A device and method for indirect retrieval of non-optically active water body parameters

Abstract

The application discloses a kind of non-optically active water body parameter indirect inversion device and inversion method, solve the secondary pollution of existing water body in the non-optically active water body parameter measurement process, long time-consuming, step cumbersome and frequent maintenance problem, including cabinet and the spectrum measurement module, physicochemical measurement module, power supply / communication module and control display module connected in cabinet outer wall set in cabinet;Spectrum measurement module is used to measure the absorption spectrum of water body, and physicochemical measurement module is used to measure the pH value, conductivity and turbidity of water body in physicochemical measurement pool;Power supply / communication module is electrically connected spectrum measurement module, physicochemical measurement module, control display module respectively, for power supply to spectrum measurement module, physicochemical measurement module, while transmitting the data obtained by measurement;Control display module is electrically connected power supply / communication module, for displaying the data transmitted by power supply / communication module.

Description

Technical Field

[0001] This invention pertains to water chemistry metrological analysis devices and methods, specifically relating to a device and method for indirect inversion of non-optically active water parameters. Background Technology

[0002] Non-optically active water parameters refer to water parameters that do not have a direct optical response, such as total nitrogen, dissolved oxygen, and total phosphorus. These parameters are crucial for assessing water quality and ecological health because they directly affect eutrophication and the living environment of organisms. Unlike optically active water parameters (such as chlorophyll and chemical oxygen demand), these parameters are difficult to measure using traditional optical methods, but accurate monitoring of them is of great significance for water resource management and pollution control.

[0003] In recent years, technologies and instruments for the automated determination of total nitrogen and total phosphorus content in water bodies have gradually matured, with typical examples being instruments developed by Hach Corporation of Japan and Tianjian Innovation Co., Ltd. of China. These instruments strictly adhere to national standard methods; for example, total phosphorus is measured using the ammonium molybdate spectrophotometric method specified in national standard GB11893-89, while total nitrogen is measured using the alkaline potassium persulfate digestion ultraviolet spectrophotometric method specified in national standard GB11894-89. However, these methods suffer from problems such as cumbersome procedures, secondary chemical pollution, and frequent maintenance, and the fastest measurement cycle can only reach 35 minutes.

[0004] With the continuous development of spectroscopic technology, especially the trend towards miniaturization of equipment, this technology can be more easily integrated into water quality monitoring devices. Companies such as Austria's s::can and the United States' Xylem have successfully developed water quality monitoring devices based on ultraviolet-visible absorption spectroscopy. While these devices are advertised as having a wide range of applications, in practice, they are not explicitly stated to be able to retrieve non-optically reactive water parameters such as total nitrogen, dissolved oxygen, and total phosphorus.

[0005] As machine learning algorithms are increasingly applied to water chemistry quantification, researchers are beginning to explore the possibility of indirectly retrieving non-optically reactive water parameters using remote sensing technology. For example, Li Lan and colleagues at the Shanghai Institute of Technical Physics successfully retrieved non-optically reactive water parameters such as dissolved oxygen, total phosphorus, and ammonia nitrogen using remote sensing data. This complex coupling relationship, partly attributed to various nutrients in the water body, may induce covariance in optical characteristics. Therefore, exploring the use of ultraviolet-visible-near-infrared absorption spectroscopy to retrieve non-optically reactive water parameters is a promising research direction, although it is still rare in related studies both domestically and internationally.

[0006] In addition, using physicochemical measurement data, meteorological data, and land use rate as parameters to retrieve water body parameters is an emerging research field. Given that physicochemical measurement parameters (such as pH, conductivity, and turbidity) are readily available, and their measuring electrodes are commercially available, miniaturized, and easily integrated, using these parameters as features to input into machine learning models and studying their potential to improve model performance has become an important research direction in the current field of water quality monitoring. Summary of the Invention

[0007] The purpose of this invention is to solve the problems of chemical secondary pollution, long time consumption, cumbersome steps and frequent maintenance in the existing measurement process of non-optically active water parameters, and to provide a device and method for indirect inversion of non-optically active water parameters.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] A non-optically active water body parameter indirect inversion device includes a chassis, which is characterized by further including a spectral measurement module, a physicochemical measurement module, a power supply / communication module and a control display module connected to the outer wall of the chassis, all disposed inside the chassis.

