Solid waste pile point groundwater pollution diffusion trend evaluation method

Abstract

The invention provides a solid waste pile point groundwater pollution diffusion trend assessment method, and relates to the technical field of water resource pollution assessment, and the method comprises the steps: obtaining the monitoring data of a target region; obtaining the data volume of the monitoring data, obtaining a first index feature, judging whether the trend change of the monitoring data is relatively stable or not, obtaining a second index feature, judging whether the data distribution of the monitoring data meets a preset statistical hypothesis or not, obtaining a third index feature, judging whether the monitoring data has a seasonal feature or not, and obtaining a fourth index feature; screening preset groundwater pollution diffusion trend evaluation methods according to all the index characteristics to obtain an optimal evaluation method; and carrying out groundwater pollution diffusion trend analysis and evaluation on the monitoring data by using an optimal evaluation method to obtain an evaluation result. According to the method, the pollution diffusion trend of the site groundwater can be evaluated more efficiently, flexibly and at low cost, and a thought method is provided for accurate risk management and control of the polluted site groundwater.

Description

Technical Field

[0001] The present invention relates to the technical field of water resource pollution assessment, and in particular to a method for assessing the diffusion trend of groundwater pollution at a solid waste dump site. Background Art

[0002] In the process of conducting groundwater risk assessment at solid waste dump sites, the traditional method usually uses groundwater monitoring data to compare with the relevant specified indicator limits or regional groundwater background levels (i.e., single comparison method) to assess the risk level. For example, for groundwater in suspected contaminated areas and land boundaries, pollutants are evaluated using one standard limit; groundwater pollutants at groundwater sensitive targets are evaluated using another standard limit.

[0003] Relevant regulations also require that after the storage site or landfill is closed, the groundwater monitoring system should continue to operate normally, with a monitoring frequency of at least once every six months, until the groundwater quality does not exceed the groundwater background level for two consecutive years. After the tailings pond is closed, if no leachate is generated for two consecutive years or the generated leachate can be discharged stably and meet the standards without treatment, and the groundwater quality does not exceed the water quality of the upstream monitoring wells or the regional groundwater background level for two consecutive years, its environmental supervision level may no longer be divided. After the tailings pond is closed, the operation and management units of the tailings pond shall take measures to ensure that the groundwater quality monitoring wells continue to operate normally, and continue to monitor the groundwater quality in accordance with relevant regulations until the downstream groundwater quality does not exceed the upstream groundwater quality or the regional groundwater background level for two consecutive years.

[0004] In general, the traditional single comparison method has many limitations and irrationalities, and imposes strict requirements on groundwater risk supervision, which significantly increases the cost of groundwater risk management at solid waste dump sites. Summary of the invention

[0005] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a method for assessing the pollution diffusion trend of groundwater at solid waste dump sites, which can more efficiently, flexibly and at low cost assess the pollution diffusion trend of groundwater at the site, and provide ideas and methods for precise risk control of groundwater at polluted sites.

[0006] To achieve the above object, the present invention provides the following solutions: A method for assessing the diffusion trend of groundwater pollution at solid waste dump sites, comprising: Obtain monitoring data for target areas; Obtaining the data volume of the monitoring data to obtain a first indicator feature, and determining whether the trend change of the monitoring data is relatively stable to obtain a second indicator feature, and determining whether the data distribution of the monitoring data meets a preset statistical hypothesis to obtain a third indicator feature, and determining whether the monitoring data has seasonal characteristics to obtain a fourth indicator feature; Screening a preset groundwater pollution diffusion trend evaluation method according to the first indicator feature, the second indicator feature, the third indicator feature, and the fourth indicator feature to obtain an optimal evaluation method; The optimal evaluation method is used to analyze and evaluate the groundwater pollution diffusion trend of the monitoring data to obtain an evaluation result.

[0007] Preferably, judging whether the trend change of the monitoring data is relatively stable to obtain the second indicator feature includes: The Z-score method is used to calculate the Z score of each data point in the monitoring data; Determine the data points whose Z scores exceed ±3 as outliers; If the proportion of abnormal points in all the data points exceeds 10%, the second indicator feature is determined as a significantly unstable trend change; otherwise, the second indicator feature is determined as a stable trend change.

[0008] Preferably, the statistical assumptions include: polynomial regression, exponential regression and logarithmic regression.

