainly uses physical and chemical methods to adjust the wetland status. For example, chemical methods are used to enrich pollutants in the water. After gradual decomposition, the ecological environment in the water body is restored, achieving the purpose of rebuilding the river and lake water ecosystem. After the implementation of ecological restoration measures, continuous observation and evaluation of ecological restoration measures are required, and subsequent ecological adjustment operations are carried out based on the evaluation results.

[0003] In the related technology, sampling is carried out directly at multiple sampling points in the entire river basin, lake and wetlands to evaluate the ecological restoration measures at the current moment. In this way, due to the diversity of wetland types and the different feedback effects of different types of wetlands on ecological restoration measures, the ecological carrying capacity is different, and multiple wetland areas will have mutual influences, which leads to poor reliability of direct analysis based on all sampling points and low accuracy of the analysis results. Summary of the invention

[0004] In order to solve the technical problem that the relevant technologies do not consider the different feedback effects of different types of wetlands on ecological restoration measures, the differences in ecological carrying capacity, and the mutual influence between multiple wetland areas, which leads to poor reliability of directly combining all sampling points for analysis and low accuracy of analysis results, the present invention provides an intelligent evaluation method for the implementation effect of ecological restoration of river and lake wetlands in a basin, and the technical scheme adopted is as follows:

[0005] The present invention proposes an intelligent evaluation method for the implementation effect of ecological restoration of river and lake wetlands in a river basin. There are wetland areas of different wetland types distributed in the same river basin. The method comprises:

[0006] After the preset ecological restoration measures are taken, sampling data from different sampling points in different wetland areas in the same watershed are periodically obtained;

[0007] According to the difference of sampling data at different sampling moments at the same sampling point, determine the data change range of the sampling point at each sampling moment; according to the data change range of different sampling points at the same sampling moment, determine the impact of the repair measures of any sampling point at any sampling moment;

[0008] Determine the ecological carrying capacity of the wetland area based on the numerical distribution of the impact of restoration measures at all sampling points in the same wetland area at all sampling times;

[0009] The other wetland areas connected to any wetland area are regarded as neighboring areas. The confidence level of the ecological restoration effect of the wetland area is determined based on the changing characteristics of the impact of the restoration measures at the sampling points in the wetland area and its neighboring areas, as well as the ecological carrying capacity of the wetland area.

[0010] According to the confidence level of the ecological restoration effect of each wetland area, the sampling data of the sampling points in the wetland area at the current moment are adjusted to obtain confidence data; based on the confidence data of all sampling points, the restoration effect evaluation of the preset ecological restoration measures is implemented to obtain the evaluation results.

[0011] Furthermore, the method for obtaining the data variation range includes:

[0012] At the same sampling point, the absolute value of the difference between the sampled data at any sampling moment and the previous sampling moment is determined to obtain the data change amplitude at the corresponding sampling moment.

[0013] Furthermore, the method for obtaining the impact degree of the repair measures includes:

[0014] At the same sampling time, the overall measure influencing factor is determined based on the numerical distribution of the data change amplitude of all sampling points;

[0015] According to the difference between the normalized value of the data change amplitude of any sampling point and the overall measure influencing factor, the impact degree of the repair measures at the sampling point at the corresponding sampling time is determined.

[0016] Furthermore, determining the overall measure influencing factor according to the numerical distribution of the data change amplitude of all sampling points includes:

[0017] The overall measure influence factor is determined according to the numerical dispersion and numerical mean of the data change amplitude of all sampling points, wherein the numerical dispersion is negatively correlated with the overall measure influence factor, the numerical mean is positively correlated with the overall measure influence factor, and the value of the overall measure influence factor is a normalized value.

[0018] Furthermore, the method for obtaining the ecological carrying capacity includes:

[0019] According to the numerical distribution of the impact of restoration measures at the same sampling point at all sampling moments, the stable moment of ecological stability at the sampling point is determined;

[0020] Determine the point load influence factor of the sampling point according to the time sequence position of the stable moment in all sampling moments, wherein the closer the stable moment is to the initial moment in the time sequence, the greater the value of the point load influence factor;

[0021] According to the point carrying capacity influencing factors of all sampling points in the same wetland area, the ecological carrying capacity of the wetland area is obtained.

[0022] Furthermore, the method for obtaining the stable moment of ecological stability of the sampling point includes:

[0023] Based on the time series, the impact degree of the repair measures of the same sampling point at all sampling moments is sorted to obtain the impact time series sequence;

[0024] Taking any moment as a division moment, dividing the impact time series based on different division moments respectively to obtain two subsequences;

[0025] Determine the degree variance and degree range of the impact of all repair measures in each subsequence; determine the stability factor of the subsequence based on the degree variance and degree range, wherein the degree variance and degree range are negatively correlated with the stability factor, and the value of the stability factor is a normalized value;

[0026] All sampling moments are traversed in time sequence as the division moments. When the stability factor of the next subsequence in time sequence is greater than a preset stability threshold, the traversal is stopped and the corresponding division moment is used as the stable moment of the sampling point.

