Bottom mud resuspension dimming method for water source algae control

Abstract

The invention discloses a bottom mud resuspension dimming method for water source algae control, and relates to the technical field of blue-green algae prevention and control, the method comprises the following steps: establishing an experiment system comprising a plurality of groups of independent water body simulation devices, each group of device being provided with a bivariate combination of bottom mud concentration and resuspension frequency; constructing a parameterized extinction model related to the sediment concentration and the sedimentation time based on the real-time illumination data of the vertical layered optical monitoring network; the turbidity of the water body is monitored in real time, when the turbidity exceeds a critical value, a dynamic compensation coefficient is generated, and a theoretical daily light receiving quantity threshold value is increased according to a direct proportion relation; traversing all double-variable combinations, and screening variable combinations which simultaneously meet the condition that the actual daily light receiving quantity is not greater than the theoretical threshold value subjected to turbidity correction and the product of the total bottom mud adding quantity and the mechanical energy consumption is minimized. According to the scheme, the parameter adaptability under the complex hydrological condition is remarkably improved, the theoretical optimal cost boundary is approached, and the algae control interruption risk is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of cyanobacteria prevention and control, and particularly relates to a method for controlling algae in water source by resuspending and light adjusting of sediment. BACKGROUND

[0002] The ecological competitive advantage of filamentous cyanobacteria is derived from its strong adaptability to low light environment, and its proliferation in moderately eutrophic water bodies seriously threatens water safety. The resuspension technology of sediment has become one of the core means of physical algae control by disturbing sediments to increase water turbidity and reduce underwater light transmittance to inhibit cyanobacterial photosynthesis. The existing technology mainly determines the operation parameters by establishing a static mapping relationship between sediment concentration and extinction coefficient, or combines a simple cost function to screen the resuspension scheme. This kind of method forms a basic technical path in shallow reservoirs, but it is difficult to adapt to the dynamic hydrological environment of deep reservoirs and the differences in the photosynthetic characteristics of filamentous cyanobacteria.

[0003] The limitations of the current technology mainly reflect in the following aspects: 1. The parameter optimization focuses on a single variable of concentration, ignoring the dynamic sedimentation compensation effect of resuspension frequency, resulting in fluctuations in actual light exposure exceeding the theoretical threshold within the algae control period; 2. The extinction model does not integrate the background disturbance factors of water body, and the Mie scattering of suspended particles in high turbidity water will increase the measured extinction value, and seasonal water level changes will cause the mixed layer depth to deviate, both of which will cause calculation deviation of daily light exposure; 3. The optimization goal only meets the algae control light threshold, without coupling the collaborative constraints of sediment dosage and mechanical energy consumption, causing material waste and soaring operating costs. Therefore, based on the above problems, the present application proposes a method for controlling algae in water source by resuspending and light adjusting of sediment. SUMMARY

[0004] PURPOSE OF THE INVENTION In order to solve the above problems, the purpose of the present application is to provide a method for controlling algae in water source by resuspending and light adjusting of sediment, which aims to overcome the defects of traditional methods that only focus on sediment concentration and ignore the dynamic compensation effect of resuspension frequency, avoid turbidity accumulation out of control caused by high-frequency resuspension, establish a light attenuation dynamic calibration mechanism, solve the problem of excessive sediment discharge and mechanical energy consumption redundancy caused by relying on a single algae control threshold in the prior art, and propose a collaborative optimization path under cost constraints.

[0005] TECHNICAL SCHEME To achieve the above object, the application provides a bottom mud resuspension light adjustment method for water source algae control, which comprises the following steps.

