Water body turbidity measuring method and system for water ecology investigation

Abstract

The invention provides a water turbidity measurement method and system for water ecological investigation, and the method comprises the steps: determining the scattering difference characteristics of suspended particles in a to-be-detected water body to light through collecting a scattered light signal of the to-be-detected water body and a light signal of a corresponding environment background of the to-be-detected water body; determining a disturbance error of the flow velocity in the to-be-measured water body during measurement of the suspended particles; determining the turbidity gradient of the suspended particles in the to-be-detected water body based on the turbidity inversion model in combination with the scattering difference characteristics and the disturbance error; determining the viscosity state of the water body power in the to-be-detected water body, and determining the attenuation relationship between the suspended particles in the to-be-detected water body and the temperature according to the viscosity state and the fluctuation characteristics of the ambient temperature around the to-be-detected water body; and dynamically compensating the turbidity gradient of the suspended particles in the to-be-detected water body through the attenuation relationship to obtain a dynamic turbidity value of the to-be-detected water body. By adopting the scheme of the invention, the influence of multi-parameter dynamic interference on the measurement of the water turbidity in the to-be-measured water can be reduced.

Description

Technical Field

[0001] The present application relates to the technical field of water turbidity measurement, and more specifically, to a water turbidity measurement method and system for water ecological surveys. Background Art

[0002] Water turbidity is an important water quality indicator that measures the ability of suspended particles in water (such as sediment, algae, organic matter, etc.) to scatter and absorb light. Its measurement aims to quantify water transparency and pollution level, and provide key data support for water ecological monitoring, water source protection, sewage treatment, etc. Common measurement methods include visual turbidimetry, spectrophotometry, and turbidity meter methods (such as scattered light turbidimeter).

[0003] In aquatic ecological surveys, water turbidity, as an important parameter characterizing the health of aquatic ecosystems, is a key indicator for water quality monitoring and hydrological research. Traditional turbidity measurement methods are mostly based on fixed-angle scattered light detection or transmitted light attenuation. Photoelectric sensors capture the scattered or absorbed light signals of suspended particles to infer turbidity values. However, the dynamic complexity of natural water environments presents significant limitations to existing technologies. First, periodic variations in ambient background light (such as shifts in sunlight angle and fluctuations in water surface reflection) can interfere with the target scattered signal, making it difficult for conventional single-light source measurement systems to effectively separate the valid signal. Second, suspended particles in flowing water are affected by flow velocity, resulting in a non-uniform distribution. Traditional static models are unable to correct for turbidity gradient distortion caused by particle drift. Third, the temperature sensitivity of water viscosity can cause variations in the settling rate of suspended particles. Existing methods lack dynamic compensation mechanisms for the temperature-viscosity coupling effect. This is particularly true in open waters with significant diurnal temperature fluctuations, which can easily lead to systematic biases in long-term monitoring data. Therefore, mitigating the impact of dynamic multi-parameter interference on turbidity measurements has become a major challenge facing the industry. Summary of the Invention

[0004] The present application provides a water turbidity measurement method and system for water ecological surveys, which can reduce the impact of multi-parameter dynamic interference on the measurement of water turbidity in the water body to be measured.

[0005] In a first aspect, the present application provides a method for measuring water turbidity for water ecological surveys, comprising the following steps: Alternately irradiating a water body to be measured and collecting scattered light signals of the water body to be measured; Synchronously fitting the scattered light signal and the light signal of the environmental background corresponding to the water body to be measured to obtain the scattering difference characteristics of the suspended particles in the water body to be measured, and determining the disturbance error of the flow velocity in the water body to be measured on the suspended particles; Constructing a turbidity inversion model for the water body to be measured, and performing turbidity inversion on the suspended particles in the water body to be measured based on the turbidity inversion model in combination with the scattering difference characteristics and the disturbance error to obtain a turbidity gradient of the suspended particles in the water body to be measured; Determining the viscosity state of the water body dynamics in the water body to be measured, and determining the attenuation relationship between suspended particles and temperature in the water body to be measured based on the viscosity state and the fluctuation characteristics of the ambient temperature of the water body to be measured; The turbidity gradient of the suspended particles in the water body to be measured is dynamically compensated by the attenuation relationship, thereby obtaining the dynamic turbidity value of the water body to be measured.

[0006] In some embodiments, synchronously fitting the scattered light signal and the light signal of the environmental background corresponding to the water body to be tested to obtain the scattering difference characteristics of the suspended particles in the water body to be tested specifically includes: Collecting the light signal of the environmental background corresponding to the water body to be measured; Preprocessing the scattered light signal and the light signal of the environmental background to obtain a preprocessed scattered light signal and a preprocessed light signal of the environmental background; Performing time series alignment on the preprocessed scattered light signal and the preprocessed ambient background light signal to obtain a time series signal data set; The light scattering difference characteristics of suspended particles in the water body to be tested are extracted from the time series signal data set.

