Method for evaluating influence of wetland hydrological dynamic change on lake water quality

Abstract

The invention provides a method for evaluating the influence of wetland hydrological dynamic change on lake water quality, and relates to the technical field of water quality evaluation.According to the method, hydrological and water quality data are collected, data cleaning and time scale processing are carried out, correlation coefficients are calculated to remove collinear variables, and a comprehensive index is constructed; and fitting and significance testing are performed by using a generalized addition model, so that visual display is finally realized, and a scientific basis is provided for wetland protection and water quality management.

Description

Technical Field

[0001] The invention relates to the technical field of water quality assessment, and in particular to a method for assessing the impact of dynamic changes in wetland hydrology on lake water quality. Background Art

[0002] As global climate change intensifies, the regulation function of wetland ecosystems in the basin hydrological cycle becomes increasingly important. However, many existing studies focus on "the relationship between climate change and river and lake water quality" or "analysis of the relationship between climate indicators and water quality indicators based on nonlinear models (such as GAM)", and lack a systematic assessment of the impact of wetland hydrological dynamics (including water level fluctuations, flow velocity changes, etc.) on lake water quality. Its main defects are:

[0003] Most existing technologies use temperature, precipitation, wind speed, etc. as explanatory variables, ignoring the entire process and coupling effects of wetland drainage, inflow, evaporation, surface runoff, and changes in wetland vegetation that affect lake water quality.

[0004] Existing technologies often use linear or semi-linear methods (such as single regression or linear models) to explain the causal relationship between wetland hydrological changes and water quality indicators, which cannot capture the multi-factor coupling and nonlinear coupling effects of wetland hydrological dynamics on water quality.

[0005] Although a small number of studies have adopted nonlinear methods such as generalized additive models (GAMs), they are mostly limited to the analysis of climate-dominated factors, and do not take wetland hydrological dynamics as the core influencing factor to separately measure its contribution and scope of influence, resulting in insufficient accuracy in the prediction and assessment of lake water quality. Summary of the invention

[0006] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a method for evaluating the impact of dynamic changes in wetland hydrology on lake water quality, which can not only accurately evaluate the impact of dynamic changes in wetland hydrology on lake water quality, but also provide important scientific basis and technical support for wetland ecosystem protection and lake water quality management.

[0007] To achieve the above object, the present invention provides the following solutions:

[0008] A method for assessing the impact of wetland hydrological dynamics on lake water quality, comprising:

[0009] Collect hydrological dynamic change data of target wetlands and water quality index data of target lakes according to the preset sampling period;

[0010] Performing data cleaning and time scale processing on the hydrological dynamic change data and the water quality index data to obtain hydrological preprocessing data and water quality preprocessing data;

[0011] The Pearson correlation analysis method is used to calculate the correlation coefficients between the hydrological preprocessing data and between the hydrological preprocessing data and the water quality preprocessing data, and the collinear variables in the hydrological preprocessing data are eliminated according to the correlation coefficients to obtain a list of wetland hydrological dynamic change indicators;

[0012] Determine a comprehensive index based on the list of wetland hydrological dynamic change indicators; each of the comprehensive indexes represents a key dimension of wetland hydrological dynamic change;

[0013] Fitting and significance testing are performed based on the comprehensive index and the preset generalized additive model, and the fitting results and test results are visualized to evaluate the impact of wetland hydrological dynamics on lake water quality.

[0014] Preferably, fitting and significance testing are performed based on the comprehensive index and the preset generalized additive model, and the fitting results and the test results are visualized to evaluate the impact of wetland hydrological dynamic changes on lake water quality, including:

[0015] Taking the comprehensive index as the explanatory variable and the water quality pretreatment data as the response variable, the spline smoothing function in the GAM model is used for fitting to obtain a first fitting result, and a significance test is performed based on the first fitting result to obtain a first test result and a list of single factors that pass the significance test;

[0016] The indicators in the single factor list that passed the significance test are combined in pairs to construct interaction items, and the water quality pretreatment data is used as the response variable, and the single factor list and the interaction item are used as the explanatory variables to construct a GAM interaction model, and a spline smoothing function is used to fit the nonlinear response of the interaction item to the water quality pretreatment data to obtain a second fitting result, and a significance test is performed according to the first fitting result to obtain a second test result and a list of interaction items that passed the significance test;

