River and lake recovery method based on ecological system dynamic change process and time lag effect

Abstract

The invention discloses a river and lake recovery method based on an ecological system dynamic change process and a time lag effect. The method comprises the following steps: step 1, determining a river and lake resuscitation target; 2, determining response delay time of the ecological system; and 3, determining a river and lake resuscitation scheme. The river and lake recovery method based on the ecological system dynamic change process and the time lag effect is provided for the first time, recovery targets of low, medium and high levels are determined by considering the historical change process and the current situation of the ecological system condition, and the scientificity and reliability of river and lake recovery are improved; the time that the response of the ecosystem lags behind the driving pressure is scientifically judged through the hysteresis correlation between the ecosystem condition and the external driving pressure; according to the established relation between the ecological system condition based on the time-delay effect and the driving pressure, the regulation and control strength of the driving pressure under different levels of recovery targets is provided, whether an artificial or natural recovery means is adopted is determined, the success rate of river and lake recovery is increased, and excessive recovery is avoided.

Description

Technical Field

[0001] The present invention relates to the field of river and lake ecological protection and restoration, and more specifically to a river and lake recovery method based on the dynamic change process of the ecosystem and the time lag effect. Background Art

[0002] The speed of river and lake ecosystem recovery usually lags significantly behind the speed of ecological damage. Ecological recovery often requires a long process and has a significant time lag effect, especially the recovery of biodiversity, which may even lag behind the implementation of ecological protection measures for more than ten years or even longer. The existing river and lake recovery methods have the following problems: First, the formulation of river and lake recovery goals often ignores the historical process of dynamic changes in ecosystems. They are usually designed based on static problems at a certain stage, which is out of touch with reality, resulting in goals that are too high to be achieved or too low to restore the normal functions of ecosystems. Second, the existing river and lake recovery plan determination method does not take into account the time lag of ecosystem response, which often leads to unclear correlation between ecosystem changes and external driving pressures. The formulation of ecological recovery plans lacks scientific basis, resulting in insufficient ecological recovery efforts and difficulty in achieving ecological recovery goals, or insufficient consideration of the self-repair ability of the ecosystem, resulting in excessive artificial restoration in pursuit of short-term results, which is labor-consuming and time-consuming. Therefore, it is urgent to study a river and lake recovery method that improves the accuracy of ecological regulation and is highly operational to guide river and lake recovery actions. Summary of the invention

[0003] The purpose of the present invention is to provide a river and lake recovery method based on the dynamic change process and time lag effect of the ecosystem, so as to improve the accuracy and operability of river and lake ecological recovery.

[0004] In order to achieve the above-mentioned purpose, the technical scheme of the present invention is: a river and lake recovery method based on the dynamic change process of the ecosystem and the time lag effect, by carrying out the change rate of the river and lake ecosystem status and the external driving pressure factor over the years and the hysteresis correlation analysis between the two, overcoming the influence of the ecosystem time lag effect, determining the river and lake recovery target, and proposing a corresponding recovery plan; The specific method includes the following steps: Step 1: Determine river and lake recovery goals; Obtain a long-term sequence of river and lake ecosystem conditions and external driving pressure indexes, establish historical change curves of ecosystem conditions and external driving pressure indexes, and determine low, medium, and high levels of river and lake recovery targets by considering the historical changes in ecosystem conditions and the current ecological conditions; Step 2: Determine the ecosystem response lag time; By conducting a hysteresis correlation analysis between the ecosystem status index and the external driving pressure index, the lag time of ecosystem response was determined; Step 3: Determine the river and lake recovery plan; By establishing the relationship between the state of the ecosystem and external driving pressure based on the time lag of ecosystem response, the regulation intensity and regulation plan of external driving pressure under low, medium and high levels of river and lake recovery goals are determined.

[0005] In the above technical solution, in step one, the goal of river and lake recovery is determined, which specifically includes the following steps: S11: Obtain the river and lake ecosystem status and external driving pressure index for more than n years; n≥20; S12: Standardize the selected river and lake ecosystem status index values ​​and external driving pressure index values; the standardization formula is: inds i =(ind i -ind min ) / (ind max -ind min ); dris i =(dri i -dri min ) / (dri max -dri min ); Among them, i is the year, ind i is the ecosystem status indicator value in the i-th year, inds i is the standardized value of the ecosystem status indicator in the i-th year, ind min is the minimum value in the ecosystem status indicator series, ind max is the maximum value in the ecosystem status indicator series, dri i is the external driving pressure index value in the i-th year, dris i is the standardized value of the external driving pressure index in the i-th year, dri min is the minimum value in the external driving pressure index series, dri max It is the maximum value in the external driving pressure index series; S13: Arrange the river and lake ecosystem status index values ​​of n years (n ≥ 20) in ascending order, and calculate the empirical frequency corresponding to each indicator according to the formula; The empirical frequency p of the mth term m The calculation formula is as follows: F m =m / (n+1)×100%, where m=1,2,3,…,n; Among them, n is the statistical number of river and lake ecosystem conditions, m is the sequence number of each ecosystem condition data from small to large, F m is the frequency of occurrence of the river and lake ecosystem status corresponding to the mth item in the ranking in the data series; Fm The larger the value, the worse the river and lake ecosystem condition. m The smaller it is, the better the river and lake ecosystem is. The present invention determines the ecological recovery target through empirical frequency and theoretical frequency curves; S14: Fit the theoretical frequency curve based on the river and lake ecological status index corresponding to different empirical frequencies; the theoretical frequency formula is: S=af 2 +bf+c; Among them, S is the ecosystem status index, f is the theoretical frequency corresponding to different ecosystem status indices, and a, b, and c are related parameters; If the average empirical frequency of ecological integrity in the past three years is within the range of 75% to 100%, the ecological integrity corresponding to the frequencies of 70%, 50% and 30% are calculated by the theoretical frequency formula as the low, medium and high targets of ecological recovery respectively; the frequency corresponding to the low target ecological integrity is (75%-70%) to (100%-70%) higher than the current situation, that is, 5 to 30% higher; the frequency corresponding to the medium target ecological integrity is (75%-50%) to (100%-50%) higher than the current situation, that is, 25% to 50% higher; the frequency corresponding to the high target ecological integrity is (75%-30%) to (100%-30%) higher than the current situation, that is, 45% to 70% higher; If the average empirical frequency of ecological integrity in the past three years is within the range of 55% to 75%, the ecological integrity corresponding to the frequencies of 50%, 35% and 20% are calculated through the theoretical frequency formula as the low, medium and high targets of ecological recovery respectively; the frequency corresponding to the low target ecological integrity is (55%-50%) to (75%-50%) higher than the current situation, that is, 5 to 25%, the frequency corresponding to the medium target ecological integrity is (55%-35%) to (75%-35%) higher than the current situation, that is, 20% to 40%, and the frequency corresponding to the high target ecological integrity is (55%-20%) to (75%-20%) higher than the current situation, that is, 35% to 55%; If the average empirical frequency of ecological integrity in the past three years is within the range of 35% to 55%, the ecological integrity corresponding to frequencies of 30%, 20% and 10% are calculated by the theoretical frequency formula as the low, medium and high targets of ecological recovery respectively; the frequency corresponding to the low target ecological integrity is higher than the current situation by (35%-30%)~(55%-30%), that is, 5~25%, the frequency corresponding to the medium target ecological integrity is higher than the current situation by (35%-20%)~(55%-20%), that is, 15%~30%, and the frequency corresponding to the high target ecological integrity is higher than the current situation by (35%-10%)~(55%-10%), that is, 25%~45%; the present invention adopts the above method to improve the accuracy and operability of determining the recovery targets.

