Hydrodynamic force and water quality cooperative regulation and control method of river channel and multi-pond communication system

Abstract

The invention relates to a hydrodynamic force and water quality coordinated regulation and control method for a river channel and multi-pond communication system, which comprises the following steps of: quantifying a trade-off relationship between HRT and pollutant removal rate by coupling hydrodynamic force and water quality models, and introducing a dynamic regulation and control strategy; the problems of insufficient model separation and eutrophication risk control, single regulation and control means, disjunction of design parameters and engineering effects and the like in the prior art are solved, and the water quality improvement effect and the operation stability of the river-pond communication system are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of ecological water conservancy projects and environmental governance, and particularly relates to a method for collaborative regulation of hydrodynamic and water quality of a river channel and multi-pond connection system. Background Technique

[0002] As a common means of water resource regulation and pollution control, the river channel and pond connection system is widely used in urban flood control, agricultural irrigation, ecological restoration and other fields. The existing technologies mainly include the following aspects:

[0003] (1) Hydrodynamic model: Traditional methods mostly calculate the river channel flow and the internal flow field of the pond separately, but do not consider the dynamic flow exchange between the pond and the river channel;

[0004] (2) Water quality model: Existing water quality models are mostly based on the convection-diffusion equation (such as models for water quality simulation and prediction), which are used to simulate the migration of pollutants, but do not consider the influence of thermal stratification effects on pollutant release;

[0005] (3) Pond design method: Traditional design methods mostly determine the pond volume and water diversion flow based on empirical formulas, but do not quantify the relationship between the hydraulic retention time (HRT) and the pollutant removal rate;

[0006] (4) Regulation technology: Existing regulation technologies mostly adopt fixed gate openings or static scheduling strategies, but lack dynamic optimization driven by real-time data.

[0007] The existing technologies have the following problems and deficiencies:

[0008] (1) Separation of hydrodynamic and water quality models leads to low prediction accuracy: In the existing technologies, the hydrodynamic model and the water quality model of the river channel and the pond usually operate independently, lacking coupled analysis, and unable to accurately simulate the dynamic interaction between the river channel and the pond (such as flow exchange, pollutant migration), and unable to accurately predict the long-term impact of the pond on the water quality of the river channel. Traditional methods only estimate the pollutant removal rate through empirical formulas, ignoring the temporal and spatial changes of the internal flow regime, thermal stratification effects and pollutant migration in the pond;

[0009] (2) Insufficient control of eutrophication risk: Existing pond designs mostly focus on the pollutant interception effect, but do not fully consider the correlation between the hydraulic retention time (HRT) and the risk of algal proliferation, resulting in the pond becoming a new pollution source (such as endogenous release). For example, pond stratification during the high-temperature period in summer may lead to hypoxia at the bottom layer, releasing phosphorus and heavy metals in the sediment, which instead exacerbates the pollution of the downstream river channel;

[0010] (3) Single and lack of dynamic optimization of regulation means: Most of the existing technologies adopt fixed water diversion flow or static scheduling strategies, which cannot adapt to the dynamic demands of hydrological conditions (such as rainfall, drought) and water quality changes. For example, traditional gate control lacks real-time data driving and is difficult to respond quickly in case of sudden pollution events;

[0011] (4) Disconnection between design parameters and engineering effects: In the existing technologies, design parameters such as pond volume and water diversion flow are mostly based on experience or simplified formulas, lacking quantitative optimization of pollutant removal rate, hydraulic retention time (HRT) and ecological risks. The quantitative relationship between the interception efficiency of the pond for suspended solids and nutrients and the improvement of river water quality is not considered during design. Summary of the Invention

[0012] To solve the above problems, the present invention provides a method for coordinated regulation of hydrodynamic and water quality of a river channel and multi-pond connection system. By coupling the hydrodynamic model and the water quality model, the retention effect of the pond on pollutants and the potential eutrophication risk are quantified, and an optimization design criterion based on the matching of hydraulic retention time (HRT) and pollutant removal rate is proposed; the problems of low prediction accuracy of the impact of the pond connection project on river water quality and single regulation means in the traditional method are solved.