[0017] Visual display is performed based on the first test result, the list of single factors that passed the significance test, the second test result, and the list of interactive items that passed the significance test to show the impact of the dynamic changes in wetland hydrology on lake water quality;

[0018] By comparing the deviation interpretation of each GAM model, the contribution rate of each wetland hydrological dynamic index to lake water quality was quantified;

[0019] The GAM interactive model was used to calculate the comprehensive impact of the coupling effect of wetland hydrological dynamic changes on lake water quality, so as to quantitatively evaluate the impact of the coupling effect on water quality under different indicator combinations;

[0020] The influence of small changes in wetland hydrological dynamics indicators on lake water quality response is quantified based on response variables and explanatory variables, so as to evaluate the impact of wetland hydrological dynamics on lake water quality.

[0021] Preferably, the data cleaning step includes:

[0022] The hydrological dynamic change data and the water quality index data are grouped according to the sampling period to obtain a plurality of data groups;

[0023] Calculate the difference coefficient between the current data group and the previous data group in sequence;

[0024] Determine whether the value of the coefficient of difference is within a preset range;

[0025] If the value of the difference coefficient is not within the preset range, the corresponding data group is removed;

[0026] If the value of the difference coefficient is within the preset range, the corresponding data group will be retained until all data groups are traversed to obtain the hydrological dynamic change data and water quality index data after data cleaning.

[0027] Preferably, the coefficient of difference calculation formula is:

[0028]

[0029] Among them, p X,Y is the coefficient of difference, cov(X,Y) represents the covariance between the current data set X and the previous data set Y, α X represents the mean of the current data set X, β Y Represents the mean of the previous data set Y.

[0030] Preferably, the hydrological dynamic change data include: water level fluctuations, flow and flow direction changes, precipitation, evaporation and wetland vegetation coverage.

[0031] Preferably, the water quality index data include: water temperature, dissolved oxygen, ammonia nitrogen, total phosphorus, chlorophyll, algae abundance and eutrophication index.

[0032] Preferably, the standard for the time scale processing is the daily scale.

[0033] Preferably, the calculation formula for the contribution rate of wetland hydrological dynamic indicators to lake water quality is:

[0034]

[0035] Among them, C i is the contribution rate of wetland hydrological dynamic change index i to lake water quality, D iis the deviation explanation of wetland hydrological dynamic change index i in the GAM model, D total is the total deviance explained by the GAM interaction model.

[0036] Preferably, the calculation formula for the influence of coupling effect on water quality under different indicator combinations is:

[0037]

[0038] Among them, C ij D is the impact of wetland hydrological dynamic change indicators i and j on water quality; ij is the deviation explanation of the GAM interaction model containing the interaction term i×j.

[0039] Preferably, the calculation formula for the influence of a small change in the wetland hydrological dynamic change index on the lake water quality response is:

[0040]

[0041] Among them, S i is the impact of small changes on lake water quality response, Y is the lake water quality index, X i is the wetland hydrological dynamic change index i, The lake water quality index Y is the wetland hydrological dynamic change index X i The partial derivative of .

[0042] The present invention discloses the following technical effects:

[0043] The present invention provides a method for evaluating the impact of wetland hydrological dynamic changes on lake water quality, including: collecting hydrological dynamic change data of target wetlands and water quality index data of target lakes according to a preset sampling period; performing data cleaning and time scale processing on the hydrological dynamic change data and the water quality index data to obtain hydrological preprocessing data and water quality preprocessing data; using the Pearson correlation analysis method to calculate the correlation coefficients between the hydrological preprocessing data and between the hydrological preprocessing data and the water quality preprocessing data, and eliminating the collinear variables in the hydrological preprocessing data according to the correlation coefficient to obtain a list of wetland hydrological dynamic change indicators; determining a comprehensive index according to the list of wetland hydrological dynamic change indicators; each of the comprehensive indexes represents a key dimension of wetland hydrological dynamic change; fitting and significance testing are performed according to the comprehensive index and a preset generalized additive model, and the fitting results and the test results are visualized to evaluate the impact of wetland hydrological dynamic changes on lake water quality. The present invention can not only accurately evaluate the impact of wetland hydrological dynamic changes on lake water quality, but also provide important scientific basis and technical support for wetland ecosystem protection and lake water quality management. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0045] Figure 1 A flow chart of a method provided by an embodiment of the present invention;