[0010] The physicochemical measurement module includes a physicochemical measurement cell, a pH electrode, a conductivity electrode, and a turbidity electrode. The physicochemical measurement cell is fixedly connected inside the chassis and is connected to an inlet pipe and a first outlet pipe. The inlet pipe extends to the outside of the chassis. The pH electrode, conductivity electrode, and turbidity electrode are respectively installed inside the physicochemical measurement cell and are used to measure the acidity, alkalinity, conductivity, and turbidity of the water in the physicochemical measurement cell.

[0011] The spectral measurement module is used to measure the ultraviolet-visible-near-infrared absorption spectrum of water bodies. It includes a scintillation xenon lamp, a self-cleaning optical observation component, and a core spectrometer connected in sequence by optical fiber. The self-cleaning optical observation component is connected to a first water outlet pipe and a second water outlet pipe, with the second water outlet pipe extending to the outside of the chassis.

[0012] The power supply / communication module is electrically connected to the scintillation xenon lamp, the core spectrometer, the self-cleaning optical observation component, the pH electrode, the conductivity electrode, and the turbidity electrode, respectively, for power supply and transmission of the measured acidity, alkalinity, conductivity, and turbidity.

[0013] The control display module is electrically connected to the power supply / communication module and is used to display the data transmitted by the power supply / communication module.

[0014] Furthermore, the self-cleaning optical observation assembly includes a lead screw linear motor, a scraper, and a cuvette;

[0015] The lead screw linear motor is fixedly connected to the inner side wall of the housing. The working end of the lead screw linear motor is fixedly connected to a scraper. The scraper extends into the cuvette and cleans the inner wall of the cuvette under the drive of the lead screw linear motor. The lead screw linear motor is electrically connected to a power supply / communication module.

[0016] Furthermore, the chassis is connected to a vertically installed partition. The physicochemical measuring cell, pH electrode, conductivity electrode, turbidity electrode, and core spectrometer are all located on the same side of the partition inside the chassis, while the scintillation xenon lamp and self-cleaning optical observation assembly are located on the other side of the partition inside the chassis.

[0017] Furthermore, the optical fiber used in the spectral measurement module is an ultraviolet quartz optical fiber.

[0018] A method for indirect inversion of non-optically active water parameters, characterized by the following steps:

[0019] Step 1: Collect several water samples and measure the non-optically active water body parameters and physicochemical parameters of the water samples using the national standard method;

[0020] Step 2: Add the water samples to the spectral measurement module to obtain the absorption spectrum, and use ultrapure water as a reference to calculate the absorbance;

[0021] Step 3: Use absorbance and corresponding physicochemical measurement parameters as features and corresponding physicochemical measurement parameters as labels to construct a dataset. Divide the dataset into a training set and a test set in an 8:2 ratio.

[0022] Step 4: Construct the XGBoost model. Use the training set to optimize and train the XGBoost model. Based on the non-optically active water body parameters in Step 1, use OPTUNA and the 5-fold crossover algorithm to select the optimal hyperparameters of the XGBoost model. After testing with the test set, the optimized XGBoost model is obtained.

[0023] Step 5: Add the water body to be tested into the physicochemical measurement module, measure the physicochemical parameters of the water body, and then add it into the spectral measurement module through the first water outlet to measure the ultraviolet-visible-near-infrared absorption spectrum of the water body and calculate the absorbance of the water body.

[0024] Step 6: Input the physicochemical measurement parameters and absorbance of the water body to be tested into the optimized XGBoost model for inversion to obtain the non-optically active water body parameters of the water body to be tested.

[0025] Furthermore, step 6 is followed by:

[0026] The non-optically active water parameters of the water body to be tested are measured periodically according to the national standard method. The non-optically active water parameters generated by steps 5 and 6 are recorded. The XGBoost model is then finely adjusted and optimized using the slope deviation correction method.

[0027] Furthermore, after step 6, the following steps are also included: taking the non-optically active water parameters obtained from each inversion as labels, and the corresponding water physicochemical measurement parameters and absorbance as features, adding them to the dataset of step 3, and updating the optimized XGBoost model after accumulating a certain amount of data.