[0013] The technical solution adopted by the present invention is: A method for coordinated regulation of hydrodynamic and water quality of a river channel and multi-pond connection system, including the following steps:

[0014] S1: Data input

[0015] River channel cross-section data, pond terrain data, hydrological time series (flow, water level), water quality monitoring data;

[0016] S2: Control system input

[0017] Input of control gate and weir control building control points and characteristic parameters of the river channel and multi-pond connection system;

[0018] S3: Construct a hydrodynamic model module

[0019] Construct a hydrodynamic model of the river channel - pond connection system. By establishing a one-dimensional river channel water flow simulation calculation model and a two-dimensional shallow water flow field simulation calculation model inside the pond, and through the coupling of the one-dimensional and two-dimensional models, a coupling calculation model for river channel and pond flow exchange is established to accurately simulate the water flow movement and flow exchange between the river channel and the pond, and solve the problem of low prediction accuracy caused by model separation in the traditional method;

[0020] S4: Construct a water quality model coupling module

[0021] Simulate the migration of pollutants using the convection-diffusion-reaction equation, correct the pollutant concentration by combining the sedimentation rate, biodegradation coefficient and thermal stratification effect of the pond, and quantify the retention effect of the pond on pollutants and the potential eutrophication risk through biological action modeling, so as to solve the problem of low accuracy of water quality prediction in traditional methods;

[0022] S5: Construct a parameter optimization module

[0023] Generate the optimal design parameters of the pond volume and the diversion flow rate based on the multi-objective optimization algorithm. Through the quantitative relationship between the hydraulic retention time HRT and the pollutant removal rate, use the multi-objective optimization algorithm to optimize the matching parameters of the pond volume and the river diversion flow rate, so as to solve the problem of insufficient control of the eutrophication risk in the traditional design;

[0024] S6: Construct a dynamic regulation module

[0025] Collect data in real time through the integrated control device, drive the dynamic regulation of the gate and the aeration device, adjust the dissolved oxygen in the pond by controlling the diversion flow rate of the gate or starting the aeration device, and dynamically adjust and improve the water quality until the parameter optimization goal is met. Through the dynamic regulation strategy driven by real-time data, the problem of single regulation means and lack of dynamic optimization in traditional methods is solved;

[0026] S7: Output the regulation plan

[0027] Based on the model prediction results, generate a regulation plan to reduce the pollutant flux in the downstream river and inhibit the eutrophication risk of the pond; output the river diversion flow rate, the opening and flow rate of each control gate and weir, the effluent flow rate, the opening of the aeration device, and the water quality monitoring data of the purified river and each pond.

[0028] Preferably, in step S3, the one-dimensional river flow simulation calculation model:

[0029]

[0030] Where: Q is the flow rate, A is the cross-sectional area of flow, h is the water depth, n is the Manning roughness coefficient, R is the hydraulic radius, t is the time, x is the distance in the direction of the water flow, and g is the acceleration due to gravity.

[0031] Preferably, in step S3, the two-dimensional shallow water flow field simulation calculation model inside the pond:

[0032]

[0033] Where: u is the velocity component in the horizontal direction of the water flow and v is the velocity component in the vertical direction of the water flow, h is the water depth, η is the water level, t is the time, x is the distance in the direction of the water flow, y is the distance in the vertical direction of the water flow, τ x is the shear stress in the direction of the water flow, τ yτ is the shear stress in the direction perpendicular to the water flow direction, ρ is the density of water, and g is the acceleration due to gravity.

[0034] Preferably, in step S3, the flow exchange coupling calculation model between the river channel and the pond is as follows:

[0035]

[0036] where: Q is the flow rate, Cw is the weir flow coefficient, Cp is the pipe flow coefficient, L is the weir width, A is the pipe cross-sectional area, which is used for the flow rate calculation in the mixed water diversion mode; h up is the water depth at the upstream inlet, h down is the water depth at the downstream outlet.

[0037] Preferably, in step S4, the convection-diffusion-reaction equation is as follows:

[0038]

[0039] where: h is the water depth, C is the pollutant concentration, u is the flow velocity, D is the diffusion coefficient, S source is the external source input, S source is the external source input, S sink is the degradation / sedimentation, x is the distance in the direction of the water flow, and t is the time.

