River and Lake Recovery Method Based on the Dynamic Change Process and Time Delay Effect of Ecosystems

Abstract

The present invention discloses a method for the revival of rivers and lakes based on the dynamic change process and time-delay effect of the ecosystem. It includes the following steps: Step 1: Determine the revival goals of rivers and lakes; Step 2: Determine the lag time of ecosystem response; Step 3: Determine the revival plan for rivers and lakes. The present invention first proposes a method for the revival of rivers and lakes based on the dynamic change process and time-delay effect of the ecosystem. By considering the historical change process and current situation of the ecosystem, different levels of revival goals, namely low, medium, and high levels, are determined, improving the scientificity and reliability of the revival of rivers and lakes; through the lag correlation between the ecosystem status and external driving pressure, the time when the ecosystem response lags behind the driving pressure is scientifically determined; by establishing the relationship between the ecosystem status and driving pressure based on the time-delay effect, the regulation intensity of the driving pressure under different levels of revival goals is proposed, and it is determined whether to adopt artificial or natural restoration means, improving the success rate of the revival of rivers and lakes and avoiding over-restoration.

Description

Technical Field

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

[0002] The restoration speed of river and lake ecosystems is usually significantly lagging behind the speed of ecological destruction. Ecological revival often requires a long process and has a significant time lag effect. Especially the restoration of biodiversity may even lag behind for more than ten years or even longer after the implementation of ecological protection measures. The existing methods for river and lake revival have the following problems: First, the formulation of river and lake revival goals often ignores the historical process of the dynamic change of the ecosystem, and is usually designed based on the static problems at a certain stage, deviating from the reality, resulting in overly high goals that cannot be achieved or overly low goals that cannot restore the normal functions of the ecosystem. Second, the existing methods for determining river and lake revival plans do not consider the time lag of ecosystem response, often resulting in an unclear correlation between ecosystem changes and external driving pressures. The formulation of ecological revival plans lacks a scientific basis, leading to insufficient ecological revival efforts and difficulty in achieving ecological revival goals, or not fully considering the self-repair ability of the ecosystem, resulting in excessive artificial restoration for short-term results, consuming a lot of labor and time. Therefore, it is urgent to study a method for river and lake revival that improves the accuracy and operability of ecological regulation to guide river and lake revival actions. Summary of the Invention

[0003] The purpose of the present invention is to provide a method for river and lake revival 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 revival.

[0004] To achieve the above purpose, the technical solution of the present invention is: A method for river and lake revival based on the dynamic change process and time lag effect of the ecosystem. By conducting a lag correlation analysis of the annual change rates of the river and lake ecosystem status and external driving pressure factors over the years and the relationship between the two, the influence of the ecosystem time lag effect is overcome, the river and lake revival goals are determined, and corresponding revival plans are proposed;

[0005] Specific methods include the following steps:

[0006] Step 1: Determine the river and lake revival goals;

[0007] Obtain the long-term sequence of river and lake ecosystem status and external driving pressure indices, establish the historical change process curve of the ecosystem status and external driving pressure indices, and determine the river and lake revival goals at different levels of low, medium, and high by considering the historical change process of the ecosystem status and the current ecological status;

[0008] Step 2: Determine the ecosystem response lag time;

[0009] By conducting a lag correlation analysis between the ecosystem status index and the external driving pressure index, determine the lag time of ecosystem response;

[0010] Step 3: Determine the river and lake restoration plan;

[0011] Based on the established relationship between ecosystem status and external driving pressure with ecosystem response time lag, determine the regulation intensity and regulation plan of external driving pressure under different levels of river and lake restoration goals, namely low, medium, and high.

[0012] In the above technical solution, in Step 1, to determine the river and lake restoration goals, the specific steps are as follows:

[0013] S11: Obtain the ecosystem status and external driving pressure index of the river and lake for more than n years; n≥20;

[0014] S12: Standardize the selected ecosystem status index values and external driving pressure index values; the standardization formula is:

[0015] inds i = (ind i - ind min ) / ( ind max - ind min );

[0016] dris i = ( dri i - dri min ) / ( dri max - dri min );

[0017] Where i is the year, ind i is the ecosystem status index value of the i-th year, inds i is the value of the ecosystem status index after standardization for the i-th year, ind min is the minimum value in the series of ecosystem status indexes, ind max is the maximum value in the series of ecosystem status indexes, dri i is the external driving pressure index value of the i-th year, dri i is the value of the external driving pressure index after standardization for the i-th year, dri min is the minimum value in the series of external driving pressure indexes, dri max is the maximum value in the series of external driving pressure indexes;

[0018] S13: Arrange the ecosystem status index values of the river and lake for n years (n≥20) in ascending order, and calculate the empirical frequency corresponding to each index according to the formula;

[0019] The empirical frequency p of the m-th item m The calculation formula is as follows:

[0020] F m = m / (n + 1) × 100%, where m = 1, 2, 3, ……, n;

[0021] Among them, n is the statistical quantity of the river and lake ecosystem status, m is the serial number of the data of each ecosystem status sorted from small to large, and F m is the frequency of the river and lake ecosystem status corresponding to the m-th item in the data series; the larger F m is, the worse the river and lake ecosystem status is, and the smaller F m is, the better the river and lake ecosystem status is; the present invention determines the ecological restoration goal through the empirical frequency and the theoretical frequency curve;

[0022] S14: Fit the theoretical frequency curve according to the river and lake ecological status indexes corresponding to different empirical frequencies; the theoretical frequency formula is:

[0023] S = af 2 + bf + c;

[0024] Among them, S is the ecological system status index, f is the theoretical frequency corresponding to different ecological system status indexes, and a, b, and c are relevant parameters;

[0025] If the average value of the empirical frequencies of ecological integrity in the past three years is in the range of 75% - 100%, then the ecological integrity corresponding to the frequencies of 70%, 50%, and 30% is calculated through the theoretical frequency formula and used as the low, medium, and high goals of ecological restoration respectively; the frequency corresponding to the low-goal ecological integrity is increased by (75% - 70%) - (100% - 70%) compared with the current situation, that is, 5% - 30%, the frequency corresponding to the medium-goal ecological integrity is increased by (75% - 50%) - (100% - 50%) compared with the current situation, that is, 25% - 50%, and the frequency corresponding to the high-goal ecological integrity is increased by (75% - 30%) - (100% - 30%) compared with the current situation, that is, 45% - 70%;