[0007] In some embodiments, determining the disturbance error of the flow velocity in the measured water body on the measured suspended particles specifically includes: Obtaining a three-dimensional flow velocity distribution of the water body to be measured; Determine the horizontal loss and vertical loss of suspended particles due to the flow velocity in the water body to be measured according to the three-dimensional flow velocity distribution; The disturbance error of the flow velocity in the water body to be measured on the measurement of suspended particles is determined by the horizontal loss and the vertical loss.

[0008] In some embodiments, performing turbidity inversion on the suspended particles in the water body to be measured based on the turbidity inversion model in combination with the scattering difference characteristics and the disturbance error to obtain the turbidity gradient of the suspended particles in the water body to be measured specifically includes: performing normalization processing on the scattering difference feature to obtain a standardized scattering difference feature; The turbidity gradient of suspended particles in the water body to be measured is determined based on the turbidity inversion model combined with the standardized scattering difference characteristics and the disturbance error.

[0009] In some embodiments, determining the viscosity state of the water body dynamics in the water body to be measured specifically includes: Monitoring temperature, salinity and pressure data at different depths in the water body to be measured; The viscosity state of the water body dynamics in the water body to be measured is determined based on the temperature, salinity and pressure data at different depths.

[0010] In some embodiments, determining the attenuation relationship between suspended particles and temperature in the water body to be tested based on the viscosity state and the fluctuation characteristics of the ambient temperature of the water body to be tested specifically includes: Determining the fluctuation characteristics of the ambient temperature of the water body to be measured; performing correlation analysis on the viscosity state and the fluctuation characteristics of the ambient temperature to obtain correlation characteristics between temperature and viscosity; The attenuation relationship between suspended particles and temperature in the water body to be measured is determined according to the correlation characteristics.

[0011] In some embodiments, dynamically compensating the turbidity gradient of suspended particles in the water body to be measured by using the attenuation relationship to thereby obtain the dynamic turbidity value of the water body to be measured specifically includes: Dynamically compensating the turbidity gradient of suspended particles in the water body to be measured according to the attenuation relationship to obtain a compensated turbidity gradient; The dynamic turbidity value of the water body to be measured is determined by the compensated turbidity gradient.

[0012] In some embodiments, a photoelectric detector is used to collect the scattered light signal of the water body to be detected.

[0013] In some embodiments, a machine learning algorithm is used to construct a turbidity inversion model for the water area to be measured.

[0014] In a second aspect, the present application provides a water turbidity measurement system for water ecological surveys, comprising: An acquisition module, configured to alternately illuminate the water body to be measured and acquire scattered light signals of the water body to be measured; a processing module for synchronously fitting the scattered light signal and the light signal of the environmental background corresponding to the water body to be measured, obtaining the scattering difference characteristics of the suspended particles in the water body to be measured, and determining the disturbance error of the flow velocity in the water body to measure the suspended particles; The processing module is further configured to construct a turbidity inversion model for the water body to be measured, and perform turbidity inversion on the suspended particles in the water body to be measured based on the turbidity inversion model in combination with the scattering difference characteristics and the disturbance error, to obtain a turbidity gradient of the suspended particles in the water body to be measured; The processing module is further configured to determine the viscosity state of the water body dynamics in the water body to be tested, and determine the attenuation relationship between the suspended particles in the water body to be tested and the temperature based on the viscosity state and the fluctuation characteristics of the ambient temperature of the water body to be tested; An execution module is used to dynamically compensate the turbidity gradient of suspended particles in the water body to be measured according to the attenuation relationship, thereby obtaining a dynamic turbidity value of the water body to be measured.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: In the water turbidity measurement method and device for water ecological survey provided in the present application, the water body to be measured is first alternately illuminated, and the scattered light signal of the water body to be measured is collected; the scattered light signal and the light signal of the corresponding environmental background of the water body to be measured are synchronously fitted to obtain the scattering difference characteristics of the suspended particles in the water body to be measured to the light, and the disturbance error of the flow velocity in the water body to be measured on the measured suspended particles is determined; a turbidity inversion model of the water area to be measured is constructed, and the turbidity inversion of the suspended particles in the water body to be measured is performed based on the turbidity inversion model combined with the scattering difference characteristics and the disturbance error to obtain the turbidity gradient of the suspended particles in the water body to be measured; the dynamic viscosity state of the water body in the water body to be measured is determined, and the attenuation relationship between the suspended particles in the water body to be measured and the temperature is determined according to the viscosity state and the fluctuation characteristics of the ambient temperature of the water body to be measured; the turbidity gradient of the suspended particles in the water body to be measured is dynamically compensated by the attenuation relationship, thereby obtaining the dynamic turbidity value of the water body to be measured.