[0006] In the first aspect, the application provides a bottom mud resuspension light adjustment method for water source algae control, which comprises the following steps. An experimental system comprising multiple groups of independent water body simulation devices is established, and each group of devices is provided with a double-variable combination of bottom mud concentration and resuspension frequency. A parameterized extinction model related to bottom mud concentration and settling time is constructed based on real-time light data of a vertical layered optical monitoring network, and the model represents an initial extinction gain coefficient and a settling attenuation coefficient by a quadratic polynomial function. The turbidity of the water body is monitored in real time, and when the turbidity exceeds a critical value, a dynamic compensation coefficient is generated, and the theoretical daily light intensity threshold is increased in a proportional relationship. All double-variable combinations are traversed, and the bottom mud concentration and resuspension frequency combination that simultaneously satisfies the actual daily light intensity not greater than the turbidity-corrected theoretical threshold and the product of the total amount of bottom mud and mechanical energy consumption minimized is screened.

[0007] Further, in the experimental setup, the bottom mud concentration gradient covers the low-concentration sensitive area to the high-concentration saturated area, and the resuspension frequency gradient covers the single-day multiple-operation range, wherein the concentration gradient is configured according to a nonlinear rule to enhance the parameter resolution in the low-concentration area.

[0008] Further, the resuspension frequency optimization is additionally constrained by an operation interval, the minimum time interval between two adjacent resuspension operations is not less than a preset threshold, and the total resuspension time in a single day is not more than half of the effective illumination period.

[0009] Further, the layered light monitoring is realized by an optical sensor array arranged in the simulation device, the sensors are distributed at equal intervals along the vertical direction, and light intensity data of at least four depth layers are collected in real time.

[0010] Further, the initial extinction gain coefficient of the parameterized extinction model is determined by a quadratic polynomial function of the bottom mud concentration, the settling attenuation coefficient is dominated by a quadratic function of the bottom mud concentration, and the final value of the extinction coefficient is expressed as a linear combination of the initial gain coefficient and the settling attenuation coefficient with respect to the logarithm of time.

[0011] Further, when the real-time water body turbidity exceeds the critical turbidity, the theoretical daily light intensity threshold is proportionally increased, and the increase amplitude is positively correlated with the turbidity value.

[0012] Further, the compensation function is:

[0013] In the formula, is the extinction coefficient compensation value; is the turbidity gain coefficient; is the real-time water body turbidity; is the critical turbidity.

[0014] By establishing a segmented function relationship between turbidity and extinction compensation coefficient, the extinction virtual increase effect caused by Mie scattering of suspended particles in high turbidity water bodies is eliminated. The dynamic calibration of the extinction model output value ensures that the actual daily light intensity calculation is consistent with the true light attenuation characteristics, thereby improving the robustness of parameter optimization in high disturbance scenarios; at the same time, by adaptively relaxing the theoretical threshold requirement, the invalid resuspension operation caused by conservative strategy is avoided, and the matching accuracy of the sediment dosage and the actual demand is significantly improved.

[0015] Further, it further includes a water level dynamic calibration mechanism, generates a water level and light attenuation correction coefficient based on historical water level data, dynamically adjusts the mixed layer depth calculation value in a proportional relationship according to the offset of the real-time water level and the reference water level, and substitutes the calibrated mixed layer depth into the daily light intensity integral calculation.

[0016] Further, the calibration function is:

[0017] In the formula, is the calibrated mixed layer depth; is the initial mixed layer depth; is the water level and light attenuation historical correction coefficient; is the difference between the real-time water level and the average water level .

[0018] Based on historical water level data, the correction coefficient is generated to dynamically calibrate the mixed layer depth calculation value. When the water level drops, the calculation depth is automatically reduced, eliminating the underestimation of light attenuation by traditional fixed depth models; when the water level rises, the depth is expanded, avoiding systematic overestimation of light intensity. The calibrated mixed layer depth accurately matches the real hydrological conditions, driving the generation of differentiated resuspension strategies with high frequency and low concentration in dry season and low frequency and high concentration in wet season, effectively reducing the risk of algae control interruption caused by hydrological period replacement, and avoiding the water source safety threshold of 200,000 cells / mL of algae density.

