A method for determining the hydrodynamic settling velocity and effective settling distance of an algae-sand mixture in a water delivery channel

Abstract

The present application provides a kind of method for determining the water channel algae sand mixture hydrodynamic settling velocity and effective settling distance, it is related to water environment and water ecological protection field, the method includes: step S1: the quantitative relationship of water body algae sand mixture turbidity and suspended solid concentration is established;Step S2: carry out algae sand mixture static water settling experiment;Step S3: calculate the characteristic static water settling velocity corresponding to different settling efficiency;Step S4: carry out algae sand mixture field hydrodynamic settling experiment;Step S5: fitting settling velocity and settling efficiency relationship model;Step S6: determine the algae sand mixture hydrodynamic settling velocity;Step S7: determine the effective settling distance of algae sand mixture.The present application can realize different design incoming flow velocity conditions, determine the settling efficiency of conveying channel algae sand mixture and its corresponding settling velocity and effective settling distance, suitable for the determination of conveying channel raw water quality settling purification engineering design parameter, can provide technical support for the design operation of national water network water quality improvement project.

Description

Technical Field

[0001] The invention relates to the field of water environment and water ecological protection, and in particular to a method for determining the dynamic water settling velocity and effective settling distance of an algae-sand mixture in a water conveyance channel. Background Art

[0002] To address the extremely uneven spatial distribution of water resources in my country, the country has implemented water network projects. Water transfer channels, exemplified by the South-to-North Water Diversion Project, have formed a network of various sizes. During operation, it has been discovered that during certain periods, the algae-sand mixture in the water can be elevated. This not only easily deposits in low-flow areas, impacting water transfer efficiency but also affecting water quality and safety.

[0003] Designing the sedimentation and removal of algae-sand mixtures within water channels requires determining their dynamic water settling patterns. Unlike typical river sediment particles, algae-sand mixtures have finer particles and lower density, leading to significant mutual interference during particle settling. Their settling performance is significantly affected by water velocity, and mature testing and calculation methods are currently lacking. Summary of the Invention

[0004] The purpose of the present invention is to overcome the shortcomings of the background technology and provide a method for determining the dynamic water settling velocity and effective sedimentation distance of the algae-sand mixture in the water supply channel. It can determine the sedimentation efficiency and corresponding sedimentation velocity of the algae-sand mixture in the water supply channel under different incoming flow rate conditions, and is suitable for determining the design parameters of the sedimentation purification project of raw water quality in the water supply channel.

[0005] To achieve the above object, the present invention provides a method for determining the dynamic water settling velocity and effective settling distance of an algae-sand mixture in a water conveyance channel, comprising the following steps:

[0006] Step S1: establishing a quantitative relationship between the turbidity of the algae-sand mixture in the water body and the concentration of suspended solids;

[0007] Step S2: Conducting a static water sedimentation experiment on the algae-sand mixture to test the turbidity change process of the water body at different sedimentation times and different sedimentation heights. The measured water turbidity is converted into the concentration of the algae-sand mixture in the water body according to the quantitative relationship between the turbidity of the algae-sand mixture in the water body and the suspended solids concentration. The percentage of residual suspended solids at the sampling port and the settling velocity of particles that just pass through the sampling port are calculated.

[0008] Step S3: Based on the percentage of suspended solids remaining at the sampling port obtained in step S2 and the settling velocity of particles just passing through the sampling port, a settling efficiency-characteristic still water settling velocity relationship model is constructed to calculate the characteristic still water settling velocity corresponding to different settling efficiencies;

[0009] Step S4: conducting an on-site dynamic water sedimentation experiment of the algae-sand mixture to obtain the flow velocity and turbidity distribution of the test section;

[0010] Step S5: converting the water turbidity of the test section obtained in step S4 into the concentration of the water algae-sand mixture according to the quantitative relationship between the turbidity of the water algae-sand mixture and the suspended solids concentration, calculating the settling efficiency and corresponding settling velocity of the monitoring sections at different distances along the drainage channel, and fitting a relationship model between the dynamic water settling velocity and the settling efficiency;