[0027] Furthermore, the confidence level of the ecological restoration effect of the wetland area includes:

[0028] Determine any wetland area as a target area, and determine the regional impact index and neighborhood impact index of the target area according to the impact degree of the restoration measures of all sampling points in the target area and all neighborhood areas of the target area at all sampling times;

[0029] The difference between the regional impact index and the neighborhood impact index is used as the restoration effect impact coefficient of the target area;

[0030] The ecological restoration effect confidence of the target area is determined based on the restoration effect influence coefficient and the ecological carrying capacity of the target area, wherein the ecological carrying capacity is positively correlated with the ecological restoration effect confidence, the restoration effect influence coefficient is negatively correlated with the ecological restoration effect confidence, and the value of the ecological restoration effect confidence is a normalized value.

[0031] Furthermore, the method for obtaining the regional impact index and the neighborhood impact index of the target area includes:

[0032] The average of the impact of the restoration measures at all sampling points in the target area at all sampling times is used as the regional impact index of the target area;

[0033] The average of the impact levels of the repair measures of all sampling points in all neighborhood areas of the target area at all sampling times is taken as the neighborhood impact index of the target area.

[0034] Furthermore, according to the confidence level of the ecological restoration effect of each wetland area, the sampling data of the sampling points in the wetland area at the current moment are adjusted to obtain confidence data, including:

[0035] Within the time range from the initial moment to the current moment, the confidence of the ecological restoration effect of the wetland area corresponding to any sampling point is used as the weight of the sampling data of the sampling point at the current moment, and the sampling data are multiplied to obtain confidence data.

[0036] Furthermore, the restoration effect evaluation of the preset ecological restoration measures is realized according to the confidence data of all sampling points to obtain the evaluation results, including:

[0037] Determine an evaluation index according to the discrete degree of confidence data of all sampling points at the current moment, wherein the evaluation index is negatively correlated with the discrete degree;

[0038] The evaluation index is used as the evaluation result.

[0039] The present invention has the following beneficial effects:

[0040] The embodiment of the present invention aims to conduct a unified analysis of wetland areas with complex distribution and certain differences in status, by periodically obtaining sampling data of different sampling points in different wetland areas in the same watershed after experiencing preset ecological restoration measures; the degree of influence of restoration measures on sampling points; the numerical values ​​of the degree of influence of restoration measures of all sampling points in the same wetland area can be combined to obtain the ecological carrying degree of the wetland area, and the ecological carrying degree characterizes the impact of the corresponding wetland area on the ecological restoration measures; according to the changing characteristics of the degree of influence of restoration measures of sampling points in the wetland area and its neighboring areas, and the ecological carrying degree of the wetland area, the confidence of the ecological restoration effect of the wetland area is determined, and the confidence of the ecological restoration effect can characterize the reliability characteristics of the wetland area itself under ecological restoration, and the wetland area with stronger reliability characteristics has a stronger ecological carrying capacity, so that the sampling data of the sampling points in the wetland area can be adjusted according to the confidence of the ecological restoration effect of each wetland area to obtain confidence data; the restoration effect evaluation of the preset ecological restoration measures is realized according to the confidence data of all sampling points to obtain the evaluation result. The present invention can combine the data feedback of preset ecological restoration measures in different wetland areas to obtain more accurate and effective confidence data, so that when the restoration effect evaluation is realized according to the confidence data, the influence of ecological carrying capacity and the mutual influence among multiple wetland areas can be avoided, thereby effectively improving the reliability of the evaluation and enhancing the accuracy of the evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A flow chart of an intelligent evaluation method for implementing ecological restoration of river, lake and wetland in a river basin provided by an embodiment of the present invention;

[0043] Figure 2 A schematic diagram of a river, lake and wetland ecological scene in a watershed provided by an embodiment of the present invention;

[0044] Figure 3 A flowchart of a method for obtaining the impact degree of a repair measure provided by an embodiment of the present invention;

[0045] Figure 4 A flow chart of a method for obtaining an ecological carrying capacity provided by an embodiment of the present invention;

[0046] Figure 5 A structural diagram of an intelligent evaluation system for implementing ecological restoration of river, lake and wetland basins provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the intelligent evaluation method for the implementation effect of ecological restoration of river, lake and wetland in a river basin proposed by the present invention, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0048] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0049] The specific scheme of the intelligent evaluation method for the implementation effect of ecological restoration of river, lake and wetland in a river basin provided by the present invention is described in detail below with reference to the accompanying drawings.

