CN111984930A - Method and system for identifying abnormal value of underground water level monitoring data - Google Patents
Method and system for identifying abnormal value of underground water level monitoring data Download PDFInfo
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- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
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- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
Abstract
The invention discloses a method and a system for identifying abnormal values of underground water level monitoring data, which comprises the following steps: acquiring underground water level monitoring data; respectively identifying a statistical abnormal extreme value and a local change abnormal value in the groundwater level monitoring data through a box diagram based on a statistical model and a distance model based on a water level difference; and the abnormal extreme value and the local change abnormal value are both groundwater level monitoring data abnormal values. The invention has the advantages that: the box-type graph can only identify the statistic extreme abnormal value of the groundwater level monitoring data in the whole range and cannot identify the local change abnormal value, so that the box-type graph is firstly used for preliminarily detecting the statistic abnormal value in the whole range, and then a distance model is used for finely detecting the local change abnormal value, so that all abnormal values in the groundwater level monitoring data set are comprehensively detected, and a foundation is laid for subsequently improving the quality of the groundwater level monitoring data.
Description
Technical Field
The invention relates to the field of analysis and research of underground water level data, in particular to a method and a system for identifying abnormal values of underground water level monitoring data.
Background
The underground water resource is a part of earth water resource, is closely related to atmospheric precipitation resource and surface water resource, is mutually transformed, and has important functions in social economy and ecological environment. The protection work of underground water resources directly influences the production and life of people, the shortage of water resources and the activation of contradiction between supply and demand, especially the management delay, can cause the situation of excessive exploitation of underground water resources to be aggravated, the underground water level to be continuously reduced, a plurality of wells in well irrigation areas are abandoned, the water yield is obviously reduced, and a series of ecological environment problems such as ground settlement, land desertification and the like are caused. The monitoring of the underground water is an important basis for knowing and mastering the dynamic change characteristics of the underground water, formulating reasonable development and utilization and effective protective measures, preventing and reducing the pollution of the underground water and the related ecological environment and the like. The implementation of the national underground water monitoring project forms a national underground water monitoring system integrating underground water information acquisition, transmission, treatment, analysis and service, greatly improves the underground water monitoring and service capability, masters the dynamic condition of underground water in real time, and provides technical support for analysis evaluation, early warning and scientific management of underground water resources.
In the process of underground water level data monitoring, transmission and storage, due to the influence of environment, monitoring instruments and human factors, some abnormal data are inevitably generated, so that the quality of the whole underground water monitoring data is influenced, even misleading information is provided, and the underground water super-mining treatment effect, underground water management implementation and decision making errors are caused. Therefore, the groundwater burial depth data needs to be cleaned, so that the value of the monitoring data is realized, and the availability and the efficiency of the groundwater monitoring system are improved.
The groundwater level anomaly data mainly comprise two types of statistic anomaly and change anomaly. In the whole range, extreme value data far away from most data are statistical abnormal data. Because the groundwater level belongs to the time sequence, the change is continuous, a reasonable change interval exists in the change rate, and the data beyond the interval is the abnormal change data. Currently, people have matured research on identification of data outliers. But no relevant research has been made on the identification of abnormal values of groundwater level monitoring data.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a method and a system for identifying an abnormal value of underground water level monitoring data, so as to solve the problem that the abnormal value of the underground water level monitoring data in the prior art is lack of research.
In order to achieve the purpose, the invention adopts the technical scheme that:
an identification method for abnormal values of underground water level monitoring data comprises the following steps:
acquiring underground water level monitoring data;
respectively identifying a statistical abnormal extreme value and a local change abnormal value in the groundwater level monitoring data through a box diagram based on a statistical model and a distance model based on a water level difference;
and the abnormal extreme value and the local change abnormal value are both groundwater level monitoring data abnormal values.
Further, the process of identifying statistically abnormal extreme values through the statistical model-based box graph is as follows:
sequencing the underground water level monitoring data of the single station from small to large;
acquiring a first quartile, a median and a third quartile in a groundwater level monitoring data sequence;
calculating the upper edge and the lower edge of the boxed graph according to the first quartile, the median and the third quartile;
and judging a statistical abnormal extreme value in the groundwater level monitoring data according to the upper edge and the lower edge.