[0009] Preferably, determining whether the monitoring data has seasonal characteristics to obtain the fourth indicator characteristic includes: Draw a time series graph based on the monitoring data; Check whether there is a periodic pattern in the monitoring data according to the time series graph. If a similar pattern repeats in the monitoring data within a specific time period, the fourth indicator feature is determined to have a seasonal feature; otherwise, the fourth indicator feature is determined to have no seasonal feature.

[0010] Preferably, the groundwater pollution diffusion trend evaluation method includes: analytical model method, regression analysis method, Theil-Sen slope estimation method and Mann-Kendall trend test method.

[0011] Preferably, the preset groundwater pollution diffusion trend evaluation method is screened according to the first indicator feature, the second indicator feature, the third indicator feature and the fourth indicator feature to obtain the optimal evaluation method, including: Determine whether the first indicator feature is less than a first preset threshold value to obtain a first judgment result. If the first judgment result is yes, determine the analytical model method as the optimal evaluation method. If the first judgment result is no, determine whether the fourth indicator feature has seasonal characteristics to obtain a second judgment result. If the second judgment result is yes, determine the Mann-Kendall trend test method as the optimal evaluation method. If the second judgment result is no, then judging whether the second indicator feature is a stable trend change, and obtaining a third judgment result; if the third judgment result is no, then determining the Theil-Sen slope estimation method or the Mann-Kendall trend test method as the optimal evaluation method according to the first indicator feature; If the third judgment result is yes, then determine whether the third indicator characteristic meets the preset statistical hypothesis to obtain the fourth judgment result. If the fourth judgment result is yes, then determine the regression analysis method as the optimal evaluation method. If the fourth judgment result is no, then determine either the Theil-Sen slope estimation method or the Mann-Kendall trend test method as the optimal evaluation method.

[0012] Preferably, determining the Theil-Sen slope estimation method or the Mann-Kendall trend test method as the optimal evaluation method according to the first indicator feature includes: Determine whether the first indicator feature is less than a second preset threshold value. If so, determine the Theil-Sen slope estimation method as the optimal evaluation method; if not, determine the Mann-Kendall trend test method as the optimal evaluation method.

[0013] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: The present invention provides a method for assessing the diffusion trend of groundwater pollution at a solid waste dump site, comprising: obtaining monitoring data of a target area; obtaining the data volume of the monitoring data to obtain a first indicator feature, and judging whether the trend change of the monitoring data is relatively stable to obtain a second indicator feature, and judging whether the data distribution of the monitoring data meets a preset statistical hypothesis to obtain a third indicator feature, and judging whether the monitoring data has seasonal characteristics to obtain a fourth indicator feature; screening a preset groundwater pollution diffusion trend assessment method according to the first indicator feature, the second indicator feature, the third indicator feature, and the fourth indicator feature to obtain an optimal assessment method; using the optimal assessment method to analyze and assess the diffusion trend of groundwater pollution in the monitoring data to obtain an assessment result. The present invention can assess the diffusion trend of groundwater pollution at a site more efficiently, flexibly, and at a low cost, and provide a method for precise risk control of groundwater at a contaminated site. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] 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.

[0015] Figure 1 A flow chart of a method provided by an embodiment of the present invention; Figure 2 A schematic diagram of the judgment logic provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0016] 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.

[0017] The purpose of the present invention is to provide a method for assessing the pollution diffusion trend of groundwater at solid waste dump sites, which can more efficiently, flexibly and at low cost assess the pollution diffusion trend of groundwater at the site, and provide ideas and methods for precise risk control of groundwater at polluted sites.

[0018] 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.

[0019] 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 assessing the diffusion trend of groundwater pollution at a solid waste dump, comprising: Step 100: Acquire monitoring data of the target area; Step 200: Obtain the data volume of the monitoring data, obtain the first indicator feature, and determine whether the trend change of the monitoring data is relatively stable, obtain the second indicator feature, and determine whether the data distribution of the monitoring data meets the preset statistical hypothesis, obtain the third indicator feature, and determine whether the monitoring data has seasonal characteristics, and obtain the fourth indicator feature; Step 300: Screening a preset groundwater pollution diffusion trend evaluation method according to the first indicator feature, the second indicator feature, the third indicator feature and the fourth indicator feature to obtain an optimal evaluation method; Step 400: Analyze and evaluate the groundwater pollution diffusion trend of the monitoring data using the optimal evaluation method to obtain an evaluation result.