[0019] In a second aspect, the present application also provides a bottom sediment resuspension light modulation system for water source algae control, which is based on the method of the first aspect and comprises: An orthogonal experiment array unit, which is composed of a plurality of independently controllable cuboid water body simulation devices, each device being equipped with a bottom sediment concentration regulator and a resuspension frequency controller; A multi-dimensional optical monitoring unit, which is integrated into a vertical layered optical sensor network in each simulation device and is used for real-time collection of underwater light intensity; A dynamic modeling unit, which is internally provided with an extinction coefficient parameterization calculation engine and a daily light exposure integral algorithm; An optimized decision unit, which is connected to a theoretical daily light exposure threshold input interface and performs double-variable combination traversal and cost minimization screening.

[0020] Further, the optimized decision unit is integrated with a cost weight configuration module, which allows self-definition of the weight ratio of the bottom sediment cost coefficient and the energy consumption cost coefficient, and generates an optimized scheme adapted to different economic conditions.

[0021] In a third aspect, the present application also provides a computer readable storage medium, which stores a computer program, and the computer program is run by a processor to execute the method for water source algae control.

[0022] The present application covers a nonlinear gradient from a low-concentration sensitive area to a high-concentration saturated area by setting double-variable combinations of bottom sediment concentration and resuspension frequency through a plurality of independent water body simulation devices, and explicitly quantifies the interaction effect of parameters; real-time light data are collected based on a vertical layered optical sensor network to establish an extinction coefficient parameterization model characterized by a quadratic polynomial function; when the water turbidity exceeds a critical value, the theoretical daily light exposure threshold is proportionally increased to offset the interference of suspended particles scattering, and a light attenuation correction coefficient is generated based on historical water level data to dynamically adjust the calculated value of the mixed layer depth; finally, the theoretical daily light exposure required for filamentous cyanobacteria inhibition is taken as a constraint to traverse the experimental combinations and screen combinations meeting the conditions.

[0023] The turbidity compensation and water level calibration mechanism of the scheme eliminates the light attenuation calculation deviation caused by the scattering effect of high-turbidity water bodies and seasonal water level fluctuations, significantly improves the parameter adaptability under complex hydrological conditions; the cost product optimization criterion drives resource collaborative constraints, reduces the bottom sediment redundancy by more than 34% and the energy consumption redundancy by more than 27% compared with the traditional single threshold method, and approaches the theoretical optimal cost boundary; the orthogonal experiment double-variable design accurately captures the interaction effect of concentration and frequency, combined with environmental adaptive correction, ensures the stable execution of the differentiated strategy of high frequency and low concentration in dry season and low frequency and high concentration in wet season, and reduces the algae control interruption risk by more than 40%.

[0024] Advantages By implementing the above-mentioned method for controlling algae in water sources by resuspending and light adjusting of sediment, the following technical effects are achieved: (1) By orthogonal experimental design of concentration and resuspension frequency, the interaction effect of parameters is quantified. The non-linear gradient configuration covers the sensitive area of low concentration to the saturation area of high concentration, strengthens the resolution of key parameters, provides high-fidelity input data set for dynamic modeling of extinction coefficient, and completely avoids the problem of light fluctuation out of control in the algae control period caused by traditional single-variable optimization.

[0025] (2) Breakthrough the traditional single algae control threshold constraint mode, add the minimum target of the product of the total amount of sediment and mechanical energy consumption. This criterion forces resource coordination constraints, synchronously inhibits excessive sediment and mechanical redundant energy consumption under the premise of meeting the algae control light threshold, makes the comprehensive resource consumption tend to the theoretical optimal boundary, and systematically solves the problem of low running efficiency caused by the lack of cost dimension in the existing method.

[0026] (3) By establishing the segmented function relationship between turbidity and extinction compensation coefficient, the extinction virtual increase effect caused by Mie scattering of suspended particles in high turbidity water is eliminated. The output value of the extinction model is dynamically calibrated to ensure that the actual daily light amount calculation is consistent with the true light attenuation characteristics, thereby improving the robustness of parameter optimization in high disturbance scenarios; at the same time, by adaptively relaxing the theoretical threshold requirement, the invalid resuspension operation caused by conservative strategy is avoided, and the matching accuracy of sediment dosage and actual demand is significantly improved.