[0026] If the average value of the empirical frequencies of ecological integrity in the past three years is in the range of 55% - 75%, then the ecological integrity corresponding to the frequencies of 50%, 35%, and 20% is calculated through the theoretical frequency formula and used as the low, medium, and high goals of ecological restoration respectively; the frequency corresponding to the low-goal ecological integrity is increased by (55% - 50%) - (75% - 50%) compared with the current situation, that is, 5% - 25%, the frequency corresponding to the medium-goal ecological integrity is increased by (55% - 35%) - (75% - 35%) compared with the current situation, that is, 20% - 40%, and the frequency corresponding to the high-goal ecological integrity is increased by (55% - 20%) - (75% - 20%) compared with the current situation, that is, 35% - 55%;

[0027] If the average value of the empirical frequency of ecological integrity in the past three years is within the range of 35% - 55%, the ecological integrity corresponding to the frequencies of 30%, 20% and 10% is calculated through the theoretical frequency formula and used as the low, medium and high targets for ecological recovery respectively; the frequency corresponding to the low target ecological integrity is increased by (35% - 30%) - (55% - 30%) compared with the current situation, that is, 5% - 25%, the frequency corresponding to the medium target ecological integrity is increased by (35% - 20%) - (55% - 20%) compared with the current situation, that is, 15% - 30%, and the frequency corresponding to the high target ecological integrity is increased by (35% - 10%) - (55% - 10%) compared with the current situation, that is, 25% - 45%; the present invention adopts the above method to improve the accuracy and operability of determining the recovery target.

[0028] In the above technical solution, in step S11, the status of the river and lake ecosystem can be represented by the ecosystem health index, biodiversity index, ecological integrity index, vegetation coverage rate, etc.;

[0029] The external driving pressure index can be selected as the pollutant inflow into the river, human disturbance index, proportion of construction land area, proportion of downstream discharge, etc., or the calculated comprehensive driving pressure index can be selected. The method of the present invention can use a single index as the external driving pressure index, or the comprehensive result of multiple indexes as the external driving pressure index. For example, the pollutant inflow into the river can be used as the external driving pressure index, or the pollutant inflow into the river and the human disturbance index can be given different weights to calculate a comprehensive driving pressure index.

[0030] In the above technical solution, in step S11, the data of the status of each river and lake ecosystem and the driving pressure data obtained in the study area can be annual data, seasonal data year by year or monthly data year by year, 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 change process of the ecosystem and improve the reliability of the lag analysis.

[0031] In the above technical solution, in step two, to determine the lag time of the ecosystem response, the following steps are specifically included:

[0032] S21: Calculate the annual change rates of the standardized river and lake ecosystem status index and the external driving pressure index in S12;

[0033] f ind ’(i) = (Fs i+1 - Fs i ) / (n i+1 - n i );

[0034] Among them, f ind (i)’ is the change rate of the river and lake ecosystem status index or the external driving pressure index in the i-th year, n iis the year of the i-th year, n i+1 is the year of the (i + 1)-th year, Fs i+1 is the value after standardization of the river and lake ecosystem status index or external driving pressure index in the (i + 1)-th year, Fs i is the value after standardization of the river and lake ecosystem status index or driving pressure index in the i-th year;

[0035] S22: Set the year corresponding to the first value of the change rate of the ecosystem status index being greater than zero for three consecutive years as s1, the year corresponding to the third value as s2, the year corresponding to the first value of the change rate of the external driving pressure index being less than zero for three consecutive years as d1, and the year corresponding to the third value as d2. Then the time range of the lag of the ecosystem status index change behind the external driving pressure index change is from s1 - d2 years to s2 - d1 years; improve the accuracy of determining the lag time of the ecosystem response;

[0036] S23: In the range from s1 - d2 years to s2 - d1 years, according to the ecosystem status index lagging behind the external driving pressure index by s1 - d2 years, s1 - d2 + 1 year, s1 - d2 + 2 years... s2 - d1 years each time, that is, calculate the correlation coefficient between the ecosystem status index and the driving pressure index every 1 year according to the lag time. The lag year number y corresponding to the largest correlation coefficient z is the number of years that the ecosystem change lags behind the external driving pressure, denoted by y z and y z is an integer between s1 - d2 years and s2 - d1;

[0037] ;

[0038] Among them, n is the quantity, 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 status index, is the average value of the driving pressure index.

[0039] In the above technical solution, in step S21, when the change rate of the ecosystem status index is greater than zero, it indicates that the ecosystem status is improving; when the change rate of the ecosystem status index is less than zero, it indicates that the ecosystem status is declining; when the change rate of the ecosystem status index is equal to zero, it indicates that the ecosystem status remains unchanged;

[0040] 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.

[0041] In the above technical solution, in step three, a river and lake recovery plan is determined, which specifically includes the following steps:

[0042] 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:

[0043] D=aS 2 +bS+c;

[0044] Among them, D is the external driving pressure index, S is the ecosystem status index, and a, b, and c are related parameters;

[0045] 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 ;

[0046] 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;

[0047] In step S33, d low ,dmid , d high The difference from d avg is the value of the external driving pressure index that needs to be reduced in ecological recovery;

[0048] d avg The difference between d low and d mid and d high If the difference is less than or equal to zero, it means that there is no need to carry out artificial-assisted ecological restoration projects, and only the current state needs to be maintained for natural restoration, and the goal of river and lake recovery can be achieved after a certain period of time;

[0049] If the difference between d avg and d low and d mid and d high is greater than zero, it means that artificial restoration measures need to be combined with natural restoration to achieve the goal of river and lake recovery; among them, artificial restoration measures include artificial measures such as pollution control, emission reduction, and greening; natural restoration is to maintain the current situation, without human participation, and use the self-repair ability of the ecosystem to slowly carry out self-repair.