[0040] Preferably, in step S4, the pollutant concentration is corrected for the thermocline effect: During the summer stratification period: the diffusion coefficient at the bottom layer is reduced to 10% - 30% of the surface layer to simulate the endogenous release of sediment; During the winter mixing period: the vertical diffusion coefficient is unified to the surface layer value.

[0041] Preferably, in step S4, the biological action is modeled: plants in the pond absorb, and microorganisms decompose (temperature and dissolved oxygen data need to be input). By coupling the water quality model, the retention effect of the pond on pollutants and the potential eutrophication risk are quantified, solving the problem of low water quality prediction accuracy in traditional methods.

[0042] Preferably, in step S5, the relationship between HRT and the pollutant removal rate is as follows:

[0043] The hydraulic retention time HRT = V / Q, where V is the volume of the pond and Q is the water diversion flow rate;

[0044] The pollutant removal rate η = 1 - e -k·HRT , where k is the degradation coefficient.

[0045] Preferably, in step S5, the multi-objective optimization algorithm is as follows:

[0046] Objective 1: Maximize the pollutant removal rate;

[0047] Objective 2: Minimize the risk of algal proliferation;

[0048] Constraint: 6 hours ≤ HRT ≤ 48 hours;

[0049] That is, the optimization objective is: the hydraulic retention time HRT = V / Q satisfies 6 hours ≤ HRT ≤ 48 hours to achieve the maximum pollutant removal rate (such as the suspended solid removal rate ≥ 40%) and minimize the risk of algal proliferation (such as the risk of algal proliferation ≤ 10%); by optimizing HRT and the diversion flow rate, the problem of insufficient control of eutrophication risk in traditional designs in ponds is solved.

[0050] Preferably, the specific steps of S6 are as follows:

[0051] S61. Real-time monitoring data

[0052] River channel flow rate, water level, water quality parameters (such as ammonia nitrogen and total phosphorus concentrations); dissolved oxygen, temperature, and algal biomass in the pond;

[0053] S62. Regulation strategy:

[0054] Gate control: Dynamically adjust the gate opening based on the flow rate - water level relationship;

[0055] Aeration device: Start or stop the aeration equipment according to the dissolved oxygen data.

[0056] S63. Adaptive optimization algorithm:

[0057] Adopt fuzzy logic control (FLC) or proportional - integral - derivative control algorithm to achieve system adaptive optimization.

[0058] The beneficial effects achieved by the present invention are as follows: By coupling the hydrodynamic and water quality models, quantifying the trade - off relationship between HRT and pollutant removal rate, and introducing a dynamic regulation strategy, the present invention solves problems such as model separation, insufficient control of eutrophication risk, single regulation means, and disconnection between design parameters and engineering effects in the prior art, and significantly improves the water quality improvement effect and operation stability of the river - pond connection system. Compared with the prior art, the present invention has the following advantages:

[0059] 1. Realize the dynamic coupling of hydrodynamic and water quality models to improve prediction accuracy: Through the joint solution of the one - dimensional river channel model and the two - dimensional pond model, accurately simulate the water flow exchange and pollutant migration process, and solve the problem of low prediction accuracy caused by model separation in traditional methods; through the coupling of hydrodynamic and water quality models, significantly improve the simulation accuracy of water flow and pollutant migration in the river - pond system, and the error is reduced by 20% - 30% compared with traditional methods;

[0060] 2. Quantify the trade-off relationship between the retention effect of the pond and the eutrophication risk to reduce the eutrophication risk: By introducing the quantitative relationships between HRT, pollutant removal rate, and the risk of algal proliferation, optimize the design of the pond volume and water diversion flow rate to prevent the pond from becoming a new pollution source; By optimizing HRT and water diversion flow rate, control the risk of algal proliferation in the pond below 10%, and at the same time ensure that the suspended solid removal rate is ≥40%;

[0061] 3. Provide dynamic regulation and adaptive optimization solutions to enhance the system regulation ability: Based on real-time monitoring data (such as flow rate, water quality parameters), dynamically adjust the opening of the gate and the operating state of the aeration device to achieve system adaptive optimization and improve the response ability to sudden pollution events; Based on the dynamic regulation strategy of real-time data, it can quickly respond in sudden pollution events and reduce the peak concentration of pollutants in the downstream river by 30% - 50%;