[0006] In the above technical solution, in step S11, the status of river and lake ecosystems can be represented by ecosystem health index, biodiversity index, ecological integrity index, vegetation coverage, etc.; The external driving pressure index can be selected from the amount of pollutants entering the river, the human interference index, the proportion of building land area, the proportion of downstream flow, etc., or a calculated comprehensive driving pressure index. The method of the present invention can use a single indicator as the external driving pressure index, or can use the comprehensive result of multiple indicators as the external driving pressure index. For example, the amount of pollutants entering the river can be used as the external driving pressure index, or the amount of pollutants entering the river and the human interference index can be given different weights to calculate a comprehensive driving pressure index.

[0007] In the above technical solution, in step S11, the ecosystem status data and driving pressure data of each river and lake in the study area obtained can be annual average data, seasonal data or monthly data, and the annual series should be greater than or equal to 20 years; the long sequence data of the present invention can more objectively reflect the changing process of the ecosystem and improve the reliability of lag analysis.

[0008] In the above technical solution, in step 2, determining the ecosystem response lag time specifically includes the following steps: S21: Calculate the annual change rate of the standardized river and lake ecosystem status index and external driving pressure index in S12; f ind '(i)=(Fs i+1 -Fs i ) / (n i+1 -n i ); Among them, f ind (i)' is the rate of change of the river and lake ecosystem status index or external driving pressure index in the i-th year, n i is the year of the ith year, n i+1 is the year of the i+1th year, Fs i+1 Fs is the standardized value of the river and lake ecosystem status index or external driving pressure index in the i+1th year, i is the standardized value of the river and lake ecosystem status index or driving pressure index in the i-th year; S22: The year corresponding to the first value of the ecosystem status index that is greater than zero for three consecutive years is set as s1, and the year corresponding to the third value is set as s2. The year corresponding to the first value of the external driving pressure index that is less than zero for three consecutive years is set as d1, and the year corresponding to the third value is set as d2. The time range of the ecosystem status index change lagging behind the external driving pressure index change is s1-d2 years to s2-d1 years; improve the accuracy of determining the lag time of ecosystem response; S23: In the range of s1-d2 to s2-d1, the correlation coefficient between the ecosystem status index and the driving pressure index is calculated according to the lag time of each ecosystem status index change to the external driving pressure index of s1-d2 years, s1-d2+1 years, s1-d2+2 years, and so on, s2-d1 years. That is, the correlation coefficient between the ecosystem status index and the driving pressure index is calculated every 1 year. The largest correlation coefficient corresponds to the lag year number y z It is the number of years that ecosystem changes lag behind external driving pressures, expressed as y z Indicates that y z It is an integer between s1-d2 and s2-d1; ; Where n is the number, S is the ecosystem status index, D is the driving pressure index, r is the correlation coefficient between S and D, i is the number, is the average value of the ecosystem condition index, is the average value of the driving pressure index.

[0009] In the above technical solution, in step S21, when the rate of change of the ecosystem status index is greater than zero, it indicates that the ecosystem status has improved; when the rate of change of the ecosystem status index is less than zero, it indicates that the ecosystem status has declined; when the rate of change of the ecosystem status index is equal to zero, it indicates that the ecosystem status remains unchanged; When the rate of change of the driving pressure index is greater than zero, it indicates that the external driving pressure increases; when the rate of change of the driving pressure index is less than zero, it indicates that the external driving pressure decreases; when the rate of change of the driving pressure index is equal to zero, it indicates that the external driving pressure remains unchanged; the present invention adopts the above method to analyze the historical change process of the ecosystem status index to determine the ecosystem response lag time; this step S21 is linked to step S14, if the rate of change of the ecological status index is greater than 0 for three consecutive years, it indicates that the ecosystem has been in an improving state for three consecutive years, then it can be considered that the ecosystem has gradually improved under the condition of reduced pressure, and the ecosystem has begun to respond to the reduction of driving pressure; similarly, if the rate of change of the external driving pressure index is less than 0 for three consecutive years, then it can be considered that the external driving pressure is decreasing; if the reduction of the external driving pressure and the improvement of the ecosystem are synchronized, it indicates that the response of the ecosystem has no lag; if the improvement of the ecosystem lags behind the reduction of the external driving pressure, it indicates that the response of the ecosystem is lagging, and then the response lag time of the ecosystem is determined.

[0010] In the above technical solution, in step three, a river and lake recovery plan is determined, which specifically includes the following steps: S31: The ecosystem status index in step S2 lags behind the external driving pressure index y z The year is fitted with the external driving pressure and the fitting formula is obtained: D=aS2 +bS+c; Among them, D is the external driving pressure index, S is the ecosystem status index, and a, b, and c are related parameters; S32: According to the fitting formula, the driving pressure index values ​​d corresponding to the low, medium and high restoration targets of the ecosystem status index are calculated respectively. low d mid d high ; S33: The average value of the external driving pressure index in the past three years is d avg , d low d mid d high With d avg The difference is the external driving pressure value that needs to be regulated when the ecosystem status is restored to low, medium and high targets respectively; the external driving pressure values ​​that need to be regulated for low, medium and high targets here correspond to the low, medium and high targets calculated in step S14, and the external driving pressure values ​​corresponding to different recovery targets can be obtained through the fitting formula of S31; In step S33, d low d mid d high With d avg The difference is the external driving pressure index value that needs to be reduced in ecological recovery; d avg With d low d mid d high If the difference is less than or equal to zero, it means that there is no need to carry out artificially assisted ecological restoration projects. It only needs to maintain the current state and carry out natural restoration for a certain period of time to achieve the goal of river and lake recovery. If d avg With d low d mid d high If the difference is greater than zero, it means that artificial restoration measures are needed to cooperate with natural restoration to achieve the goal of river and lake recovery; among them, artificial restoration measures include pollution control, emission reduction, afforestation and other artificial measures; natural restoration is to maintain the status quo without human intervention, and use the self-repair ability of the ecosystem to slowly repair itself.