[0016] It can be seen that in the process of measuring turbidity of water bodies, the present application can, firstly, eliminate the interference of ambient light (such as sunlight, instrument thermal noise) on the scattered signal by synchronously fitting the scattered light signal and the background light signal, and can separate the scattered signal fluctuations caused by flow velocity (such as Doppler effect or turbulent disturbance) by extracting difference features, quantify the dynamic error of flow velocity on turbidity measurement, and provide a basis for subsequent error compensation; secondly, based on the turbidity inversion model, the scattering difference feature and flow velocity disturbance error are integrated to dynamically correct the turbidity measurement deviation caused by uneven particle distribution or flow velocity change, and the inversion of turbidity gradient can characterize the spatial variation of particle concentration, thereby improving the spatial resolution and accuracy of turbidity measurement under complex hydrodynamic conditions. The accuracy of the model is then verified by analyzing the effect of water flow resistance on particle settling through viscosity analysis. Combined with temperature fluctuation characteristics (such as thermal expansion and enhanced Brownian motion), a temperature-turbidity attenuation model is established. This model compensates for temperature-induced drift in particle scattering characteristics (such as particle size changes or agglomeration effects), reducing the indirect interference of thermodynamic parameters on turbidity. Finally, the turbidity gradient is dynamically compensated through the attenuation relationship to obtain a dynamic turbidity value. This dynamic compensation mechanism can correct in real time the effects of the coupled effects of multiple parameters, such as temperature and viscosity, on turbidity (for example, low temperatures and high viscosity in winter lead to slow particle settling). The resulting dynamic turbidity value is stable and interference-resistant, significantly improving measurement robustness in multi-parameter interference environments. The above scheme can reduce the impact of multi-parameter dynamic interference on the measured turbidity of the water body. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is an exemplary flow chart of a water turbidity measurement method for water ecological survey according to some embodiments of the present application; Figure 2 is an exemplary diagram of alternating illumination according to some embodiments of the present application; Figure 3 is an exemplary flow chart of determining a disturbance error according to some embodiments of the present application; Figure 4 is a schematic structural diagram of a water turbidity measurement system for water ecological survey according to some embodiments of the present application; Figure 5 It is a structural diagram of a computer device for implementing a water turbidity measurement method for water ecological survey according to some embodiments of the present application. DETAILED DESCRIPTION

[0018] In order to better understand the technical solution of the present application, the technical solution of the present application will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0019] refer to Figure 1 , which is an exemplary flow chart of a water turbidity measurement method for water ecological survey according to some embodiments of the present application. The water turbidity measurement method 100 for water ecological survey mainly includes the following steps: In step 101, a water body to be measured is alternately illuminated, and scattered light signals of the water body to be measured are collected.

[0020] In specific implementation, first, a dual light source system is used as an alternating irradiation device. Two light sources of different wavelengths (such as green light and infrared light) are used to emit light to the water body to be tested at preset time intervals (for example, 1 second of green light irradiation and 1 second of infrared light irradiation alternately) under the action of a controller; then, a high-sensitivity photodetector (such as an avalanche photodiode) is installed at a certain distance from the light source at a specific angle (such as a 90-degree scattering angle, which is a commonly used angle for water turbidity measurement and can effectively collect scattered light signals) to capture the light signal generated by the suspended particles in the water body to be tested. Finally, the light signal collected by the photodetector is used as the scattered light signal of the water body to be tested; in other embodiments, other methods of collection can also be used, which are not limited here.

[0021] It should be noted that the scattered light signal in the present application represents the signal when light is scattered in the water body to be measured, which can be used to analyze the concentration, particle size distribution and optical properties of suspended particles in the water body.

[0022] In some embodiments, reference Figure 2As shown, this figure is an example of alternating illumination in some embodiments of the present application, such as Figure 2 As described above, the water body to be tested is alternately illuminated by two light sources of different wavelengths (such as green light and infrared light), and the scattered light signal is collected by the collection device.

[0023] In step 102, the scattered light signal and the light signal of the environmental background corresponding to the water body to be measured are synchronously fitted to obtain the scattering difference characteristics of the suspended particles in the water body to be measured, and determine the disturbance error of the flow velocity in the water body to measure the suspended particles.

[0024] In some embodiments, synchronously fitting the scattered light signal and the light signal of the environmental background corresponding to the water body to be tested to obtain the scattering difference characteristics of the suspended particles in the water body to be tested can be achieved by the following steps: Collecting the light signal of the environmental background corresponding to the water body to be measured; Preprocessing the scattered light signal and the light signal of the environmental background to obtain a preprocessed scattered light signal and a preprocessed light signal of the environmental background; Performing time series alignment on the preprocessed scattered light signal and the preprocessed ambient background light signal to obtain a time series signal data set; The light scattering difference characteristics of suspended particles in the water body to be tested are extracted from the time series signal data set.

