CN111339498B - Rapid correction method and system for fluorescence dissolved organic matter data - Google Patents
Rapid correction method and system for fluorescence dissolved organic matter data Download PDFInfo
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- CN111339498B CN111339498B CN202010186230.7A CN202010186230A CN111339498B CN 111339498 B CN111339498 B CN 111339498B CN 202010186230 A CN202010186230 A CN 202010186230A CN 111339498 B CN111339498 B CN 111339498B
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Abstract
The invention discloses a method for quickly correcting fluorescence dissolved organic matter data, which comprises the following steps of: the method comprises the following steps: respectively receiving FDOM data, salinity data and turbidity data from an FDOM probe, a salinity probe and a turbidity probe; step two: calculating daily tide rising and falling according to the tide type of the FDOM probe distribution area, and distinguishing and classifying according to the time of data acquired by the FDOM probe; step three: establishing a regression model of FDOM data and salinity data in each tide rising and falling interval, namely FDOM = a multiplied by salinity + b; step four: coefficient of determination (R) based on FDOM and salinity 2 ) And judging whether recalculation and correction are carried out or not according to the turbidity value. The rapid correction method not only can rapidly and accurately carry out correction and inspection on the data, but also can save a large amount of manpower and material resources and improve the correction efficiency.
Description
Technical Field
The invention relates to the field of dissolved organic matter detection in estuary regions, in particular to a method and a system for rapidly correcting fluorescence dissolved organic matter data.
Background
Dissolved organic matter is an important component of global carbon cycle, in which unsaturated groups can generate fluorescence after absorption of light, and is called Fluorescence Dissolved Organic Matter (FDOM), which can be effectively applied to research of global/regional carbon cycle. Every year, 2.5 million tons of Dissolved Organic Carbon (DOC) are output from the global river to the ocean, the river mouth is used as an important interface for communicating land-sea substance exchange, and the complex and changeable dynamic environment can change the output process of the DOC of the river, so that the conventional shipborne sampling monitoring cannot obtain data with enough space-time resolution. The FDOM probe is used for high-frequency monitoring at the estuary, so that monitoring data with long period and high resolution can be obtained, however, the phenomenon of high water body turbidity exists in most estuary areas in China. When the turbidity of the water body is increased, the monitoring efficiency of the FDOM probe is reduced due to scattering and refraction of the particles to light, and the measurement result of the probe is lower than the actual value.
The traditional FDOM probe data correction needs to be carried out on site for multiple times of sampling, water body samples with different periods and different turbidities are collected, and then a correction formula is established by comparing FDOM values before and after particles are removed for correction. Therefore, in the field sampling, a large amount of manpower and material resources are consumed in the sample collection process and the later determination work. Due to the limitations of the conventional data correction method, a low-cost and fast FDOM data correction method is required.
Disclosure of Invention
Aiming at the existing problems, the invention provides a method for rapidly correcting fluorescence dissolved organic matter data, which comprises the following steps: the method comprises the following steps: receiving FDOM data, salinity data and turbidity data; step two: calculating the daily tide time of the rising tide and the falling tide according to the tide type of the FDOM data acquisition area, and distinguishing and classifying according to the acquisition time of the FDOM data; step three: establishing a regression model of FDOM data and salinity data in each tide rising and falling interval, namely: FDOM = a × salinity + b; step four: and (3) calculating according to a regression model in the third step to obtain a corresponding decision coefficient (R2), and judging whether to directly output data or output data after recalculation and correction according to the decision coefficient (R2) of the FDOM and the salinity and the average turbidity value in the tidal cycle.
Preferably, the fast correction method further comprises, in step four: and (3) setting a standard decision coefficient (R2) and an average turbidity threshold, taking data calculated by the regression model each time as a cycle, if the calculated decision coefficient is greater than the standard decision coefficient and the calculated average turbidity is less than the average turbidity threshold, outputting the data if the cycle number is less than or equal to 1, in addition, rejecting the highest turbidity data and the corresponding FDOM data, and establishing a regression equation according to the regression model in the step three again, if the highest turbidity data and the corresponding FDOM data meet the standard, outputting the data, otherwise, repeating the operation until the data are output.
Preferably, the standard decision factor and the average turbidity threshold are set according to FDOM in a mixed mode at the local estuary.
The invention also discloses a rapid correction system of fluorescence dissolved organic matter data, which comprises a water quality monitoring buoy set and a data preprocessing module, wherein the water quality monitoring buoy set is used for acquiring the FDOM data, salinity data and turbidity data required in the step one and transmitting the FDOM data, the salinity data and the turbidity data to the data preprocessing module in real time; the data preprocessing module is used for executing the steps of the method for rapidly correcting fluorescence dissolved organic matter data.