[0011] The present invention has the following advantages: (1) The present invention determines low, medium and high river and lake restoration targets by considering the historical dynamic changes in the status of the ecosystem and the ecological status of the current conditions, thereby improving the accuracy and achievability of determining river and lake restoration targets. It solves the problem that the formulation of river and lake restoration targets in existing river and lake restoration methods ignores the historical process of dynamic changes in the ecosystem, is usually designed based on static problems at a certain stage, and is out of touch with reality, resulting in the setting of targets that are too high and cannot be achieved, or the setting of targets that are too low and cannot restore the normal functions of the ecosystem; (2) By considering the time lag of ecosystem response, the present invention can more accurately establish the correlation between ecosystem status changes and external driving pressure, and calculate the pressure index considering the hysteresis of ecosystem response. By comparing the pressure index value considering the hysteresis with the pressure index value under the current conditions, it can be determined whether auxiliary artificial restoration measures are needed, thereby improving the accuracy and rationality of the ecological recovery plan and the accuracy of ecological regulation using the river and lake recovery plan of the present invention. It solves the problem that the relationship between ecology-hydrology or ecology-water quality or ecology-pressure determined by the existing technical means does not consider the time lag of ecosystem changes, resulting in the relationship between the former and the latter being unclear or the relationship trend being wrong, and the correlation between the ecosystem and the driving pressure cannot be accurately established. There is no significant correlation between the constructed ecosystem status index and the driving pressure index, which leads to low accuracy of ecological regulation using the existing river and lake recovery plan, and it is impossible to accurately determine whether to use artificial restoration means or natural restoration means to carry out river and lake recovery, resulting in a low success rate of river and lake recovery or prone to excessive restoration and consumption of a large amount of financial, material and human resources. (3) The present invention establishes a relationship between the state of an ecosystem and driving pressure based on the time lag of ecosystem response, proposes the intensity of regulation of driving pressure under low, medium and high levels of river and lake recovery goals, and accurately determines whether to adopt artificial restoration or natural restoration, thereby improving the success rate of river and lake recovery, avoiding excessive artificial restoration, and saving financial, material and human resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is a 30-year change curve of the ecosystem health index value and the driving pressure index value in Example 1 of the present invention; Figure 2 is the theoretical frequency curve of the ecosystem health index of Example 1 of the present invention; Figure 3 The change rates of the ecosystem health index and the driving pressure index in Example 1 of the present invention; Figure 4 The ecosystem health index and driving pressure index fitting curve of Example 1 of the present invention; Figure 5 The vegetation coverage index and the driving pressure index fitting curve of Example 3 of the present invention; Figure 6 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0013] The following is a detailed description of the implementation of the present invention in conjunction with the accompanying drawings, but they do not constitute a limitation of the present invention and are only given as examples. At the same time, the advantages of the present invention are made clearer and easier to understand through the description.

[0014] The present invention proposes for the first time a river and lake recovery method based on the dynamic change process and time lag effect of the ecosystem. Through step one, the historical change process of the ecosystem status and the ecological status of the current conditions are considered to determine the river and lake recovery targets of different levels, namely low, medium and high, so as to improve the scientificity and reliability of river and lake recovery; through the hysteresis correlation analysis between the river and lake ecosystem status and the external driving pressure factors, the time when the ecosystem response lags behind the external driving pressure is accurately determined; through the relationship between the ecosystem status and the driving pressure based on the time lag of the ecosystem response established in step three, the regulation intensity of the driving pressure under the river and lake recovery targets of different levels, namely low, medium and high, is proposed, and whether to adopt artificial restoration or natural restoration means is accurately determined, so as to improve the success rate of river and lake recovery and avoid excessive artificial restoration; The steps performed in sequence in the present invention are interconnected to achieve the accurate determination of river and lake recovery targets and improve the accuracy of ecological regulation using the river and lake recovery plan of the present invention. The present invention establishes the ecosystem change process and the external driving pressure change process through step one, provides basic data for step two, and provides a recovery target for step three; determines the ecosystem response lag time through step two, and together with step one, provides an accurate river and lake recovery plan for step three and provides a precise target for ecological regulation; determines the ecosystem response lag time through step two, and lags the ecosystem status index behind the driving pressure index y in step three z In 2011, the fitting analysis between the two and the fitting formula provided y z Year.