[0050] The present invention has the following advantages:

[0051] (1) By considering the historical dynamic change process of the ecological system status and the ecological status of the current situation, the present invention determines the river and lake recovery goals at different levels of low, medium, and high, improving the accuracy and accessibility of the determination of river and lake recovery goals; it solves the problem that in the existing river and lake recovery methods, the formulation of river and lake recovery goals ignores the historical process of the dynamic change of the ecological system, usually designed according to the static problems at a certain stage, divorced from reality, resulting in the goal being set too high to be achieved or the goal being set too low to restore the normal function of the ecological system;

[0052] (2) By considering the time lag of the ecosystem response, the present invention can more accurately establish the correlation between the change in the ecosystem status and the external driving pressure, calculate the pressure index considering the lag of the ecosystem response, and determine whether auxiliary artificial restoration measures need to be carried out by comparing the pressure index value considering the lag with the pressure index value under the current conditions, so as to improve 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 and hydrology or ecology and water quality or ecology and pressure determined by the existing technical means does not consider the time lag of the ecosystem change, resulting in an unclear or incorrect relationship trend between the former and the latter, unable to accurately establish the correlation between the ecosystem and the driving pressure, and there is no significant correlation between the constructed ecosystem status index and the driving pressure index, thus leading to low accuracy of ecological regulation using the existing river and lake recovery plan, unable to accurately determine whether to use artificial restoration means or natural restoration means to carry out river and lake recovery, resulting in low success rate of river and lake recovery or easy to cause over-restoration and consume a large amount of financial, material and human resources.

[0053] (3) By establishing the relationship between the ecosystem status and the driving pressure based on the time lag of the ecosystem response, the present invention proposes the regulation intensity of the driving pressure under different levels of river and lake recovery goals of low, medium and high, and accurately determines whether to use artificial restoration or natural restoration means, improves the success rate of river and lake recovery, and can avoid excessive artificial restoration and save financial, material and human resources. Brief Description of the Drawings

[0054] Figure 1 It is the curve of the 30-year change process of the ecosystem health index value and the driving pressure index value in Embodiment 1 of the present invention;

[0055] Figure 2 It is the theoretical frequency curve of the ecosystem health index in Embodiment 1 of the present invention;

[0056] Figure 3 It is the change rate of the ecosystem health index and the driving pressure index in Embodiment 1 of the present invention;

[0057] Figure 4 It is the fitting curve of the ecosystem health index and the driving pressure index in Embodiment 1 of the present invention;

[0058] Figure 5 It is the fitting curve of the vegetation coverage rate index and the driving pressure index in Embodiment 3 of the present invention;

[0059] Figure 6 It is the method flow chart of the present invention. Detailed Embodiments

[0060] The implementation of the present invention will be described in detail below in conjunction with the accompanying drawings. However, they do not constitute a limitation to the present invention and are only for illustration purposes. At the same time, the advantages of the present invention will be made clearer and easier to understand through the description.

[0061] The present invention first proposes a method for the recovery of rivers and lakes based on the dynamic change process of the ecosystem and the time-lag effect. By considering the historical change process of the ecosystem status and the ecological status of the current situation in Step 1, different levels of river and lake recovery goals, namely low, medium, and high levels, are determined, improving the scientificity and reliability of river and lake recovery; through the lag 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; based on the relationship between the ecosystem status and the driving pressure established in Step 3, which is based on the time-lag property of the ecosystem response, the regulation intensity of the driving pressure under different levels of river and lake recovery goals, namely low, medium, and high levels, is proposed, and the means of artificial restoration or natural restoration are accurately determined, improving the success rate of river and lake recovery and avoiding excessive artificial restoration.

[0062] Each step executed in sequence by the present invention is interrelated and jointly realizes the accurate determination of the river and lake recovery goal and improves the accuracy of ecological regulation using the river and lake recovery scheme of the present invention. The present invention establishes the dynamic change process of the ecosystem and the dynamic change process of the external driving pressure in Step 1, providing basic data for Step 2 and the recovery goal for Step 3; determining the ecosystem response lag time in Step 2, together with Step 1, provides an accurate river and lake recovery scheme for Step 3 and a precise goal for ecological regulation; determining the ecosystem response lag time in Step 2 provides the basis for lagging the ecosystem status index behind the driving pressure index y z in years in Step 3, conducting a fitting analysis between the two and obtaining the fitting formula provides y z in years.

[0063] Referring to the attached Figure 1 it can be seen that the method for the recovery of rivers and lakes based on the dynamic change process of the ecosystem and the time-lag effect includes the following steps:

[0064] Step 1: Determine the river and lake recovery goal;

[0065] S11: Obtain the status of river and lake ecosystems and the driving pressure index over n (n≥20) years. The status of river and lake ecosystems can be represented by the ecosystem health index, biodiversity index, ecological integrity index, vegetation coverage rate, etc. The driving pressure indicators can be the amount of pollutants entering the river, human disturbance index, proportion of construction land area, proportion of downstream discharge, etc., or it can be the calculated comprehensive driving pressure index. The data of the status of river and lake ecosystems and driving pressure in the study area obtained can be annual average data, seasonal data year by year, or monthly data year by year. By analyzing the long-term historical change process of the ecosystem status, analyzing the empirical frequency of the ecosystem status under long-sequence conditions, obtaining the probabilities of different statuses occurring during its long-term evolution process, and combining the ecosystem status under its current conditions, determining the stage it is in, and then formulating river and lake restoration goals at different levels of high, medium, and low, fully considering the actual situation of the river and lake ecosystems, ensuring the accuracy and achievability of the river and lake restoration goals; solving the problem that the formulation of river and lake restoration goals in the existing technology ignores the historical process of the dynamic changes of the ecosystem, usually designed according to the static problems at a certain stage, divorced from the reality, resulting in the river and lake restoration goals being set too high to be achieved or the river and lake restoration goals being set too low to restore the normal functions of the ecosystem.

[0066] S12: Standardize the selected river and lake ecosystem status index values and driving pressure index values.