[0011] Step S6: Based on the dynamic water settling velocity and settling efficiency relationship model obtained in step S5, the characteristic settling velocity corresponding to different settling efficiencies under the experimental inflow velocity conditions is calculated, and the characteristic still water settling velocity corresponding to different settling efficiencies obtained in step S3 is coupled to infer the characteristic settling velocity corresponding to different settling efficiencies under the designed inflow velocity scenario of the algae-sand mixture;

[0012] Step S7: Based on the characteristic settling velocities corresponding to different settling efficiencies under the design inflow velocity scenario determined in step S6, under the design settling efficiency conditions, calculate the effective settling distance of the algae-sand mixture at different water depths and inflow velocities.

[0013] Furthermore, the step S1 specifically includes: conducting on-site monitoring of the target water channel, using a turbidity meter to test the turbidity of the algae-sand mixture in the water body, using a gravimetric method to test the suspended solids concentration in the water body, and using formula (1) to establish a quantitative relationship between the turbidity of the algae-sand mixture in the water body and the suspended solids concentration:

[0014] S=a1*Turb.+b1 (1)

[0015] Where S is the concentration of the algae-sand mixture in water, mg / L; Turb. is the turbidity of the algae-sand mixture in water, NTU; a1 and b1 are constant coefficients.

[0016] Furthermore, step S2 involves conducting a static water sedimentation experiment on the algae-sand mixture to test the turbidity change process of the water body at different sedimentation times and different sedimentation heights. Specifically, the experiment includes: taking raw water from a water supply channel and conducting a static water sedimentation experiment on the algae-sand mixture in a cylindrical static water sedimentation column made of organic glass, wherein the diameter of the sedimentation column is not less than 20 cm. A plurality of sampling ports are provided vertically along the sedimentation column to test the turbidity change process of the water body at different sedimentation times and different sedimentation heights.

[0017] Furthermore, the step S2 of calculating the percentage of suspended solids remaining at the sampling port and the settling velocity of particles just passing through the sampling port and settling downwards specifically includes:

[0018]

[0019]

[0020] Where, ω i is the sedimentation velocity of the particles just passing through the sampling port, p i is the percentage of residual suspended particles in the water sample at the sampling port, Δhi For different sedimentation times t i , the change in water surface height before and after sampling at a certain sampling port, m; h is the distance between the sampling port and the water surface, m; c i is the concentration of algae-sand mixture in the water sampled from the sampling port, mg / L; c0 is the initial concentration of algae-sand mixture in the water sampled from the sedimentation column, mg / L.

[0021] Furthermore, the step S3 specifically includes: using a power function model to fit the sedimentation velocity ω of the particles just passing through the sampling port measured in step S2 i and the percentage of residual suspended particles in the water sample at the sampling port p i :

[0022]

[0023] Where a2 and b2 are model coefficients respectively.

[0024] According to formula (4), draw ω i -p i Relationship curve, based on integral graphical method, with p0 representing the sinking velocity ω i The percentage of suspended particles with a settling velocity less than the characteristic settling velocity ω′ in the total suspended particles. Δp represents the settling velocity ω i The percentage of suspended particles in all particles is calculated for different settling times t i , the sedimentation efficiency η′ corresponding to a certain characteristic sedimentation velocity ω′:

[0025]

[0026] Based on the calculation results of formula (5), the natural exponential function is used to fit the sedimentation efficiency η-characteristic still water sinking velocity ω relationship model (6). Based on this model, the characteristic still water sinking velocity corresponding to different sedimentation efficiencies is calculated:

[0027]

[0028] Where a3, b3, c3, and d3 are model coefficients respectively.

[0029] Furthermore, the step S4 specifically includes: selecting a regular cross-section drainage channel as the on-site dynamic water sedimentation test area, and the length of the drainage channel should be no less than 1000m. If the water depth of the drainage channel is insufficient, a temporary water retaining weir is set at the tail of the drainage channel, and raw water from the water transfer channel is introduced through the upstream drainage gate of the drainage channel as experimental water. The inflow velocity is controlled by the opening of the drainage gate; several monitoring sections are set at intervals of 50-400m along the longitudinal direction of the drainage channel. Under the experimental inflow velocity conditions, when the algae sand transport process reaches dynamic equilibrium, the cross-section flow velocity and turbidity vertical distribution are tested.