[0015] See attached Figure 1 It can be seen that the river and lake recovery method based on the dynamic change process of the ecosystem and the time lag effect includes the following steps: Step 1: Determine river and lake recovery goals; S11: Obtain the river and lake ecosystem status and driving pressure index for more than n (n≥20) years. The river and lake ecosystem status can be represented by the ecosystem health index, biodiversity index, ecological integrity index, vegetation coverage rate, etc. The driving pressure index can be selected from the amount of pollutants entering the river, human interference index, proportion of building land area, proportion of downstream flow, etc., or it can be a calculated comprehensive driving pressure index. The obtained data on the ecosystem status and driving pressure of each river and lake in the study area can be annual average data, seasonal data for each year, or monthly data for each year. The present invention analyzes the long-term historical change process of the ecosystem status, analyzes the empirical frequency of the ecosystem status under the long sequence conditions, obtains the probability of different conditions occurring in the long-term evolution process, and combines the ecosystem status under the current conditions to determine the stage it is in, and then formulates river and lake recovery targets at different levels of high, medium and low, fully considering the actual situation of the river and lake ecosystem, and ensuring the accuracy and accessibility of the river and lake recovery targets; It solves the problem that the formulation of river and lake recovery targets in the prior art ignores the historical process of dynamic changes in the ecosystem, is usually designed based on static problems at a certain stage, and is divorced from reality, resulting in the problem that the river and lake recovery targets are set too high and cannot be achieved or the river and lake recovery targets are set too low and cannot restore the normal function of the ecosystem; S12: Standardize the selected river and lake ecosystem status index values ​​and driving pressure index values; inds i =(ind i -ind min ) / (ind max -ind min ); dris i =(dri i -dri min ) / (dri max -dri min ); Among them, i is the year, ind i is the ecosystem status indicator value in the i-th year, inds i is the standardized value of the ecosystem status indicator in the i-th year, ind min is the minimum value in the ecosystem status indicator series, ind max is the maximum value in the ecosystem status indicator series, dri i is the driving pressure index value in the i-th year, dris i is the standardized value of the driving pressure index in the i-th year, dri min is the minimum value in the driving pressure index series, dri max It is the maximum value in the driving pressure index series; S13: Arrange the river and lake ecosystem status index values ​​of n years (n ≥ 20) in ascending order, and calculate the empirical frequency corresponding to each indicator according to the formula; The empirical frequency p of the mth term m The calculation formula is as follows: F m =m / (n+1)×100%, where m=1, 2, 3, ..., n; Among them, n is the statistical number of river and lake ecosystem conditions, m is the sequence number of each ecosystem condition data from small to large, F m is the frequency of occurrence of the river and lake ecosystem status corresponding to the mth item in the ranking in the data series; S14: Fit the theoretical frequency curve based on the river and lake ecological status index corresponding to different empirical frequencies; If the average empirical frequency of ecological integrity in the past three years is within the range of 75% to 100%, the ecological integrity corresponding to the frequencies of 70%, 50% and 30% will be calculated through the theoretical frequency formula as the low, medium and high targets of ecological recovery respectively; If the average empirical frequency of ecological integrity in the past three years is within the range of 55% to 75%, the corresponding ecological integrity of 50%, 35%, and 20% frequencies is calculated through the theoretical frequency formula as the low, medium, and high targets of ecological recovery, respectively; If the average empirical frequency of ecological integrity in the past three years is within the range of 35% to 55%, the ecological integrity corresponding to the frequencies of 30%, 20% and 10% are calculated by the theoretical frequency formula as the low, medium and high targets of ecological recovery respectively; the present invention determines the ecological recovery target through the dynamic change process of the ecosystem history, combined with the frequency of each stage in its history and the current status in the past three years, thus improving the scientificity and accessibility of the determination of ecological recovery targets for rivers and lakes; Step 2: Determine the ecosystem response lag time; S21: Calculate the annual change rate of the standardized river and lake ecosystem status index and driving pressure index in S12; f ind '(i)=(Fs i+1 -Fs i ) / (n i+1 -n i ); Among them, f ind (i)' is the rate of change of the river-lake ecosystem status index or driving pressure index in the i-th year, n i is the year of the ith year, n i+1 is the year of the i+1th year, Fs i+1 Fs is the standardized value of the river and lake ecosystem status index or driving pressure index in the i+1th year, iis the standardized value of the river and lake ecosystem status index or driving pressure index in the i-th year; If the rate of change of the ecosystem condition index is greater than zero, it means that the ecosystem condition is improving, and if it is less than zero, it means that the ecosystem condition is declining. If the rate of change of the driving pressure index is greater than zero, it means that the external driving pressure is increasing, and if it is less than zero, it means that the external driving pressure is decreasing. S22: The year corresponding to the first value of the ecosystem status index that is greater than zero for three consecutive years is set as s1, and the year corresponding to the third value is set as s2. The year corresponding to the first value of the driving pressure index that is less than zero for three consecutive years is set as d1, and the year corresponding to the third value is set as d2. The time range of the ecosystem status index change lagging behind the driving pressure index change is s1-d2 years to s2-d1 years. S23: In the range of s1-d2 to s2-d1, the correlation coefficient between the ecosystem status index and the driving pressure index is calculated according to the lag time of s1-d2, s1-d2+1, s1-d2+2, and so on, s2-d1. The largest correlation coefficient corresponds to the lag year y. z This is the number of years that ecosystem changes lag behind driving pressures; Step 3: Determine the river and lake recovery plan; S31: Lagged the ecosystem condition index by the driving pressure index y z In 2017, a fitting analysis between the two was conducted and the fitting formula was obtained; S32: According to the fitting formula, the driving pressure index values ​​d corresponding to the low, medium and high restoration targets of the ecosystem status index are calculated respectively. low d mid d high ; S33: The average driving pressure index in the past three years is d avg , d low d mid d high With d avg The difference is the driving pressure value that needs to be regulated to restore the ecosystem to low, medium and high targets, respectively. avg With d low d mid d high If the difference is less than or equal to zero, it means that there is no need to carry out artificial ecological restoration projects. It only needs to maintain the current state and carry out natural restoration for a certain period of time to achieve the goal of river and lake recovery. avg With d low d mid d highIf the difference is greater than zero, it means that artificial restoration measures and natural restoration are needed to achieve the goal of river and lake recovery. avg With d low ,d mid ,d high The difference is the driving pressure index value that needs to be reduced in ecological recovery; The present invention establishes a more accurate fitting relationship between the state of river and lake ecosystems and driving pressure based on ecosystem response through ecosystem response hysteresis analysis (i.e., considering the time lag effect of the ecosystem), and obtains the pressure index considering the hysteresis of the ecosystem response (i.e., the corresponding driving pressure value under different recovery targets). By comparing the pressure index value considering the hysteresis with the pressure index value under the current conditions, it can be determined whether auxiliary artificial restoration measures are needed, thereby greatly improving the accuracy of ecological regulation using the river and lake recovery plan of the present invention; it solves the problem that the existing river and lake recovery plan determination method in the prior art does not consider the time lag of the ecosystem response, which often leads to unclear correlation between ecosystem changes and external driving pressure, lacks scientific basis for the formulation of ecological recovery plans, resulting in insufficient ecological recovery efforts to achieve the ecological recovery goals, or does not fully consider the self-repairing ability of the ecosystem, leading to excessive artificial restoration and waste of financial and material resources in pursuit of short-term results.

[0016] Embodiment: The present invention is now described in detail by applying the present invention to a river and lake restoration example, which also has a guiding role in applying the present invention to other ecological restorations.