[0067] inds i = (ind i - ind min ) / ( ind max - ind min );

[0068] dris i = ( dri i - dri min ) / ( dri max - dri min );

[0069] Where i is the year, ind i is the value of the ecosystem status index in the i-th year, inds i is the value of the ecosystem status index after standardization in the i-th year, ind min is the minimum value in the series of ecosystem status indicators, ind max is the maximum value in the series of ecosystem status indicators, dri i is the value of the driving pressure index in the i-th year, dris i is the value of the driving pressure index after standardization in the i-th year, dri min is the minimum value in the series of driving pressure indicators, dri maxis the maximum value in the series of driving pressure indicators;

[0070] S13: Arrange the values of the river and lake ecosystem status index for n years (n ≥ 20) in ascending order, and calculate the empirical frequency corresponding to each indicator according to the formula;

[0071] The empirical frequency p of the m-th item m The calculation formula is as follows:

[0072] F m = m / (n + 1) × 100%, where m = 1, 2, 3,..., n;

[0073] Among them, n is the statistical quantity of the river and lake ecosystem status, m is the serial number of each ecosystem status data arranged in ascending order, and F m is the frequency of the river and lake ecosystem status corresponding to the m-th item in the data series;

[0074] S14: Fit the theoretical frequency curve according to the river and lake ecological status index corresponding to different empirical frequencies;

[0075] If the average value of the empirical frequencies of ecological integrity in the past three years is in the range of 75% - 100%, the ecological integrity corresponding to the frequencies of 70%, 50% and 30% is calculated through the theoretical frequency formula respectively as the low, medium and high goals of ecological recovery;

[0076] If the average value of the empirical frequencies of ecological integrity in the past three years is in the range of 55% - 75%, the ecological integrity corresponding to the frequencies of 50%, 35% and 20% is calculated through the theoretical frequency formula respectively as the low, medium and high goals of ecological recovery;

[0077] If the average value of the empirical frequencies of ecological integrity in the past three years is in the range of 35% - 55%, the ecological integrity corresponding to the frequencies of 30%, 20% and 10% is calculated through the theoretical frequency formula respectively as the low, medium and high goals of ecological recovery; The present invention determines the ecological recovery goal through the dynamic change process of the ecosystem history, combining the frequency of each stage in its history and the current situation in the past three years, improving the scientificity and accessibility of determining the ecological recovery goal of rivers and lakes;

[0078] Step two: Determine the lag time of ecosystem response;

[0079] S21: Calculate the annual change rates of the standardized river and lake ecosystem status index and the driving pressure index in S12;

[0080] f ind ’(i) = (Fs i+1 - Fs i ) / (n i+1 - n i );

[0081] Among them, f ind (i)' is the change rate of the river and lake ecosystem status index or driving pressure index in the i-th year, n i is the year of the i-th year, n i+1 is the year of the (i + 1)-th year, Fs i+1 is the value after standardization of the river and lake ecosystem status index or driving pressure index in the (i + 1)-th year, Fs i is the value after standardization of the river and lake ecosystem status index or driving pressure index in the i-th year;

[0082] When the change rate of the ecosystem status index is greater than zero, it indicates that the ecosystem status is improving; when it is less than zero, it indicates that the ecosystem status is declining. When the change rate of the driving pressure index is greater than zero, it indicates that the external driving pressure is increasing; when it is less than zero, it indicates that the external driving pressure is decreasing;

[0083] S22: Set the year corresponding to the first value of the change rate of the ecosystem status index being greater than zero for three consecutive years as s1, the year corresponding to the third value as s2, the year corresponding to the first value of the change rate of the driving pressure index being less than zero for three consecutive years as d1, and the year corresponding to the third value as d2. Then the time range of the lag of the ecosystem status index change behind the driving pressure index change is from s1 - d2 years to s2 - d1 years;

[0084] S23: Within the range of s1 - d2 years to s2 - d1 years, according to the lag of the ecosystem status index change behind the driving pressure index by s1 - d2 years, s1 - d2 + 1 year, s1 - d2 + 2 years... s2 - d1 years, that is, find the correlation coefficient between the ecosystem status index and the driving pressure index every 1 year according to the lag time. The lag year number y z corresponding to the largest correlation coefficient is the number of years of the lag of the ecosystem change behind the driving pressure;

[0085] Step three: Determine the river and lake recovery plan;

[0086] S31: Lag the ecosystem status index behind the driving pressure index by y z years, conduct a fitting analysis between the two and find the fitting formula;

[0087] S32: According to the fitting formula, find the driving pressure index values d low 、d mid 、d high corresponding to the low, medium, and high recovery targets of the ecosystem status index respectively;

[0088] S33: The average value of the driving pressure index in the recent three years is d avg ,d low 、d mid, d high The difference from d avg is the driving pressure value that needs to be regulated for the ecosystem status to recover to low, medium, and high targets respectively. d avg The difference between d low , d mid , d high If the difference is less than or equal to zero, it means that no artificial-assisted ecological restoration project needs to be carried out, and only the current state needs to be maintained for natural restoration, and the goal of river and lake recovery can be achieved after a certain period of time. If d avg The difference between d low , d mid , d high is greater than zero, it means that artificial restoration measures and natural restoration need to be combined to achieve the goal of river and lake recovery. d avg The difference between d low , d mid , d high is the driving pressure index value that needs to be reduced during ecological recovery;

[0089] Through the analysis of the hysteresis of ecosystem response (i.e., considering the time-delay effect of the ecosystem), the present invention establishes a more accurate fitting relationship between the river and lake ecosystem status and the driving pressure based on the ecosystem response, calculates the pressure index considering the hysteresis of ecosystem response (i.e., the driving pressure value corresponding to different recovery targets), and by comparing the size of the pressure index value considering hysteresis with the pressure index value under the current conditions, it can be determined whether artificial restoration measures need to be carried out, greatly improving the accuracy of ecological regulation using the river and lake recovery scheme of the present invention; solving the problem that the existing method for determining the river and lake recovery scheme in the prior art does not consider the time-delay of ecosystem response, often resulting in an unclear correlation between ecosystem changes and external driving pressures, the lack of scientific basis for formulating ecological recovery schemes, resulting in insufficient ecological recovery efforts and difficulty in achieving ecological recovery goals, or not fully considering the self-repair ability of the ecosystem, leading to excessive artificial restoration for short-term results and wasting financial and material resources.

[0090] Example: The present invention is now applied to a river and lake recovery example to illustrate the present invention in detail. It also has guiding significance for the application of the present invention to other ecological recoveries.