[0046] Figure 2 A data cleaning flow chart provided for an embodiment of the present invention;

[0047] Figure 3 A schematic diagram of an evaluation process provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] The purpose of the present invention is to provide a method for evaluating the impact of dynamic changes in wetland hydrology on lake water quality, which can not only accurately evaluate the impact of dynamic changes in wetland hydrology on lake water quality, but also provide important scientific basis and technical support for wetland ecosystem protection and lake water quality management.

[0050] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0051] Figure 1 A flow chart of a method provided by an embodiment of the present invention, such as Figure 1 As shown, the present invention provides a method for evaluating the impact of wetland hydrological dynamic changes on lake water quality, comprising:

[0052] Step 100: Collect the hydrological dynamic change data of the target wetland and the water quality index data of the target lake according to the preset sampling period; the hydrological dynamic change data include: water level fluctuation, flow and flow direction changes, precipitation, evaporation and wetland vegetation coverage; the water quality index data include: water temperature, dissolved oxygen, ammonia nitrogen, total phosphorus, chlorophyll, algae abundance and eutrophication index.

[0053] Step 200: performing data cleaning and time scale processing on the hydrological dynamic change data and the water quality index data to obtain hydrological preprocessing data and water quality preprocessing data;

[0054] Step 300: using the Pearson correlation analysis method to calculate the correlation coefficients between the hydrological preprocessing data and between the hydrological preprocessing data and the water quality preprocessing data, and eliminating the collinear variables in the hydrological preprocessing data according to the correlation coefficients to obtain a list of wetland hydrological dynamic change indicators;

[0055] Step 400: Determine a comprehensive index based on the wetland hydrological dynamic change index list; each of the comprehensive indexes represents a key dimension of the wetland hydrological dynamic change;

[0056] Step 500: Fitting and significance testing are performed based on the comprehensive index and the preset generalized additive model, and the fitting results and the test results are visualized to evaluate the impact of wetland hydrological dynamic changes on lake water quality.

[0057] Specifically, step 100 of this embodiment includes:

[0058] Step 101: Data Collection Preparation and Planning

[0059] According to the preset sampling cycle (such as daily or hourly scale), formulate a monitoring plan for wetlands and lakes. First, determine the monitoring points of the target wetlands and lakes to ensure that the monitoring points can cover the key areas of dynamic changes in wetland hydrology (such as areas with significant water level fluctuations, major inflow and outflow points, etc.) and representative areas of lake water quality (such as the center of the lake, near the shore and the water inlet, etc.). The collection of hydrological dynamic change data can be achieved by installing automatic monitoring equipment (such as water level meters, current meters, rain gauges and evaporation dishes), and the wetland vegetation coverage rate can be obtained through remote sensing images (such as satellite images or drone aerial photography) combined with ground field surveys. The collection of lake water quality index data can be achieved by regularly collecting water samples through water quality sampling equipment (such as multi-parameter water quality meters), and analyzing indicators such as water temperature, dissolved oxygen, ammonia nitrogen, total phosphorus, chlorophyll, algae abundance and eutrophication index in the laboratory.

[0060] Step 102: Data Recording and Storage

[0061] During the collection process, ensure that all monitoring equipment is calibrated regularly to ensure the accuracy of the data. Hydrological dynamic change data (such as water level, flow, precipitation, evaporation) can be recorded in real time by automatic recorders and stored as electronic data files (such as CSV format). Wetland vegetation coverage data extracts vegetation coverage information through remote sensing image processing software (such as ArcGIS or ENVI) and stores it in raster or vector data format. Water quality index data are recorded in standardized tables through laboratory analysis results to ensure that the data timestamp is consistent with the hydrological dynamic change data. All data must be stored in a unified database and marked according to time and spatial location for subsequent analysis and processing.

