CN114861550A - Distributed rainwater storage tank optimization design method based on overflow pollution load control - Google Patents

Distributed rainwater storage tank optimization design method based on overflow pollution load control Download PDF

Info

Publication number
CN114861550A
CN114861550A CN202210585675.1A CN202210585675A CN114861550A CN 114861550 A CN114861550 A CN 114861550A CN 202210585675 A CN202210585675 A CN 202210585675A CN 114861550 A CN114861550 A CN 114861550A
Authority
CN
China
Prior art keywords
storage tank
rainwater storage
pollution load
overflow
rainfall
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202210585675.1A
Other languages
Chinese (zh)
Inventor
尹海龙
王静怡
徐祖信
郭亚丽
吴一帆
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tongji University
China Three Gorges Corp
Shanghai Investigation Design and Research Institute Co Ltd SIDRI
Original Assignee
Tongji University
China Three Gorges Corp
Shanghai Investigation Design and Research Institute Co Ltd SIDRI
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tongji University, China Three Gorges Corp, Shanghai Investigation Design and Research Institute Co Ltd SIDRI filed Critical Tongji University
Priority to CN202210585675.1A priority Critical patent/CN114861550A/en
Publication of CN114861550A publication Critical patent/CN114861550A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
    • E—FIXED CONSTRUCTIONS
    • E03—WATER SUPPLY; SEWERAGE
    • E03F—SEWERS; CESSPOOLS
    • E03F5/00—Sewerage structures
    • E03F5/10—Collecting-tanks; Equalising-tanks for regulating the run-off; Laying-up basins
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/04—Constraint-based CAD
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/08—Fluids
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A20/00—Water conservation; Efficient water supply; Efficient water use
    • Y02A20/152—Water filtration

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • General Engineering & Computer Science (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Geometry (AREA)
  • Computer Hardware Design (AREA)
  • Hydrology & Water Resources (AREA)
  • Medical Informatics (AREA)
  • Water Supply & Treatment (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • Sewage (AREA)

Abstract

The invention discloses an optimal design method of a distributed rainwater storage tank based on overflow pollution load control, which relates to the technical field of overflow pollution control of urban drainage systems and comprises the following steps: the method comprises the following steps of construction of an SWMM model, calibration and verification of SWMM model parameters, design of a rainfall process line, simulation of overflow water quality, determination of positions and quantity of rainwater storage tanks, construction of a distributed rainwater storage tank optimization model, solution of the distributed rainwater storage tank optimization model, determination of the volume of the distributed rainwater storage tank, and acquisition of Pareto optimal curves and fitting equations. Aiming at the current situations of serious overflow pollution and poor pollutant intercepting effect of the storage tank in rainy days, the invention designs the method of the rainwater storage tank according to the overflow water quality process line, and reasonably determines the volume of the storage tank so as to realize maximization of the intercepted pollutants.