[0050] See also Figure 1 , which shows a flow chart of an intelligent evaluation method for implementing ecological restoration of river, lake and wetland in a river basin provided by an embodiment of the present invention, the method comprising:

[0051] S101: After the preset ecological restoration measures are taken, sampling data from different sampling points in different wetland areas in the same watershed are periodically obtained.

[0052] A specific implementation scenario of the present invention is the ecological restoration scenario of river and lake wetlands in river basins. Different types of wetland areas can specifically include natural wetland areas and artificial wetland areas. Of course, wetland areas can also be divided according to ecological characteristics, such as mud swamps, shrub swamps, aquatic vegetation swamps, and humus swamps. Figure 2 Conduct a specific analysis. Figure 2 A schematic diagram of an ecological scene of a river, lake or wetland in a river basin provided for an embodiment of the present invention. A variety of different wetland types are located in the same river basin. Ecological changes are achieved by managing the water bodies of the rivers and lakes in the river basin, or by adjusting the overall wetland soil quality. By monitoring the ecological changes, specific analysis of ecological restoration can be performed.

[0053] In the embodiment of the present invention, the preset ecological restoration measures are measures and methods for treating the rivers and lakes in the basin, thereby affecting the ecological restoration of the wetland area, which may specifically include physical management measures such as planning the flow direction of the water bodies of rivers and lakes in the basin, controlling the width and depth of the river channel, or chemical management measures such as adding flocculants (such as polyaluminum chloride or polyferric sulfate), oxidants (such as ozone, hydrogen peroxide or potassium permanganate), acid-base regulators (such as sulfuric acid or sodium hydroxide), and heavy metal stabilizers (such as sulfides, phosphates or hydroxides) to the water bodies of rivers and lakes in the basin to cause precipitation, oxidation-reduction and other reactions of pollutants. The preset ecological restoration measures in the embodiment of the present invention are measures for overall restoration of all wetland areas, and the actual restoration effects of different types of wetland areas are different, so they need to be specifically analyzed.

[0054] In an embodiment of the present invention, the status of different wetland areas is monitored to analyze the restoration effect. Sampling points with different locations can be allocated in each wetland area, and each sampling point is configured with various types of wetland ecological data acquisition sensors, such as pH, nitrogen and phosphorus content monitoring sensors. Of course, various data such as the number of organisms and species in the corresponding wetland area can also be determined through biological detection and other methods.

[0055] It should be noted that the sampling data in the embodiment of the present invention represents the status data of the wetland area, which may be a combination of multiple data, or may be a combination of multiple types of status data through a setting method, and is used to represent the actual status of the corresponding sampling point.

[0056] After implementing the preset ecological restoration measures (such as adding a certain amount of acid-base regulator in the watershed), the embodiment of the present invention periodically collects sampling data from different sampling points in different wetland areas in the same watershed, thereby realizing the subsequent ecological restoration evaluation of the preset ecological restoration measures. The sampling period can be, for example, 1 day, that is, sampling data is collected once at all sampling points every 24 hours.

[0057] S102: Determine the data change range of the sampling point at each sampling time according to the difference of sampling data at different sampling times at the same sampling point; determine the impact degree of the repair measures of any sampling point at any sampling time according to the data change range of different sampling points at the same sampling time.

[0058] The data variation range refers to the variation of the sampled data. In the embodiment of the present invention, the data variation range can be analyzed by analyzing the variation of the sampled data of the same sampling point at different sampling moments.

[0059] Furthermore, in some embodiments of the present invention, a method for obtaining data change amplitude includes: at the same sampling point, determining the absolute value of the difference between the sampled data at any sampling moment and the previous sampling moment, and obtaining the data change amplitude at the corresponding sampling moment.

[0060] That is to say, in this embodiment, the absolute value of the difference between the sampled data at two adjacent sampling moments is used as the data change amplitude at the next sampling moment.

[0061] Of course, in some other embodiments of the present invention, multiple sampling moments before any sampling moment can also be integrated, that is, the average of the sampling data at the previous multiple sampling moments is calculated, and the absolute value of the difference between the sampling data at the sampling moment and the average of the sampling data at the previous sampling moment is calculated to obtain the data change amplitude at the corresponding sampling moment.

[0062] Combination Figure 3 A specific analysis is conducted, among which, Figure 3 A flowchart of a method for obtaining the degree of impact of repair measures provided by an embodiment of the present invention is shown in FIG. Figure 3 As shown:

[0063] S301: At the same sampling time, determine the overall measure influencing factor according to the numerical distribution of the data change amplitude of all sampling points.