[0030] Further, the step S5 specifically comprises: calculating the sedimentation efficiency η of the monitoring section at different distances along the water withdrawal channel under the current inflow velocity experimental working condition i and the corresponding settling velocity ω i to obtain the along distance distribution law of the algae-sand mixture concentration and the sedimentation efficiency:

[0031]

[0032]

[0033] In the formula, c i is the average turbidity or suspended substance concentration of the monitoring section at different distances along the water withdrawal channel, mg / L; c0 is the initial turbidity or suspended substance concentration of the water body at the outlet of the water withdrawal gate, mg / L; h is the water depth under the experimental working condition, m; L i is the horizontal distance of the monitoring section at different distances along the water withdrawal channel from the water withdrawal gate, m; u is the horizontal velocity under the experimental working condition, m / s;

[0034] The exponential function fitting experiment is used to fit the relationship model (9) of the dynamic water settling velocity ω i and the sedimentation efficiency η i under the inflow velocity working condition:

[0035]

[0036] In the formula, a4, b4 and c4 are model coefficients.

[0037] Further, by adjusting the opening degree of the water withdrawal gate upstream of the water withdrawal channel, different gradient inflow velocity conditions are set in the step S4, and the steps S4-S5 are repeated until the experimental target is achieved.

[0038] Further, the step S6 adopts linear difference calculation to calculate the characteristic settling velocity corresponding to different sedimentation efficiencies under the design inflow velocity scenario, and the design inflow velocity range is located in the maximum inflow velocity range of the different gradient inflow velocity conditions set in the step S4.

[0039] Further, the step S7 calculates the effective sedimentation distance L of the algae-sand mixture under different water depths and inflow velocities, and the formula is as follows:

[0040]

[0041] In the formula, K is a correction coefficient, and is taken as 1.0 under the condition that the velocity non-uniformity is not considered; ω is the settling velocity of the algae-sand mixture, m / s; H is the working water depth, m; and V is the inflow velocity, m / s.

[0042] The present application has the following beneficial effects:

[0043] 1. The method can quantitatively calculate the dynamic water settling velocity and effective settling distance corresponding to different settling efficiencies under different inflow velocities, filling the gap in the method for determining the dynamic water settling characteristics of algae-sand mixtures in water transfer channels.

[0044] 2. The dynamic water sedimentation velocity and effective sedimentation distance are obtained based on the prototype water quality and large-scale in-situ experimental results, which improves the reliability of the design parameters of the raw water sedimentation removal project in the water transfer channel.

[0045] 3. Through the experimental results of a limited number of groups, through model fitting and calculation, the dynamic water sedimentation velocity and effective sedimentation distance under various design flow rates and different sedimentation efficiency conditions can be obtained, which has the advantages of low workload and high scalability of results. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a flow chart of one embodiment of a method for determining the dynamic water settling velocity and effective settling distance of an algae-sand mixture in a water conveyance channel according to the present invention;

[0047] Figure 2 This is a quantitative relationship diagram between the turbidity of the raw water, algae and sand mixture and the suspended solids concentration in the water delivery channel according to an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of a hydrostatic sedimentation column according to an embodiment of the present invention;

[0049] Figure 4 This is a fitting diagram of the relationship model between the percentage of suspended solids remaining at the sampling port and the characteristic settling velocity in still water according to an embodiment of the present invention;

[0050] Figure 5 This is a fitting diagram of the relationship model between the still water characteristic settling velocity and the settling efficiency according to an embodiment of the present invention;

[0051] Figure 6 This is a schematic diagram of the arrangement of an on-site dynamic water sedimentation experiment according to an embodiment of the present invention;

[0052] Figure 7 This is a vertical turbidity distribution diagram of an on-site dynamic water sedimentation experiment according to an embodiment of the present invention;

[0053] Figure 8 The vertical average suspended solids concentration and sedimentation efficiency along the dynamic water sedimentation experiment in the embodiment of the present invention are changed;

[0054] Figure 9 This is a relationship model between dynamic water settling velocity and settling efficiency in a field dynamic water settling experiment according to an embodiment of the present invention.

