A method for preventing a blue-green algae outbreak by setting a bloom control curve

Abstract

The application discloses a method for preventing blue-green algae outbreak by setting algal bloom control curve, comprising the following steps: determining the chlorophyll a concentration threshold K of blue-green algae outbreak of a target lake; calculating the turning point time T of blue-green algae growth of the target lake z ; calculating the turning point time T s of blue-green algae growth and the chlorophyll a concentration of the target lake; calculating the algal bloom control curve one based on the turning point time T z and the chlorophyll a concentration; calculating the algal bloom control curve two based on the turning point time T z and the turning point time T s ; and setting the area below the lower curve of the two curves as the chlorophyll a concentration control range of the target lake at the corresponding time according to the algal bloom control curve one and the algal bloom control curve two. The application can prevent large-area high-concentration outbreak of blue-green algae in the lake, long-term effectively guarantee the water ecological environment quality of the lake, and reduce the cost of algal bloom control measures and fully exert the engineering benefits.

Description

Technical Field

[0001] This invention relates to a method for preventing cyanobacterial blooms, and more particularly to a method for preventing cyanobacterial blooms by setting an algal bloom control curve. Background Technology

[0002] Cyanobacteria can form dense, sometimes toxic, algal blooms in both freshwater and marine environments. The frequency and timing of these blooms vary from year to year, with distinct seasonal characteristics. A typical algal bloom can be defined as a phenomenon in which algae proliferate and aggregate under certain temperature, light, and nutrient conditions, resulting in a significant increase in biomass within a short period. This causes noticeable changes in water color and forms a thin or thick layer of blue-green, foul-smelling foam on the water surface, thus affecting the ecological balance.

[0003] Control measures for cyanobacterial blooms can be categorized into various methods, including physical methods (aeration, ultrasonic algae control, mechanical harvesting, etc.), chemical methods (flocculation, hydrogen peroxide, copper ion methods, etc.), and biological methods (classical and non-classical biomanipulation techniques, microbial algae control, aquatic plant algae control, etc.). However, once cyanobacteria bloom, they reproduce rapidly. Relying on post-bloom control measures is costly and yields low returns, and it is difficult to control the continuous and significant increase in cyanobacterial biomass.

[0004] However, a crucial fact is often overlooked: a biomass accumulation process inevitably precedes algal blooms. This process can be characterized and described by changes in chlorophyll a concentration. Some eutrophic lakes use a chlorophyll a concentration of 40.0 μg / L as the threshold for cyanobacterial blooms. Therefore, while existing control measures can control the severity of algal blooms to some extent after they occur, to prevent them—that is, to keep the maximum chlorophyll a concentration below the bloom threshold—it is essential to maintain the chlorophyll a concentration within the algal bloom control curve. This is the most effective way to ensure the long-term quality of the lake's aquatic ecosystem. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to provide a method for preventing cyanobacterial blooms by setting an algal bloom control curve. This method can prevent large-scale, high-concentration cyanobacterial blooms in lakes, providing a basis for the long-term and effective protection of the quality of the lake's aquatic ecological environment.

[0006] Technical solution: This invention includes:

[0007] Determine the chlorophyll a concentration threshold K for cyanobacterial blooms in the target lake;

[0008] Calculate and determine the inflection point time T for cyanobacterial growth in the target lake. z ;

[0009] Calculate and determine the time T of the initial peak of cyanobacterial growth in the target lake. s and chlorophyll a concentration ;

[0010] Based on the inflection point time T z and chlorophyll a concentration The first control curve for algal bloom was obtained by calculation;

[0011] Based on the inflection point time T z and the time of the beginning of the peak T s The second control curve for algal bloom was calculated.

[0012] Based on the algal bloom control curve 1 and algal bloom control curve 2, the region located below the lower curve is selected as the chlorophyll a concentration control range for the target lake at the corresponding time.

[0013] The turning point time T z Based on historical data of typical cyanobacteria growth periods, the determination was made by fitting the growth model.

[0014] The T z The calculation formula is obtained from the second derivative of the growth model:

[0015]

[0016]

[0017] when When, find the inflection point time T. z The calculation formula is:

[0018]

[0019] In this process, the parameters b and r in the fitting equation for each time period are substituted into T. z The calculation formula for the inflection point time T z The mean of the results calculated for each time period is rounded up to the nearest integer.