[0064] The embodiment of the present invention performs analysis in the time series dimension at the same sampling moment. Since different sampling points may represent different wetland environments, the numerical distribution of the data change amplitudes of all sampling points can be combined to perform change analysis on the overall wetland area at each sampling moment after implementing the preset ecological restoration measures.

[0065] Furthermore, in some embodiments of the present invention, the overall measure influence factor is determined based on the numerical distribution of the data change amplitude of all sampling points, including: determining the overall measure influence factor based on the numerical dispersion and numerical mean of the data change amplitude of all sampling points, wherein the numerical dispersion is negatively correlated with the overall measure influence factor, the numerical mean is positively correlated with the overall measure influence factor, and the value of the overall measure influence factor is a normalized value.

[0066] Among them, a positive correlation means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. The specific relationship can be a multiplication relationship, an addition relationship, or the power of an exponential function, which is determined by actual application; a negative correlation means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc., which is determined by actual application.

[0067] In one embodiment of the present invention, the normalization processing can be specifically, for example, maximum and minimum value normalization processing, and the normalization in subsequent steps can all adopt maximum and minimum value normalization processing. In other embodiments of the present invention, other normalization methods can be selected according to the specific range of numerical values, which will not be described in detail.

[0068] It should be noted that in order to ensure that the calculation results are meaningful, when the negative correlation is a division relationship, a parameter adjustment factor greater than 0 must be added to the denominator to prevent the denominator from being 0. The value of the parameter adjustment factor can be specifically, for example, 0.01, which is set by the implementer according to actual conditions, and this application does not impose any special restrictions.

[0069] The degree of numerical dispersion can be specifically calculated using variance. Of course, other forms such as standard deviation can also be used, and there is no limitation to this.

[0070] In an embodiment of the present invention, the ratio of the numerical mean to the numerical dispersion degree can be calculated, and the ratio can be normalized by the maximum and minimum values ​​to obtain the overall measure influence factor. That is to say, the greater the data change amplitude of all sampling points and the more stable the distribution, the greater the overall measure influence factor.

[0071] S302: Determine the impact degree of the repair measure of the sampling point at the corresponding sampling time according to the difference between the normalized value of the data change amplitude of any sampling point and the overall measure impact factor.

[0072] The embodiment of the present invention can perform maximum and minimum value normalization processing on the data variation amplitude of each sampling point to obtain the data variation coefficient of each sampling point.

[0073] In an embodiment of the present invention, when the data change of a sampling point is similar to the overall data change, the data change coefficient of the sampling point is close to the value of the overall measure impact factor, and the absolute value of the difference is low. When the overall measure impact factor is large but the data change coefficient is small, or when the overall measure impact factor is small but the data change coefficient is large, it indicates that the data change of the sampling point is abnormal, that is, the more abnormal the impact of the preset ecological restoration measures on the sampling point, the greater the corresponding absolute value of the difference.

[0074] Therefore, the present invention calculates the absolute value of the difference between the data variation coefficient of the sampling point and the overall measure influencing factor to obtain the impact degree of the restoration measure. The greater the impact degree of the restoration measure, the greater the impact of the preset ecological restoration measure on the corresponding sampling point.

[0075] In this way, the degree to which each sampling point is affected by the preset ecological restoration measures at each sampling time can be accurately determined, thereby achieving effective analysis of the impact status of the preset ecological restoration measures.

[0076] S103: Determine the ecological carrying capacity of the wetland area based on the numerical distribution of the impact of restoration measures at all sampling points in the same wetland area at all sampling times.

[0077] In the embodiments of the present invention, it can be understood that the wetland area has a corresponding ecological carrying capacity for different preset ecological restoration measures. For example, the reduction of water has a lower impact on shrub swamps, but a higher impact on aquatic vegetation swamps. Therefore, it is necessary to analyze the carrying capacity of wetland areas of different wetland types for preset ecological restoration measures.

[0078] Further, in some embodiments of the present invention, in combination Figure 4 Conduct a specific analysis. Figure 4 This is a flow chart of a method for obtaining ecological carrying capacity provided by an embodiment of the present invention. Figure 4 As shown:

[0079] S401: Determine the stabilization moment of ecological stability at the sampling point based on the numerical distribution of the impact of restoration measures at the same sampling point at all sampling times.

[0080] Among them, since all wetland areas are in the process of changing to stabilizing after the implementation of the preset ecological restoration measures, in this process, the moment of gradual change to stabilization can be determined as the stabilization moment.