[0020] Preferably, judging whether the trend change of the monitoring data is relatively stable to obtain the second indicator feature includes: The Z-score method is used to calculate the Z score of each data point in the monitoring data; Determine the data points whose Z scores exceed ±3 as outliers; If the proportion of abnormal points in all the data points exceeds 10%, the second indicator feature is determined as a significantly unstable trend change; otherwise, the second indicator feature is determined as a stable trend change.

[0021] Specifically, this embodiment uses the Z-Score method to identify the number of outliers: the Z-score is an indicator of the number of standard deviations between a data point and the mean. Generally, data points with a Z-score exceeding ±3 are considered outliers. If the proportion of outliers in the data exceeds 10%, it can generally be considered that the trend change is significantly unstable.

[0022] Preferably, the statistical assumptions include: polynomial regression, exponential regression and logarithmic regression.

[0023] Preferably, determining whether the monitoring data has seasonal characteristics to obtain the fourth indicator characteristic includes: Draw a time series graph based on the monitoring data; Check whether there is a periodic pattern in the monitoring data according to the time series graph. If a similar pattern repeats in the monitoring data within a specific time period, the fourth indicator feature is determined to have a seasonal feature; otherwise, the fourth indicator feature is determined to have no seasonal feature.

[0024] Optionally, this embodiment visually checks whether there is a periodic pattern in the data by drawing a time series graph. If the data repeats similar patterns within a specific time period, this indicates the presence of seasonal characteristics.

[0025] Preferably, the groundwater pollution diffusion trend evaluation method includes: analytical model method, regression analysis method, trend test method (Theil-Sen slope estimation method, Mann-Kendall trend test method).

[0026] Specifically, the analytical model method uses the analytical model of lateral migration of solute groundwater (such as the steady-state Domenico model, the non-steady-state Domenico model, and the Ogata Banks model) to evaluate the spatiotemporal variation of pollutant concentrations in aquifers. When the amount of monitoring data n is small (n < 6), the analytical model method is used. Based on regional geological and hydrogeological conditions and solid waste landfill pollution data, pollution simulation and prediction analysis are carried out to simulate the pollution process. After expanding a certain amount of data, regression analysis or trend test methods (Theil-Sen slope estimation method, Mann-Kendall trend test method) are used to evaluate the pollution diffusion trend.

[0027] Furthermore, regression analysis and trend test methods are used to evaluate the spread of groundwater pollution by analyzing the trend (increasing or decreasing trend) of long-term series monitoring data of pollutant concentrations in groundwater.

[0028] Among them, regression analysis aims to determine the correlation between the dependent variable and certain independent variables, establish a regression equation (function expression) with good correlation, and add extrapolation to predict the changing trend of the dependent variable. Common regression analysis methods include linear regression, polynomial regression, exponential regression, and logarithmic regression.

[0029] The conditions for judging the stability of diffusion trend by regression analysis are as follows: at a confidence level of 95% (i.e., P value < 0.05), if the slope of the trend line is significantly greater than 0, it means that the concentration of groundwater pollutants is on an upward trend; if the slope of the trend line is significantly less than 0, it means that the concentration of groundwater pollutants is on a downward trend; if the slope of the trend line is not significantly different from 0, it means that the concentration of groundwater pollutants is stable. When the concentration of pollutants in groundwater is stable or on a downward trend, it can be judged that the groundwater risk is small.

[0030] Among them, the trend test method is to determine the direction or magnitude of the increase or decrease of groundwater pollutant concentrations by comparing the long-term series monitoring data, so as to grasp the trend of groundwater monitoring data or find abnormal changes. Typical trend test methods are Theil-Sen slope estimation method and Mann-Kendall trend test method.

[0031] Theil-Sen slope estimation method, also known as Sen slope estimation, is a robust nonparametric statistical trend calculation method. This method calculates the slope between two pairs of data in the time series and takes the median of the slope as the overall trend of the time series change. This method has high computational efficiency and is insensitive to outliers. It is suitable for trend analysis of small sample data (6≤data volume n<10).

[0032] The Mann-Kendal (MK) trend test is a nonparametric time series trend test method that does not require the measured values ​​to follow a normal distribution and is not affected by missing values ​​and outliers. It is suitable for significant trend tests (monotonic growth or downward trend) of long time series data. This method is widely used in environmental monitoring, climate change, water resources management and other fields. The Mann-Kendall trend test method has certain requirements for the amount of data n (usually n≥10).