[0055] In the figure: 1-static water sedimentation column, 2-sampling port, 3-vent valve, 4-temporary water retaining weir, 5-water discharge gate, 6-monitoring section. DETAILED DESCRIPTION

[0056] The preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. However, these embodiments do not limit the present invention and are merely examples to help those skilled in the art to more clearly understand the contents and advantages of the present invention.

[0057] like Figure 1 As shown, an embodiment of the present invention provides a method for determining the dynamic water settling velocity and effective settling distance of an algae-sand mixture in a water conveyance channel, comprising the following steps:

[0058] Step S1: establishing a quantitative relationship between the turbidity of the algae-sand mixture in the water body and the concentration of suspended solids;

[0059] Specifically, the target water channel was used as the research object. During the period when the content of algae-sand mixture was high, on-site monitoring was carried out. The turbidity of the water was measured using a portable turbidity meter (Hach 2100Q). The suspended solids concentration in the water was measured based on the gravimetric method (GB11901-89). The linear quantitative relationship between the turbidity of the raw water algae-sand mixture and the suspended solids concentration in the water channel was fitted (S = 2.6478*Turb.+2.6547, R 2 =0.84, Figure 2 ), the subsequent steps S2 and S4 both quickly convert the measured water turbidity into the concentration of the algae-sand mixture in the water according to formula (1).

[0060] Step S2: conducting a static water sedimentation experiment of the algae-sand mixture;

[0061] Specifically, the raw water from the water channel is taken, and a cylindrical hydrostatic sedimentation column 1 (made of organic glass) is used. Figure 3 ) to conduct static water settling experiments on algae-sand mixtures. Several sampling ports 2 were vertically arranged along a static water settling column 1, with a vent valve 3 at the bottom. Turbidity changes were measured at different settling times and settling heights. The percentage of suspended solids remaining at the sampling ports and the settling velocity of particles that just passed through the sampling ports were calculated.

[0062]

[0063]

[0064] Where Δh i For different sedimentation times t i , the change in water surface height before and after sampling at a certain sampling port, m; h is the distance between the sampling port and the water surface, m; p i is the percentage of residual suspended particles in the water sample at the sampling port; c i is the turbidity of the water sampled at the sampling port, NTU; c0 is the initial turbidity of the water sample in the sedimentation column, NTU.

[0065] Step S3: calculating characteristic still water settling velocities corresponding to different settling efficiencies;

[0066] Specifically, such as Figure 4 , using the power function to fit the ω measured in step S2 i and p i :

[0067]

[0068] According to the above formula, draw ω i -p i Relationship curve, based on integral graphical method, with p0 representing the sinking velocity ω i The percentage of suspended particles with a settling velocity less than the characteristic settling velocity ω′ in the total suspended particles. Δp represents the settling velocity ω i The percentage of suspended particles in all particles is calculated for different settling times t i , the sedimentation efficiency η′ corresponding to a certain characteristic sedimentation velocity ω′.

[0069]

[0070] like Figure 5 The natural exponential function is used to fit the sedimentation efficiency η-characteristic still water sinking velocity ω relationship model. Based on this model, the characteristic still water sinking velocity corresponding to different sedimentation efficiencies is calculated.

[0071] η=0.280e -1.883 +0.669e -0.074ω , R 2 =0.959

[0072] Step S4: conducting an on-site dynamic water sedimentation experiment of the algae-sand mixture;

[0073] Specifically, such as Figure 6 A regular cross-section drainage channel with a length of approximately 1,400 meters was selected as the on-site dynamic water sedimentation test area. Due to the insufficient water depth of the drainage channel, a temporary water retaining weir 4 was set up at the end of the drainage channel to ensure that the experimental water depth was above 2.5 meters. Raw water from the water supply channel was introduced through the upstream drainage gate 5 of the drainage channel as experimental water. The experimental flow rate was controlled by the opening of the drainage gate. Several monitoring sections 6 were set up at intervals of 50-400 meters along the longitudinal direction of the drainage channel. Under the experimental inflow velocity conditions, when the algae sand transport process reached dynamic equilibrium, the cross-section flow rate and vertical turbidity distribution were tested.