[0017] Example 1: A case study on the healthy restoration of a river ecosystem; This embodiment uses the method of the present invention to revitalize rivers and lakes, including the following steps: Step 1: Obtain the ecosystem health index and driving pressure index of a river in the past 30 years; Step 2: Standardize the selected ecosystem health index and driving pressure index according to the following formula; ind s =(ind i -ind min ) / (ind max -ind min ); dri s =(dri i -dri min ) / (dri max -dri min ); Among them, i is the year, ind i is the ecosystem status indicator value in the i-th year, inds iis the standardized value of the ecosystem status indicator in the i-th year, ind min is the minimum value in the ecosystem status indicator series, ind max is the maximum value in the ecosystem status indicator series, dri i is the driving pressure index value in the i-th year, dris i is the standardized value of the driving pressure index in the i-th year, dri min is the minimum value in the driving pressure index series, dri max It is the maximum value in the driving pressure index series; This example uses the method of the present invention to perform standardization. The results are shown in Table 1 and Figure 1 As shown; among them, Figure 1 This is a display of the dynamic changes in the ecosystem health index and driving pressure index of a river in the past 30 years in this embodiment, providing a basis for other steps; the condition index in Table 1 refers to the ecosystem health index of a river in this embodiment; Table 1 Standardization results ; Step 3: Arrange the 30 continuous ecosystem health indices in descending order, calculate the empirical frequency of each data according to the following formula, and find the theoretical frequency formula: y = 0.5445x 2 - 1.2942x + 1.0406 (R 2 = 0.9801), where x is the theoretical frequency and y is the ecosystem health index; F m =m / (n+1)×100%, where m=1, 2, 3, ..., n; Among them, n is the statistical number of river and lake ecosystem conditions, m is the sequence number of each ecosystem condition data from small to large, F m is the frequency of occurrence of the river and lake ecosystem status corresponding to the mth item in the ranking in the data series; This embodiment uses the theoretical frequency curve of the ecosystem health index obtained by the present invention as shown in Figure 2 As shown; this embodiment is Figure 2 The theoretical frequency curve determines the river and lake recovery target; Step 4: The empirical frequencies of ecosystem health (i.e., ecosystem status) in the past three years (numbers 28, 29, and 30) are 45.16%, 48.39%, and 51.61%, respectively. The average value is 48.39%, which is within the range of 35% to 55%. m The ecosystem health index values ​​corresponding to the m items of 30%, 20%, and 10% are used as the low, medium, and high targets of ecological recovery, respectively; Step 5: According to the theoretical frequency formula, the ecosystem health index corresponding to the frequencies of 30%, 20% and 10% is calculated as 0.80, 0.88 and 0.97 respectively, that is, the low, medium and high targets of ecological recovery are 0.80, 0.88 and 0.97 respectively; Step 6: Calculate the rate of change of the ecosystem health index and driving pressure index (e.g. Figure 3 As shown, Figure 3 The change rates of the ecosystem health index and the driving pressure index are shown, which are used to determine whether the ecosystem condition is getting better or worse, whether the pressure is increasing or decreasing, and to determine the lag time of ecosystem response, so as to provide accurate river and lake recovery plans for the next steps and precise targets for ecological regulation. The first year corresponding to the value of the ecosystem health index change rate greater than zero for three consecutive years is numbered 20, and the third year corresponding to the value is numbered 22. The first year corresponding to the driving pressure index change rate less than zero for three consecutive years is numbered 14, and the third year corresponding to the value is numbered 16. The time range of the ecosystem health change lagging behind the driving pressure change is between 20-16=4 years and 22-14=8 years. Step 7: The correlation coefficients of ecosystem health changes lagging behind driving pressure factors by 4, 5, 6, 7, and 8 years were respectively -0.79, -0.88, -0.95, -0.97, and -0.95. The largest correlation coefficient among the 4-8 years of ecosystem health changes lagging behind driving pressure changes was -0.97 (7 years lag), which means that ecosystem health will be significantly improved 7 years after driving pressure decreases. Step 8: According to the ecosystem health index determined in step 4, which lags behind the driving pressure index by 7 years, a fitting analysis is conducted between the two and the fitting formula y = 1.2756x 2 - 2.5125x + 1.6231 (R 2 = 0.9607), where x is the ecosystem health index and y is the driving pressure index; the fitting curve of the ecosystem health index and the driving pressure index calculated by the method of the present invention in this embodiment is as follows Figure 4 As shown; Figure 4 The correlation between the ecosystem health index and the driving pressure index with and without considering hysteresis in this embodiment is shown. Figure 4 It can be seen that the relationship curve of the present invention using the method of the present invention considering the hysteresis of the ecosystem response has a good fit and a significant correlation; while the fit between the ecosystem health index and the driving pressure without considering the hysteresis in the present embodiment is poor, and the correlation is not obvious; Step 9: According to the fitting formula, the driving pressure index values ​​corresponding to the low, medium and high recovery targets of the ecosystem are calculated to be 0.43, 0.36 and 0.32 respectively. The average driving pressure index in the past three years is 0.39. Since 0.43>0.39, no additional artificial restoration measures are required to achieve the low recovery target, and only the natural restoration of the ecosystem can be relied on. Artificial restoration measures are required to achieve the medium and high recovery targets. Through artificial restoration measures, the driving pressure index will be reduced from the current value of 0.39 to 0.03 and 0.07, that is, to 0.36 and 0.32 respectively.

[0018] Conclusion: This example takes the restoration of a river ecosystem health as an example, and directly obtains the ecosystem health index value and driving pressure index value of the past years. The change of river ecological integrity obviously lags behind the change of driving force by about 7 years, that is, the health of the river ecosystem will obviously and continuously improve 7 years after the implementation of ecological recovery measures; the average value of the empirical frequency of the ecosystem health index value in the past three years is 48.39%, which is in the range of 35% to 55%. The ecosystem health index corresponding to the frequencies of 30%, 20% and 10% is used as the low, medium and high targets of ecological recovery respectively; the low recovery target of ecosystem health can be achieved only by relying on the natural restoration of the ecosystem, and the medium and high recovery targets need to be artificially restored. On the one hand, this example determines the high, medium and low ecological recovery targets by adopting the 30-year historical dynamic changes of ecosystem health and the current status of the past three years in the method of the present invention. The ecological recovery targets are accurately determined. Compared with the existing technology that determines the ecological recovery targets according to the current status of the ecosystem or the static characteristics of a certain stage, the accuracy and objectivity of the recovery target determination are greatly improved, the success rate of river and lake recovery is improved, and excessive artificial restoration can be avoided, saving financial, material and human resources. On the other hand, since the existing technology does not consider the lag of ecosystem changes (i.e., the lag time in step 7 of the existing technology is 0 years), the correlation coefficient between the ecosystem health index and the driving pressure index is -0.25, and the fitting formula between it and the driving pressure index is: y = -1.5036x 2 + 1.6433x + 0.3079 (R 2 = 0.1291), there is no significant correlation, and the change trend is not in line with common sense (such as Figure 4 As shown in the figure, it is impossible to accurately determine the target of river and lake recovery, and the accuracy of ecological regulation using the existing river and lake recovery method is low; however, this implementation adopts the present invention to consider the hysteresis of ecosystem response, and can accurately establish the correlation between the ecosystem and the driving pressure. The accuracy of the correlation curve between the constructed ecosystem health index and the driving pressure index is greatly improved, and the correlation coefficient is increased from -0.25 in the prior art to -0.97, and the R of the fitting curve is 2The value is increased from 0.1291 in the prior art to 0.9607, which greatly improves the accuracy and operability of ecological regulation using the river and lake recovery plan of the present invention.