[0081] Furthermore, in some embodiments of the present invention, a method for obtaining a stable moment of ecological stability of a sampling point includes: sorting the impact degrees of restoration measures of the same sampling point at all sampling moments based on time sequence to obtain an impact time series; taking any moment as a division moment, and dividing the impact time series based on different division moments to obtain two subsequences; determining the degree variance and degree range of the impact degrees of all restoration measures in each subsequence; determining a stability factor of the subsequence based on the degree variance and degree range, wherein the degree variance and degree range are negatively correlated with the stability factor, and the value of the stability factor is a normalized value; traversing all sampling moments in time sequence as division moments, and when the stability factor of the subsequent subsequence in time sequence is greater than a preset stability threshold, stopping the traversal, and taking the corresponding division moment as the stable moment of the sampling point.

[0082] Taking the t-th sampling moment as a specific example, the influence degree of the repair measures at all moments before the t-th sampling moment (that is, the first moment to the t-1th moment) is arranged in time sequence as a subsequence, which is called the first subsequence in the embodiment of the present invention; the influence degree of the repair measures at all moments after the t-th sampling moment (that is, the t-th moment to the current moment) is arranged in time sequence as a subsequence, which is called the second subsequence in the embodiment of the present invention. It can be understood that by calculating the stability factors of the first subsequence and the second subsequence, stability analysis is achieved.

[0083] Among them, the degree variance of the impact of the repair measures is the variance value of the impact of all the repair measures in the corresponding subsequence, and the degree range represents the range value of the impact of all the repair measures in the corresponding subsequence.

[0084] In an unstable situation, the larger the degree variance and degree range corresponding to the subsequence are, that is, the degree variance and degree range are negatively correlated with the stability factor. The value of the stability factor is a normalized value, then the product of the degree variance and the degree range can be calculated, and the inverse of the product can be found, and the maximum and minimum values ​​are normalized to obtain the stability factor.

[0085] Since the second subsequence is in a stable stage after being in a stable stage, when the stability factor of the second subsequence is greater than a preset stability threshold, the traversal is stopped and the corresponding division time is used as the stable time of the sampling point.

[0086] The preset stability threshold is the threshold value of the stability factor. The preset stability threshold in the embodiment of the present invention can be specifically, for example, 0.9, and there is no limitation on this. That is, from the first moment to the t-1th moment, the corresponding stability factor of the subsequent subsequence is less than or equal to 0.9, until the tth moment, the corresponding stability factor of the subsequent subsequence is greater than 0.9, then the tth moment is regarded as the stable moment, indicating that the ecological change of the sampling point at the tth moment tends to be stable.

[0087] S402: determining a point load influence factor of a sampling point according to a time sequence position of the stable moment in all sampling moments, wherein the closer the stable moment is to the initial moment in the time sequence, the greater the value of the point load influence factor.

[0088] In an embodiment of the present invention, the closer the stabilization moment is to the initial moment when the preset ecological restoration measures begin, the stronger the environmental carrying capacity of the corresponding sampling point is. In an embodiment of the present invention, the initial moment can be taken as the first moment, and the subsequent sampling moments can be numbered with positive integers. The smaller the number corresponding to the stabilization moment is, the larger the value of the point carrying capacity influence factor is.

[0089] That is, the inverse of the sequence corresponding to the stable moment can be taken as the point load influence factor.

[0090] S403: Obtain the ecological carrying capacity of the wetland area according to the point carrying capacity influencing factors of all sampling points in the same wetland area.

[0091] In the embodiment of the present invention, the point bearing impact factors of all sampling points in the same wetland area are specifically analyzed. Since each sampling point in the wetland area represents part of the characteristics of the corresponding wetland area, the embodiment of the present invention can calculate the mean of the point bearing impact factors of all sampling points in the same wetland area as the ecological carrying degree of the wetland area.

[0092] Of course, in other embodiments of the present invention, the distance from the sampling point to the river, or the closest distance to the preset ecological restoration measures, can also be determined, and the distance can be used as a weight to achieve weighted addition of the point carrying capacity influencing factors. That is, the farther the distance, the smaller the weight, and the overall ecological carrying capacity is calculated, and there is no restriction on this.

[0093] S104: Other wetland areas connected to any wetland area are regarded as neighboring areas. The confidence level of the ecological restoration effect of the wetland area is determined based on the changing characteristics of the impact of restoration measures at sampling points in the wetland area and its neighboring areas, as well as the ecological carrying capacity of the wetland area.

[0094] Among them, the neighborhood area, that is, the adjacent area, for example, when the wetland area A is adjacent to the wetland areas B and C, the wetland areas B and C are regarded as the neighborhood area of ​​the wetland area A.