[0062] 4. Establish a quantitative relationship between design parameters and engineering effects to optimize engineering design: Through model prediction and multi-objective optimization algorithms, clarify the impacts of design parameters such as pond volume and water diversion flow rate on pollutant removal rate, HRT, and ecological risk, providing a scientific basis for engineering design; Provide a quantitative design parameter optimization plan to reduce the engineering trial-and-error cost and improve the effect of river water quality improvement, applicable to various scenarios such as urban river treatment and agricultural non-point source pollution interception. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 is a schematic diagram of the system of the present invention (marking the water intake, water outlet, and monitoring section);

[0064] Figure 2 is a flow chart of the present invention;

[0065] Figure 3 is a trade-off curve of ammonia nitrogen removal rate and the risk of algal proliferation under different HRTs;

[0066] Among them: 1. River; 2. 1# Pond; 3. 2# Pond; 4. Water intake control gate (weir); 5. Connecting control gate (weir); 6. Water outlet control gate (weir); 7. Monitoring point; 8. Aeration device. DETAILED DESCRIPTION OF THE INVENTION

[0067] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0068] As Figure 1 shown, a river and multi-pond connection system of the present invention includes:

[0069] Data acquisition module: Real-time acquisition of river channel flow rate, water level and water quality parameters;

[0070] Model calculation module: Generate multi-scenario predictions based on the hydrodynamic and water quality coupling model;

[0071] Regulation execution module: Control the diversion flow rate through the gate or start the aeration device to adjust the dissolved oxygen in the pond.

[0072] By coupling the hydrodynamic and water quality models, optimizing the design parameters of the pond, and introducing dynamic regulation strategies, the problems in the prior art such as model separation, insufficient control of eutrophication risk, single regulation means, and disconnection between design parameters and engineering effects are solved. This patent realizes the coordinated regulation of hydrodynamic and water quality in the river channel and multi-pond connection system, solves the key problems in the prior art, and has significant technical advantages and application values.

[0073] Combined with Figures 2 - 3 As shown in the figure, a method for coordinated regulation of hydrodynamic and water quality in a river channel and multi-pond connection system of the present invention includes the following steps:

[0074] S1: Data input

[0075] River channel cross-section data, pond terrain data, hydrological time series (flow rate, water level), water quality monitoring data;

[0076] S2: Control system input

[0077] Input of control gate and weir control building control points and characteristic parameters of the river channel and multi-pond connection system;

[0078] S3: Construct a hydrodynamic model module

[0079] Construct a hydrodynamic model of the river channel - pond connection system. By establishing a one-dimensional river channel water flow simulation calculation model and a two-dimensional shallow water flow field simulation calculation model inside the pond, and through the coupling of the one-dimensional and two-dimensional models, establish a coupling calculation model for river channel and pond flow exchange, accurately simulate the water flow movement and flow exchange between the river channel and the pond, and solve the problem of low prediction accuracy caused by model separation in traditional methods;

[0080] 1. One-dimensional river channel water flow simulation calculation model:

[0081]

[0082] Where: Q is the flow rate, A is the cross-sectional area of flow, h is the water depth, n is the Manning roughness coefficient, R is the hydraulic radius, t is the time, x is the distance in the direction of the water flow, and g is the acceleration due to gravity.

[0083] 2. Two-dimensional shallow water flow field simulation calculation model inside the pond:

[0084]

[0085] where: u is the velocity component in the horizontal direction along the water flow, v is the velocity component perpendicular to the water flow, h is the water depth, η is the water level, t is the time, x is the distance along the water flow direction, y is the distance perpendicular to the water flow direction, and τ x is the shear stress in the direction of the water flow, and τ y is the shear stress perpendicular to the water flow direction, ρ is the density of water, and g is the acceleration due to gravity.