[0019] Example 2: A case study of biodiversity restoration in a river; This embodiment uses the method of the present invention to revitalize rivers and lakes, including the following steps: Step 1: Obtain river biodiversity for the past 30 years as an indicator of ecosystem status, and select pollutant inflow and river connectivity as driving pressure indicators; Step 2: Standardize the selected biodiversity, pollutant inflow into the river, and river connectivity, and use the average value of the two indicators of pollutant inflow into the river and river connectivity as the driving pressure index; the standardization results of this embodiment using the method of the present invention are shown in Table 2; wherein the condition index in Table 2 refers to the biodiversity index of a river in this embodiment; Table 2 Standardization results ; Step 3: Arrange the 30 continuous biodiversity indices in descending order, calculate the empirical frequency of each data, and find the theoretical frequency formula: y = 0.6378x 2 - 1.1811x + 0.9701 (R 2 = 0.9787), where x is the theoretical frequency and y is the biodiversity index; If the average empirical frequency of biodiversity in the past three years is between 55% and 75%, the biodiversity corresponding to the frequencies of 50%, 35% and 20% will be used as the low, medium and high targets for ecological recovery respectively; Step 4: The frequencies of biodiversity in the past three years (numbers 28, 29, and 30) were 51.61%, 70.97%, and 74.19%, respectively, with an average of 65.59%, which is within the range of 55% to 75%. The biodiversity index values ​​corresponding to the frequencies of 50%, 35%, and 20% are used as the low, medium, and high targets for ecological recovery, respectively; Step 5: According to the theoretical frequency formula, the biodiversity indexes corresponding to the frequencies of 50%, 35%, and 20% are calculated to be 0.54, 0.63, and 0.76, respectively. That is, the low, medium, and high targets for ecological recovery are 0.54, 0.63, and 0.76, respectively. Step 6: Calculate the change rate of the biodiversity index and the driving pressure index. The year corresponding to the first value of the change rate of the biodiversity index that is greater than zero for three consecutive years is numbered 25, and the year corresponding to the third value is numbered 27. The year corresponding to the first value of the change rate of the driving pressure index that is less than zero for three consecutive years is numbered 14, and the year corresponding to the third value is numbered 16. The time range of biodiversity change lagging behind driving pressure change is between 25-16=9 years and 27-14=13 years. Step 7: The correlation coefficients of biodiversity changes lagging behind driving pressure factors by 9, 10, 11, 12, and 13 years are respectively -0.89, -0.77, -0.65, -0.46, and -0.21. The largest correlation coefficient is -0.89, which lags behind the driving factor by 9 years. It is believed that biodiversity will be significantly improved 9 years after the driving pressure decreases. Step 8: Lag the biodiversity index in step 4 by 9 years behind the driving index, conduct a fitting analysis between the two and obtain the fitting formula y = 0.6595x 2 - 2.4278x + 1.8154 (R 2 = 0.8458), where x is the biodiversity index and y is the driving pressure index; Step nine: According to the fitting formula, the driving pressure index values ​​corresponding to the low, medium and high restoration targets of the ecosystem are calculated to be 0.30, 0.19 and 0.08 respectively. The average driving pressure index in the past three years is 0.47. The difference between it and the current driving pressure is the regulation intensity of the driving factors in the river and lake recovery plan, that is, the driving pressure index needs to be reduced by 0.17, 0.28 and 0.39 respectively under the low, medium and high restoration targets.

[0020] Conclusion: This example takes the restoration of a river's biodiversity as an example, and obtains the river's biodiversity index, the amount of pollutants entering the river, and river connectivity. The driving pressure index needs to be calculated first. The empirical frequency average of the biodiversity index in the past three years is 65.59%, which is within the range of 55% to 75%. The biodiversity index corresponding to the frequencies of 50%, 35%, and 20% are used as the low, medium, and high targets for ecological recovery, respectively. The driving pressure index needs to be reduced to 0.30, 0.19, and 0.08, respectively; the change in river biodiversity obviously lags behind the change in driving force by about 9 years, and the biodiversity recovery time is relatively long. This example uses the existing technology to perform ecological recovery, and it is impossible to accurately determine the lag time of ecosystem changes. It is possible that the recovery effect will not be seen for 1 to 3 years after the ecological restoration measures are taken, which will lead to the misunderstanding that the biodiversity has recovered. The ecological restoration measures are not strong enough, and the ecological restoration measures are strengthened, resulting in blind restoration and excessive restoration; this embodiment, according to the method of the present invention, will fully consider the hysteresis of biodiversity changes, accurately determine the lag time of ecosystem changes, thereby giving the ecosystem enough recovery time, improving the success rate of river and lake recovery, avoiding excessive artificial restoration, and saving financial, material and human resources; if the lag of ecosystem changes is not considered (that is, the lag time in step seven of the prior art is 0 years), the correlation coefficient between the biodiversity index and the driving pressure index is -0.26, and the fitting formula between it and the driving pressure index is: y = -2.9971x 2 + 3.6328x - 0.3304 (R 2 = 0.258), there is no significant correlation, and the change trend is not in line with common sense, so it is impossible to determine the target of river and lake recovery; after considering the hysteresis of ecosystem change, the correlation coefficient between the biodiversity index and the driving pressure index increased from -0.26 to -0.89, and the R 2 The value increased from 0.258 to 0.8458, which greatly improved the accuracy and scientificity of ecological regulation using the river and lake restoration plan of the present invention.