The invention has the beneficial effects that:
firstly, the following steps: the method is simple and quick, the FDOM data can be corrected without complicated sampling work and later-period experiments, and more manpower and material resources are not wasted;
II, secondly: the method has reliable and effective correction result. The method is applied to data correction of the FDOM probe at the estuary of the Jiulongjiang river, the logarithmic decrement relationship between the attenuation degree and the turbidity of the corrected FDOM signal is very close to that of the traditional method (figure 3), and the correction method is considered to be reliable.
Drawings
Hereinafter, the present invention will be explained in more detail with reference to the accompanying drawings. Throughout the drawings, the same reference numerals indicate the same or equivalent features:
FIG. 1 is a flow chart of a method for rapid correction of fluorescence-solubilized organic matter data according to the present invention;
FIG. 2 is a schematic diagram of the FDOM data calibration based on estuary chemistry in FIG. 1;
FIG. 3a is a graph showing the relationship between the percentage of attenuation of FDOM signals and turbidity obtained after data correction of FDOM buoys at the entrance of the nine Dragon according to the fast correction method of the present invention;
FIG. 3b is a graph of the percentage of FDOM signal attenuation versus turbidity obtained after calibration of the Jiulongjiang FDOM buoy data using a conventional calibration method.
Detailed Description
To further illustrate the various embodiments, the invention provides the accompanying drawings. The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the embodiments. Those skilled in the art will appreciate still other possible embodiments and advantages of the present invention with reference to these figures. The components in the drawings are not necessarily to scale, and similar reference numerals are generally used to identify similar components.
The invention will now be further described with reference to the accompanying drawings and detailed description.
Referring to fig. 1, fig. 1 is a flowchart of a method for rapidly calibrating fluorescence dissolved organic matter data according to the present invention. The quick correction method comprises the following steps: the method comprises the following steps: FDOM data, salinity data, and turbidity data are received from the FDOM probe, the salinity probe, and the turbidity probe, respectively. Step two: calculating the daily tide time of rising and falling tide according to the tide type of an FDOM probe distribution area, and distinguishing and classifying according to the time of the data acquired by the FDOM probe, taking the mansion area as an example, the daily tide rising and falling calculation formula is as follows:
first one to fifteen of lunar calendar: flood tide time =0.8 hx [ lunar calendar date-1 ] + high tide gap
Lunar calendar sixteen to thirty: flood tide time =0.8 hx [ lunar calendar date-16 ] + high tide gap
The transformation of the lunar calendar and the tidal time calculation involved in the part of the calculation process can be completed by a Python program set in advance. Step three: establishing a regression model of FDOM data and salinity data in each tide rising and falling interval, and obtaining the FDOM abundance according to the basic principle of conservative mixing of dissolved organic matters in estuary regionsThe salinity and salinity are mainly affected by physical mixing processes such as dilution in the estuary region, so that the two should form a good linear relationship as shown in fig. 2, namely: FDOM = a × salinity + b, where a is the slope of the regression equation, being a constant, and b is the intercept of the regression equation, being a constant, representing the FDOM abundance at 0 salinity (x =0, i.e. river water). Step four: coefficient of determination (R) based on FDOM and salinity 2 ) And the turbidity value is judged whether to carry out recalculation and correction, the condition should be adjusted according to different application environments, wherein a coefficient (R) is determined 2 ) The proportion of all variations in the dependent response variable that can be explained by the independent variable by regression relationships. Colloquially, it is used to evaluate the completeness or goodness of fit of a regression equation. Step five: and setting a standard decision coefficient and an average turbidity threshold according to the environment condition of the local estuary, outputting data if the calculated decision coefficient is greater than the standard decision coefficient and the calculated average turbidity is less than the average turbidity threshold and the cycle number is less than or equal to 1, otherwise, rejecting the highest turbidity data and the corresponding FDOM data, and re-establishing a regression equation. Theoretically, the influence of turbidity on the working efficiency of the FDOM probe can be corrected by only one cycle. Similarly, jiulongjiang estuary in mansion area is taken as an example. (1) The method comprises the following steps Coefficient of determination of regression equation for both FDOM and salinity>0.9 and the average turbidity of the water body in the rising/falling tide<50NTU, the data is considered valid and output. (2) The method comprises the following steps When determining the coefficient<0.9 or average turbidity>And when 50NTU is needed, removing the highest turbidity data and the corresponding FDOM data and reestablishing a regression equation, and if the decision coefficient and the average turbidity of the established regression equation meet the condition (1), calculating the FDOM by using salinity according to the new regression equation and deriving all the FDOM data.
Referring to fig. 3, fig. 3a and fig. 3b are graphs showing the result of the fast calibration method according to the present invention and the result of the calibration of the jiulongjiang FDOM buoy data by using the conventional calibration method. As shown in fig. 3a, when the method is used to correct the data of the FDOM buoy at the jiulong estuary, the signal obtained by the FDOM probe starts to be attenuated to a larger extent when the turbidity is higher than 50NTU, and when the turbidity of the water body is greater than 200, the FDOM signal is attenuated to enter the stage, and the attenuation amplitude is increased to a smaller extent. Compared with the experimental correction of the traditional sampling correction method established by Downing et al, (2012) and the like in the united states of connecticut river, the response elasticity of the attenuation degree of the FDOM optical signal to the turbidity of the water body is different, which is caused by the difference of particle size, properties and the like of different rivers.