[0027] (4) Based on the historical water level data to generate a correction coefficient to dynamically calibrate the calculated value of the mixed layer depth. When the water level drops, the calculated depth is automatically reduced to eliminate the underestimation of light attenuation by the traditional fixed depth model; when the water level rises, the depth is expanded to avoid systematic overestimation of light amount. The calibrated mixed layer depth accurately matches the real hydrological conditions to generate differentiated resuspension strategies of high frequency and low concentration in dry season and low frequency and high concentration in wet season, effectively reducing the risk of algae control interruption caused by hydrological period replacement. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to make the above-mentioned method for controlling algae in water sources by resuspending and light adjusting of sediment of the present application more obvious and easy to understand, the drawings needed in the specific embodiments of the present application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application, and other drawings can be obtained from these drawings without creative labor for those skilled in the art.

[0029] Figure 1 The flowchart of the method of the present application is shown; Figure 2 The flowchart of the system construction of the orthogonal experiment is shown; Figure 3 The flowchart of the system hardware integration is shown. DETAILED DESCRIPTION

[0030] Example 1 A sediment resuspension light modulation method for water source algae control is provided, and the method flow is shown in Figure 1 The method comprises the following steps: establishing an experimental system comprising a plurality of groups of independent water body simulation devices, each group of devices being provided with a double variable combination of sediment concentration and resuspension frequency; constructing a parameterized extinction model related to sediment concentration and sedimentation time based on real-time light data of a vertical layered optical monitoring network, the model representing an initial extinction gain coefficient and a sedimentation attenuation coefficient by a quadratic polynomial function; monitoring the turbidity of the water body in real time, generating a dynamic compensation coefficient when the turbidity exceeds a critical value, and proportionally increasing the theoretical daily light threshold; traversing all double variable combinations and selecting a combination of sediment concentration and resuspension frequency that simultaneously satisfies the actual daily light not being greater than the turbidity corrected theoretical threshold and the product of the total amount of sediment and mechanical energy consumption being minimized.

[0031] The specific implementation is as follows.

[0032] The orthogonal experimental system construction process is shown in Figure 2 Suppose that 25 groups of cuboid water body simulation devices are deployed in a reservoir, with a size of 4.0m×0.5m×0.5m, and the bottom of the device is open to maintain hydraulic exchange.

[0033] The sediment concentration gradient is set to 0.1, 1.0, 4.0, 6.0, and 8.0g / L, covering the low concentration sensitive area to the high concentration saturation area; the resuspension frequency gradient is set to 1, 3, and 5 times / day, with an adjacent operation interval of ≥150 minutes.

[0034] Five layers of optical sensors are vertically arranged in each device, specifically at water depths of 0.5, 1.0, 2.0, 3.0, and 4.0m, and the light intensity is recorded every 15 minutes for 48 hours.

[0035] Based on the vertical layered light data, a quadratic polynomial extinction model is established:

[0036]

[0037]

[0038] In the formula, is a dynamic extinction coefficient; is an initial extinction gain coefficient; is a sedimentation attenuation coefficient; is a sedimentation time; is an initial gain calibration coefficient, preferably 0.781; is an initial gain calibration coefficient, preferably 2.03; is the concentration of the sediment; is the initial gain calibration coefficient, preferably -0.196; is the settling decay calibration coefficient, preferably -0.071; is the settling decay calibration coefficient, preferably 0.601; is the settling decay calibration coefficient, preferably -0.057.

[0039] The integral solution of the actual daily light exposure is:

[0040] In the formula, is the total daily light exposure of the algal cells; and is the effective light illumination start and end time; is the surface light intensity; is the dynamic extinction coefficient; is the water body mixed layer depth.

[0041] Real-time monitoring of water turbidity is performed, and when the water turbidity > 50 NTU:

[0042] In the formula, is the theoretical daily light exposure; is the water turbidity.

[0043] Dry season reference water level , real-time water level :

[0044] The fixed value is replaced by to calculate .

[0045] The external system provides the theoretical daily light exposure .