[0062] Preferably, if Figure 2 As shown, the data cleaning step of this embodiment includes:

[0063] Step 201: grouping the hydrological dynamic change data and water quality index data according to the sampling period to obtain multiple data groups;

[0064] Step 202: Calculate the difference coefficient between the current data group and the previous data group in sequence;

[0065] Step 203: Determine whether the value of the difference coefficient is within a preset range;

[0066] Step 204: If the value of the difference coefficient is not within the preset range, the corresponding data group is removed;

[0067] Step 205: If the value of the difference coefficient is within the preset range, the corresponding data group is retained until all data groups are traversed to obtain the hydrological dynamic change data and water quality index data after data cleaning.

[0068] Preferably, the coefficient of difference calculation formula is:

[0069]

[0070] Among them, p X,Y is the coefficient of difference, cov(X,Y) represents the covariance between the current data set X and the previous data set Y, α X represents the mean of the current data set X, β Y Represents the mean of the previous data set Y.

[0071] Specifically, since the data acquisition device may be affected by its own parameters or environmental factors, the measured value collected by the data acquisition device at a certain moment may deviate greatly from the actual value. Therefore, the present application can screen out abnormal monitoring values ​​through the coefficient of difference, thereby ensuring the accuracy of the data.

[0072] Preferably, the standard for the time scale processing is the daily scale.

[0073] Specifically, after completing data cleaning, this embodiment converts the cleaned hydrological dynamic change data and water quality index data into a daily time scale. Specifically, for hourly scale data, the arithmetic mean (such as continuous variables such as water level fluctuations and flow) or cumulative value (such as cumulative variables such as precipitation) of each day is calculated to unify the time scale. For water quality index data (such as dissolved oxygen, total phosphorus, etc.), the daily average value is also calculated to ensure the consistency of the hydrological dynamic change data and water quality index data in the time scale. Finally, the hydrological preprocessing data and water quality preprocessing data on a daily scale are output to provide standardized input data for subsequent analysis.

[0074] Preferably, if Figure 3 As shown, this embodiment performs fitting and significance testing based on the comprehensive index and the preset generalized additive model, and visualizes the fitting results and the test results to evaluate the impact of wetland hydrological dynamic changes on lake water quality, including:

[0075] Taking the comprehensive index as the explanatory variable and the water quality pretreatment data as the response variable, the spline smoothing function in the GAM model was used for fitting to obtain the first fitting result, and a significance test was performed based on the first fitting result to obtain the first test result and a list of single factors that passed the significance test;

[0076] The indicators in the single factor list that passed the significance test were combined in pairs to construct interaction items, and the water quality pretreatment data was used as the response variable, and the single factor list and interaction items were used as explanatory variables to construct a GAM interaction model. The spline smoothing function was used to fit the nonlinear response of the interaction item to the water quality pretreatment data to obtain the second fitting result, and a significance test was performed based on the first fitting result to obtain the second test result and a list of interaction items that passed the significance test;

[0077] Visual display is performed based on the first test results, the list of single factors that passed the significance test, the second test results, and the list of interactive items that passed the significance test to show the impact of wetland hydrological dynamic changes on lake water quality;

[0078] By comparing the deviation interpretation of each GAM model, the contribution rate of each wetland hydrological dynamic index to lake water quality was quantified;

[0079] The GAM interactive model was used to calculate the comprehensive impact of the coupling effect of wetland hydrological dynamic changes on lake water quality, so as to quantitatively evaluate the impact of the coupling effect on water quality under different indicator combinations;

[0080] The influence of small changes in wetland hydrological dynamics indicators on lake water quality response is quantified based on response variables and explanatory variables, so as to evaluate the impact of wetland hydrological dynamics on lake water quality.

[0081] Specifically, the comprehensive index is used as the explanatory variable, the water quality pretreatment data is used as the response variable, and the spline smoothing function in the GAM model is used for fitting to obtain a first fitting result, and a significance test is performed based on the first fitting result to obtain a first test result and a list of single factors that pass the significance test, including:

[0082] First, the comprehensive index is used as the explanatory variable, and the water quality pretreatment data (such as dissolved oxygen, total phosphorus, total nitrogen and other water quality indicators) is used as the response variable to ensure that the two are consistent in time scale (such as daily scale). The generalized additive model (GAM) is used for modeling. The GAM model uses a spline smoothing function to fit the nonlinear response relationship between the comprehensive index and the water quality indicators. Specifically, the form of the GAM model is:

[0083] Y=β 0 +f(X)+∈

[0084] Among them, Y represents the water quality pretreatment data (response variable), X represents the comprehensive index (explanatory variable), f(X) is the spline smoothing function, β 0 is the intercept term, and ∈ is the error term. Through model fitting, we can get the smooth fitting result of the comprehensive index to the water quality index, which is the first fitting result.