[0033] When the trend test method (i.e., Theil-Sen slope estimation method and Mann-Kendall trend test method) is used for the diffusion trend of groundwater pollution at solid waste dump sites, the stability judgment conditions of the diffusion trend are as follows: at a 95% confidence level (i.e., P value < 0.05), if the pollutant concentration has a trend of increasing or decreasing over time, it means that the groundwater pollutant concentration is showing an upward or downward trend; if the trend of the pollutant concentration over time is not significant, it is considered that the diffusion has stabilized. When the pollutant concentration in the groundwater shows a steady state or a downward trend, it can be judged that the groundwater risk is small.

[0034] The advantages and disadvantages of each method can be seen in Table 1.

[0035] Table 1 Comparison table of various methods in this embodiment like Figure 2 As shown, in this embodiment, the preset groundwater pollution diffusion trend evaluation method is screened according to the first indicator feature, the second indicator feature, the third indicator feature and the fourth indicator feature to obtain the optimal evaluation method, including: It is determined whether the first indicator characteristic is less than the first preset threshold value to obtain a first judgment result. If the first judgment result is yes, the analytical model method is determined as the optimal evaluation method. If the first judgment result is no, it is determined whether the fourth indicator characteristic has seasonal characteristics to obtain a second judgment result. If the second judgment result is yes, the Mann-Kendall trend test method is determined as the optimal evaluation method. It takes 4 to 8 quarters of monitoring data to determine whether the groundwater remediation effect meets the standard according to the preset standard (the preset standard can refer to the "Technical Guidelines for Groundwater Remediation and Risk Control of Contaminated Land" (HJ25.6-2019)). At the same time, considering that the regression analysis method usually requires at least 5 data points for fitting analysis, the first preset threshold in this embodiment is set to 6.

[0036] If the second judgment result is no, then determine whether the second indicator feature is a stable trend change, and obtain a third judgment result. If the third judgment result is no, then determine the Theil-Sen slope estimation method or the Mann-Kendall trend test method as the optimal evaluation method according to the first indicator feature; exemplary, determine the Theil-Sen slope estimation method or the Mann-Kendall trend test method as the optimal evaluation method according to the first indicator feature, including: determine whether the first indicator feature is less than the second preset threshold value, if so, determine the Theil-Sen slope estimation method as the optimal evaluation method; if not, determine the Mann-Kendall trend test method as the optimal evaluation method. The Mann-Kendall trend test method requires the data volume n≥10, so the second preset threshold value of this embodiment is set to 10. When the data volume n is large (n≥10), the Mann-Kendall trend test method is selected; when the data volume n is large (6≤n<10), the Theil-Sen slope estimation method is selected.

[0037] If the third judgment result is yes, then determine whether the third indicator characteristic meets the preset statistical hypothesis to obtain the fourth judgment result. If the fourth judgment result is yes, then determine the regression analysis method as the optimal evaluation method. If the fourth judgment result is no, then determine either the Theil-Sen slope estimation method or the Mann-Kendall trend test method as the optimal evaluation method.

[0038] Specifically, when there are many outliers (i.e., the change trend is unstable), this embodiment recommends using the Theil-Sen slope estimation method or the Mann-Kendall trend test method; the difference between the two is that the Theil-Sen slope estimation method is for a small amount of data, while the Mann-Kendall trend test method is for a large amount of data; in addition, only the Mann-Kendall trend test method can consider the seasonal characteristics of the data.

[0039] As another optional implementation, in this embodiment, whether the data distribution satisfies certain statistical assumptions or has a monotonic trend: whether it conforms to a certain regression model (i.e., satisfies certain statistical assumptions) is determined based on the distribution characteristics of the data and prior knowledge. If the fitting significance is good (e.g., P < 0.05), regression analysis is preferred (because quantitative prediction can be made). If the fitting significance is poor, further analysis is performed to determine whether the data has a monotonic trend. If the data has a monotonic trend, the Theil-Sen slope estimation method or the Mann-Kendall trend test method is used (the difference between the two is that the former is for a small amount of data, while the latter is for a large amount of data); when the data has no monotonic trend and the data distribution satisfies certain statistical assumptions, regression analysis (e.g., polynomial regression, exponential regression, logarithmic regression, etc.) is used.

[0040] Furthermore, when there are no monitoring wells or monitoring data are very scarce, it is recommended to use analytical modeling methods based on regional geological and hydrogeological empirical parameters, combined with solid waste landfill pollution data, to conduct pollution simulation and prediction analysis, simulate the pollution occurrence process, evaluate and determine the pollution change trend, and then use regression analysis or trend test methods to evaluate the diffusion trend after expanding a certain amount of data.