[0095] It is understandable that since the wetland area is not a strict regional division, each corresponding wetland area will have multiple directly adjacent wetland areas, and will have mutual influence. Therefore, the embodiment of the present invention combines the ecological carrying capacity of the wetland area and the impact of the restoration measures on the sampling points in the wetland area and its neighboring areas to conduct a specific analysis of the mutually influencing wetland areas.

[0096] Furthermore, in some embodiments of the present invention, the confidence in the ecological restoration effect of a wetland area includes: determining any wetland area as a target area, and determining the regional impact index and the neighborhood impact index of the target area according to the degree of influence of restoration measures at all sampling points in the target area and all neighboring areas of the target area at all sampling times; using the difference between the regional impact index and the neighborhood impact index as the restoration effect influence coefficient of the target area; determining the ecological restoration effect confidence of the target area according to the restoration effect influence coefficient and the ecological carrying capacity of the target area, wherein the ecological carrying capacity is positively correlated with the ecological restoration effect confidence, the restoration effect influence coefficient is negatively correlated with the ecological restoration effect confidence, and the value of the ecological restoration effect confidence is a normalized value.

[0097] Among them, any wetland area is selected as the target area, and the average impact of the restoration measures of all sampling points in the target area at all sampling times can be used as the regional impact index of the target area; the average impact of the restoration measures of all sampling points in all neighborhood areas of the target area at all sampling times can be used as the neighborhood impact index of the target area.

[0098] That is, the regional influence index represents the influence degree of the target area at all sampling times, while the neighborhood influence index is the influence degree obtained by integrating all neighborhood areas.

[0099] In an embodiment of the present invention, the restoration effect influence coefficient of the target area can be obtained by calculating the absolute value of the difference between the regional impact index and the neighborhood impact index, that is, the restoration effect is the difference after excluding the influence of the neighborhood area. Due to the connection relationship between the water bodies between adjacent wetland areas, the stages of the change trend of their detection data should be consistent. The larger the restoration effect influence coefficient, the greater the abnormality of the restoration effect of the target area itself.

[0100] Therefore, according to the restoration effect influence coefficient and the ecological carrying capacity of the target area, the confidence level of the ecological restoration effect of the target area is determined. The confidence level of the ecological restoration effect indicates the stability of the corresponding sampling point. That is, the greater the ecological carrying capacity, the easier it is for the corresponding wetland area to enter a stable state and the greater the stability. The larger the restoration effect influence coefficient, the greater the abnormality of the restoration effect of the target area itself, and the more abnormal the corresponding data is, the lower the stability. Therefore, the ratio of the ecological carrying capacity to the restoration effect influence coefficient can be calculated, and the maximum and minimum values ​​can be normalized to obtain the confidence level of the ecological restoration effect.

[0101] S105: According to the confidence of the ecological restoration effect of each wetland area, the sampling data of the sampling points in the wetland area at the current moment are adjusted to obtain confidence data; the restoration effect evaluation of the preset ecological restoration measures is implemented according to the confidence data of all sampling points to obtain the evaluation results.

[0102] The higher the confidence level of the ecological restoration effect in the embodiment of the present invention, the greater the possibility that the corresponding sampling point in the corresponding wetland area is in a stable stage, and the more reliable the result of evaluating the effect of ecological restoration implementation using its data is. Therefore, the sampling data of each sampling point at the current moment can be adjusted based on this to obtain confidence data.

[0103] In an embodiment of the present invention, within the time range from the initial moment to the current moment, the confidence in the ecological restoration effect of the wetland area corresponding to any sampling point is used as the weight of the sampling data of the sampling point at the current moment, and the sampling data is multiplied to obtain confidence data. That is to say, the product of the confidence in the ecological restoration effect and the sampling data is calculated as the confidence data. Thus, each sampling point is adjusted to obtain the confidence data of each sampling point at the current moment.

[0104] The confidence data is adjusted to combine the time series changes and changes in different wetland areas to obtain the data used for evaluation. The confidence data can enhance the weight of stable state data, thereby avoiding the impact of the evaluation results in a changing state and enhancing the overall evaluation effect.

[0105] Furthermore, in some embodiments of the present invention, the restoration effect evaluation of preset ecological restoration measures is implemented based on the confidence data of all sampling points to obtain an evaluation result, including: determining an evaluation index based on the degree of discreteness of the confidence data of all sampling points at the current moment, wherein the evaluation index is negatively correlated with the degree of discreteness; and using the evaluation index as the evaluation result.

[0106] Specifically, the variance can be used as the degree of discreteness to calculate the variance of the confidence data of all sampling points at the current moment, and the reciprocal of the variance is calculated. The reciprocal is normalized by the maximum and minimum values ​​to obtain an evaluation index, and the evaluation index is directly used as the evaluation result.