[0086] 3. Coupled calculation model for the flow exchange between the river channel and the pond:

[0087]

[0088] where: Q is the flow rate, Cw is the weir flow coefficient, Cp is the pipe flow coefficient, L is the weir width, A is the cross-sectional area of the pipe, which is used for the flow rate calculation in the mixed water diversion mode; h up is the water depth at the upstream inlet, and h down is the water depth at the downstream outlet.

[0089] S4: Construct a water quality model coupling module

[0090] Simulate the migration of pollutants using the convection-diffusion-reaction equation, correct the pollutant concentration by combining the sedimentation rate, biodegradation coefficient and thermal stratification effect of the pond, and quantify the retention effect of the pond on pollutants and the potential risk of eutrophication through biological action modeling, so as to solve the problem of low water quality prediction accuracy in traditional methods;

[0091] S41. Convection-diffusion-reaction equation (pollutant migration equation):

[0092]

[0093] where: h is the water depth, C is the pollutant concentration, u is the flow velocity, D is the diffusion coefficient, S source is the external source input, S source is the external source input, S sink is the degradation / sedimentation, x is the distance along the water flow direction, and t is the time;

[0094] S42. Correct the pollutant concentration by the thermal stratification effect: In the summer stratification period, the diffusion coefficient at the bottom layer is reduced to 10% - 30% of the surface layer to simulate the endogenous release of sediments; in the winter mixing period, the vertical diffusion coefficient is unified to the surface layer value;

[0095] S43. Biological action modeling: Absorption by plants and decomposition by microorganisms in the pond (temperature and dissolved oxygen data need to be input). By coupling the water quality model, the retention effect of the pond on pollutants and the potential risk of eutrophication are quantified, and the problem of low water quality prediction accuracy in traditional methods is solved.

[0096] S5: Construct a parameter optimization module

[0097] Generate the optimal design parameters of the pond volume and the diversion flow rate based on the multi-objective optimization algorithm. Through the quantitative relationship between the hydraulic retention time (HRT) and the pollutant removal rate, adopt the multi-objective optimization algorithm to optimize the matching parameters of the pond volume and the river diversion flow rate, and solve the problem of insufficient control of the eutrophication risk in the traditional design of the pond;

[0098] S51. Relationship between HRT and pollutant removal rate:

[0099] The hydraulic retention time HRT = V / Q, where V is the pond volume and Q is the diversion flow rate;

[0100] The pollutant removal rate η = 1 - e -k·HRT , where k is the degradation coefficient;

[0101] S52. Multi-objective optimization algorithm:

[0102] Objective 1: Maximize the pollutant removal rate;

[0103] Objective 2: Minimize the risk of algal proliferation;

[0104] Constraint condition: 6 hours ≤ HRT ≤ 48 hours;

[0105] That is, the optimization objective is: the hydraulic retention time HRT = V / Q satisfies 6 hours ≤ HRT ≤ 48 hours to achieve the maximization of the pollutant removal rate (such as the suspended solid removal rate ≥ 40%) and the minimization of the risk of algal proliferation (such as the risk of algal proliferation ≤ 10%); by optimizing HRT and the diversion flow rate, the problem of insufficient control of the eutrophication risk in the traditional design of the pond is solved.

[0106] S6: Construct a dynamic regulation module

[0107] Collect data in real time through the integrated control device, drive the dynamic regulation of the gate and the aeration device, adjust the dissolved oxygen in the pond by controlling the diversion flow rate of the gate or starting the aeration device, and dynamically adjust and improve the water quality until the parameter optimization objective is met. Through the dynamic regulation strategy driven by real-time data, the problem of single regulation means and lack of dynamic optimization in the traditional method is solved;

[0108] S61. Real-time monitoring data

[0109] River flow rate, water level, water quality parameters (such as ammonia nitrogen and total phosphorus concentrations); dissolved oxygen, temperature, and algal biomass in the pond;

[0110] S62. Regulation strategy:

[0111] Gate control: Dynamically adjust the gate opening based on the flow rate - water level relationship;

[0112] Aeration device: Start or stop the aeration equipment according to the dissolved oxygen data;

[0113] S63. Adaptive optimization algorithm:

[0114] Adopt fuzzy logic control (FLC) or proportional-integral-derivative control algorithm to achieve system adaptive optimization.