Further, the calculation formula of the upper edge is as follows:
Upperlimit= Q3+（Q3- Q1）×1.5 （1）
the calculation formula of the lower edge is as follows:
Lowerlimit= Q3-（Q3- Q1）×1.5 （2）
wherein Upperlimit represents the upper edge, Lowerlimit represents the lower edge, and Q1Representing the first quartile, Q3Representing the third quartile.
Further, the process of identifying locally varying outliers by the distance model based on water head difference is as follows:
calculating the change rate of groundwater level at a plurality of adjacent moments;
calculating the mean value and the variance of the water level change rates of the plurality of underground water;
and judging local change abnormal values in the groundwater level monitoring data according to the mean value and the variance.
Further, the calculation formula of the mean value is as follows:
the formula for the variance shown is:
where μ is the mean, σ is the variance, Δ XiThe change rate of the groundwater level at the adjacent moment is n, and the n is the total number of the change rates of the groundwater level at the adjacent moment.
Further, the method for judging the local change abnormal value in the groundwater level monitoring data according to the mean value and the variance comprises the following steps:
calculating the fluctuation range of the normal value according to the mean value and the variance;
if the underground water level monitoring data is in the fluctuation range, the underground water level monitoring data is a normal value, and if not, the underground water level monitoring data is a local change abnormal value. ((
A system for identifying outliers of groundwater level monitoring data, the system comprising:
an acquisition module: the system is used for acquiring underground water level monitoring data;
an identification module: the system comprises a statistical model-based box diagram and a water level difference-based distance model, wherein the statistical model-based box diagram and the water level difference-based distance model are used for respectively identifying a statistical abnormal extreme value and a local change abnormal value in the underground water level monitoring data; and the abnormal extreme value and the local change abnormal value are both groundwater level monitoring data abnormal values.
A system for identifying abnormal values of groundwater level monitoring data, the system comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate according to the instructions to perform the steps of the method described above.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method described above.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, only the statistic extreme abnormal value of the groundwater level monitoring data in the whole range can be identified through the box type graph, and the local change abnormal value cannot be identified, so that the statistic abnormal value in the whole range is firstly preliminarily detected by using the box type graph, and then the local change abnormal value is finely detected by using the distance model, so that all abnormal values in the groundwater level monitoring data set are comprehensively detected, and a foundation is laid for subsequently improving the quality of the groundwater level monitoring data.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a time sequence of groundwater level monitoring data of a solid mouth station.
FIG. 3 shows the arrangement of groundwater level monitoring data of a fixed port station from small to large.
FIG. 4 is an overall statistical outlier of groundwater level monitoring data of a fixed-mouth station.
FIG. 5 is a time series of groundwater level change rates at a cementing station.
FIG. 6 is a local variation abnormal value of groundwater level monitoring data of a solid mouth station.
FIG. 7 shows all abnormal values of groundwater level monitoring data of the solid mouth station.
Detailed Description
The present invention is further illustrated by the following figures and specific examples, which are to be understood as illustrative only and not as limiting the scope of the invention, which is to be given the full breadth of the appended claims and any and all equivalent modifications thereof which may occur to those skilled in the art upon reading the present specification.
As shown in fig. 1, an identification method for abnormal values of underground water level monitoring data includes the following steps:
s1: and acquiring groundwater level data monitored by a groundwater monitoring system.
Underground water level data { X) acquired by underground water monitoring systemiH, i =1, 2 …, n, where n represents the number of data.
S2: and identifying the statistic abnormal value of the groundwater level monitoring data in the whole range by utilizing a box type graph based on a statistical model.