[0046] The 25 sets of experimental data are traversed to screen for: 1, ; 2, minimize the cost product = (total amount of sediment addition) × (mechanical energy consumption).

[0047] The optimal solution combination is shown in Table 1: Table 1, optimal solution combination Combination Sediment concentration (g / L) Resuspension frequency (times / day) Total light received per day (mol / m2 / d) Cost product M7 2 3 5.15 42 M12 4 2 4.98 64.8 The M7 combination is selected, which satisfies the light constraint and has the lowest cost product.

[0048] After water level calibration, the total daily light exposure calculation deviation is reduced from 18.2% to 2.1%; compared with the traditional single variable method, the sediment dosage is reduced by 31% and the energy consumption is reduced by 28%.

[0049] Example 2: The Mie scattering effect of suspended particles in high-turbidity water can artificially inflate measured extinction values, leading to errors in transmittance calculations. This mechanism addresses this by establishing a piecewise functional relationship between turbidity and the extinction compensation coefficient, dynamically calibrating the extinction model: When the real-time turbidity is below the critical value, the baseline extinction model is maintained; When the turbidity exceeds the critical value, a compensation coefficient proportional to the turbidity increment is introduced to counteract the light scattering interference from suspended particles.

[0050] Setting the critical turbidity threshold: Calibrating the critical turbidity based on historical reservoir data. For example, 50 NTU; Construct the compensation function:

[0051] In the formula, This is the extinction coefficient compensation value; This is the turbidity gain coefficient; Real-time water turbidity; This is the critical turbidity.

[0052] Will Superimposed on parameterized extinction coefficient Generate calibrated extinction values .

[0053] System hardware integration process as follows Figure 3 As shown.

[0054] In the scenario of torrential rain runoff, the error in light transmittance calculation was reduced from 18.7% to 3.2% using traditional methods; and the cost of redundant materials was reduced by 34% due to accurate control of the amount of sediment added.

[0055] The results show that traditional methods, by neglecting the Mie scattering effect of suspended particles in high-turbidity water, lead to an overestimation of the extinction coefficient, resulting in a systematic underestimation of sediment concentration. This mechanism, through dynamic compensation triggered by a turbidity threshold, ensures that the output value of the extinction model always matches the actual light attenuation characteristics, thus minimizing the calculation error of actual daily light received. In scenarios with sudden turbidity changes such as torrential rain runoff, the system automatically relaxes the theoretical daily light received threshold requirement, avoiding ineffective resuspension operations caused by conservative strategies. This mechanism improves the matching degree between sediment dosage and actual demand to near-ideal levels, completely avoiding the redundant dosage problem caused by parameter distortion in traditional methods.

[0056] Example 3: Seasonal water level fluctuation causes the mixed layer depth to deviate. To avoid the distortion of light attenuation calculation caused by the fixed depth value in the traditional method, a water level and mixed layer depth dynamic calibration algorithm is added. The algorithm constructs a depth calibration function through the water level deviation and historical attenuation coefficient to dynamically adjust the mixed layer calculation value.

[0057] The average water level in the dry season of the water intake reservoir is the reference value; The calibration function is generated:

[0058] In the formula, is the calibrated mixed layer depth; is the initial mixed layer depth; is the water level and light attenuation historical correction coefficient; is the difference between the real-time water level and the average water level .

[0059] Substitute the fixed depth value with in the daily light exposure integral algorithm.

[0060] When the water level drops by 2 m, the daily light exposure calculation deviation is compressed from 21.5% to 4.1%. Due to the accurate matching of the mixed layer depth, the daily average energy consumption is reduced by 27% after optimizing the resuspension frequency.

[0061] The results show that when the water level drops, the algorithm automatically reduces the mixed layer calculation depth, eliminating the underestimation of light attenuation by the traditional fixed depth model. When the water level rises, the depth is expanded to avoid underestimation of light exposure. The calibrated mixed layer depth is completely consistent with the real hydrological conditions, making the daily light exposure integral result accurately reflect the actual light exposure level of filamentous cyanobacteria. The calibration algorithm drives the parameter optimization module to generate differentiated resuspension schemes. In the dry season, a high-frequency low-concentration strategy is adopted to match the shallow water environment, and in the wet season, a low-frequency high-concentration mode is switched to adapt to deep water diffusion, significantly reducing the risk of algae control interruption caused by hydrological period replacement.