[0025] In the specific implementation, first, before the irradiation device irradiates the water body to be tested, the light signal of the environmental background is collected by using the same photoelectric detector as that for collecting the scattered light signal, thereby reducing the interference of the ambient stray light. Then, the scattered light signal and the light signal of the environmental background are preprocessed, namely: the median filtering algorithm is first used to remove the salt and pepper noise in the scattered light signal and the light signal of the environmental background, and then the wavelet denoising algorithm is used to decompose the scattered light signal and the light signal of the environmental background into different frequency layers, and the high-frequency noise in the scattered light signal and the light signal of the environmental background is eliminated by threshold processing, thereby obtaining the preprocessed scattered light signal and the light signal of the preprocessed environmental background. Then, the interpolation alignment method based on the timestamp is used to align the preprocessed scattered light signal and the preprocessed environmental background. The light signals of the scene are aligned in time series, and the aligned data set is used as the time series signal data set. If the sampling frequencies of the two signals are different, the low-frequency signal is resampled to the sampling frequency of the high-frequency signal using the cubic spline interpolation algorithm, so that the time points of the two types of signals are completely corresponding. Finally, the time series signal data set is curve fitted using the least squares method to establish a mathematical relationship model (such as a linear model or a nonlinear model) between the scattered light signal and the ambient background light signal. The difference in the scattered light intensity relative to the background light intensity at different wavelengths and the signal change slope are extracted from the mathematical relationship model, and all the differences and signal change slopes are used as the scattering difference characteristics of suspended particles in the water body to be tested to light. In other embodiments, other methods can also be used for determination, which are not limited here.

[0026] It should be noted that the scattering difference characteristics in this application represent the difference characteristics of the scattering effect of suspended particles in the water body to be tested on light relative to the ambient background light signal, which can be used to analyze the interference of background light, thereby reducing the impact of background light on the detection of suspended particles in the water body to be tested.

[0027] In some embodiments, reference Figure 3 As shown in FIG. 1 , this figure is an exemplary flow chart for determining disturbance errors in some embodiments of the present application. In this embodiment, determining the disturbance error of the flow velocity in the measured water body on the measurement of suspended particles can be achieved by using the following steps: First, in step 1021, the three-dimensional flow velocity distribution of the water body to be measured is obtained; Next, in step 1022, the horizontal loss and vertical loss of suspended particles due to the flow velocity in the water body to be measured are determined based on the three-dimensional flow velocity distribution; Finally, in step 1023, the disturbance error of the flow velocity in the measured water body on the measurement of suspended particles is determined by using the horizontal loss and the vertical loss.

[0028] In specific implementation, first, the three-dimensional flow velocity distribution of the water body to be measured can be obtained in the following manner, namely: using an acoustic Doppler current meter to perform multi-point measurements at different positions and depths of the water body to be measured to obtain the flow velocity components of the water body in three-dimensional space (x, y, z directions), and then construct a three-dimensional flow velocity distribution of the water body to be measured, wherein the three-dimensional flow velocity distribution represents the flow velocity distribution in the three-dimensional space of the water body to be measured. If the measurement area is large, it can be combined with a cruise-type acoustic Doppler current meter for continuous measurement, and the discrete measurement data can be spatially interpolated using the Kriging interpolation method to obtain a continuous and smooth three-dimensional flow velocity distribution; in other embodiments, other methods can be used to obtain it, which is not limited here.

[0029] In specific implementation, the horizontal loss and vertical loss of suspended particles due to the flow velocity in the water body to be measured can be determined according to the three-dimensional flow velocity distribution. That is, when calculating the horizontal loss, the water flow advection effect is taken into account, and the movement trajectory of suspended particles with the water flow is tracked in the horizontal direction by using the Lagrangian particle tracking method. The number or mass of particles that move out of the measurement area due to the water flow advection effect per unit time is counted to determine the horizontal loss amount, and the horizontal loss amount is used as the horizontal loss of suspended particles due to the flow velocity in the water body to be measured, wherein the horizontal loss represents the horizontal loss of suspended particles due to the flow velocity in the water body to be measured. The parameter value of the degree of loss of particles in the horizontal direction; when calculating the vertical loss, combined with Stokes' law, the sedimentation velocity of the particles and the vertical velocity component of the water flow are considered, and by establishing the motion equation of the particles in the vertical direction, the loss of particles due to the vertical movement of the water flow and their own sedimentation is solved, and the loss due to the vertical movement of the water flow and its own sedimentation is used as the vertical loss of suspended particles due to the flow velocity in the water body to be tested, wherein the vertical loss represents the parameter value of the degree of loss of suspended particles in the vertical direction due to the flow velocity in the water body to be tested; in other embodiments, other methods can also be used for determination, which are not limited here.

[0030] In specific implementation, the disturbance error of the flow velocity in the water body to be measured on the measurement of suspended particles is determined by the horizontal loss and the vertical loss, that is: the horizontal loss and the vertical loss are vector-synthesized (such as by the square root of the sum of squares), and the loss obtained by the vector synthesis is used as the disturbance error of the flow velocity in the water body to be measured on the measurement of suspended particles; in other embodiments, other methods can also be used for determination, which are not limited here.

[0031] It should be noted that the disturbance error in this application represents the error when the flow velocity in the water body to be measured interferes with the suspended particles, which can be used to analyze the state of suspended particles in the water body to be measured, thereby reducing the influence of flow velocity on the detection of suspended particles.