[0074] The relationship model between the turbidity of the water body algae-sand mixture and the suspended solids concentration established in step S1 is used to convert the water body turbidity into the concentration of the water body algae-sand mixture.

[0075] Step S5: fitting a settling velocity and settling efficiency relationship model;

[0076] Specifically, under the current inflow velocity experimental conditions, the settlement efficiency η of the monitoring section at different distances along the drainage channel is calculated. i and the corresponding sinking speed ω i,like Figure 7 and Figure 8 The distribution patterns of algae-sand mixture concentration and sedimentation efficiency along the flow path were obtained:

[0077]

[0078]

[0079] Where c i is the average concentration of algae-sand mixture at different monitoring sections along the discharge channel, mg / L; c0 is the initial concentration of algae-sand mixture in the water body at the discharge gate outlet, mg / L; ω i is the settlement efficiency η of the monitoring section at different distances along the process i Corresponding sinking speed, m / s; L i is the horizontal distance from the different monitoring sections along the process to the water discharge gate, m; u is the horizontal flow velocity under the test conditions, m / s.

[0080] The exponential function fitting experiment is used to calculate the dynamic water sinking velocity ω under the flow velocity condition. i and sedimentation efficiency η i Relational models (such as Figure 9 shown):

[0081]

[0082] By adjusting the opening of the upstream discharge gate of the discharge channel, different gradient water flow conditions are set as shown in Table 1, and steps S4-S5 are repeated until the experimental goal is achieved.

[0083] Table 1 On-site dynamic water settlement test conditions

[0084]

[0085] Step S6: determining the dynamic water settling velocity of the algae-sand mixture;

[0086] Specifically, the results of the dynamic water sedimentation experiments under different working conditions were comprehensively analyzed, and based on the relationship model between the dynamic water sedimentation velocity and sedimentation efficiency obtained in step S5, the characteristic sedimentation velocity corresponding to the different sedimentation efficiencies under the experimental incoming flow velocity conditions was calculated. The characteristic still water sedimentation velocity corresponding to the different sedimentation efficiencies obtained in step S3 and the characteristic dynamic water sedimentation velocity corresponding to the different sedimentation efficiencies obtained in step S5 were coupled. Based on the analysis results of the four experimental working conditions of 0, 0.029, 0.054, and 0.109 m / s, the characteristic sedimentation velocity corresponding to the different sedimentation efficiencies under the designed incoming flow velocity scenario was calculated using linear difference, as shown in Table 2. The characteristic incoming flow velocity range is within the range of 0 m / s to the maximum incoming flow velocity of 0.109 m / s adopted in step S4.

[0087] Table 2 Sedimentation velocities corresponding to different horizontal flow rates and sedimentation efficiencies

[0088]

[0089] Step S7: Determine the effective settling distance of the algae-sand mixture.

[0090] Specifically, according to the characteristic settling velocities corresponding to different settling efficiencies under the design inflow velocity scenario determined in step S6, under the design settling efficiency condition, the effective settling distance L of the algae-sand mixture at different water depths and inflow velocities is calculated:

[0091]

[0092] Where K is the correction coefficient, which can be taken as 1.0 without considering the uneven flow rate; ω is the settling velocity of the algae-sand mixture, m / s; H is the working water depth, m; and V is the incoming flow velocity, m / s.

[0093] In this example, under the condition of a designed settling efficiency of 70%, the effective settling distance of the algae-sand mixture corresponding to different water depths and incoming flow velocities was calculated, as shown in Table 3.

[0094] Table 3 Effective sedimentation distance corresponding to different water depths and inflow velocities

[0095]

[0096] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by technicians in this technical field within the technical scope disclosed in the present invention should be covered by the scope of protection of the present invention.