[0021] Example 3: Case analysis of vegetation coverage restoration in a watershed; This embodiment uses the method of the present invention to revitalize rivers and lakes, including the following steps: Step 1: Obtain the vegetation coverage and driving pressure index of a watershed in the past 25 years; Step 2: Standardize the vegetation coverage and driving pressure index. The standardization results of the method of the present invention in this embodiment are shown in Table 3. The condition index in Table 3 refers to the vegetation coverage index of a watershed in this embodiment. Table 3 Standardization results ; Step 3: Arrange the 25 consecutive vegetation coverage indices in descending order, calculate the empirical frequency of each data, and find the theoretical frequency formula: y = 1.1603x 2 - 2.2248x + 1.1071 (R 2 = 0.9835), where x is the theoretical frequency and y is the vegetation coverage index; Step 4: The empirical frequencies of vegetation coverage in the past three years (numbers 23, 24, and 25) are 46.15%, 50.00%, and 38.46%, respectively, and their average value is 44.87%, which is within the range of 35% to 55%. m The vegetation coverage index values ​​corresponding to the m item of 30%, 20% and 10% are respectively used as the low, medium and high targets of ecological recovery; Step 5: According to the theoretical frequency formula, the vegetation coverage index corresponding to the frequencies of 30%, 20% and 10% is calculated as 0.54, 0.71 and 0.90 respectively, that is, the low, medium and high targets of ecological recovery are 0.54, 0.71 and 0.90 respectively; Step 6: Calculate the change rate of the vegetation coverage index and the driving pressure index. The year corresponding to the first value of the vegetation coverage index that is greater than zero for three consecutive years is numbered 15, and the year corresponding to the third value is numbered 17. The year corresponding to the first value of the driving pressure index that is less than zero for three consecutive years is numbered 17, and the year corresponding to the third value is numbered 19. The time range for the vegetation coverage change to lag behind the driving pressure change is between 17-17=0 years and 19-15=4 years. Step 7: The correlation coefficients of vegetation coverage rate lag behind driving pressure factor by 0, 1, 2, 3 and 4 years are respectively -0.37, -0.50, -0.64, -0.76 and -0.86. The largest correlation coefficient is -0.86, which lags behind driving factor by 4 years. It is believed that vegetation coverage rate will be significantly improved 4 years after driving pressure decreases. Step 8: Based on the lag of the vegetation coverage index by 4 years compared with the driving pressure index, a fitting analysis was conducted between the two and the fitting formula y = 0.7939x2 - 1.4728x + 0.9924 (R 2 = 0.7816), where x is the vegetation coverage index and y is the driving pressure index; the fitting curve of the vegetation coverage index and the driving pressure index calculated by the method of the present invention in this embodiment is as follows: Figure 5 As shown; Figure 5 The correlation between the ecosystem status index and the pressure index with and without considering hysteresis in this embodiment is shown. Figure 5It can be seen that the relationship curve of the present invention using the method of the present invention considering the hysteresis of the ecosystem response has a good fit and a significant correlation; while the fit between the state and pressure in the present embodiment without considering the hysteresis is poor, and the correlation is not obvious; Step 9: According to the fitting formula, the driving pressure index values ​​corresponding to the low, medium and high restoration targets of the ecosystem are calculated to be 0.43, 0.35 and 0.31 respectively. The average driving pressure index of the status quo in the past three years is 0.16, which is smaller than the driving pressure index corresponding to each restoration target. This indicates that due to the lag in the response of the ecosystem itself, no additional artificially assisted ecological recovery measures are needed in the near future. It is only necessary to maintain the current status and carry out ecosystem conservation and self-repair.

[0022] Conclusion: This example takes the restoration of a watershed vegetation coverage as an example, and obtains the watershed vegetation coverage and driving pressure index. The empirical frequency average of the watershed vegetation coverage index in the past three years is 44.87%, which is within the range of 35% to 55%. The vegetation coverage index corresponding to the frequencies of 30%, 20% and 10% are used as the low, medium and high targets of ecological recovery, respectively, and the corresponding driving pressure indexes are 0.43, 0.35 and 0.31, respectively; the change of the watershed vegetation coverage obviously lags behind the change of the driving force by about 4 years, because the driving pressure index corresponding to the high, medium and low recovery targets is greater than the average driving pressure index of 0.16 in the past three years, indicating that artificial restoration measures are not needed in the near future, and only ecosystem conservation and self-repair of the ecosystem are needed; according to the existing technology for ecological restoration, the effect of vegetation coverage restoration may not be seen within 1 to 2 years, which will lead to the mistaken belief that the ecological restoration measures are not strong enough, and then lead to blind restoration and over-restoration; according to the method of the present invention, the hysteresis of the change of vegetation coverage will be fully considered, giving the ecosystem enough recovery time, and improving the success rate of river and lake recovery. If the hysteresis of ecosystem changes is not considered (i.e., the lag time in step 7 of the prior art is 0 years), the correlation coefficient between the vegetation coverage index and the driving pressure index is -0.37, and the fitting formula between the vegetation coverage index and the driving pressure index is: y = 0.7672x 2 - 1.0791x + 0.827 (R 2 = 0.1829), there is no significant correlation, and the change trend is not in line with common sense (such as Figure 5 As shown in the figure, it is impossible to determine the target of river and lake recovery; after considering the hysteresis of ecosystem change, the correlation coefficient between the biodiversity index and the driving pressure index increased from -0.37 to -0.86, and the R 2 The value increased from 0.1829 to 0.7816, which greatly improved the accuracy and scientificity of ecological regulation using the river and lake restoration plan of the present invention.

[0023] In the above embodiments, embodiments 1 and 2 are cases of ecosystem health and biodiversity restoration, respectively, and embodiment 3 is a case of vegetation coverage restoration; embodiments 1 and 2 are cases of combining artificial restoration and natural restoration, and embodiment 3 is a case of natural restoration; the ecological restoration objects, driving pressures, and series years of embodiments 1, 2, and 3 are different, and the lag time of each object of the ecosystem analyzed by this method is different, and the corresponding ecological recovery goals and ecological recovery plans are also different; it can be seen that: the present invention has strong applicability, and is suitable for both river and lake ecosystem health restoration and biodiversity restoration, and for basin vegetation coverage restoration; the river and lake restoration method of the present invention can objectively, clearly, and accurately determine the river and lake restoration goals, greatly improving the accuracy of ecological regulation using the river and lake restoration plan of the present invention; it solves the problem that the existing technology cannot determine the river and lake restoration goals in combination with the historical change process, cannot accurately determine the river and lake restoration goals, and the existing technology does not consider the hysteresis of ecosystem changes, cannot accurately establish the correlation between the ecosystem and the driving pressure, and there is no significant correlation between the constructed ecosystem health index and the driving pressure index, which leads to the low accuracy of ecological regulation using the existing river and lake restoration plan.

[0024] Other parts not described belong to the prior art.

Claims

1. A river and lake recovery method based on the dynamic change process of the ecosystem and the time lag effect, characterized by: By analyzing the change rate of river and lake ecosystem conditions and external driving pressure factors over the years and the hysteresis correlation between the two, we can determine the river and lake recovery goals and propose corresponding recovery plans; The specific method includes the following steps: Step 1: Determine river and lake recovery goals; Obtain a long-term sequence of river and lake ecosystem conditions and driving pressure indexes, establish a historical change curve of ecosystem conditions and driving pressure indexes, and determine low, medium, and high levels of river and lake recovery targets by considering the historical changes in ecosystem conditions and the current ecological conditions; Step 2: Determine the ecosystem response lag time; Determine the lag time of ecosystem response by conducting hysteresis correlation analysis between ecosystem condition index and driving pressure index; Step 3: Determine the river and lake recovery plan; By establishing the relationship between ecosystem status and driving pressure based on the time lag of ecosystem response, the regulation intensity and regulation plan of driving pressure under low, medium and high levels of river and lake recovery goals are determined.