S2.1: sequencing the underground water level monitoring data of the single station from small to large;
s2.2: calculating the minimum value Q of the single-site underground water level monitoring data sequenceminA first quartile Q1Median Q2A third quartile Q3Maximum value QmaxThese 5 data statistics;
s2.3: calculating the upper edge Upperlimit and the lower edge Lowerlimit of the boxed graph, wherein:
Upperlimit= Q3+（Q3- Q1）×1.5 （11）
Lowerlimit= Q3-（Q3- Q1）×1.5 （12）
s2.4: according to the interval estimation method: and calculating the fluctuation range [ Lowerlimit, Upperlimit ] of the normal value of the groundwater level, wherein the groundwater level monitoring data in the fluctuation range is the normal value, and otherwise, the groundwater level monitoring data is the statistical abnormal value in the whole range.
S3: and identifying local change abnormal values of the underground water level monitoring data by adopting a distance model based on the water level burial depth difference.
S3.1: calculating the change rate delta X of the groundwater level at the adjacent momenti；
ΔXi=Xi+1-Xi(i =1, 2 …, n, where n represents the number of data) (13)
S3.2: calculating Δ XiMean μ and variance σ:
s3.3: according to the interval estimation method: calculating the change rate Delta X of the groundwater leveliThe fluctuation range of the normal value of (μ -3 σ, μ +3 σ);
s3.4: the groundwater level at the monitoring moment corresponding to the groundwater level change rate within the fluctuation range is a normal value, otherwise, the groundwater level is a local change abnormal value.
And S4, identifying all the groundwater level depth abnormal data.
And (4) merging the two different types of underground water level abnormal data identified in the step (2) and the step (3), namely obtaining all underground water level abnormal data.
The following takes a mouth fixing station as an example to illustrate the specific implementation process of the invention:
s1: and acquiring groundwater level data monitored by a groundwater monitoring system. The groundwater level data described in this embodiment is obtained from time series data of 2016.1-2017.1 fixed-mouth stations, the time scale is 1 month, 133 data are total, fig. 2 is a time series of groundwater level data,
s2: and identifying the abnormal statistical value of the underground water level monitoring data of the solid outlet station by using a box type graph based on a statistical model.
S2.1: figure 3 shows the groundwater level is arranged from large to small,
s2.2: calculating the minimum value Qmin =0.37, the first quartile Q1=3.08, the median Q2=3.76, the third quartile Q3=4.16 and the maximum value Qmax =4.76 of the ground water level monitoring data sequence of the fixed port station
S2.3: calculating the upper edge Upperlimit and the lower edge Lowerlimit of the boxed graph, wherein:
Upperlimit= Q1-（Q3- Q1）×1.5=3.08-(4.16-3.08) ×1.5=1.46 （16）
Lowerlimit= Q3+（Q3- Q1）×1.5=4.16+(4.16-3.08) ×1.5=5.78 （17）
s2.4: according to the interval estimation method: and calculating the fluctuation range [1.46, 5.78] of the normal value of the groundwater level, wherein the groundwater level monitoring data in the fluctuation range is the normal value, and otherwise, the groundwater level monitoring data is the statistical abnormal value in the whole range. The number of the obtained statistical abnormal data of the groundwater level data of the fixed port stations 2016.1-2017.1 is 6, and the distribution situation of the groundwater level normal data and the statistical abnormal data is shown in figure 4.
S3: and identifying local change abnormal values of underground water level monitoring data of the solid outlet station by adopting a distance model based on the water level burial depth difference.
S3.1: calculating the change rate delta X of the groundwater level at the adjacent momenti：
ΔXi=Xi+1-Xi(i =1, 2 …, n, where n represents the number of data) (18)
The rate of change of groundwater level is shown in fig. 5.
S3.2: calculating Δ XiMean μ and variance σ:
s3.3: according to the interval estimation method: calculating the change rate Deltax of the groundwater leveliThe fluctuation range of the normal value of [ -1.7786, 2.3934]；
S3.4: the groundwater level at the monitoring moment corresponding to the groundwater level change rate within the fluctuation range is a normal value, otherwise, the groundwater level is a local change abnormal value. The number of the abnormal data of the change of the groundwater level data of the solid mouth stations 2016.1-2017.1 is 2, and the distribution of the abnormal data of the groundwater level change is shown in figure 6.
S4: and (3) taking and integrating the groundwater level abnormal data of two different types identified in the step (2) and the step (3), wherein the groundwater level abnormal data are all groundwater level abnormal data, and all the abnormal data of the groundwater levels of the fixed port stations 2016.1-2017.1 are shown in the figure 7.