[0085] A significance test is performed on the first fitting result to evaluate whether the impact of the comprehensive index on water quality indicators is statistically significant. The significance test is usually based on hypothesis testing, and the null hypothesis is that "the comprehensive index has no significant effect on water quality indicators". By calculating the p-value of the smoothing function, if the p-value is less than the preset significance level (such as 0.05), it is considered that the comprehensive index has a significant impact on water quality indicators. The comprehensive index that passes the significance test is recorded in the single factor list as the key variable for subsequent analysis. The results of the significance test include the p-value, deviation explained (Deviance Explained) and significance mark of each comprehensive index.

[0086] According to the results of the significance test, a list of single factors that passed the significance test is generated, and a visualization chart of the first fitting result is output. The visualization chart includes:

[0087] Horizontal axis: measured value of the comprehensive index.

[0088] Vertical axis: smoothed fitting value of comprehensive index to water quality index.

[0089] Confidence Intervals: Plot 95% confidence intervals for the smooth fit curve to demonstrate the range of uncertainty in the model fit.

[0090] Through these results, the nonlinear impact of the comprehensive index on water quality indicators can be intuitively demonstrated, laying the foundation for the subsequent construction of interaction terms and coupling effect analysis.

[0091] Specifically, the indicators in the single factor list that passed the significance test are combined in pairs to construct interaction items, and the water quality pretreatment data is used as the response variable, and the single factor list and the interaction item are used as the explanatory variables to construct a GAM interaction model, and a spline smoothing function is used to fit the nonlinear response of the interaction item to the water quality pretreatment data to obtain a second fitting result, and a significance test is performed according to the first fitting result to obtain a second test result and a list of interaction items that passed the significance test, including:

[0092] Select variables from the single-factor list that passed the significance test, calculate the correlation coefficients between these variables, and use the Pearson correlation analysis method to determine the collinearity between the variables. If the absolute value of the correlation coefficient between two variables is greater than 0.5, it is considered that there is serious collinearity, and only one of the variables is retained as the explanatory variable; if the absolute value of the correlation coefficient is less than 0.5, the two variables are directly combined to construct an interaction term. The form of the interaction term is the product of the two variables (such as X i ×X j ) is used to capture the coupling effects between variables. The variables in the single factor list and the constructed interaction terms are used as explanatory variables, and the water quality pretreatment data (such as dissolved oxygen, total phosphorus, etc.) are used as response variables to prepare the input data for the GAM interaction model.

[0093] The generalized additive model (GAM) was used to construct an interaction model, with water quality pretreatment data as the response variable and the variables and interaction terms in the single factor list as explanatory variables. The model form is:

[0094] Y=β 0 +f 1 (X i )+f 2 (X j )+f ij (X i ×X j )+∈

[0095] Among them, Y is the water quality preprocessing data, f 1 (X i ) and f 2 (X j ) is a single factor spline smoothing function, f ij (X i ×X j) is the spline smoothing function of the interaction term, β 0 is the intercept term, and ∈ is the error term. Through model fitting, the nonlinear effects of single factors and interaction terms on water quality indicators can be captured.

[0096] A significance test is performed on the fitting results of the interaction model to evaluate whether the effect of each interaction term on the water quality index is statistically significant. The significance test is based on hypothesis testing, and the null hypothesis is that "the interaction term has no significant effect on the water quality index". By calculating the p-value of the smooth function of the interaction term, if the p-value is less than the preset significance level (such as 0.05), it is considered that the interaction term has a significant effect on the water quality index. The interaction terms that pass the significance test are recorded, a list of interaction terms is generated, and the second fitting result is output, including the smoothed fitting value and deviation explanation of the interaction term.