[0020] The chlorophyll a concentration This represents the average chlorophyll a concentration at the initial peak point of each time period.

[0021] The T s Based on historical data of typical cyanobacteria growth periods, the determination was made by fitting the growth model.

[0022] The T s The calculation formula is obtained from the third derivative of the growth model:

[0023]

[0024] when and At that time, the initial peak time T is obtained. s The calculation formula is:

[0025]

[0026] In this process, the parameters b and r in the fitting equation for each time period are substituted into T. s The calculation formula for the initial peak time T s The mean of the results calculated for each time period is rounded down to the nearest integer.

[0027] The calculation formula for the growth model is as follows:

[0028]

[0029] In the formula, t represents time; N t Let be the chlorophyll a concentration at time t; K be the chlorophyll a concentration threshold; e be the base of the natural logarithm; b and r are constants.

[0030] The calculation formula for the first algal bloom control curve is as follows:

[0031]

[0032] in,

[0033]

[0034]

[0035] Where a1 and r1 are constants.

[0036] The calculation formula for the second algal bloom control curve is as follows:

[0037]

[0038] in,

[0039]

[0040]

[0041] Where a2 and r2 are constants.

[0042] The historical typical cyanobacterial growth period shall be no less than two periods, and the chlorophyll a concentration threshold of each period shall be less than the K value.

[0043] Beneficial Effects: This invention establishes two algal bloom control curves and defines the region below the lower curve as the chlorophyll a concentration control range. On one hand, it minimizes the cumulative biomass from the initial bloom point to the inflection point, preventing large-scale cyanobacterial blooms. On the other hand, it minimizes the cumulative biomass from the inflection point to the chlorophyll a concentration threshold, preventing high-concentration cyanobacterial blooms, thus effectively ensuring the long-term quality of the lake's aquatic ecosystem. Furthermore, implementing different types of algal bloom control measures within the chlorophyll a concentration control range defined by this invention helps reduce the cost of algal bloom control measures and fully realizes the benefits of the project. Attached Figure Description

[0044] Figure 1 This example shows the fitting curve and equation for a typical cyanobacteria growth in a lake during 2021.

[0045] Figure 2 This example shows the control curve and range of a single algal bloom in a lake within a year. Detailed Implementation

[0046] The invention will now be further described with reference to the accompanying drawings.

[0047] This invention relates to a method for preventing cyanobacterial blooms by setting an algal bloom control curve, comprising the following steps:

[0048] Step 1: Determine the chlorophyll a concentration threshold K for cyanobacterial blooms in the target lake. Some eutrophic lakes use a chlorophyll a concentration of 40.0 μg / L as the K value, or the multi-year average chlorophyll a concentration of the month of the first cyanobacterial bloom can be used as the K value.

[0049] Step 2: Based on historical typical cyanobacteria growth period data, calculate and determine the cyanobacteria growth inflection point time T of the target lake after fitting the growth model. z ;

[0050] Step 3: Based on historical typical cyanobacteria growth period data, calculate and determine the initial peak time T of cyanobacteria growth in the target lake after fitting the growth model. s and chlorophyll a concentration ;

[0051] Step 4: Based on the turning point time T in Step 2 z And the chlorophyll a concentration in step three According to T z and The calculation formula is obtained by solving the simultaneous equations and using the growth model to obtain the algal bloom control curve.

[0052] Step 5: Based on the turning point time T in Step 2 z And the initial peak time T in step three s According to Tz and T s The calculation formula is obtained by solving the simultaneous equations and using the growth model to obtain the second algal bloom control curve;

[0053] Step 6: Based on the algal bloom control curve 1 and algal bloom control curve 2 determined in steps 4 and 5, select the area below the lower curve of the two curves and set it as the chlorophyll a concentration control range of the target lake at the corresponding time.

[0054] Step 7: Implement corresponding algal bloom control measures according to the control range determined in Step 6 to ensure that the chlorophyll a concentration is within the control range.