[0091] Example 1: Case analysis for the health restoration of a river ecosystem;

[0092] This example uses the method of the present invention for river and lake recovery, including the following steps:

[0093] Step 1: Obtain the ecological system health index and driving pressure index of a certain river in the past 30 years;

[0094] Step 2: Standardize the selected ecosystem health index and driving pressure index according to the following formula;

[0095] ind s = (ind i - ind min ) / (ind max - ind min );

[0096] dri s = (dri i - dri min ) / (dri max - dri min );

[0097] Where i is the year, ind i is the value of the ecosystem status indicator for the ith year, inds i is the value of the ecosystem status indicator after standardization for the ith year, ind min is the minimum value in the series of ecosystem status indicators, ind max is the maximum value in the series of ecosystem status indicators, dri i is the value of the driving pressure indicator for the ith year, dris i is the value of the driving pressure indicator after standardization for the ith year, dri min is the minimum value in the series of driving pressure indicators, dri max is the maximum value in the series of driving pressure indicators;

[0098] The standardization results using the method of the present invention in this embodiment are shown in Table 1 and Figure 1 as follows; where Figure 1 shows the dynamic change process of the ecosystem health index and driving pressure index of a certain river in this embodiment over the past 30 years, providing a basis for other steps; the status index in Table 1 refers to the ecosystem health index of a certain river in this embodiment;

[0099] Table 1 Standardization Results

[0100] ;

[0101] Step 3: Arrange the 30 consecutive ecosystem health indices in descending order, calculate the empirical frequency of each data according to the following formula, and obtain 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;

[0102] Fm = m / (n + 1) × 100%, where m = 1, 2, 3, ……, n;

[0103] Among them, n is the statistical quantity of the river and lake ecosystem status, m is the serial number of the data of each ecosystem status sorted from small to large, and F m is the frequency of the river and lake ecosystem status corresponding to the m-th item in the data series;

[0104] The theoretical frequency curve of the ecosystem health index obtained by using the present invention in this embodiment is as Figure 2 shown; in this embodiment, the Figure 2 theoretical frequency curve is used to determine the river and lake recovery target;

[0105] Step Four: The empirical frequencies of the ecosystem health (i.e., the ecosystem status) in the past three years (numbers 28, 29, 30) are 45.16%, 48.39%, and 51.61% respectively, and their average value is 48.39%, which is within the range of 35% - 55%. Then, the m items corresponding to the frequencies F m of 30%, 20%, and 10% are used as the low, medium, and high targets for ecological recovery respectively;

[0106] Step Five: According to the theoretical frequency formula, the ecosystem health indices corresponding to the frequencies of 30%, 20%, and 10% are calculated to be 0.80, 0.88, and 0.97 respectively. That is, the low, medium, and high targets for ecological recovery are 0.80, 0.88, and 0.97 respectively;

[0107] Step Six: Calculate the change rates of the ecosystem health index and the driving pressure index (as Figure 3 shown, Figure 3 which shows the change rates of the ecosystem health index and the driving pressure index, used to determine whether the ecosystem status is getting better or worse, and whether the pressure is increasing or decreasing, used to determine the ecological system response lag time, providing an accurate river and lake recovery plan for the next step and providing a precise target for ecological regulation). The year number corresponding to the first value of the change rate of the ecosystem health index that is greater than zero for three consecutive years is 20, and the year number corresponding to the third value is 22. The year number corresponding to the first value of the change rate of the driving pressure index that is less than zero for three consecutive years is 14, and the year number corresponding to the third value is 16. Then, the time range of the lag of the ecosystem health change behind the driving pressure change is between 20 - 16 = 4 years and 22 - 14 = 8 years;

[0108] Step 7: The correlation coefficients of the ecosystem health change lagging behind the driving pressure factors by 4 years, 5 years, 6 years, 7 years, and 8 years are -0.79, -0.88, -0.95, -0.97, and -0.95 respectively. Among the 4 - 8 years of lag between the ecosystem health change and the driving pressure change, the maximum correlation coefficient is -0.97 (lagging 7 years). It is considered that the ecosystem health will be significantly improved 7 years after the driving pressure decreases;

[0109] Step 8: According to the ecosystem health index lagging behind the driving pressure index by 7 years determined in Step 4, conduct a fitting analysis between the two and obtain 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 Figure 4 shown; Figure 4 shows the correlation between the ecosystem health index and the driving pressure index considering hysteresis and not considering hysteresis in this embodiment. From Figure 4 it can be seen that the fitting degree of the relationship curve considering the ecosystem response hysteresis by the method of the present invention in this embodiment is better and the correlation is significant; while in the case of not considering hysteresis in this embodiment, the fitting degree between the ecosystem health index and the driving pressure is poor and the correlation is not obvious;

[0110] 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 0.43, 0.36, and 0.32 respectively, and the average value of the driving pressure index in the recent three years is 0.39; Since 0.43 > 0.39, therefore, to achieve the low recovery target, no additional artificial restoration measures are required, and only the natural restoration of the ecosystem can be relied on; To achieve the medium and high recovery targets, artificial restoration measures need to be carried out, and the driving pressure index is reduced by 0.03 and 0.07 respectively from the current 0.39 through artificial restoration measures, that is, reduced to 0.36 and 0.32.

[0111] Conclusion: Taking the restoration of the ecological health of a certain river as an example, the ecological health index values and driving pressure index values over the years are directly obtained in this embodiment. The change in river ecological integrity lags significantly behind the change in driving forces by about 7 years, that is, the ecological health of the river ecosystem will improve significantly and continuously 7 years after the implementation of ecological restoration measures; the average empirical frequency of the ecological health index values in the past three years is 48.39%, which is within the range of 35% - 55%. The ecological health indexes corresponding to the frequencies of 30%, 20% and 10% are respectively used as the low, medium and high goals of ecological restoration; achieving the low restoration goal of ecosystem health only requires relying on the natural restoration of the ecosystem, while achieving the medium and high restoration goals requires artificial restoration. On the one hand, in this embodiment, by adopting the 30-year historical dynamic changes of ecosystem health and the current situation in the past three years in the method of the present invention, the ecological restoration goals at different levels of high, medium and low are determined. The ecological restoration goals are accurately determined. Compared with the prior art that determines the ecological restoration goals based on the current situation of the ecosystem or the static characteristics at a certain stage, the accuracy and objectivity of the determined restoration goals are greatly improved, the success rate of river and lake restoration is increased, and excessive artificial restoration can be avoided, saving financial, material and human resources. On the other hand, due to the prior art not considering the lag of ecosystem changes (that is, the lag time in step seven of the prior art is 0 years), the correlation coefficient between the ecological health index and the driving pressure index is -0.25, and its fitting formula with 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 does not conform to common sense (as Figure 4 shown), and the river and lake restoration goals cannot be accurately determined. The accuracy of ecological regulation using the existing river and lake restoration methods is low; while this embodiment of the present invention considers the lag of ecosystem response, can accurately establish the correlation between the ecosystem and the driving pressure, and the accuracy of the correlation curve between the constructed ecological health index and the driving pressure index is greatly improved. The correlation coefficient is increased from -0.25 in the prior art to -0.97, and the R 2 value of the fitting curve is increased from 0.1291 in the prior art to 0.9607, greatly improving the accuracy and operability of ecological regulation using the river and lake restoration scheme of the present invention.