[0107] Of course, in other embodiments of the present invention, the mean of the confidence data of all sampling points may also be calculated as an evaluation result of the status analysis of the overall wetland ecology, and there is no limitation to this.

[0108] The evaluation results in the embodiments of the present invention are mainly used to characterize the status of all wetland areas at the current moment. Further, the subsequent wetland restoration measures can be adjusted based on the evaluation results. Subsequent wetland restoration measures can be adjusted as follows: further optimize the buffer zone, such as increasing vegetation density, adjusting the layout of the buffer zone, etc., to improve its ability to intercept and purify pollutants. Strengthen the management and maintenance of aquatic plants to ensure that they can continue to play a good ecological function, etc., without restriction.

[0109] The embodiment of the present invention aims to conduct a unified analysis of wetland areas with complex distribution and certain differences in status, by periodically obtaining sampling data of different sampling points in different wetland areas in the same watershed after experiencing preset ecological restoration measures; the degree of influence of restoration measures on sampling points; the numerical values ​​of the degree of influence of restoration measures of all sampling points in the same wetland area can be combined to obtain the ecological carrying degree of the wetland area, and the ecological carrying degree characterizes the impact of the corresponding wetland area on the ecological restoration measures; according to the changing characteristics of the degree of influence of restoration measures of sampling points in the wetland area and its neighboring areas, and the ecological carrying degree of the wetland area, the confidence of the ecological restoration effect of the wetland area is determined, and the confidence of the ecological restoration effect can characterize the reliability characteristics of the wetland area itself under ecological restoration, and the wetland area with stronger reliability characteristics has a stronger ecological carrying capacity, so that the sampling data of the sampling points in the wetland area can be adjusted according to the confidence of the ecological restoration effect of each wetland area to obtain confidence data; the restoration effect evaluation of the preset ecological restoration measures is realized according to the confidence data of all sampling points to obtain the evaluation result. The present invention can combine the data feedback of preset ecological restoration measures in different wetland areas to obtain more accurate and effective confidence data, so that when the restoration effect evaluation is realized according to the confidence data, the influence of ecological carrying capacity and the mutual influence among multiple wetland areas can be avoided, thereby effectively improving the reliability of the evaluation and enhancing the accuracy of the evaluation results.

[0110] The present invention also provides an intelligent evaluation system for the implementation effect of ecological restoration of river, lake and wetland in the basin, see Figure 5 , Figure 5This is a structural diagram of a system for intelligently evaluating the implementation effect of ecological restoration of river, lake and wetland in a river basin provided by an embodiment of the present invention. The system 600 includes a memory 601, a processor 602, and a computer program 603 stored in the memory 601 and executable on the processor 602. When the processor 602 executes the computer program 603, the steps of the aforementioned method for intelligently evaluating the implementation effect of ecological restoration of river, lake and wetland in a river basin are implemented.

[0111] This embodiment also provides a computer-readable storage medium, which stores computer program code. When the computer program code runs on a computer, the computer executes the above-mentioned related method steps to implement an intelligent evaluation method for the implementation effect of ecological restoration of river, lake and wetland in a river basin provided by the above embodiment.

[0112] This embodiment also provides a computer program product. When the computer program product runs on a computer, it enables the computer to execute the above-mentioned related steps to realize an intelligent evaluation method for the implementation effect of ecological restoration of river, lake and wetland in a river basin provided by the above embodiment.

[0113] Among them, the system, computer-readable storage medium or computer program product provided in this embodiment is used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method provided above, and will not be repeated here.