[0028] Furthermore, in steps 2 and 5, the formula for calculating the absorbance is as follows:

[0029]

[0030] In the formula, A is the absorbance of the water sample or the water body to be tested, I0 is the light intensity measured by the reference ultrapure water spectrometer, and I t The light intensity is measured by a spectrometer on the water body under test.

[0031] Furthermore, in step 4, the optimal hyperparameters of the XGBoost model include: number of iterations, L1 regularization coefficient, L2 regularization coefficient, sampling ratio of features when constructing the tree, sampling ratio of training samples in the training set, learning rate, maximum tree depth, and minimum instance weights required in child nodes.

[0032] Furthermore, the non-optically active water parameters include total nitrogen, dissolved oxygen, and total phosphorus;

[0033] The physicochemical measurement parameters include pH, conductivity, and turbidity.

[0034] The beneficial effects of this invention are:

[0035] (1) This invention provides a device and method for indirect inversion of non-optically active water parameters, which is reagent-free and free from secondary chemical pollution. It opens up new avenues for real-time on-site / in-situ analysis of sensitive water quality parameters and may have a positive impact on aquaculture and fisheries management, agricultural runoff management and industrial wastewater treatment, making water quality assessment easier to implement and more sustainable.

[0036] (2) The present invention provides a device and method for indirect inversion of non-optically active water parameters, which can work in all weather and all time with good time continuity.

[0037] (3) The present invention provides a device and method for indirect inversion of non-optically active water parameters. The device is small in size, highly integrated, easy to install, and requires no maintenance for a long time.

[0038] (4) The present invention provides a device and method for indirect inversion of non-optically active water parameters, which has a fast inversion speed and can reach the second-level monitoring speed.

[0039] (5) The present invention provides a device for indirect inversion of non-optically active water parameters, which can simultaneously measure a variety of water quality parameters, such as total nitrogen, total phosphorus, dissolved oxygen, chemical oxygen demand, chlorophyll, color, nitrate nitrogen, turbidity, conductivity, pH, etc.

[0040] (6) The present invention provides a device and method for indirect inversion of non-optically active water parameters, with high inversion accuracy and a relative error of less than 10%.

[0041] (7) The present invention provides a device and method for indirect inversion of non-optically active water parameters, which adopts an XGBoost model with slope deviation correction and update optimization, and can maintain measurement accuracy for a long time. Attached Figure Description

[0042] Figure 1 A front view of an embodiment of the device for indirect inversion of non-optically active water parameters provided by the present invention;

[0043] Figure 2 This is a schematic diagram of the internal structure of an embodiment of the device for indirect inversion of non-optically active water parameters provided by the present invention;

[0044] Figure 3 A three-dimensional structural schematic diagram of an embodiment of the device for indirect inversion of non-optically active water parameters provided by the present invention;

[0045] Figure 4 This is a three-dimensional structural schematic diagram from another angle of an embodiment of the device for indirect inversion of non-optically active water parameters provided by the present invention;

[0046] Figure 5 This invention provides a flowchart of an embodiment of an indirect inversion method for parameters of non-optically active water bodies;

[0047] Figure 6 This invention provides an absorbance curve diagram for an indirect inversion method for parameters of non-optically active water bodies.

[0048] Figure 7 This is a prediction result diagram from an embodiment of an indirect inversion method for non-optically active water parameters provided by the present invention. Attached image description:

[0050] 1-Chassis, 101-Mounting partition; 2-Spectroscopic measurement module, 201-Scintillation xenon lamp, 202-Self-cleaning optical observation component, 2021-Linear motor with lead screw, 2022-Scraper, 2023-Cuvette, 203-Core spectrometer, 204-Second water outlet pipe; 3-Physicochemical measurement module, 301-Physicochemical measurement cell, 302-pH electrode, 303-Conductivity electrode, 304-Turbidity electrode, 305-Inlet pipe, 306-First water outlet pipe; 4-Power supply / communication module; 5-Control and display module. Detailed Implementation

[0051] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0052] This embodiment provides a device for indirect inversion of non-optically active water parameters, such as... Figures 1-4 As shown, it includes a chassis 1 and a spectral measurement module 2, a physicochemical measurement module 3, a power supply / communication module 4, and a control and display module 5 connected to the outer wall of the chassis 1, all of which are installed inside the chassis 1.