[0032] In step 103, a turbidity inversion model of the water body to be measured is constructed, and turbidity inversion is performed on the suspended particles in the water body to be measured based on the turbidity inversion model combined with the scattering difference characteristics and the disturbance error to obtain the turbidity gradient of the suspended particles in the water body to be measured.

[0033] In specific implementation, the turbidity inversion model of the water area to be measured can be constructed in the following manner, namely: when constructing the turbidity inversion model, a machine learning algorithm (such as a random forest or a neural network) can be used to use the historical measured scattering difference characteristics, disturbance error data and the corresponding actual turbidity values ​​as a training set, and the nonlinear mapping relationship between the three is learned through model training optimization parameters. The disturbance error is used as a correction factor, the scattering difference characteristics are used as a core variable, and a fitting equation is established. The fitting equation is used as a turbidity inversion model between the disturbance error, the scattering difference characteristics and the water turbidity. The turbidity inversion model represents an algorithm model established by the quantitative relationship between the light signal (such as scattered light, transmitted light, reflected light) in the water body and the water turbidity, and can be used to predict the water turbidity in the water body to be measured; in other embodiments, other methods can also be used for construction, which are not limited here.

[0034] In some embodiments, turbidity inversion is performed on the suspended particles in the water body to be measured based on the turbidity inversion model combined with the scattering difference characteristics and the disturbance error to obtain the turbidity gradient of the suspended particles in the water body to be measured. The following steps can be used to achieve this: performing normalization processing on the scattering difference feature to obtain a standardized scattering difference feature; The turbidity gradient of suspended particles in the water body to be measured is determined based on the turbidity inversion model combined with the standardized scattering difference characteristics and the disturbance error.

[0035] It should be noted that the scattering difference characteristic is essentially an external manifestation of the optical properties of the particles, while the disturbance error is an external manifestation of the dynamic properties of the particles. Both are determined by the intrinsic characteristics of the particles (concentration, particle size, density), and therefore have an intrinsic physical connection. Turbidity, as a comprehensive representation of particle concentration, not only reflects the optical scattering ability (the higher the concentration, the stronger the scattering), but is also affected by water flow (the faster the flow rate, the more uneven the particle distribution). Therefore, the turbidity gradient of suspended particles in the water body to be tested can be constructed based on the scattering difference characteristic and the disturbance error.

[0036] In a specific implementation, the scattering difference feature is normalized to obtain a standardized scattering difference feature, that is, the scattering difference feature is normalized by using a minimum-maximum normalization algorithm to normalize the scattering difference feature, linearly mapping the original scattering difference feature data to the interval [0, 1], and using the result after normalization as the standardized scattering difference feature, thereby eliminating the differences in dimension and order of magnitude of data at different measurement points, and obtaining a standardized scattering difference feature; in other embodiments, other methods can also be used for determination.

[0037] In a specific implementation, the turbidity gradient of suspended particles in the water body to be tested is determined based on the turbidity inversion model in combination with the standardized scattering difference characteristics and the disturbance error. This can be achieved in the following manner: the entire water body to be tested is gridded (e.g., using a square or hexagonal grid) based on interactive partitioning of a geographic information system to obtain a plurality of grid cells. The standardized scattering difference characteristics and the calculated disturbance error data are input as input parameters into a constructed turbidity inversion model. The turbidity value of each grid cell is calculated by the turbidity inversion model. The discrete turbidity values ​​are then spatially interpolated using the Kriging interpolation method to generate a continuous turbidity distribution surface. The turbidity change rate of each point on the turbidity distribution surface is calculated using spatial derivatives, thereby using all turbidity change rates as the turbidity gradient of suspended particles in the water body to be tested. In other embodiments, other methods can also be used for determination, which are not limited here.

[0038] It should be noted that the turbidity gradient in the present application represents the gradient of turbidity change of suspended particles in the water body to be tested, which can be used to intuitively present the spatial variation trend of turbidity, thereby facilitating the analysis of turbidity in the water body to be tested.

[0039] In step 104, the viscosity state of the water body dynamics in the water body to be measured is determined, and the attenuation relationship between the suspended particles in the water body to be measured and the temperature is determined based on the viscosity state and the fluctuation characteristics of the ambient temperature of the water body to be measured.

[0040] In some embodiments, determining the viscosity state of the water body dynamics in the water body to be measured can be achieved by using the following steps: Monitoring temperature, salinity and pressure data at different depths in the water body to be measured; The viscosity state of the water body dynamics in the water body to be measured is determined based on the temperature, salinity and pressure data at different depths.

[0041] In specific implementation, first, a high-precision temperature-salinity-depth meter can be used to measure the temperature, salinity and pressure data of the water body to be measured at different depths. Then, the measured data is substituted into the viscosity empirical formula (such as based on the international seawater state equation) to calculate the theoretical value of the dynamic viscosity of the water body at each measurement point, and all the theoretical values ​​of the dynamic viscosity are used as the dynamic viscosity state of the water body in the water body to be measured; in other embodiments, other methods can also be used for determination, which is not limited here.