According to another preferred embodiment of the present invention, there is also provided a rapid calibration system for fluorescence dissolved organic matter data, which is used for processing the steps of the rapid calibration method for fluorescence dissolved organic matter data. In a specific application, the quick correction system comprises a water quality monitoring buoy set and a data preprocessing module. The water quality monitoring buoy set is used for monitoring the water quality in at least one river mouth water area in real time and transmitting FDOM data, salinity data and turbidity data to the data preprocessing module in real time. And the data preprocessing module is used for distinguishing and classifying the received FDOM data, the salinity data and the turbidity data and then sending the FDOM data, the salinity data and the turbidity data to the remote control center.
The quick correction system also comprises a mobile terminal, such as a mobile phone or a notebook, wherein the mobile terminal is used for receiving the operation and correction results in real time and displaying the operation and correction results through an operation interface.
While the invention has been particularly shown and described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (4)
1. A method for rapidly correcting fluorescence dissolved organic matter data is characterized by comprising the following steps:
the method comprises the following steps: receiving FDOM data, salinity data and turbidity data;
step two: calculating the daily tide time of the rising tide and the falling tide according to the tide type of the FDOM data acquisition area, and distinguishing and classifying according to the acquisition time of the FDOM data;
step three: establishing a regression model of FDOM data and salinity data in each tide rising and falling interval, namely FDOM = a multiplied by salinity + b, wherein a is the slope of a regression equation and is a constant, b is the intercept of the regression equation and is a constant, and the FDOM abundance at the salinity of 0 is represented;
step four: calculating to obtain corresponding determination coefficient R according to the regression model in step three 2 According to FDOM and salinity 2 And judging whether to directly output the data or output the data after recalculation and correction according to the average turbidity value in the tide period, wherein S0: setting a standard decision coefficient and an average turbidity threshold value, taking data calculated by the regression model every time as a cycle, outputting the data if the calculated decision coefficient is greater than the standard decision coefficient and the calculated average turbidity is less than the average turbidity threshold value and the cycle number is less than or equal to 1, removing the highest turbidity data and the corresponding FDOM data, and establishing a regression equation according to the regression model in the step three again,
if the standard is met, outputting data; otherwise, repeating the operation S0 until the data is output.
2. The method for rapidly calibrating fluorescence dissolved organic matter data according to claim 1, wherein the setting of the standard decision coefficient and the average turbidity threshold is performed according to FDOM in a mixed mode at the local estuary.
3. A quick correction system for fluorescence dissolved organic matter data is characterized by comprising a water quality monitoring buoy set and a data preprocessing module, wherein the water quality monitoring buoy set is used for acquiring FDOM data, salinity data and turbidity data required in the first step and transmitting the FDOM data, the salinity data and the turbidity data to the data preprocessing module in real time; the data pre-processing module is used for performing the steps of the method for the rapid correction of fluorescence dissolved organic matter data according to any one of claims 1-2.
4. The system for rapidly correcting fluorescence dissolved organic matter data according to claim 3, further comprising a mobile terminal, wherein the mobile terminal is used for receiving the operation and correction results in real time and displaying the operation and correction results through an operation interface.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107924612A (en) * | 2015-08-28 | 2018-04-17 | 日产自动车株式会社 | Detection data collection method and detection data collection device |
| CN108519472A (en) * | 2018-08-03 | 2018-09-11 | 中国科学院烟台海岸带研究所 | A kind of more water layer aquatic environment multi-parameter original position on-line monitoring systems of aquafarm |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107924612A (en) * | 2015-08-28 | 2018-04-17 | 日产自动车株式会社 | Detection data collection method and detection data collection device |
| CN108519472A (en) * | 2018-08-03 | 2018-09-11 | 中国科学院烟台海岸带研究所 | A kind of more water layer aquatic environment multi-parameter original position on-line monitoring systems of aquafarm |
Non-Patent Citations (1)
| Title |
|---|
| Tidally Driven Export of Dissolved Organic Carbon, Total Mercury, and Methylmercury from a Mangrove-Dominated Estuary;Brian A. Bergamaschi;《Environmental Science & Technology 2012》;20111229;第46卷(第3期);原文第1371-1376页 * |
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Inventor after: Wu Yufang Inventor after: Xu Jing Inventor after: Yu Xiuxia Inventor after: Lin Zhiyu Inventor after: Shao Mingfei Inventor after: Guo Weidong Inventor before: Wu Yufang Inventor before: Xu Jing Inventor before: Yu Xiuxia Inventor before: Lin Zhiyu Inventor before: Shao Mingfei Inventor before: Guo Weidong |
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