[0055] The growth model in steps two through five belongs to a type of S-shaped growth curve. S-shaped curves are commonly used to represent population growth under finite environmental conditions. Growth model fitting can be performed using data analysis software such as Origin and SPSS to obtain the fitting curves and equations for each time period. The calculation formula for the growth model in this invention is:

[0056]

[0057] In the formula, t represents time; N t Let be the chlorophyll a concentration at time t; K be the chlorophyll a concentration threshold; e be the base of the natural logarithm; and b and r be constants. This is obtained by fitting a growth model function, or by simultaneously solving the equations T... z and T s The equations are calculated, or T is solved simultaneously. z and The equation was calculated to obtain the result.

[0058] Among them, there should be no fewer than two historical typical cyanobacterial growth periods in steps two and three, and the chlorophyll a concentration threshold in each period should be less than the K value in step one.

[0059] The turning point in steps two, four, and five refers to the point where the chlorophyll a concentration increases at the greatest rate, corresponding to time T. z The calculation formula is obtained from the second derivative of the growth model:

[0060]

[0061]

[0062] when When, find the inflection point time T. z The calculation formula is:

[0063]

[0064] In this process, the parameters b and r in the fitting equation for each time period are substituted into T.z The calculation formula, the inflection point time T in step two. z Round the mean of the results calculated for each time period to the nearest integer, and then set this T... z Substitute these values ​​into steps four and five for subsequent calculations.

[0065] The initial peak point in steps three, four, and five refers to the point where the acceleration of chlorophyll a concentration increase is greatest, corresponding to time T. s The calculation formula is obtained from the third derivative of the growth model:

[0066]

[0067] when and At that time, the initial peak time T is obtained. s The calculation formula is:

[0068]

[0069] In this process, the parameters b and r in the fitting equation for each time period are substituted into T. s The calculation formula, the initial peak time T in step three. s Round the mean of the results calculated for each time period down to the nearest integer, and then use this T... s Substitute this into step five for subsequent calculations; chlorophyll a concentration This represents the average chlorophyll a concentration corresponding to the initial peak point at each time period. Then, this... Substitute this into step four.

[0070] The calculation process for the first control curve for algal bloom is as follows:

[0071]

[0072] in,

[0073]

[0074]

[0075] The calculation process for the second control curve for algal bloom is as follows:

[0076]

[0077] in,

[0078]

[0079]

[0080] This invention can prevent large-scale, high-concentration outbreaks of cyanobacteria in lakes, effectively protect the quality of the lake's aquatic ecological environment in the long term, reduce the cost of algal bloom control measures, and fully realize the benefits of engineering projects.

[0081] Example

[0082] The first cyanobacterial bloom in a certain lake occurred in April. The average chlorophyll a concentration in that month from 2010 to 2021 was approximately 48.4 μg / L. This value was set as the chlorophyll a concentration threshold K.

[0083] like Figure 1 As shown, data from two typical cyanobacteria growth periods in the lake during 2021 were selected. Based on the growth model equation, the fitting curves and equations for each time period were calculated and plotted using Origin data analysis software.

[0084] The fitted equation for the period from March 20th to March 28th is as follows:

[0085]

[0086] Where parameter b is 1037.46 and parameter r is 1.75, substituting into T z The calculation formula yields 3.97, which is then substituted into T. s The calculation formula yields 3.22, and T... s Substitute N t The calculation formula yields 1.74;

[0087] The fitted equation for the period from August 10th to August 22nd is as follows:

[0088]

[0089] Where parameter b is 747.89 and parameter r is 1.16, substituting into T z The calculation formula yields 5.70, which is then substituted into T. s The calculation formula yields 4.57, and T... s Substitute N t The calculation formula yields 6.36;

[0090] The average of the calculation results for March 20-March 28 and August 10-August 22 is taken as follows:

[0091]

[0092]

[0093]

[0094] T z Rounding up to the nearest integer gives 5. Then, set T... sRounding down to the nearest integer gives 3;

[0095] Substitute the above calculation results into T according to steps four and five. z T s and N t The calculation formula;

[0096] Lianli T z and The equation:

[0097]

[0098] The calculated parameter b is 396.82, the parameter r is 1.20, and the first control curve for algal bloom is as follows:

[0099]

[0100] Lianli T z and T s The equation:

[0101]

[0102] The calculated parameter b is 26.91, the parameter r is 0.66, and the second control curve for algal bloom is:

[0103]

[0104] like Figure 2 As shown, after steps four and five, the first and second control curves for a single algal bloom in a certain lake within the year are calculated. After step six, the area below the lower curve of the two curves is set as the control range for the single chlorophyll a concentration of the target lake within the year. According to step seven, the corresponding algal bloom control measures are implemented to ensure that the chlorophyll a concentration is within the control range.