[0115] S7: Output the regulation plan

[0116] Based on the model prediction results, generate a regulation plan to reduce the pollutant flux in the downstream river channel and inhibit the risk of eutrophication in the water ponds; output the river channel diversion flow rate, the opening degree and flow rate of each control sluice and weir, the effluent flow rate, the opening degree of the aeration device, and the water quality monitoring data of the purified river channel and each water pond.

[0117] Implementation case 1: Connectivity project of a plain river channel and two water storage ponds

[0118] 1. Data input:

[0119] River channel cross-section data (such as bottom width 10m, slope 1:2, Manning coefficient 0.025, etc.);

[0120] Water pond volume curve (V1 of pond 1 = 30000m 3 , V2 of pond 2 = 20000m 3 );

[0121] Water quality parameters: Initial ammonia nitrogen concentration 2.0mg / L, degradation coefficient k = 0.15d-1;

[0122] 2. Input of the control system: Input the positions and characteristic parameters of the control sluices and weirs of the river channel and multiple water ponds;

[0123] 3. Model calculation and calculation result output:

[0124] Set the diversion flow rate Q = 5m 3 / s, and calculate HRT = 4.8 hours;

[0125] The simulation shows that the suspended solid removal rate is 38% (lower than the threshold), but the risk of algae proliferation reaches 15% (exceeding the threshold);

[0126] Adjust Q to 3m 3 / s, extend HRT to 6.6 hours, the suspended solid removal rate increases to 48%, and the risk of algae proliferation drops to 8%, meeting the optimization goal;

[0127] 4. Output the regulation plan:

[0128] During the high-temperature period in summer, limit the diversion flow rate ≤ 3m 3 / s, and start the bottom aeration device of the water pond;

[0129] In winter, the diversion flow rate can be increased to 6 m 3 / s to enhance the dilution effect;

[0130] It can be adjusted in real time according to specific situations daily.

[0131] Here, it should be noted that the description of the above technical solution is exemplary. This specification can be embodied in different forms and should not be construed as limited to the technical solutions described herein. On the contrary, providing these descriptions will make the disclosure of the present invention thorough and complete, and will fully convey the scope disclosed in this specification to those skilled in the art. In addition, the technical solutions of the present invention are only defined by the scope of the claims.

[0132] Finally, it should be pointed out that the above embodiments are only relatively representative examples of the present invention. Obviously, the present invention is not limited to the above embodiments and there can be many variations. Any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention should be considered as belonging to the protection scope of the present invention.

Claims

1. A method for collaborative regulation of hydrodynamic and water quality in a connected system of river channels and multiple ponds, characterized in that: It includes the following steps: S1: Data input River cross-section data, pond terrain data, hydrological time series, water quality monitoring data; S2: Control system input Input of control gate and weir control building control points and characteristic parameters of the river and multi-pond connection system; S3: Construct a hydrodynamic model module Construct a hydrodynamic model of the river-pond connection system. By establishing a one-dimensional river flow simulation calculation model and a two-dimensional shallow water flow field simulation calculation model inside the pond, and through the coupling of the one-dimensional and two-dimensional models, establish a coupling calculation model for river-pond flow exchange to accurately simulate the water flow movement and flow exchange between the river and the pond; S4: Construct a water quality model coupling module Use the convection-diffusion-reaction equation to simulate pollutant migration, correct the pollutant concentration by combining the sedimentation rate, biodegradation coefficient and thermal stratification effect of the pond, and quantify the retention effect of the pond on pollutants and the potential eutrophication risk through biological action modeling; S5: Construct a parameter optimization module Generate the optimal design parameters of the pond volume and water diversion flow based on the multi-objective optimization algorithm. Through the quantitative relationship between the hydraulic retention time HRT and the pollutant removal rate, use the multi-objective optimization algorithm to optimize the matching parameters of the pond volume and the river water diversion flow; S6: Construct a dynamic regulation module Collect data in real time through integrated control equipment, drive the dynamic regulation of the gate and aeration device, adjust the dissolved oxygen in the pond by controlling the water diversion flow or starting the aeration device, and dynamically adjust and improve the water quality until the parameter optimization goal is met; S7: Output the regulation plan Based on the model prediction results, generate a regulation plan to reduce the pollutant flux in the downstream river and inhibit the eutrophication risk of the pond; Output the river water diversion flow, the opening and flow of each control gate and weir, the outlet flow, the opening of the aeration device, and the water quality monitoring data of the purified river and each pond.