Claims

1. A method for determining the dynamic water settling velocity and effective settling distance of an algae-sand mixture in a water conveyance channel, characterized by: The following steps are involved: Step S1: establishing a quantitative relationship between the turbidity of the algae-sand mixture in the water body and the concentration of suspended solids; Step S2: Conducting a static water sedimentation experiment on the algae-sand mixture to test the change process of water turbidity at different sedimentation times and different sedimentation heights. Convert the measured water turbidity into the concentration of the algae-sand mixture based on the quantitative relationship between the turbidity of the algae-sand mixture and the suspended solids concentration in the water body. Calculate the percentage of suspended solids remaining at the sampling port and the static water settling velocity of particles that just pass through the sampling port and settle downward. Step S3: Based on the percentage of suspended solids remaining at the sampling port obtained in step S2 and the static water settling velocity of particles just settling downward through the sampling port, a settling efficiency-characteristic static water settling velocity relationship model is constructed to calculate the characteristic static water settling velocity corresponding to different settling efficiencies; Step S4: conducting an on-site dynamic water sedimentation experiment of the algae-sand mixture to obtain the flow velocity and turbidity distribution of the test section; Step S5: converting the water turbidity of the test section obtained in step S4 into the concentration of the algae-sand mixture in the water body according to the quantitative relationship between the turbidity of the algae-sand mixture in the water body and the suspended solids concentration, calculating the settling efficiency and corresponding dynamic water settling velocity of the monitoring sections at different distances along the drainage channel, and fitting a relationship model between the dynamic water settling velocity and the settling efficiency; Step S6: Based on the dynamic water settling velocity and settling efficiency relationship model obtained in step S5, the characteristic dynamic water settling velocity corresponding to different settling efficiencies under the experimental inflow velocity conditions is calculated, and the characteristic static water settling velocity corresponding to different settling efficiencies obtained in step S3 is coupled, and the characteristic settling velocity corresponding to different settling efficiencies under the designed inflow velocity scenario of the algae-sand mixture is inferred using linear interpolation; Step S7: Based on the characteristic settling velocities corresponding to different settling efficiencies under the design inflow velocity scenario determined in step S6, under the design settling efficiency condition, calculating the effective settling distance of the algae-sand mixture at different water depths and inflow velocities; The step S2 of calculating the percentage of suspended solids remaining at the sampling port and the still water settling velocity of particles just passing through the sampling port and settling downwards specifically includes: （2）； （3）； Where, is the still water settling velocity of the particles just passing through the sampling port, is the percentage of suspended particles remaining in the water sample at the sampling port, ∆h i For different sedimentation times t i , the change in water surface height before and after sampling at a certain sampling port, m; h is the distance between the sampling port and the water surface, m; is the concentration of algae-sand mixture in the water sampled at the sampling port, mg / L; is the initial algae-sand mixture concentration of the sedimentation column water sample, mg / L; The step S3 specifically includes: using a power function model to fit the static water settling velocity of the particles just passing through the sampling port measured in step S2 and : （4）； Where, and are the model coefficients respectively; According to formula (4), draw - Relationship curve, based on integral graphical method, with p0 representing still water sinking velocity Less than characteristic still water sinking velocity The percentage of suspended particles in the total suspended particles, Δp represents the still water sedimentation velocity The percentage of suspended particles in all particles is calculated for different settling times t i , a characteristic still water sinking velocity Corresponding sedimentation efficiency : （5）； Based on the calculation results of formula (5), the natural exponential function is used to fit the sedimentation efficiency - Characteristic still water sinking speed Relationship model (6), based on which the characteristic still water settling speed corresponding to different settling efficiencies is calculated : （6）； Where, 、 、 、 are the model coefficients respectively; The step S5 specifically includes: calculating the settlement efficiency η of the monitoring section at different distances along the drainage channel under the current inflow velocity experimental working condition i and the corresponding dynamic water sinking speed ω fi , the distribution of algae-sand mixture concentration and sedimentation efficiency along the way is obtained: (7)； (8)； Where, The average turbidity or suspended matter concentration at monitoring sections at different distances along the drainage channel, mg / L; is the initial turbidity or suspended matter concentration of the water at the outlet of the water discharge gate, mg / L; h is the water depth of the test condition, m; is the horizontal distance from the different monitoring sections along the way to the water discharge gate, m; u is the horizontal flow velocity under the test condition, m / s; The exponential function fitting experiment is used to calculate the dynamic water sinking velocity ω under the flow velocity condition. fi and sedimentation efficiency Relational Model (9): (9)； Where, 、 、 are the model coefficients respectively; The step S6 is based on the model (9) and calculates the characteristic dynamic water settling velocity ω corresponding to different settling efficiencies under the flow velocity conditions of the on-site dynamic water experiment. f ; Combined with the characteristic still water sinking velocity obtained in step S3 , the linear difference calculation design is used to calculate the characteristic sedimentation velocity corresponding to different sedimentation efficiencies under the flow velocity scenario , the designed incoming flow velocity range is within the range of 0 to the maximum incoming flow velocity among the different gradient incoming flow velocity conditions set in step S4; The formula for calculating the effective settling distance L of the algae-sand mixture at different water depths and incoming flow rates in step S7 is: （10）； Where K is the correction coefficient, which is taken as 1.0 without considering the flow velocity heterogeneity; ω is the characteristic settling velocity corresponding to different settling efficiencies of the algae-sand mixture, m / s; H is the working water depth, m; and V is the incoming flow velocity, m / s.