[0105] Since implementing cyanobacterial bloom control measures in 2021 according to the annual single bloom control curve and its extent to prevent cyanobacterial outbreaks, the chlorophyll a concentration of the lake remained within the controlled range throughout 2022, as indicated by the typical growth curve of cyanobacteria. The chlorophyll a concentration in the water body remained consistently low, with an annual average of 3.7 μg / L, a maximum of 10.2 μg / L, and a minimum of 0.9 μg / L. This demonstrates that the method of this invention effectively prevents large-scale, high-concentration cyanobacterial blooms in the lake, providing a basis for the long-term and effective protection of the lake's aquatic ecological environment quality.

Claims

1. A method for preventing cyanobacterial blooms by setting an algal bloom control curve, characterized in that, include: Determine the chlorophyll a concentration threshold K for cyanobacterial blooms in the target lake; Calculate and determine the inflection point time T for cyanobacterial growth in the target lake. z The turning point refers to the point where the chlorophyll a concentration increases at the greatest rate. Calculate and determine the time T of the initial peak of cyanobacterial growth in the target lake. s and chlorophyll a concentration ; Based on the inflection point time T z and chlorophyll a concentration The first control curve for algal bloom was obtained by calculation; Based on the inflection point time T z and the time of the beginning of the peak T s The second control curve for algal bloom was calculated. Based on the algal bloom control curve 1 and algal bloom control curve 2, the region located below the lower curve is selected as the chlorophyll a concentration control range for the target lake at the corresponding time.

2. The method for preventing cyanobacterial blooms by setting an algal bloom control curve according to claim 1, characterized in that, The turning point time T z Based on historical data of typical cyanobacteria growth periods, the determination was made by fitting the growth model.

3. A method for preventing cyanobacterial blooms by setting an algal bloom control curve according to claim 1 or 2, characterized in that, The T z The calculation formula is obtained from the second derivative of the growth model: when When, find the inflection point time T. z The calculation formula is: In this process, the parameters b and r in the fitting equation for each time period are substituted into T. z The calculation formula for the inflection point time T z The mean of the results calculated for each time period is rounded up to the nearest integer.

4. The method for preventing cyanobacterial blooms by setting an algal bloom control curve according to claim 1, characterized in that, The chlorophyll a concentration This represents the average chlorophyll a concentration at the initial peak point of each time period.

5. The method for preventing cyanobacterial blooms by setting an algal bloom control curve according to claim 1, characterized in that, The T s Based on historical data of typical cyanobacteria growth periods, the determination was made by fitting the growth model.

6. The method for preventing cyanobacterial blooms by setting an algal bloom control curve according to claim 3, characterized in that, The T s The calculation formula is obtained from the third derivative of the growth model: when and At that time, the initial peak time T is obtained. s The calculation formula is: In this process, the parameters b and r in the fitting equation for each time period are substituted into T. s The calculation formula for the initial peak time T s The mean of the results calculated for each time period is rounded down to the nearest integer.

7. The method for preventing cyanobacterial blooms by setting an algal bloom control curve according to claim 6, characterized in that, The calculation formula for the growth model is as follows: In the formula, t represents time; N t Let be the chlorophyll a concentration at time t; K be the chlorophyll a concentration threshold; e be the base of the natural logarithm; b and r are constants.

8. The method for preventing cyanobacterial blooms by setting an algal bloom control curve according to claim 7, characterized in that, The calculation formula for the first algal bloom control curve is as follows: in, Where a1 and r1 are constants.

9. A method for preventing cyanobacterial blooms by setting an algal bloom control curve according to claim 7, characterized in that, The calculation formula for the second algal bloom control curve is as follows: in, Where a2 and r2 are constants.

10. A method for preventing cyanobacterial blooms by setting an algal bloom control curve according to claim 2, characterized in that, The historical typical cyanobacterial growth period shall be no less than two periods, and the chlorophyll a concentration threshold of each period shall be less than the K value.

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