[0042] It should be noted that the viscosity state in this application refers to the state of the dynamic viscosity of the water body in the water body to be measured, including viscosity values ​​at different depths and different areas, which can be used to analyze the turbidity of the water body.

[0043] In some embodiments, determining the attenuation relationship between suspended particles and temperature in the water body to be tested based on the viscosity state and the fluctuation characteristics of the ambient temperature of the water body to be tested can be achieved by the following steps: Determining the fluctuation characteristics of the ambient temperature of the water body to be measured; performing correlation analysis on the viscosity state and the fluctuation characteristics of the ambient temperature to obtain correlation characteristics between temperature and viscosity; The attenuation relationship between suspended particles and temperature in the water body to be measured is determined according to the correlation characteristics.

[0044] It should be noted that temperature fluctuations will change the dynamic viscosity of water through the viscosity-temperature effect, and viscosity directly affects the fluid resistance experienced by suspended particles. When the ambient temperature rises, the viscosity of the water decreases, and the resistance during particle sedimentation or diffusion decreases, resulting in an increase in the rate of movement, thereby accelerating the migration (attenuation) of particles from the water. Conversely, when the temperature decreases, the viscosity increases, the movement of particles is hindered, and the attenuation rate slows down. Therefore, the attenuation relationship between suspended particles and temperature in the water to be tested can be determined by the viscosity state and the fluctuation characteristics of the ambient temperature surrounding the water to be tested.

[0045] In specific implementation, the fluctuation characteristics of the ambient temperature of the water body to be measured can be determined in the following manner, namely: using a high-precision temperature sensor (such as a platinum resistance temperature sensor) to collect the ambient temperature of the water body to be measured at a high frequency (such as once per second) to obtain a temperature value time series of the ambient temperature of the water body to be measured, converting the temperature value time series into frequency domain data through fast Fourier transform, calculating the amplitude and variation range of the temperature fluctuation in the frequency domain data, and using the amplitude and variation range of the temperature fluctuation as the fluctuation characteristics of the ambient temperature of the water body to be measured, wherein the fluctuation characteristics represent the characteristics of the degree of fluctuation of the ambient temperature of the water body to be measured; in other embodiments, other methods can also be used for determination, which are not limited here.

[0046] In a specific implementation, the viscosity state and the fluctuation characteristics of the ambient temperature are correlated and analyzed to obtain the correlation characteristics between temperature and viscosity. This can be achieved in the following manner: a theoretical model of the relationship between fluid viscosity and temperature is constructed based on the Andrade equation, the fluctuation characteristics of the ambient temperature are used as the independent variable, and the viscosity state is used as the dependent variable, so as to output the change in viscosity per unit value change in temperature through the theoretical model, and the change in viscosity per unit value change in temperature is used as the correlation characteristic between temperature and viscosity, wherein the correlation characteristic represents the characteristic of the degree of correlation between temperature and viscosity.

[0047] In specific implementation, the attenuation relationship between the suspended particles and temperature in the water body to be measured can be determined according to the correlation characteristics in the following manner, namely: using Stokes' law to analyze the influence of viscosity changes on the resistance to movement of suspended particles to establish a functional relationship between particle movement speed and viscosity. When the temperature change causes the viscosity to change, the change in particle movement speed is calculated through this functional relationship, and this change is combined with the particle dynamics theory to quantify the attenuation degree of suspended particles caused by temperature changes in the coagulation and sedimentation process, and this attenuation degree is used as the attenuation relationship of suspended particles in the measured water body. For example, by calculating the particle reduction ratio caused by temperature-viscosity changes per unit time, or the decrease in the effective concentration of particles, the attenuation relationship of temperature on suspended particles is finally determined; in other embodiments, other methods can also be used for determination, which are not limited here.

[0048] It should be noted that the attenuation relationship in this application represents the relationship between temperature changes and the attenuation degree of suspended particles in the water body to be tested, such as the attenuation degree of suspended particles caused by temperature changes during the coagulation and sedimentation process, which can be used to analyze the suspended particles in the water body to be tested, thereby reducing the impact of temperature on the measurement of water turbidity in the water body to be tested.

[0049] In step 105, the turbidity gradient of the suspended particles in the water body to be measured is dynamically compensated by the attenuation relationship, thereby obtaining the dynamic turbidity value of the water body to be measured.

[0050] In some embodiments, dynamically compensating the turbidity gradient of suspended particles in the water body to be measured by using the attenuation relationship to obtain the dynamic turbidity value of the water body to be measured can be achieved by the following steps: Dynamically compensating the turbidity gradient of suspended particles in the water body to be measured according to the attenuation relationship to obtain a compensated turbidity gradient; The dynamic turbidity value of the water body to be measured is determined by the compensated turbidity gradient.

[0051] It should be noted that dynamic compensation refers to the process of correcting the original turbidity gradient measurement value through a mathematical model or algorithm on the basis of considering the attenuation relationship related to suspended particles in the water body to be measured (such as the influence of temperature and viscosity environmental factors on the optical properties or motion state of suspended particles) over time or space, so as to eliminate or weaken the interference of environmental factors, thereby obtaining a dynamic turbidity value that more accurately reflects the true turbidity state of the water body.