[0053] In this embodiment, the chassis 1 has a conventional chassis structure with a wall-mounting port for easy installation; it is equipped with a support base for debugging, and raising the chassis height facilitates the installation of water inlet and outlet pipes; it is equipped with heat dissipation holes to reduce the temperature of chassis 1; it is equipped with peripheral interfaces, which are used for powering the device and for connecting keyboards, mice, and USB flash drives for debugging functions and data copying.

[0054] The physicochemical measurement module 3 includes a physicochemical measurement cell 301, a pH electrode 302, a conductivity electrode 303, and a turbidity electrode 304. The physicochemical measurement cell 301 is fixedly connected inside the housing 1. The physicochemical measurement cell 301 is connected to an inlet pipe 305 and a first outlet pipe 306. The inlet pipe 305 extends to the outside of the housing 1. The pH electrode 302, conductivity electrode 303, and turbidity electrode 304 are respectively installed inside the physicochemical measurement cell 301 to measure the acidity, alkalinity, conductivity, and turbidity of the water in the physicochemical measurement cell 301. A water pump is connected to the other end of the inlet pipe 305 to pump the water to be tested into the physicochemical measurement cell 301. The pH electrode 302, conductivity electrode 303, and turbidity electrode 304 measure the acidity, alkalinity, conductivity, and turbidity of the water to be tested, which are the physicochemical measurement parameters.

[0055] The spectral measurement module 2 is used to measure the ultraviolet-visible-near-infrared absorption spectrum of water. It includes a scintillation xenon lamp 201, a self-cleaning optical observation component 202, and a core spectrometer 203 connected in sequence via ultraviolet quartz optical fibers. The self-cleaning optical observation component 202 is connected to a first water outlet pipe 306 and a second water outlet pipe 204. Water from the physicochemical measurement pool 301 is input into the self-cleaning optical observation component 202 through the first water outlet pipe 306 to measure the absorption spectrum of the water. During measurement, the scintillation xenon lamp 201 is turned on, emitting a broad spectrum light source covering ultraviolet-visible-near-infrared. The light is transmitted to the self-cleaning optical observation component 202 through the ultraviolet quartz optical fiber. After the light is attenuated by the water to be measured, it enters the core spectrometer 203 through another ultraviolet quartz optical fiber to obtain the absorption spectrum of the water to be measured. The measured water is discharged through the second water outlet pipe 204.

[0056] The self-cleaning optical observation component 202 includes a lead screw linear motor 2021, a scraper 2022, and a cuvette 2023. The lead screw linear motor is fixedly connected to the inner wall of the housing 1. The working end of the lead screw linear motor 2021 is fixedly connected to the scraper 2022, which extends into the cuvette 2023 and cleans the inner wall of the cuvette 2023 under the action of the lead screw linear motor 2021. The lead screw linear motor 2021 is electrically connected to the power supply / communication module 4. The lead screw linear motor 2021 drives the scraper 2022 to clean the cuvette 2023.

[0057] The power supply / communication module 4 is electrically connected to the scintillation xenon lamp 201, the core spectrometer 203, the self-cleaning optical observation component 202, the pH electrode 302, the conductivity electrode 303, and the turbidity electrode 304, respectively, for power supply and transmission of the measured acidity, alkalinity, conductivity, and turbidity. The main power supply is connected from the interface of the external chassis 1 to the chassis 1, and is adapted to connect to the scintillation xenon lamp 201, the core spectrometer 203, the self-cleaning optical observation component 202, the pH electrode 302, the conductivity electrode 303, and the turbidity electrode 304, respectively. The power supply / communication module 4 has a high degree of integration and is helpful for troubleshooting when the device malfunctions.

[0058] The control display module 5 is electrically connected to the power supply / communication module 4 and is used to display the data transmitted by the power supply / communication module.