[0114] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0115] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. An intelligent evaluation method for the implementation effect of ecological restoration of river, lake and wetland in a river basin, characterized in that: In a wetland area with different wetland types distributed under the same watershed, the method comprises: After the preset ecological restoration measures are taken, sampling data from different sampling points in different wetland areas in the same watershed are periodically obtained; According to the difference of sampling data at different sampling moments at the same sampling point, determine the data change range of the sampling point at each sampling moment; according to the data change range of different sampling points at the same sampling moment, determine the impact of the repair measures of any sampling point at any sampling moment; Determine the ecological carrying capacity of the wetland area based on the numerical distribution of the impact of restoration measures at all sampling points in the same wetland area at all sampling times; The other wetland areas connected to any wetland area are regarded as neighboring areas. The confidence level of the ecological restoration effect of the wetland area is determined based on the changing characteristics of the impact of the restoration measures at the sampling points in the wetland area and its neighboring areas, as well as the ecological carrying capacity of the wetland area. According to the confidence of the ecological restoration effect of each wetland area, the sampling data of the sampling points in the wetland area at the current moment are adjusted to obtain confidence data; the restoration effect evaluation of the preset ecological restoration measures is realized according to the confidence data of all sampling points to obtain the evaluation results; The method for obtaining the ecological carrying capacity includes: According to the numerical distribution of the impact of restoration measures at the same sampling point at all sampling moments, the stable moment of ecological stability at the sampling point is determined; Determine the point load influence factor of the sampling point according to the time sequence position of the stable moment in all sampling moments, wherein the closer the stable moment is to the initial moment in the time sequence, the greater the value of the point load influence factor; According to the point carrying impact factors of all sampling points in the same wetland area, the ecological carrying degree of the wetland area is obtained; The method for obtaining the stable moment of ecological stability of the sampling point includes: Based on the time series, the impact degree of the repair measures of the same sampling point at all sampling moments is sorted to obtain the impact time series sequence; Taking any moment as a division moment, dividing the impact time series based on different division moments respectively to obtain two subsequences; Determine the degree variance and degree range of the impact of all repair measures in each subsequence; determine the stability factor of the subsequence based on the degree variance and degree range, wherein the degree variance and degree range are negatively correlated with the stability factor, and the value of the stability factor is a normalized value; Traverse all sampling moments in time sequence as the division moment. When the stability factor of the next subsequence in time sequence is greater than the preset stability threshold, stop traversing and take the corresponding division moment as the stable moment of the sampling point. The confidence level of the ecological restoration effect of the wetland area includes: Determine any wetland area as a target area, and determine the regional impact index and neighborhood impact index of the target area according to the impact degree of the restoration measures of all sampling points in the target area and all neighborhood areas of the target area at all sampling times; The difference between the regional impact index and the neighborhood impact index is used as the restoration effect impact coefficient of the target area; The ecological restoration effect confidence of the target area is determined according to the restoration effect influence coefficient and the ecological carrying capacity of the target area, wherein the ecological carrying capacity is positively correlated with the ecological restoration effect confidence, the restoration effect influence coefficient is negatively correlated with the ecological restoration effect confidence, and the ecological restoration effect confidence is a normalized value; The method for obtaining the regional impact index and the neighborhood impact index of the target area includes: The average of the impact of the restoration measures at all sampling points in the target area at all sampling times is used as the regional impact index of the target area; The average of the impact levels of the repair measures of all sampling points in all neighborhood areas of the target area at all sampling times is taken as the neighborhood impact index of the target area.

2. The intelligent evaluation method for implementing ecological restoration of river, lake and wetland in a river basin as claimed in claim 1 is characterized in that: The method for obtaining the data variation range includes: At the same sampling point, the absolute value of the difference between the sampled data at any sampling moment and the previous sampling moment is determined to obtain the data change amplitude at the corresponding sampling moment.

3. The intelligent evaluation method for implementing ecological restoration of river, lake and wetland in a river basin as claimed in claim 1 is characterized in that: The method for obtaining the impact degree of the remediation measures includes: At the same sampling time, the overall measure influencing factor is determined based on the numerical distribution of the data change amplitude of all sampling points; According to the difference between the normalized value of the data change amplitude of any sampling point and the overall measure influencing factor, the impact degree of the repair measures at the sampling point at the corresponding sampling time is determined.

4. The intelligent evaluation method for implementing ecological restoration of river, lake and wetland in a river basin as claimed in claim 3 is characterized in that: The overall measure influencing factors are determined based on the numerical distribution of the data change amplitudes of all sampling points, including: The overall measure influence factor is determined according to the numerical dispersion and numerical mean of the data change amplitude of all sampling points, wherein the numerical dispersion is negatively correlated with the overall measure influence factor, the numerical mean is positively correlated with the overall measure influence factor, and the value of the overall measure influence factor is a normalized value.

5. The intelligent evaluation method for implementing ecological restoration of river, lake and wetland in a river basin as claimed in claim 1 is characterized in that: According to the confidence level of the ecological restoration effect of each wetland area, the sampling data of the sampling points in the wetland area at the current moment are adjusted to obtain confidence data, including: Within the time range from the initial moment to the current moment, the confidence of the ecological restoration effect of the wetland area corresponding to any sampling point is used as the weight of the sampling data of the sampling point at the current moment, and the sampling data are multiplied to obtain confidence data.

6. The intelligent evaluation method for implementing ecological restoration of river, lake and wetland in a river basin as claimed in claim 1 is characterized in that: The restoration effect evaluation of the preset ecological restoration measures is realized according to the confidence data of all sampling points, and the evaluation results are obtained, including: Determine an evaluation index according to the discrete degree of confidence data of all sampling points at the current moment, wherein the evaluation index is negatively correlated with the discrete degree; The evaluation index is used as the evaluation result.

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