2. A method for determining the dynamic water settling velocity and effective settling distance of an algae-sand mixture in a water conveyance channel according to claim 1, characterized in that: The step S1 specifically includes: conducting on-site monitoring of the target water channel, using a turbidity meter to test the turbidity of the algae-sand mixture in the water body, using a gravimetric method to test the suspended solids concentration in the water body, and using formula (1) to establish a quantitative relationship between the turbidity of the algae-sand mixture in the water body and the suspended solids concentration: （1）； Where, S is the concentration of algae-sand mixture in water, mg / L; Turb. is the turbidity of algae-sand mixture in water, NTU; and is a constant coefficient.

3. The method for determining the dynamic water settling velocity and effective settling distance of an algae-sand mixture in a water conveyance channel according to claim 1, characterized in that: In the step S2, a static water sedimentation experiment of the algae-sand mixture is carried out to test the turbidity change process of the water body at different sedimentation times and different sedimentation heights. Specifically, the experiment includes: taking raw water from the water supply channel and carrying out a static water sedimentation experiment of the algae-sand mixture in a cylindrical static water sedimentation column made of plexiglass, wherein the diameter of the sedimentation column is not less than 20 cm; a plurality of sampling ports are set vertically along the sedimentation column to test the turbidity change process of the water body at different sedimentation times and different sedimentation heights.

4. The method for determining the dynamic water settling velocity and effective settling distance of an algae-sand mixture in a water conveyance channel according to claim 1, characterized in that: The step S4 specifically includes: selecting a regular cross-section drainage channel as the on-site dynamic water sedimentation test area, and the length of the drainage channel should be no less than 1000 m. If the water depth of the drainage channel is insufficient, a temporary water retaining weir is set at the tail of the drainage channel, and raw water from the water supply channel is introduced as experimental water through the upstream drainage gate of the drainage channel. The inflow velocity is controlled by the opening of the drainage gate; several monitoring sections are set at intervals of 50-400 m along the longitudinal direction of the drainage channel. Under the experimental inflow velocity conditions, when the algae sand transport process reaches dynamic equilibrium, the cross-section flow velocity and turbidity vertical distribution are tested.

5. The method for determining the dynamic water settling velocity and effective settling distance of an algae-sand mixture in a water conveyance channel according to claim 1, characterized in that: By adjusting the opening of the upstream discharge gate of the discharge channel, different gradient flow rate conditions are set in step S4, and steps S4-S5 are repeated until the experimental goal is achieved.

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