[0097] The interaction items that pass the significance test are visualized, and three-dimensional surface maps or contour maps are drawn to intuitively show the nonlinear response of the interaction items to water quality indicators. The horizontal and vertical coordinates of the visualization graph represent the measured values ​​of the two explanatory variables, respectively, and the vertical coordinates or colors represent the smoothed fitting values ​​of the interaction items to the water quality indicators. At the same time, this embodiment adds a 95% confidence interval to the graph to show the uncertainty range of the model fitting. Through these visualization results, the influence process of the coupling effect between the dynamic change indicators of wetland hydrology on the water quality of lakes can be clearly portrayed, providing a scientific basis for subsequent contribution rate calculations and management decisions.

[0098] Optionally, in this embodiment, a visualization is performed based on the first test result, the list of single factors that passed the significance test, the second test result, and the list of interactive items that passed the significance test to show the impact of the dynamic changes in wetland hydrology on lake water quality, including:

[0099] According to the first test results and the list of single factors that passed the significance test, a visualization chart of the single factor model is drawn. For each single factor variable that passed the significance test, a smooth fitting curve for the lake water quality index is drawn. Specifically, the horizontal axis represents the measured value of the single factor variable (such as wetland hydrological dynamic change indicators, such as water level fluctuations, precipitation, etc.), and the vertical axis represents the smooth fitting value of the single factor variable for the lake water quality indicators (such as dissolved oxygen, total phosphorus, etc.). A 95% confidence interval is added to the figure to show the uncertainty range of the model fitting. Through these charts, the nonlinear impact process of the single factor of the dynamic change of wetland hydrology on the lake water quality can be intuitively demonstrated, which helps to identify the key driving factors.

[0100] According to the results of the second test and the list of interaction items that passed the significance test, a visualization chart of the interaction model is drawn. For each interaction item that passed the significance test, a three-dimensional surface map or contour map is drawn to show the nonlinear response of the interaction item to the lake water quality index. Specifically, the horizontal and vertical coordinates of the three-dimensional surface map represent the measured values ​​of the two interaction variables (such as water level fluctuation and precipitation), and the vertical coordinate represents the smoothed fitting value of the interaction item on the lake water quality index; the contour map uses color gradients to represent the impact intensity of the interaction item. These charts can intuitively reveal the comprehensive impact of the coupling effect between the dynamic change indicators of wetland hydrology on the lake water quality.

[0101] The visualization results of the single factor model and the interaction model are integrated into a comprehensive display to form a complete visualization report on the impact of dynamic changes in wetland hydrology on lake water quality. The report includes smooth fitting curves of single factors, three-dimensional surface maps or contour maps of interaction terms, and annotations of the deviation explained and significance test results of each model. Through these visualization results, the impact of dynamic changes in wetland hydrology on lake water quality can be fully demonstrated, and the contribution of single factors and coupling effects can be quantitatively evaluated, providing a scientific basis for wetland ecosystem protection and lake water quality management.

[0102] Preferably, the calculation formula for the contribution rate of wetland hydrological dynamic indicators to lake water quality is:

[0103]

[0104] Parameter explanation:

[0105] C i :Contribution rate (percentage) of wetland hydrological dynamic change index i to lake water quality.

[0106] D i : Deviation Explained of wetland hydrological dynamic change index i in the single factor model, that is, the independent explanatory ability of this index on lake water quality.

[0107] D total : The total deviation explanation of the multi-factor model, that is, the total explanatory power of all wetland hydrological dynamic change indicators on lake water quality.

[0108] Preferably, the calculation formula for the influence of coupling effect on water quality under different indicator combinations is:

[0109]

[0110] Parameter explanation:

[0111] C ij: Coupling contribution rate (percentage) of wetland hydrological dynamic change indicators i and j.

[0112] D ij : The bias explanation of the multi-factor GAM model containing the interaction term i×j.

[0113] D i , D j : are the deviation explanations of wetland hydrological dynamic change indicators i and j in the single factor model.

[0114] D total : Total deviance explained by the multifactor model.

[0115] Preferably, the calculation formula for the influence of a small change in the wetland hydrological dynamic change index on the lake water quality response is:

[0116]

[0117] Parameter explanation:

[0118] S i : Sensitivity coefficient of wetland hydrological dynamic change index i.