2. The hydrodynamic and water quality collaborative regulation method of the river channel and multi-pond connectivity system according to claim 1, characterized in that: In step S3, the one-dimensional river flow simulation calculation model: Where: Q is the flow rate, A is the cross-sectional area of flow, h is the water depth, n is the Manning roughness coefficient, R is the hydraulic radius, t is the time, x is the distance in the direction of the water flow, and g is the acceleration due to gravity.

3. The hydrodynamic and water quality collaborative regulation method of the river channel and multi-pond connectivity system according to claim 1, characterized in that: In step S3, the two-dimensional shallow water flow field simulation calculation model inside the pond: where: u is the velocity component in the horizontal direction along the water flow, v is the velocity component perpendicular to the water flow direction, h is the water depth, η is the water level, t is the time, x is the distance along the water flow direction, y is the distance perpendicular to the water flow direction, τ x is the shear stress in the direction of the water flow, τ y is the shear stress perpendicular to the water flow direction, ρ is the density of water, and g is the acceleration due to gravity.

4. The hydrodynamic and water quality collaborative regulation method of the river channel and multi-pond connectivity system according to claim 1, characterized in that: In step S3, the coupling calculation model for river-pond flow exchange: Where: Q is the flow rate, Cw is the weir flow coefficient, Cp is the pipeline flow coefficient, L is the weir width, A is the pipeline cross-sectional area, which is used for the flow rate calculation in the mixed water diversion mode; h up is the water depth at the upstream inlet, h down is the water depth at the downstream outlet.

5. The hydrodynamic and water quality collaborative regulation method of the river channel and multi-pond connectivity system according to claim 1, characterized in that: In step S4, the convection-diffusion-reaction equation: Where: h is the water depth, C is the pollutant concentration, u is the flow velocity, D is the diffusion coefficient, S source is the external source input, S source is the external source input, S sink is the degradation / sedimentation, x is the distance in the downstream direction of the water flow, and t is the time.

6. The hydrodynamic and water quality collaborative regulation method of the river channel and multi-pond connection system according to claim 1, characterized in that: In step S4, the correction of pollutant concentration by thermal stratification effect: In the summer stratification period, the bottom diffusion coefficient is reduced to 10% - 30% of the surface layer to simulate the endogenous release of sediment; in the winter mixing period, the vertical diffusion coefficient is unified to the surface layer value.

7. The hydrodynamic and water quality collaborative regulation method of the river channel and multi-pond connectivity system according to claim 1, characterized in that: In step S4, biological action modeling: Plant absorption and microbial decomposition in the pond.

8. The hydrodynamic and water quality collaborative regulation method for the river channel and multi-pond connectivity system according to claim 1, characterized in that: In step S5, the relationship between HRT and pollutant removal rate: The hydraulic retention time HRT = V / Q, where V is the pond volume and Q is the water diversion flow; The pollutant removal rate η = 1 - e -k·HRT , where k is the degradation coefficient.

9. The hydrodynamic and water quality collaborative regulation method of the river channel and multi-pond connectivity system according to claim 1, characterized in that: In step S5, the multi-objective optimization algorithm: Objective 1: Maximize the pollutant removal rate; Objective 2: Minimize the risk of algal proliferation; Constraint condition: 6 hours ≤ HRT ≤ 48 hours.

10. The hydrodynamic and water quality collaborative regulation method for the river channel and multi-pond connectivity system according to claim 1, characterized in that: The specific steps of S6 are: S61. Real-time monitoring data River flow rate, water level, water quality parameters; dissolved oxygen, temperature, algal biomass in the pond; S62. Regulation strategy: Gate control: Dynamically adjust the gate opening based on the flow rate-water level relationship; Aeration device: Start or stop the aeration equipment according to the dissolved oxygen data. S63. Adaptive optimization algorithm: Adopt fuzzy logic control or proportional-integral-derivative control algorithm to achieve system adaptive optimization.

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