[0059] The chassis 1 is connected to a vertically arranged mounting partition 101. The inlet pipe 305, the second outlet pipe 204, the physicochemical measurement cell 301, the pH electrode 302, the conductivity electrode 303, the turbidity electrode 304, and the core spectrometer 203 are all on the same side of the mounting partition 101 inside the chassis 1. The first outlet pipe 306, the scintillation xenon lamp 201, and the self-cleaning optical observation component 202 are on the other side of the mounting partition 101 inside the chassis 1.

[0060] This embodiment also provides an indirect inversion method for non-optically active water body parameters, such as... Figure 5 As shown, it includes the following steps:

[0061] Step 1: Collect 131 sets of water samples and measure the non-optically active water parameters and physicochemical parameters of the water samples using the national standard method. In the national standard method, pH refers to GB 6920-86, conductivity refers to HJ / T97-2003, turbidity refers to HJ 1075-2019, total nitrogen refers to HJ 636-2012, dissolved oxygen refers to HJ 925-2017, and total phosphorus refers to GB11893-89.

[0062] Non-optically active water parameters include total nitrogen, dissolved oxygen, and total phosphorus.

[0063] Physicochemical measurement parameters include pH, conductivity, and turbidity.

[0064] Step 2: Add the water samples to the spectral measurement module 2 to obtain the absorption spectrum, and use ultrapure water as a reference to calculate the absorbance;

[0065] The formula for calculating absorbance is:

[0066]

[0067] In the formula, A is the absorbance of the water sample or the water body to be tested, I0 is the light intensity measured by the reference ultrapure water spectrometer, and I t The light intensity is measured by a spectrometer on the water body under test.

[0068] The absorbance transformation curve of the water sample is as follows: Figure 6 As shown,

[0069] Step 3: Use absorbance and corresponding physicochemical measurement parameters as features and corresponding physicochemical measurement parameters as labels to construct a dataset. Divide the dataset into a training set and a test set in an 8:2 ratio.

[0070] Step 4: Construct the XGBoost model. Optimize and train the XGBoost model using the training set. Based on the non-optically active water body parameters from Step 1, use OPTUNA and the 5-fold crossover algorithm to select the optimal hyperparameters of the XGBoost model, including: number of iterations (n_estimators), L1 regularization coefficient (reg_alpha), L2 regularization coefficient (reg_lambda), feature sampling ratio when constructing the tree (colsample_bytree), sampling ratio of training samples in the training set (subsample), learning rate (learning_rate), maximum tree depth (max_depth), and minimum sum of instance weights required in child nodes (min_child_weight).

[0071] The optimal hyperparameters of the XGBoost model are shown in Table 1:

[0072] Table 1

[0073]

[0074] The trained XGBoost model was tested using a test set to obtain an optimized XGBoost model. During testing, relative error was selected as the evaluation metric. Relative error = (predicted value - measured value) / measured value × 100%. The results are as follows: Figure 7 As shown, from top to bottom, the predicted results for total nitrogen, dissolved oxygen, and total phosphorus are presented. Figure 7 It can be seen that the relative errors are all within 10%.

[0075] Freeze and save the optimized XGBoost model.

[0076] Step 5: Add the water body to be tested into the physicochemical measurement module 3, measure the physicochemical parameters of the water body, and then add it into the spectral measurement module 2 through the first water outlet pipe 306 to measure the ultraviolet-visible-near-infrared absorption spectrum of the water body and calculate the absorbance of the water body.

[0077] Step 6: Input the physicochemical measurement parameters and absorbance of the water body to be tested into the saved optimized XGBoost model for inversion, obtain the non-optically active water body parameters of the water body to be tested, and display them on the control display module 5.

[0078] The non-optically active water parameters of the water body to be tested are measured periodically according to the national standard method. The non-optically active water parameters generated by steps 5 and 6 are recorded. The XGBoost model is then finely adjusted and optimized using the slope deviation correction method.

[0079] The non-optically active water parameters obtained from each inversion are used as labels, and the corresponding water physicochemical measurement parameters and absorbance are used as features. These are added to the dataset in step 3, and the optimized XGBoost model is updated after accumulating a certain amount of data.