[0119] Y: Lake water quality index (response variable).

[0120] X i :Wetland hydrological dynamic change index i (explanatory variable).

[0121] Lake water quality index Y versus wetland hydrological dynamics index X i The partial derivative of .

[0122] The beneficial effects of the present invention are as follows:

[0123] (1) The present invention covers the complete process of assessing the impact of wetland hydrological dynamic changes on lake water quality, from data collection to model construction, ensuring the systematic nature of the analysis; it includes a multi-step process from data cleaning, correlation analysis to comprehensive index construction and nonlinear modeling, which can comprehensively capture the multi-dimensional impact of wetland hydrological dynamic changes on lake water quality.

[0124] (2) The present invention eliminates collinear variables through Pearson correlation analysis, reduces the interference of redundant information between variables, and improves the accuracy of the evaluation results; integrates multiple wetland hydrological dynamic change indicators into key dimensions, so that complex multidimensional data are effectively simplified, while retaining the main information and improving the fitting accuracy of the model.

[0125] (3) The present invention adopts the generalized additive model (GAM) and its spline smoothing function, which can capture the nonlinear relationship between the dynamic changes of wetland hydrology and lake water quality, and significantly improves the model's ability to describe complex ecosystems.

[0126] (4) The present invention screens out key influencing factors through significance tests, ensuring that the selected variables have statistical significance for lake water quality, thereby improving the scientific nature of the model; through the visualization of the model fitting results (such as smooth curves, three-dimensional interactive graphs, etc.), the impact of wetland hydrological dynamic changes on lake water quality is intuitively reflected, providing researchers and decision makers with a clear basis for analysis.

[0127] (5) The time scale flexibility of the present invention: through data cleaning and time scale processing, it can flexibly adapt to data of different time granularities (such as hours, days, and months), and is suitable for different research needs; the method is applicable to various types of wetland and lake ecosystems, and can not only evaluate the impact of specific wetlands on lake water quality, but can also be extended to the study of other hydrological ecosystems.

[0128] (6) Through significance tests and model fitting results, the present invention can quantify the impact of wetland hydrological dynamic changes on lake water quality, providing a scientific basis for wetland protection, lake water quality management and pollution control; through comprehensive indexes and nonlinear modeling results, it can identify the hydrological dynamic change factors that have the greatest impact on lake water quality, helping managers to formulate more targeted ecological protection measures.

[0129] (7) The present invention reduces the complexity of model calculation by constructing a comprehensive index and eliminating collinear variables, while retaining key information, making the model calculation more efficient. This method can reveal the complex coupling relationship between wetland hydrological dynamics and lake water quality, especially the interactive effects between multiple factors, and provides scientific support for further understanding the functions and mechanisms of wetland ecosystems.

[0130] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0131] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for assessing the impact of wetland hydrological dynamics on lake water quality, characterized in that: include: Collect hydrological dynamic change data of target wetlands and water quality index data of target lakes according to the preset sampling period; Performing data cleaning and time scale processing on the hydrological dynamic change data and the water quality index data to obtain hydrological preprocessing data and water quality preprocessing data; The Pearson correlation analysis method is used to calculate the correlation coefficients between the hydrological preprocessing data and between the hydrological preprocessing data and the water quality preprocessing data, and the collinear variables in the hydrological preprocessing data are eliminated according to the correlation coefficients to obtain a list of wetland hydrological dynamic change indicators; Determine a comprehensive index based on the list of wetland hydrological dynamic change indicators; each of the comprehensive indexes represents a key dimension of wetland hydrological dynamic change; Fitting and significance testing are performed based on the comprehensive index and the preset generalized additive model, and the fitting results and test results are visualized to evaluate the impact of wetland hydrological dynamics on lake water quality.