[0041] In addition, if the data characteristics are not obvious, multiple methods can be used at the same time, and finally a comprehensive analysis and judgment can be made based on the results of different evaluation methods.

[0042] The beneficial effects of the present invention are as follows: The present invention can effectively solve the limitations and irrationality of the traditional single comparison method, and can evaluate the pollution diffusion trend of groundwater on site more efficiently, flexibly and at low cost, providing ideas and methods for precise risk control of groundwater in polluted sites.

[0043] 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.

[0044] 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 diffusion trend of groundwater pollution at solid waste dump sites, characterized in that: include: Obtain monitoring data for target areas; Obtaining the data volume of the monitoring data to obtain a first indicator feature, and determining whether the trend change of the monitoring data is relatively stable to obtain a second indicator feature, and determining whether the data distribution of the monitoring data meets a preset statistical hypothesis to obtain a third indicator feature, and determining whether the monitoring data has seasonal characteristics to obtain a fourth indicator feature; Screening a preset groundwater pollution diffusion trend evaluation method according to the first indicator feature, the second indicator feature, the third indicator feature, and the fourth indicator feature to obtain an optimal evaluation method; The optimal evaluation method is used to analyze and evaluate the groundwater pollution diffusion trend of the monitoring data to obtain an evaluation result.

2. The method for assessing the diffusion trend of groundwater pollution at solid waste dump sites according to claim 1 is characterized in that: Determining whether the trend change of the monitoring data is relatively stable to obtain a second indicator feature includes: The Z-score method is used to calculate the Z score of each data point in the monitoring data; Determine the data points whose Z scores exceed ±3 as outliers; If the proportion of abnormal points in all the data points exceeds 10%, the second indicator feature is determined as a significantly unstable trend change; otherwise, the second indicator feature is determined as a stable trend change.

3. The method for assessing the diffusion trend of groundwater pollution at solid waste dump sites according to claim 1, characterized in that: The statistical assumptions include: polynomial regression, exponential regression and logarithmic regression.

4. The method for assessing the diffusion trend of groundwater pollution at solid waste dump sites according to claim 1, characterized in that: Determining whether the monitoring data has seasonal characteristics to obtain the fourth indicator characteristics includes: Draw a time series graph based on the monitoring data; Check whether there is a periodic pattern in the monitoring data according to the time series graph. If a similar pattern repeats in the monitoring data within a specific time period, the fourth indicator feature is determined to have a seasonal feature; otherwise, the fourth indicator feature is determined to have no seasonal feature.

5. The method for assessing the diffusion trend of groundwater pollution at solid waste dump sites according to claim 1, characterized in that: The groundwater pollution diffusion trend evaluation method includes: analytical model method, regression analysis method, trend test method; the trend test method includes: Theil-Sen slope estimation method and Mann-Kendall trend test method.

6. The method for assessing the diffusion trend of groundwater pollution at solid waste dump sites according to claim 5 is characterized in that: The preset groundwater pollution diffusion trend evaluation method is screened according to the first indicator feature, the second indicator feature, the third indicator feature and the fourth indicator feature to obtain the optimal evaluation method, including: Determine whether the first indicator feature is less than a first preset threshold value to obtain a first judgment result. If the first judgment result is yes, determine the analytical model method as the optimal evaluation method. If the first judgment result is no, determine whether the fourth indicator feature has seasonal characteristics to obtain a second judgment result. If the second judgment result is yes, determine the Mann-Kendall trend test method as the optimal evaluation method. If the second judgment result is no, then judging whether the second indicator feature is a stable trend change, and obtaining a third judgment result; if the third judgment result is no, then determining the Theil-Sen slope estimation method or the Mann-Kendall trend test method as the optimal evaluation method according to the first indicator feature; If the third judgment result is yes, then determine whether the third indicator characteristic meets the preset statistical hypothesis to obtain the fourth judgment result. If the fourth judgment result is yes, then determine the regression analysis method as the optimal evaluation method. If the fourth judgment result is no, then determine either the Theil-Sen slope estimation method or the Mann-Kendall trend test method as the optimal evaluation method.

7. The method for assessing the diffusion trend of groundwater pollution at solid waste dump sites according to claim 6, characterized in that: Determining the Theil-Sen slope estimation method or the Mann-Kendall trend test method as the optimal evaluation method according to the first indicator feature includes: Determine whether the first indicator feature is less than a second preset threshold value. If so, determine the Theil-Sen slope estimation method as the optimal evaluation method; if not, determine the Mann-Kendall trend test method as the optimal evaluation method.

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