[0112] Example 2: Case analysis for the restoration of river biodiversity;

[0113] This embodiment uses the method of the present invention for river and lake restoration, including the following steps:

[0114] Step 1: Obtain the river biodiversity of a certain river in the past 30 years as an indicator of the ecosystem status, and select the pollutant inflow into the river and river connectivity as driving pressure indicators;

[0115] Step 2: Standardize the selected biodiversity, pollutant inflow into the river, and river connectivity. Use the average of the two indicators of pollutant inflow into the river and river connectivity as the driving pressure index. The standardized results using the method of the present invention in this embodiment are shown in Table 2. Among them, the condition index in Table 2 refers to the biodiversity index of a certain river in this embodiment.

[0116] Table 2 Standardized Results

[0117] ;

[0118] Step 3: Arrange the 30 consecutive biodiversity indices in descending order, calculate the empirical frequency of each data item, and obtain 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.

[0119] If the average of the empirical frequencies of biodiversity in the past three years is in the range of 55% - 75%, then the biodiversities corresponding to the frequencies of 50%, 35%, and 20% are used as the low, medium, and high targets for ecological restoration, respectively.

[0120] Step 4: The frequencies of biodiversity in the past three years (numbers 28, 29, and 30) are 51.61%, 70.97%, and 74.19% respectively, and their average is 65.59%, which is in the range of 55% - 75%. Then the biodiversity index values corresponding to the frequencies of 50%, 35%, and 20% are used as the low, medium, and high targets for ecological restoration, respectively.

[0121] Step 5: According to the theoretical frequency formula, the biodiversity indices 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 restoration are 0.54, 0.63, and 0.76 respectively.

[0122] Step 6: Calculate the change rates of the biodiversity index and the driving pressure index. The year number corresponding to the first value of the change rate of the biodiversity index that is greater than zero for three consecutive years is 25, and the year number corresponding to the third value is 27. The year number corresponding to the first value of the change rate of the driving pressure index that is less than zero for three consecutive years is 14, and the year number corresponding to the third value is 16. Then the time range of the lag of biodiversity change behind the driving pressure change is between 25 - 16 = 9 years and 27 - 14 = 13 years.

[0123] Step 7: Calculate the correlation coefficients when the biodiversity change lags behind the driving pressure factor by 9 years, 10 years, 11 years, 12 years, and 13 years, which are -0.89, -0.77, -0.65, -0.46, and -0.21 respectively. The largest correlation coefficient is -0.89 when lagging behind the driving factor by 9 years. It is considered that the biodiversity will be significantly improved 9 years after the driving pressure decreases.

[0124] 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.

[0125] Step 9: According to the fitting formula, calculate the driving pressure index values corresponding to the low, medium, and high ecosystem recovery targets, which are 0.30, 0.19, and 0.08 respectively. The average value of the 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 factor 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 recovery targets.

[0126] Conclusion: Taking the restoration of the biodiversity of a certain river as an example in this embodiment, the obtained are the river biodiversity index, the amount of pollutants entering the river, and the river connectivity. It is necessary to first calculate the driving pressure index. The empirical frequency average value of the biodiversity index in the past three years is 65.59%, which is within the range of 55% - 75%. The biodiversity indices corresponding to the frequencies of 50%, 35%, and 20% are used as the low, medium, and high targets for ecological restoration respectively, and the driving pressure index needs to be reduced to 0.30, 0.19, and 0.08 respectively; the change in river biodiversity lags significantly behind the change in the driving force by about 9 years, and the time for biodiversity restoration is relatively long. In this embodiment, when conducting ecological restoration according to the existing technology, the lag time of ecosystem change cannot be accurately determined. It may be that no recovery effect can be seen in 1 - 3 years after taking ecological restoration measures, which may lead to the misunderstanding that the intensity of ecological restoration measures is insufficient, and then strengthen the intensity of ecological restoration measures, resulting in blind restoration and over - restoration; in this embodiment, according to the method of the present invention, the lag of biodiversity change will be fully considered, and the lag time of ecosystem change will be accurately determined, so as to give the ecosystem enough time for recovery, improve the success rate of river and lake recovery, and avoid excessive artificial restoration and save financial, material, and human resources; if the lag of ecosystem change is not considered (that is, the lag time in Step 7 of the existing technology is 0 years), the correlation coefficient between the biodiversity index and the driving pressure index is -0.26, and its fitting formula with 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 does not conform to common sense, so the goal of river and lake recovery cannot be determined; after considering the lag 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 value increased from 0.258 to 0.8458, greatly improving the accuracy and scientific nature of ecological regulation using the river and lake recovery plan of the present invention.

[0127] Example 3: Case analysis of vegetation coverage restoration in a certain basin;

[0128] The method of the present invention is used for river and lake recovery in this example, including the following steps:

[0129] Step 1: Obtain the vegetation coverage rate and driving pressure index of a certain basin in the past 25 years;

[0130] Step 2: Standardize the vegetation coverage rate and the driving pressure index; the standardization results using the method of the present invention in this example are shown in Table 3; among them, the condition index in Table 3 refers to the vegetation coverage rate index of a certain basin in this example;

[0131] Table 3 Standardization results

[0132] ;

[0133] Step 3: Arrange the 25 consecutive vegetation coverage rate indexes in descending order, calculate the empirical frequency of each item of data, and obtain 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 rate index;

[0134] Step 4: The empirical frequencies of the vegetation coverage rates in the recent three years (numbers 23, 24, 25) are 46.15%, 50.00%, and 38.46% respectively, and their average value is 44.87%, which is within the range of 35% - 55%. Then, the vegetation coverage rate index values corresponding to the m items with frequencies F m of 30%, 20%, and 10% are used as the low, medium, and high goals of ecological recovery respectively;