[0062] Those skilled in the art will appreciate that embodiments of the present application can be provided as methods, systems or computer program products. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable non-transitory storage media having computer-usable program code embodied in the medium.

[0063] The present application can provide computer program instructions to the management platform of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the management platform of the computer or other programmable data processing device generate a device for implementing the system.

[0064] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function specified.

[0065] These computer program instructions can also be loaded into a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing other functions which are specified.

Claims

1. A method for sediment resuspension dimming for water source algae control, characterized in that, Comprising: Establishing an experimental system containing multiple groups of independent water body simulation devices, each group of devices setting a two-variable combination of sediment concentration and resuspension frequency; Based on the real-time light data of the vertical stratified optical monitoring network, a parameterized extinction model related to sediment concentration and settling time is constructed; Real-time monitoring of water turbidity, when the turbidity exceeds the critical value, a dynamic compensation coefficient is generated, and the theoretical daily light threshold is proportionally increased; Iterate through all two-variable combinations and select the variable combination that simultaneously satisfies the actual daily light intensity not greater than the turbidity corrected theoretical threshold and the product of the total amount of sediment added and the mechanical energy consumption minimized.

2. The method of claim 1, wherein: In the experimental setup, the sediment concentration gradient covers the low concentration sensitive area to the high concentration saturation area, and the resuspension frequency gradient covers the single day multiple operation range, wherein the concentration gradient is configured according to a nonlinear rule.

3. The method of claim 2, wherein: The resuspension frequency optimizes the additional operation interval constraint, the minimum time interval between adjacent two resuspension operations is not less than a preset threshold, and the total resuspension time per day is not more than half of the effective illumination period.

4. The method of claim 1, wherein: The stratified light monitoring is realized by arranging an optical sensor array in the simulation device, the sensors are equally spaced along the vertical direction, and the light intensity data of at least four depth layers are collected in real time.

5. The method of claim 1, wherein: The initial extinction gain coefficient of the parameterized extinction model is determined by a quadratic polynomial function of the sediment concentration, the settling decay coefficient is dominated by a quadratic function of the sediment concentration, and the final extinction coefficient is expressed as a linear combination of the initial gain coefficient and the settling decay coefficient with respect to the logarithm of time.

6. The method of claim 1, wherein: When the real-time water turbidity exceeds the critical turbidity, the theoretical daily light threshold is proportionally increased, and the increase amplitude is positively correlated with the turbidity value.

7. The method of claim 1, further comprising: A water level dynamic calibration mechanism, based on historical water level data to generate water level and light attenuation correction coefficients, according to the offset of real-time water level and reference water level, proportionally adjusting the mixed layer depth calculation value, and substituting the calibrated mixed layer depth into the daily light integral calculation.

8. A sediment resuspension light modulation system for water source algae control, characterized in that: The implementation of the system is based on the method of any one of claims 1-7: The system comprises: An orthogonal experiment array unit composed of several independent controllable cuboid water body simulation devices, each device equipped with a sediment concentration regulator and a resuspension frequency controller; A multi-dimensional optical monitoring unit integrated with a vertical stratified optical sensor network in each simulation device for real-time acquisition of underwater light intensity; A dynamic modeling unit with a parameterized calculation engine of extinction coefficient and a daily light integral algorithm; An optimization decision unit connected to a theoretical daily light threshold input interface, performing two-variable combination iteration and cost minimization screening.

9. The system of claim 8, wherein: The optimization decision unit integrates a cost weight configuration module, which allows customizing the weight ratio of the sediment cost coefficient and the energy consumption cost coefficient.

10. A computer readable storage medium having stored therein a computer program, characterized in that: The computer program, when executed by a processor, performs the method of any one of claims 1-7.

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