2. The method for evaluating the impact of wetland hydrological dynamic changes on lake water quality according to claim 1 is characterized in that: Fitting and significance testing are performed based on the comprehensive index and the preset generalized additive model, and the fitting results and test results are visualized to evaluate the impact of wetland hydrological dynamics on lake water quality, including: Taking the comprehensive index as the explanatory variable and the water quality pretreatment data as the response variable, the spline smoothing function in the GAM model is used for fitting to obtain a first fitting result, and a significance test is performed based on the first fitting result to obtain a first test result and a list of single factors that pass the significance test; The indicators in the single factor list that passed the significance test are combined in pairs to construct interaction items, and the water quality pretreatment data is used as the response variable, and the single factor list and the interaction item are used as the explanatory variables to construct a GAM interaction model, and a spline smoothing function is used to fit the nonlinear response of the interaction item to the water quality pretreatment data to obtain a second fitting result, and a significance test is performed according to the first fitting result to obtain a second test result and a list of interaction items that passed the significance test; Visual display is performed based on the first test result, the list of single factors that passed the significance test, the second test result, and the list of interactive items that passed the significance test to show the impact of the dynamic changes in wetland hydrology on lake water quality; By comparing the deviation interpretation of each GAM model, the contribution rate of each wetland hydrological dynamic index to lake water quality was quantified; The GAM interactive model was used to calculate the comprehensive impact of the coupling effect of wetland hydrological dynamic changes on lake water quality, so as to quantitatively evaluate the impact of the coupling effect on water quality under different indicator combinations; The influence of small changes in wetland hydrological dynamics indicators on lake water quality response is quantified based on response variables and explanatory variables, so as to evaluate the impact of wetland hydrological dynamics on lake water quality.

3. The method for evaluating the impact of wetland hydrological dynamic changes on lake water quality according to claim 1 is characterized in that: The data cleaning steps include: The hydrological dynamic change data and the water quality index data are grouped according to the sampling period to obtain a plurality of data groups; Calculate the difference coefficient between the current data group and the previous data group in sequence; Determine whether the value of the coefficient of difference is within a preset range; If the value of the difference coefficient is not within the preset range, the corresponding data group is removed; If the value of the difference coefficient is within the preset range, the corresponding data group will be retained until all data groups are traversed to obtain the hydrological dynamic change data and water quality index data after data cleaning.

4. The method for assessing the impact of wetland hydrological dynamic changes on lake water quality according to claim 3 is characterized in that: The coefficient of difference calculation formula is: Among them, p X,Y is the coefficient of difference, cov(X,Y) represents the covariance between the current data set X and the previous data set Y, α X represents the mean of the current data set X, β Y Represents the mean of the previous data set Y.

5. The method for evaluating the impact of wetland hydrological dynamic changes on lake water quality according to claim 1 is characterized in that: The hydrological dynamic change data include: water level fluctuations, flow and flow direction changes, precipitation, evaporation and wetland vegetation coverage.

6. The method for assessing the impact of wetland hydrological dynamics on lake water quality according to claim 1, characterized in that: The water quality index data include: water temperature, dissolved oxygen, ammonia nitrogen, total phosphorus, chlorophyll, algae abundance and eutrophication index.

7. The method for evaluating the impact of wetland hydrological dynamic changes on lake water quality according to claim 1 is characterized in that: The standard for the time scale processing is the daily scale.

8. The method for assessing the impact of wetland hydrological dynamics on lake water quality according to claim 2, characterized in that: The calculation formula for the contribution rate of wetland hydrological dynamic indicators to lake water quality is: Among them, C i is the contribution rate of wetland hydrological dynamic change index i to lake water quality, D i is the deviation explanation of wetland hydrological dynamic change index i in the GAM model, D total is the total deviation explained by the GAM interaction model.

9. The method for evaluating the impact of wetland hydrological dynamic changes on lake water quality according to claim 8 is characterized in that: The calculation formula for the influence of coupling effect on water quality under different index combinations is: Among them, C ij D is the impact of wetland hydrological dynamic change indicators i and j on water quality; ij is the deviation explanation of the GAM interaction model containing the interaction term i×j.

10. The method for assessing the impact of wetland hydrological dynamics on lake water quality according to claim 9, characterized in that: The calculation formula for the influence of a small change in the wetland hydrological dynamic change index on the lake water quality response is: Among them, S i is the impact of small changes on lake water quality response, Y is the lake water quality index, X i is the wetland hydrological dynamic change index i, The lake water quality index Y is the wetland hydrological dynamic change index X i The partial derivative of .

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