[0135] Step 5: According to the theoretical frequency formula, find the vegetation coverage rate indexes corresponding to the frequencies of 30%, 20%, and 10% are 0.54, 0.71, and 0.90 respectively, that is, the low, medium, and high goals of ecological recovery are 0.54, 0.71, and 0.90 respectively;

[0136] Step 6: Calculate the change rates of the vegetation coverage rate index and the driving pressure index. The year number corresponding to the first value of the change rate of the vegetation coverage rate index that is greater than zero for three consecutive years is 15, and the year number corresponding to the third value is 17. The year number corresponding to the first value of the change rate of the driving pressure index that is less than zero for three consecutive years is 17, and the year number corresponding to the third value is 19. Then the time range of the lag of the vegetation coverage rate change behind the driving pressure change is from 17 - 17 = 0 year to 19 - 15 = 4 years;

[0137] Step 7: Calculate the correlation coefficients when the vegetation coverage rate change lags behind the driving pressure factor by 0 year, 1 year, 2 years, 3 years, and 4 years, which are -0.37, -0.50, -0.64, -0.76, and -0.86 respectively. The largest correlation coefficient is -0.86 when lagging behind the driving factor by 4 years. It is considered that the vegetation coverage rate will be significantly improved 4 years after the driving pressure decreases;

[0138] Step 8: According to the vegetation coverage rate index lagging behind the driving pressure index by 4 years, conduct a fitting analysis between the two and obtain the fitting formula y = 0.7939x2 - 1.4728x + 0.9924 (R 2 = 0.7816), where x is the vegetation coverage rate index and y is the driving pressure index; The fitting curve of the vegetation coverage rate index and the driving pressure index calculated by the method of the present invention in this embodiment is as Figure 5 shown; Figure 5 shows the correlation between the ecosystem condition index and the pressure index considering hysteresis and not considering hysteresis in this embodiment. From Figure 5 it can be seen that the fitting degree of the relationship curve considering the hysteresis of the ecosystem response by the method of the present invention in this embodiment is good and the correlation is significant; while the fitting degree between the condition and the pressure is poor and the correlation is not obvious when not considering hysteresis in this embodiment;

[0139] Step 9: According to the fitting formula, calculate the driving pressure index values corresponding to the low, medium, and high recovery targets of the ecosystem, which are 0.43, 0.35, and 0.31 respectively. The average value of the driving pressure index in the current situation in the recent three years is 0.16, which is less than the driving pressure index corresponding to each recovery target. It indicates that due to the hysteresis of the response of the ecosystem itself, there is no need to supplement additional artificial-assisted ecological recovery measures in the near future. Only the current state needs to be maintained, and ecosystem conservation and self-repair of the ecosystem need to be carried out.

[0140] Conclusion: Taking the restoration of the vegetation coverage rate in a certain basin as an example, this embodiment obtains the vegetation coverage rate and the driving pressure index of the basin. The average empirical frequency of the vegetation coverage rate index in the basin in the past three years is 44.87%, which is within the range of 35% - 55%. The vegetation coverage rate indexes corresponding to the frequencies of 30%, 20%, and 10% are respectively used as the low, medium, and high targets for ecological restoration, and the corresponding driving pressure indexes are 0.43, 0.35, and 0.31 respectively. The change in the vegetation coverage rate of the basin lags significantly behind the change in the driving force by about 4 years. Since the driving pressure indexes corresponding to the high, medium, and low restoration targets are all greater than the average driving pressure index of the past three years, which is 0.16, it indicates that artificial restoration measures are not required in the near future, and only ecological system conservation and the self - restoration of the ecological system need to be carried out. According to the existing technology for ecological restoration, it may be impossible to see the restoration effect of the vegetation coverage rate within 1 - 2 years, which may lead to the misunderstanding that the intensity of ecological restoration measures is insufficient, and then lead to blind restoration and over - restoration. According to the method of the present invention, the lag of the change in the vegetation coverage rate will be fully considered, giving the ecological system enough time to recover and improving the success rate of river and lake restoration. If the lag of the ecological system change is not considered (that is, the lag time in step seven of the existing technology is 0 years), the correlation coefficient between the vegetation coverage rate index and the driving pressure index is - 0.37, and the fitting formula between it 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 does not conform to common sense (as Figure 5 shown), and the river and lake restoration target cannot be determined. After considering the lag of the ecological system change, the correlation coefficient between the biodiversity index and the driving pressure index has increased from - 0.37 to - 0.86, and the R 2 value of the fitting curve has increased from 0.1829 to 0.7816, greatly improving the accuracy and scientificity of ecological regulation using the river and lake restoration plan of the present invention.

[0141] In the above embodiments, Embodiment 1 and Embodiment 2 are cases of ecosystem health and biodiversity restoration respectively, and Embodiment 3 is a case of vegetation coverage restoration; Embodiment 1 and Embodiment 2 are cases combining artificial restoration and natural restoration, and Embodiment 3 is a case of natural restoration; the ecological recovery objects, driving pressures, and series of years of Embodiment 1, 2, and 3 are different. Using this method, the lag times of various objects in the ecosystem are different, and the corresponding ecological recovery goals and ecological recovery plans also vary; it can be seen from this that: the applicability of the present invention is strong, and it is applicable to both the health restoration of river and lake ecosystems and biodiversity restoration, and also applicable to the restoration of basin vegetation coverage; the river and lake recovery method described in the present invention can objectively, clearly, and accurately determine the river and lake recovery goals, greatly improving the accuracy of ecological regulation using the river and lake recovery plan of the present invention; it solves the problems that the prior art cannot determine the river and lake recovery goals in combination with the historical change process, cannot accurately determine the river and lake recovery goals, and the prior art does not consider the lag 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, resulting in low accuracy of ecological regulation using the existing river and lake recovery plan.

[0142] Other parts not described are all prior art.