[0052] In specific implementation, the turbidity gradient of suspended particles in the water body to be tested is dynamically compensated according to the attenuation relationship. The compensated turbidity gradient can be obtained by the following method: spatially matching the attenuation relationship with the turbidity gradient of the water body to be tested based on the spatial interpolation method of the geographic information system. For each turbidity in the turbidity gradient of the water body to be tested, the turbidity is multiplied by the compensation coefficient (compensation coefficient = 1-attenuation relationship) to achieve dynamic compensation of the turbidity gradient, thereby obtaining a compensated turbidity gradient. The compensated turbidity gradient reflects the compensated turbidity gradient under the influence of temperature and can intuitively reflect the effect of the attenuation relationship on reducing turbidity. The dynamic turbidity value of the water body to be tested determined by the compensated turbidity gradient can be achieved by the following method: weighted summing the compensated turbidity values ​​in the compensated turbidity gradient can be performed using the area weighted average method, and the value obtained by the weighted summing is used as the dynamic turbidity value of the water body to be tested. In other embodiments, other methods can be used for determination, which are not limited here.

[0053] It should be noted that the dynamic turbidity value in the present application refers to the turbidity value obtained after dynamic compensation of the turbidity value in the water body to be measured, which can be used to predict the turbidity value in the water body to be measured.

[0054] In addition, in another aspect of the present application, in some embodiments, the present application provides a water turbidity measurement system for water ecological survey, referring to Figure 4 This figure is a schematic structural diagram of a water turbidity measurement system for water ecological survey according to some embodiments of the present application. The water turbidity measurement system 400 for water ecological survey includes: an acquisition module 401, a processing module 402, and an execution module 403, which are described as follows: Acquisition module 401, in this application, the acquisition module 401 is mainly used to alternately illuminate the water body to be measured and collect the scattered light signal of the water body to be measured; Processing module 402, in the present application, is used to synchronously fit the scattered light signal and the light signal of the environmental background corresponding to the water body to be measured, obtain the scattering difference characteristics of the suspended particles in the water body to be measured, and determine the disturbance error of the flow velocity in the water body to be measured on the suspended particles; It should be noted that the processing module 402 in the present application is also used to construct a turbidity inversion model for the water body to be measured, and perform turbidity inversion on the suspended particles in the water body to be measured based on the turbidity inversion model combined with the scattering difference characteristics and the disturbance error to obtain the turbidity gradient of the suspended particles in the water body to be measured; In addition, it should be noted that the processing module 402 in the present application is also used to determine the viscosity state of the water body dynamics in the water body to be tested, and determine the attenuation relationship between the suspended particles in the water body to be tested and the temperature based on the viscosity state and the fluctuation characteristics of the ambient temperature of the water body to be tested; The execution module 403 in this application is mainly used to dynamically compensate the turbidity gradient of the suspended particles in the water body to be measured through the attenuation relationship, and then obtain the dynamic turbidity value of the water body to be measured.

[0055] In addition, the present application also provides a computer device, which includes a memory and a processor, wherein the memory stores code, and the processor is configured to obtain the code and execute the above-mentioned water turbidity measurement method for water ecological survey.

[0056] In some embodiments, reference Figure 5 , which is a schematic diagram of the structure of a computer device for implementing a water turbidity measurement method for water ecological survey according to some embodiments of the present application. The water turbidity measurement method for water ecological survey in the above embodiment can be Figure 5 The computer device 500 shown in FIG. 5 is implemented as shown in FIG. 5 . The computer device 500 includes at least one processor 501 , a communication bus 502 , a memory 503 , and at least one communication interface 504 .

[0057] The processor 501 may be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0058] The communication bus 502 may be used to transmit information between the aforementioned components.

[0059] The memory 503 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, a random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. The memory 503 may be independent and connected to the processor 501 via the communication bus 502. The memory 503 may also be integrated with the processor 501.

[0060] The memory 503 is used to store program code for executing the solution of the present application, and is controlled by the processor 501. The processor 501 is used to execute the program code stored in the memory 503. The program code may include one or more software modules. The method used in the above embodiment can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0061] The communication interface 504 uses any device such as a transceiver to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0062] In a specific implementation, as an example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor herein may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0063] The aforementioned computer device can be a general-purpose computer device or a dedicated computer device. In a specific implementation, the computer device can be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of this application do not limit the type of computer device.

[0064] In addition, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned water turbidity measurement method for water ecological survey.