[0080] The above description is merely a specific embodiment of the present invention and a comparison of the effects of the specific embodiments with relevant comparative examples. However, the scope of protection of the present invention is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present invention should be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A non-optically active water body parameter indirect inversion device comprising a cabinet (1), characterized in that: The application also comprises a spectrum measurement module (2), a physical and chemical measurement module (3), a power supply / communication module (4) arranged in the cabinet (1), and a control display module (5) connected to the outer wall of the cabinet (1). The physical and chemical measurement module (3) comprises a physical and chemical measurement pool (301), a pH electrode (302), a conductivity electrode (303) and a turbidity electrode (304), the physical and chemical measurement pool (301) is fixedly connected to the cabinet (1), the physical and chemical measurement pool (301) is connected to a water inlet pipe (305) and a first water outlet pipe (306) respectively, the water inlet pipe (305) extends to the outside of the cabinet (1), the pH electrode (302), the conductivity electrode (303) and the turbidity electrode (304) are arranged in the physical and chemical measurement pool (301) respectively, for measuring the pH, conductivity and turbidity of the water in the physical and chemical measurement pool (301). The spectrum measurement module (2) is used for measuring the ultraviolet-visible-near infrared absorption spectrum of the water, comprising a flash xenon lamp (201), a self-cleaning optical observation assembly (202) and a core spectrometer (203) connected through optical fibers in sequence, the first water outlet pipe (306) and a second water outlet pipe (204) are connected to the self-cleaning optical observation assembly (202) respectively, and the second water outlet pipe (204) extends to the outside of the cabinet (1). The power supply / communication module (4) is electrically connected to the flash xenon lamp (201), the core spectrometer (203), the self-cleaning optical observation assembly (202), the pH electrode (302), the conductivity electrode (303) and the turbidity electrode (304) respectively, for supplying power and transmitting the measured pH, conductivity and turbidity. The control display module (5) is electrically connected to the power supply / communication module (4), for displaying the data transmitted by the power supply / communication module (4).

2. The non-optically active water body parameter indirect inversion device according to claim 1, characterized in that: The self-cleaning optical observation assembly (202) comprises a lead screw linear motor (2021), a scraper (2022) and a cuvette (2023). The lead screw linear motor (2021) is fixedly connected to the inner side wall of the cabinet (1), the working end of the lead screw linear motor (2021) is fixedly connected to the scraper (2022), the scraper (2022) extends into the cuvette (2023) and cleans the inner wall of the cuvette (2023) under the driving of the lead screw linear motor (2021), and the lead screw linear motor (2021) is electrically connected to the power supply / communication module (4).

3. The non-optically active water body parameter indirect inversion device according to claim 1, characterized in that: A vertical mounting partition (101) is connected in the cabinet (1), the physical and chemical measurement pool (301), the pH electrode (302), the conductivity electrode (303), the turbidity electrode (304), the water inlet pipe (305), the second water outlet pipe (204) and the core spectrometer (203) are arranged on the same side of the mounting partition (101) in the cabinet (1), and the flash xenon lamp (201), the self-cleaning optical observation assembly (202) and the first water outlet pipe (306) are arranged on the other side of the mounting partition (101) in the cabinet (1).

4. The non-optically active water body parameter indirect inversion device according to claim 1, characterized in that: The optical fiber used in the spectrum measurement module (2) is an ultraviolet quartz optical fiber.

5. A non-optically active method for indirect retrieval of water body parameters, characterized in that, The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring.

6. The non-optically active water body parameter indirect inversion method according to claim 5, characterized in that, The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring.

7. The method of claim 5, wherein the non-optically active water body parameter is selected from the group consisting of: temperature, salinity, chlorophyll concentration, and dissolved oxygen concentration. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring.

8. The method of claim 5, wherein the non-optically active water body parameter is selected from the group consisting of: temperature, salinity, chlorophyll concentration, and dissolved oxygen concentration. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. In the formula, A is the absorbance of water or the water body to be measured, I0 is the light intensity measured by the reference ultrapure water spectrometer, and I t is the light intensity measured by the water body spectrometer.

9. The method of claim 5, wherein the non-optically active water body parameter is selected from the group consisting of: temperature, salinity, chlorophyll-a concentration, and dissolved oxygen concentration. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring.

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The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of water quality monitoring. The application discloses a non-optically active water body parameter indirect inversion device, and relates to the technical field of

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