Claims

1. A method for the revival of rivers and lakes based on the dynamic change process and time-delay effect of the ecosystem, characterized in that: By conducting an analysis of the annual change rates of the river and lake ecosystem status and external driving pressure factors, as well as the lag correlation between the two, determine the river and lake recovery goals and propose corresponding recovery plans; The specific method includes the following steps: Step 1: Determine the river and lake recovery goals; Obtain the long-term series of river and lake ecosystem status and driving pressure indices, establish the historical change process curve of the ecosystem status and driving pressure indices, and determine the low, medium, and high-level river and lake recovery goals by considering the historical change process of the ecosystem status and the current ecological status; Step 2: Determine the lag time of ecosystem response; Determine the lag time of ecosystem response by conducting a lag correlation analysis of the ecosystem status index and the driving pressure index; Step 3: Determine the river and lake recovery plan; Determine the regulation intensity and regulation plan of the driving pressure under different low, medium, and high-level river and lake recovery goals by establishing the relationship between the ecosystem status and the driving pressure based on the time lag of ecosystem response; Specifically, it includes the following steps: S31: Lag the ecosystem condition index behind the driving pressure index y z In year, conduct a fitting analysis between the two and obtain the fitting formula; S32: According to the fitting formula, respectively calculate the driving pressure index values d low , d mid , d high ; S33: The average value of the driving pressure index in the past three years is d avg , d low , d mid , d high and the differences from d avg are the driving pressure values that need to be regulated for the ecosystem status to recover to low, medium, and high targets respectively; When the driving pressure value is less than or equal to zero, no artificial-assisted ecological restoration project is carried out, and only the current state is maintained for natural restoration, and the river and lake recovery goal can be achieved after a certain period of time; When the driving pressure value is greater than zero, artificial restoration measures are carried out to cooperate with natural restoration to achieve the river and lake recovery goal.

2. The method for river and lake recovery based on the dynamic change process of the ecosystem and time lag effect according to claim 1, characterized in that: In Step 1, to determine the river and lake recovery goals, it specifically includes the following steps: S11: Obtain the river and lake ecosystem status and driving pressure indices for more than n years; n≥20; S12: Standardize the selected river and lake ecosystem status index values and 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 ); where \(i\) represents the year, and \(ind\) i is the value of the ecosystem status index for the \(i\)-th year, and \(inds\) i is the value of the standardized ecosystem status index for the \(i\)-th year, \(ind\) min is the minimum value in the series of ecosystem status indices, \(ind\) max is the maximum value in the series of ecosystem status indices, \(dri\) i is the value of the driving pressure index for the \(i\)-th year, \(dris\) i is the value of the standardized driving pressure index for the \(i\)-th year, \(dri\) min is the minimum value in the series of driving pressure indices, \(dri\) max is the maximum value in the series of driving pressure indices; S13: Arrange the standardized river and lake ecosystem status index values for n years in ascending order, and calculate the empirical frequencies corresponding to each index according to the formula; The empirical frequency F of the m-th item 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 quantity of the ecological system status of rivers and lakes, m is the serial number of the data of each ecological system status sorted from small to large, and F m is the empirical frequency of the ecological system status of rivers and lakes corresponding to the m-th item in the sorted data series; S14: Fit the theoretical frequency curve based on the river and lake ecological status indices corresponding to different empirical frequencies; If the average value of the empirical frequencies of ecological integrity in the past three years is in the range of 75% - 100%, calculate the ecological integrity corresponding to the 70%, 50%, and 30% frequencies through the theoretical frequency formula respectively as the low, medium, and high goals of ecological recovery; If the average value of the empirical frequencies of ecological integrity in the past three years is in the range of 55% - 75%, calculate the ecological integrity corresponding to the 50%, 35%, and 20% frequencies through the theoretical frequency formula respectively as the low, medium, and high goals of ecological recovery; If the average value of the empirical frequencies of ecological integrity in the past three years is in the range of 35% - 55%, calculate the ecological integrity corresponding to the 30%, 20%, and 10% frequencies through the theoretical frequency formula respectively as the low, medium, and high goals of ecological recovery.

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 status includes the ecosystem health index, biodiversity index, ecological integrity index, and vegetation coverage rate; The driving pressure indicators can be selected from one or more of the pollutant inflow into the river, human disturbance index, proportion of construction land area, proportion of downstream discharge, or the calculated comprehensive driving pressure index.

4. The method for river and lake recovery based on the dynamic change process of the ecosystem and time delay effect according to claim 3, characterized in that: In step S11, the data of the ecological system status and driving pressure of each river and lake in the study area obtained are annual average data, seasonal data of each year, or monthly data of each year, 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 two, determine the lag time of the ecosystem response, which specifically includes the following steps: S21: Calculate the annual change rates 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 change rate of the river and lake ecosystem status index or driving pressure index in the i-th year, n i is the year of the i-th year, n i+1 is the year of the (i + 1)-th year, Fs i+1 is the value after standardization of the river and lake ecosystem status index or driving pressure index in the (i + 1)-th year, Fs i is the value after standardization of the river and lake ecosystem status index or driving pressure index in the i-th year; S22: Set the year corresponding to the first value where the change rate of the ecosystem status index is greater than zero for three consecutive years as s1, the year corresponding to the third value as s2, the year corresponding to the first value where the change rate of the driving pressure index is less than zero for three consecutive years as d1, and the year corresponding to the third value as d2. Then the time range for the change of the ecosystem status index to lag behind the change of the driving pressure index is from s1 - d2 years to s2 - d1 years; S23: In the range from s1 - d2 years to s2 - d1 years, according to the fact that the change of the ecosystem status index lags behind the driving pressure index by s1 - d2 years, s1 - d2 + 1 years, s1 - d2 + 2 years... s2 - d1 years, that is, the correlation coefficients between the ecosystem status index and the driving pressure index are calculated respectively every 1 year according to the lag time. The lag years corresponding to the largest correlation coefficient are the years when the ecosystem change lags behind the driving pressure, and it is represented by y z which is z an integer between s1 - d2 years and s2 - d1 years; ； Among them, n is the quantity, S is the ecosystem status index, D is the driving pressure index, r is the correlation coefficient between S and D, and i is the serial number. is the average value of the ecosystem status 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, wherein: In step S21, when the change rate of the ecosystem status index is greater than zero, it indicates that the ecosystem status is improving; when the change rate of the ecosystem status index is less than zero, it indicates that the ecosystem status is declining; when the change rate of the ecosystem status index is equal to zero, it indicates that the ecosystem status remains unchanged; When the change rate of the driving pressure index is greater than zero, it indicates that the external driving pressure is increasing; when the change rate of the driving pressure index is less than zero, it indicates that the external driving pressure is decreasing; when the change rate of the driving pressure index is equal to zero, it indicates that the external driving pressure remains unchanged.

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