[0065] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0066] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for measuring water turbidity for water ecological survey, characterized in that: The steps include: Alternately irradiating a water body to be measured and collecting scattered light signals of the water body to be measured; Synchronously fitting the scattered light signal and the light signal of the environmental background corresponding to the water body to be measured to obtain the scattering difference characteristics of the suspended particles in the water body to be measured, and determining the disturbance error of the flow velocity in the water body to be measured on the suspended particles; Constructing a turbidity inversion model for the water body to be measured, and performing turbidity inversion on the suspended particles in the water body to be measured based on the turbidity inversion model in combination with the scattering difference characteristics and the disturbance error to obtain a turbidity gradient of the suspended particles in the water body to be measured; Determining the viscosity state of the water body dynamics in the water body to be measured, and determining the attenuation relationship between suspended particles and temperature in the water body to be measured based on the viscosity state and the fluctuation characteristics of the ambient temperature of the water body to be measured; The turbidity gradient of the suspended particles in the water body to be measured is dynamically compensated by the attenuation relationship, thereby obtaining the dynamic turbidity value of the water body to be measured.

2. The method according to claim 1, wherein Synchronously fitting the scattered light signal and the light signal of the environmental background corresponding to the water body to be tested to obtain the scattering difference characteristics of the suspended particles in the water body to be tested specifically includes: Collecting the light signal of the environmental background corresponding to the water body to be measured; Preprocessing the scattered light signal and the light signal of the environmental background to obtain a preprocessed scattered light signal and a preprocessed light signal of the environmental background; Performing time series alignment on the preprocessed scattered light signal and the preprocessed ambient background light signal to obtain a time series signal data set; The light scattering difference characteristics of suspended particles in the water body to be tested are extracted from the time series signal data set.

3. The method according to claim 1, wherein Determining the disturbance error of the flow velocity in the measured water body on the measurement of suspended particles specifically includes: Obtaining a three-dimensional flow velocity distribution of the water body to be measured; Determine the horizontal loss and vertical loss of suspended particles due to the flow velocity in the water body to be measured according to the three-dimensional flow velocity distribution; The disturbance error of the flow velocity in the water body to be measured on the measurement of suspended particles is determined by the horizontal loss and the vertical loss.

4. The method according to claim 1, wherein Performing turbidity inversion on the suspended particles in the water body to be measured based on the turbidity inversion model in combination with the scattering difference characteristics and the disturbance error to obtain the turbidity gradient of the suspended particles in the water body to be measured specifically includes: performing normalization processing on the scattering difference feature to obtain a standardized scattering difference feature; The turbidity gradient of suspended particles in the water body to be measured is determined based on the turbidity inversion model combined with the standardized scattering difference characteristics and the disturbance error.

5. The method according to claim 1, wherein Determining the viscosity state of the water body dynamics in the water body to be measured specifically includes: Monitoring temperature, salinity and pressure data at different depths in the water body to be measured; The viscosity state of the water body dynamics in the water body to be measured is determined based on the temperature, salinity and pressure data at different depths.

6. The method according to claim 1, wherein Determining the attenuation relationship between suspended particles and temperature in the water body to be measured according to the viscosity state and the fluctuation characteristics of the ambient temperature of the water body to be measured specifically includes: Determining the fluctuation characteristics of the ambient temperature of the water body to be measured; performing correlation analysis on the viscosity state and the fluctuation characteristics of the ambient temperature to obtain correlation characteristics between temperature and viscosity; The attenuation relationship between suspended particles and temperature in the water body to be measured is determined according to the correlation characteristics.

7. The method according to claim 1, wherein Dynamically compensating the turbidity gradient of suspended particles in the water body to be measured by using the attenuation relationship, and then obtaining the dynamic turbidity value of the water body to be measured specifically includes: Dynamically compensating the turbidity gradient of suspended particles in the water body to be measured according to the attenuation relationship to obtain a compensated turbidity gradient; The dynamic turbidity value of the water body to be measured is determined by the compensated turbidity gradient.

8. The method according to claim 1, wherein A photoelectric detector is used to collect the scattered light signal of the water body to be measured.

9. The method according to claim 1, wherein A machine learning algorithm is used to construct a turbidity inversion model for the water area to be measured.

10. A water turbidity measurement system for water ecological survey, characterized in that: include: An acquisition module, configured to alternately illuminate the water body to be measured and acquire scattered light signals of the water body to be measured; a processing module for synchronously fitting the scattered light signal and the light signal of the environmental background corresponding to the water body to be measured, obtaining the scattering difference characteristics of the suspended particles in the water body to be measured, and determining the disturbance error of the flow velocity in the water body to measure the suspended particles; The processing module is further configured to construct a turbidity inversion model for the water body to be measured, and perform turbidity inversion on the suspended particles in the water body to be measured based on the turbidity inversion model in combination with the scattering difference characteristics and the disturbance error, to obtain a turbidity gradient of the suspended particles in the water body to be measured; The processing module is further configured to determine the viscosity state of the water body dynamics in the water body to be tested, and determine the attenuation relationship between the suspended particles in the water body to be tested and the temperature based on the viscosity state and the fluctuation characteristics of the ambient temperature of the water body to be tested; An execution module is used to dynamically compensate the turbidity gradient of suspended particles in the water body to be measured according to the attenuation relationship, thereby obtaining a dynamic turbidity value of the water body to be measured.

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