The above calculation shows that the method provided by the invention can effectively identify the abnormal value in the groundwater level data and can be used for actual groundwater level data cleaning.
A system for identifying outliers of groundwater level monitoring data, the system comprising:
an acquisition module: the system is used for acquiring underground water level monitoring data;
an identification module: the system comprises a statistical model-based box diagram and a water level difference-based distance model, wherein the statistical model-based box diagram and the water level difference-based distance model are used for respectively identifying a statistical abnormal extreme value and a local change abnormal value in the underground water level monitoring data; and the abnormal extreme value and the local change abnormal value are both groundwater level monitoring data abnormal values.
A system for identifying abnormal values of groundwater level monitoring data, the system comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate according to the instructions to perform the steps of the method described above.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method described above.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.
Claims (9)
1. The method for identifying the abnormal value of the underground water level monitoring data is characterized by comprising the following steps of:
acquiring underground water level monitoring data;
respectively identifying a statistical abnormal extreme value and a local change abnormal value in the groundwater level monitoring data through a box diagram based on a statistical model and a distance model based on a water level difference;
and the abnormal extreme value and the local change abnormal value are both groundwater level monitoring data abnormal values.
2. The method for identifying abnormal values of the monitoring data of the underground water level as claimed in claim 1, wherein the process of identifying the abnormal statistical extreme values through the statistical model-based box chart is as follows:
sequencing the underground water level monitoring data of the single station from small to large;
acquiring a first quartile, a median and a third quartile in a groundwater level monitoring data sequence;
calculating the upper edge and the lower edge of the boxed graph according to the first quartile, the median and the third quartile;
and judging a statistical abnormal extreme value in the groundwater level monitoring data according to the upper edge and the lower edge.
3. The method for identifying abnormal values of underground water level monitoring data according to claim 1, wherein the calculation formula of the upper edge is as follows:
Upperlimit= Q3+（Q3- Q1）×1.5 （1）
the calculation formula of the lower edge is as follows:
Lowerlimit= Q3-（Q3- Q1）×1.5 （2）
wherein Upperlimit represents the upper edge, Lowerlimit represents the lower edge, and Q1Denotes the first quartile, Q3Representing the third quartile.
4. The method for identifying the abnormal value of the underground water level monitoring data according to claim 1, wherein the process of identifying the local change abnormal value through the distance model based on the water level difference is as follows:
calculating the change rate of groundwater level at a plurality of adjacent moments;
calculating the mean value and the variance of the water level change rates of the plurality of underground water;
and judging local change abnormal values in the groundwater level monitoring data according to the mean value and the variance.
5. The method for identifying the abnormal value of the underground water level monitoring data according to claim 4, wherein the calculation formula of the mean value is as follows:
the formula for the variance shown is:
where μ is the mean, σ is the variance, Δ XiThe change rate of the groundwater level at the adjacent moment is n, and the n is the total number of the change rates of the groundwater level at the adjacent moment.
6. The method for identifying the abnormal value of the underground water level monitoring data according to claim 4, wherein the method for judging the abnormal value of the local change in the underground water level monitoring data according to the mean value and the variance comprises the following steps:
calculating the fluctuation range of the normal value according to the mean value and the variance;
if the underground water level monitoring data is in the fluctuation range, the underground water level monitoring data is a normal value, and if not, the underground water level monitoring data is a local change abnormal value.
7. A system for identifying abnormal values of groundwater level monitoring data, the system comprising:
an acquisition module: the system is used for acquiring underground water level monitoring data;
an identification module: the system comprises a statistical model-based box diagram and a water level difference-based distance model, wherein the statistical model-based box diagram and the water level difference-based distance model are used for respectively identifying a statistical abnormal extreme value and a local change abnormal value in the underground water level monitoring data; and the abnormal extreme value and the local change abnormal value are both groundwater level monitoring data abnormal values.
8. An identification system for abnormal values of groundwater level monitoring data, the system comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps of the method according to any one of claims 1 to 6.
9. Computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
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