2. The method for river and lake recovery based on the dynamic change process and time lag effect of the ecosystem according to claim 1, characterized in that: In step one, determine the river and lake recovery goals, including the following steps: S11: Obtain the river and lake ecosystem status and driving pressure index for more than n years; n≥20; S12: Standardize the selected river and lake ecosystem status index values ​​and driving pressure index values; The normalization formula is: ind i =(in i -in min ) / (in max -in min ); dry i =(from i -from min ) / (from max -from min ); Among them, i is the year, ind i is the ecosystem status indicator value in the i-th year, inds i is the standardized value of the ecosystem status indicator in the i-th year, ind min is the minimum value in the ecosystem status indicator series, ind max is the maximum value in the ecosystem status indicator series, dri i is the driving pressure index value in the i-th year, dris i is the standardized value of the driving pressure index in the i-th year, dri min is the minimum value in the driving pressure index series, dri max It is the maximum value in the driving pressure index series; S13: Arrange the river and lake ecosystem status index values ​​of n years in ascending order, and calculate the empirical frequency corresponding to each indicator according to the formula; The empirical frequency p of the mth term m The calculation formula is as follows: F m =m / (n+1)×100%, where m=1,2,3,…,n; Among them, n is the statistical number of river and lake ecosystem conditions, m is the sequence number of each ecosystem condition data from small to large, F m is the frequency of occurrence of the river and lake ecosystem status corresponding to the mth item in the ranking in the data series; S14: Fit the theoretical frequency curve based on the river and lake ecological status index corresponding to different empirical frequencies; If the average empirical frequency of ecological integrity in the past three years is within the range of 75% to 100%, the ecological integrity corresponding to the frequencies of 70%, 50% and 30% will be calculated through the theoretical frequency formula as the low, medium and high targets of ecological recovery respectively; If the average empirical frequency of ecological integrity in the past three years is within the range of 55% to 75%, the corresponding ecological integrity of 50%, 35%, and 20% frequencies is calculated through the theoretical frequency formula as the low, medium, and high targets of ecological recovery, respectively; If the average empirical frequency of ecological integrity in the past three years is within the range of 35% to 55%, the ecological integrity corresponding to frequencies of 30%, 20% and 10% will be calculated using the theoretical frequency formula as the low, medium and high targets for ecological recovery, respectively.

3. The method for river and lake recovery based on the dynamic change process and time lag effect of the ecosystem according to claim 2, characterized in that: In step S11, the river and lake ecosystem conditions include ecosystem health index, biodiversity index, ecological integrity index, and vegetation coverage; The driving pressure index may be one or more of the amount of pollutants entering the river, the human interference index, the proportion of building land area, the proportion of downstream flow, or an already calculated comprehensive driving pressure index.

4. The method for river and lake recovery based on the dynamic change process and time lag effect of the ecosystem according to claim 3 is characterized by: In step S11, the ecosystem status data and driving pressure data of each river and lake in the study area are obtained as annual average data, seasonal data or monthly data, and the annual series is greater than or equal to 20 years.

5. The method for river and lake recovery based on the dynamic change process and time lag effect of the ecosystem according to claim 4, characterized in that: In step 2, the ecosystem response lag time is determined, which includes the following steps: S21: Calculate the annual change rate of the standardized river and lake ecosystem status index and driving pressure index in S12; f ind ’(i)=(Fs i+1 -Fs i ) / (n i+1 -n i ); Among them, f ind (i)' is the rate of change of the river-lake ecosystem status index or driving pressure index in year i, n i is the year of the ith year, n i+1 is the year of the i+1th year, Fs i+1 Fs is the standardized value of the river and lake ecosystem status index or driving pressure index in the i+1th year, i is the standardized value of the river and lake ecosystem status index or driving pressure index in the i-th year; S22: The year corresponding to the first value of the ecosystem status index that is greater than zero for three consecutive years is set as s1, and the year corresponding to the third value is set as s2. The year corresponding to the first value of the driving pressure index that is less than zero for three consecutive years is set as d1, and the year corresponding to the third value is set as d2. The time range of the ecosystem status index change lagging behind the driving pressure index change is s1-d2 years to s2-d1 years. S23: In the range of s1-d2 to s2-d1, the correlation coefficient between the ecosystem status index and the driving pressure index is calculated according to the lag time of s1-d2, s1-d2+1, s1-d2+2, and so on, s2-d1. That is, the correlation coefficient between the ecosystem status index and the driving pressure index is calculated every 1 year. The lag years corresponding to the largest correlation coefficient are the years in which the ecosystem change lags behind the driving pressure, and the correlation coefficient is expressed as y z Indicates that y z It is an integer between s1-d2 and s2-d1; ； Where n is the number, S is the ecosystem status index, D is the driving pressure index, r is the correlation coefficient between S and D, i is the number, is the average value of the ecosystem condition index, is the average value of the driving pressure index.

6. The method for river and lake recovery based on the dynamic change process and time lag effect of the ecosystem according to claim 5, characterized in that: In step S21, when the rate of change of the ecosystem status index is greater than zero, it indicates that the ecosystem status is improving; when the rate of change of the ecosystem status index is less than zero, it indicates that the ecosystem status is declining; when the rate of change of the ecosystem status index is equal to zero, it indicates that the ecosystem status is unchanged; When the change rate of the driving pressure index is greater than zero, it indicates that the external driving pressure increases; when the change rate of the driving pressure index is less than zero, it indicates that the external driving pressure decreases; when the change rate of the driving pressure index is equal to zero, it indicates that the external driving pressure remains unchanged.

7. The method for river and lake recovery based on the dynamic change process and time lag effect of the ecosystem according to claim 6, characterized in that: In step three, determine the river and lake recovery plan, which includes the following steps: S31: Lagged the ecosystem condition index by the driving pressure index y z In 2017, a fitting analysis between the two was conducted and the fitting formula was obtained; S32: According to the fitting formula, the driving pressure index values ​​d corresponding to the low, medium and high restoration targets of the ecosystem status index are calculated respectively. low d mid d high ; S33: The average driving pressure index in the past three years is d avg , d low d mid d high With d avg The difference is the driving pressure value that needs to be regulated to restore the ecosystem status to low, medium and high targets respectively; When avg With d low d mid d high If the difference is less than or equal to zero, no artificially assisted ecological restoration project will be carried out, and the goal of river and lake recovery can be achieved after a certain period of time by simply maintaining the current state and carrying out natural restoration; When avg With d low d mid d high If the difference is greater than zero, artificial restoration measures will be carried out to cooperate with natural restoration to achieve the goal of river and lake recovery.

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