Description

Distributed rainwater storage tank optimization design method based on overflow pollution load control
Technical Field
The invention relates to the technical field of overflow pollution control of urban drainage systems, in particular to an optimal design method of a distributed rainwater storage tank based on overflow pollution load control.
Background
With the continuous improvement of urban sewage treatment infrastructure in China, the sewage nano-tube collection rate is continuously improved, and the problem that sewage is directly discharged into a river channel in dry days is effectively solved. However, in rainy days, overflow rain sewage exceeding the design interception multiple of a pipe network is discharged into a river channel to form impact pollution load, so that the water quality of the river channel is poor in rainy days, and the problem is a bottleneck problem limiting the improvement of the water environment quality. The basic principle of the method is that part of rain sewage exceeding the interception capacity of a pipeline in rainy days is intercepted and stored in a peak shifting scheduling mode, and the intercepted rain sewage is conveyed to a sewage treatment plant for treatment and then discharged after a rainfall event is finished.
In the release of the design standard for outdoor drainage (GB 50014-2021) and the technical specification for urban rainwater regulation and storage engineering (GB 51174-2017) in China, the capacity of a regulation and storage tank is determined according to the closure scale of initial rainwater, and the method is a capacity design method for a regulation and storage facility based on water quantity. The method has the following defects: firstly, the influence of the water quality process line of the drainage pipeline during rainfall is not considered. Influenced by factors such as rain and sewage mixed connection, pipeline sediment scouring in rainy days and the like, the process line of discharging water quality at the tail end of the drainage pipeline shows complex changes: the water quality concentration of the pipeline is high at the early stage of rainfall; and the water quality concentration of the pipeline in the middle and later periods of rainfall is possibly high. Therefore, the conventional regulation and storage tank working mode for intercepting in the early rainfall stage may not be capable of intercepting the pollution load to the maximum extent. The dynamic change of water quantity and water quality needs to be comprehensively considered, and the maximization of interception of overflow pollution load by a storage and regulation facility is realized. Secondly, an optimization design method aiming at the distributed storage regulation pool is lacked. Different from developed countries, the built urban areas in various parts of China have high building density, so that large-scale available space is limited. How to utilize the distributed urban available space according to local conditions is also a problem to be solved based on minimum construction cost to realize the control target of the overflow pollution in rainy days.
Therefore, an optimal design method for a distributed rainwater storage tank based on overflow pollution load control is provided to solve the difficulties in the prior art, which is a problem that needs to be solved urgently by those skilled in the art.
Disclosure of Invention
In view of the above, the invention provides an optimal design method for a distributed rainwater storage tank based on overflow pollution load control, and aims at the current situations of serious overflow pollution and poor pollutant intercepting effect of the storage tank in rainy days, the method for designing the rainwater storage tank according to an overflow water quality process line is used for reasonably determining the volume of the storage tank so as to maximize the pollutant interception.
In order to achieve the purpose, the invention adopts the following technical scheme:
the distributed rainwater storage tank optimization design method based on overflow pollution load control comprises the following steps:
s101, construction of an SWMM model: constructing an SWMM model which comprises a hydrological module, a hydrodynamic module and a water quality module;
s201, the calibration and verification steps of the SWMM model parameters are as follows: selecting three typical rainfall events of light rain, medium rain and heavy rain, and monitoring at least m effective rainfall events to carry out calibration and verification on SWMM model parameters, wherein m is more than or equal to 3;
s301, designing a rainfall process line: a rainfall process line is generated by utilizing a Chicago rain type, and rainfall intensity-time sequences under different rainfall recurrence period conditions are generated;
s401, an overflow water quality simulation step: simulating to obtain a change curve of the quality of the water of the overflow water at the tail discharge port of the rainwater pipe network along with time under different rainfall recurrence periods and the total discharge amount of pollution load at the discharge port when the regulation and storage pool is not arranged based on the calibrated SWMM model;
s501, rainwater storage tank position and quantity determination step: determining the number of the storage tanks and the position of each storage tank according to the land utilization type of the research area;
s601, constructing a distributed rainwater storage tank optimization model: constructing a distributed rainwater storage tank optimization model by taking the minimization of the total volume of the storage tank and the maximization of overflow pollution load reduction as optimization targets, taking the maximum available land areas at different positions as constraint conditions and the volumes of the storage tanks at different positions as objective functions;
s701, solving an optimization model of the distributed rainwater storage tank: firstly, randomly generating an initial population, and generating a new population through a distributed rainwater storage tank optimization model;
s801, determining the volume of a distributed rainwater storage tank: determining a target overflow pollution load reduction rate, searching in all individuals of the population to obtain an optimal individual corresponding to the target reduction rate, and thus obtaining the closure time and volume of each corresponding rainwater storage tank;
s901.pareto optimal curve and fitting equation obtaining steps: aiming at the optimal individuals in the population, drawing a Pareto optimal curve according to the corresponding objective function, fitting the relation between the drain overflow pollution load and the minimum storage tank total volume under different typical rainfall recurrence period conditions by utilizing a quadratic function to obtain a fitting equation, and realizing the optimal design of the rainwater storage tank by utilizing the fitting equation.
Optionally, the parameters of the hydrological module and the hydrodynamic module in S101 include, but are not limited to: manning coefficient, depression water storage depth and infiltration model parameters; the water quality module parameters comprise: maximum cumulant, half-saturation accumulation time, scouring coefficient and scouring index corresponding to different land utilization types.
Optionally, the coefficient R is adjusted by Nash in S201 NS To analyze water quantity and water quality simulation in rainfall eventThe matching degree between the measured value and the value is used to calibrate and verify the model parameter.
Optionally, R NS The calculation formula of (a) is as follows:
Figure BDA0003665844070000031
in the formula, R NS Is the Nash coefficient; q obs The measured value at the moment i; q sim Is the analog value at the moment i; q ave Is the average of all measured values; and n is the monitoring times.
Optionally, the specific content of S301 is: based on a designed rainstorm intensity formula, selecting a Chicago rain type rainfall generation process line as an input condition of the SWMM model, wherein the rainstorm intensity formula is as follows:
Figure BDA0003665844070000041
in the formula, q is designed rainstorm strength; p is the designed rainfall recurrence period; t is the duration of rainfall; x, Y, Z, k are all local parameters, and are obtained according to historical statistical rainfall data.
Optionally, the specific content of S501 is: determining the number m of the storage tanks and the position of each storage tank i according to the land utilization type of the research area; wherein m is an integer more than or equal to 1, i is the number of the regulation and storage tank, and i is an integer in the interval [1, m ].
Optionally, the specific content of S601 is: in the SWMM model, the starting closure time t of the regulation reservoir is controlled by a control rule 1 And ending the closure time t 2 To determine the volume V of the reservoir i at different positions i (ii) a The maximum available land area S at different positions is optimized by minimizing the total volume of the storage tank and maximizing the reduction of overflow pollution load i As a constraint, the volume V of the storage tank i is regulated at different positions i And constructing a distributed rainwater storage tank optimization model for the objective function.
Optionally, the specific content of S701 is: firstly, randomly generating an initial population, calling an SWMM model for each individual in the initial population to perform simulation calculation, simultaneously obtaining a total volume objective function and an overflow pollution load objective function of a storage tank, and generating a new population through selection, intersection and variation operations; and judging whether the maximum iteration times is reached, if so, ending the iteration to obtain a new population, otherwise, continuing returning to the step of calling the SWMM model to perform simulation calculation until the maximum iteration times is reached.
Optionally, the fitting equation in S901 is a quadratic function relationship, which is specifically shown in the following formula:
L＝AV 2 +BV+C (3)
wherein L is the pollution load of the overflow of the discharge port, and the unit is kg; v is the total volume of the minimum regulation and storage tank and is in m 3 (ii) a A. B, C are fitting equation coefficients.
Optionally, before S101, a model data obtaining step is further included, configured to obtain data for constructing the SWMM model.
According to the technical scheme, compared with the prior art, the invention provides the distributed rainwater storage tank optimization design method based on overflow pollution load control, which comprises the following steps: designing the effective volume of the regulation and storage pool based on the water quality process line of the discharged water in rainy days and controlling the starting closure time and the ending closure time of the regulation and storage pool by a control rule in an SWMM model, and optimally designing the volume of the regulation and storage pool by a coupling multi-objective optimization algorithm; by adopting the design method for the rainwater storage tank, the dual targets of minimizing the total volume of the storage tank and maximizing the reduction of the overflow pollution load can be realized, the Pareto optimal curve and the fitting equation are further determined, and finally the relation graph of the minimum total volume of the storage tank and the overflow pollution load under different rainfall recurrence period working conditions can be obtained, so that the scientific and reasonable design method for the rainwater storage tank is provided.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of an optimal design method of a distributed rainwater storage tank based on overflow pollution control according to the present invention;
FIG. 2 is a flow chart of a SWMM model and multi-objective optimization algorithm coupling provided by the present invention;
FIG. 3 is a diagram showing the optimization result of the total volume of the storage tank and the COD pollution load at the discharge port;
FIG. 4 is a Pareto optimal curve and a fitting equation chart (a relation curve of the total volume of the minimum storage tank and the COD pollution load at the discharge port) provided by the invention;
FIG. 5 is a Pareto optimal curve and a fitting equation chart provided by the invention (a relation curve of the total volume of a minimum storage tank and the ammonia nitrogen pollution load at a discharge port);
fig. 6 is a structural block diagram of a distributed rainwater storage tank optimization design system based on overflow pollution control provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention discloses an optimal design method of a distributed rainwater storage tank based on overflow pollution load control, which comprises the following steps:
s101, construction of an SWMM model: constructing an SWMM model which comprises a hydrological module, a hydrodynamic module and a water quality module;
s201, the calibration and verification steps of the SWMM model parameters are as follows: selecting three typical rainfall events of light rain, medium rain and heavy rain, and monitoring at least m effective rainfall events to carry out calibration and verification on SWMM model parameters, wherein m is more than or equal to 3;
s301, designing a rainfall process line: a rainfall process line is generated by utilizing a Chicago rain type, and rainfall intensity-time sequences under different rainfall recurrence period conditions are generated;
s401, simulating the water quality of overflow water: simulating to obtain a change curve of the quality of the water of the overflow water at the tail discharge port of the rainwater pipe network along with time under different rainfall recurrence periods and the total discharge amount of pollution load at the discharge port when the regulation and storage pool is not arranged based on the calibrated SWMM model;
s501, rainwater storage tank position and quantity determination step: determining the number of the storage tanks and the position of each storage tank according to the land utilization type of the research area;
s601, constructing a distributed rainwater storage tank optimization model: constructing a distributed rainwater storage tank optimization model by taking the minimization of the total volume of the storage tank and the maximization of overflow pollution load reduction as optimization targets, taking the maximum available land areas at different positions as constraint conditions and the volumes of the storage tanks at different positions as objective functions;
s701, solving an optimization model of the distributed rainwater storage tank: firstly, randomly generating an initial population, and generating a new population through a distributed rainwater storage tank optimization model;
s801, determining the volume of a distributed rainwater storage tank: determining a target overflow pollution load reduction rate, searching in all individuals of the population to obtain an optimal individual corresponding to the target reduction rate, and thus obtaining the closure time and volume of each corresponding rainwater storage tank;
s901.pareto optimal curve and fitting equation obtaining steps: aiming at the optimal individuals in the population, drawing a Pareto optimal curve according to the corresponding objective function, fitting the relation between the overflow pollution load and the minimum storage tank total volume under different typical rainfall recurrence period conditions by utilizing a quadratic function to obtain a fitting equation, and realizing the optimal design of the rainwater storage tank by utilizing the fitting equation.
Further, the hydrographic module and hydrodynamic module parameters in S101 include, but are not limited to: manning coefficient, depression water storage depth and infiltration model parameters; the water quality module parameters comprise: maximum cumulant, half-saturation accumulation time, scouring coefficient and scouring index corresponding to different land utilization types.
Further, in S201, the coefficient R is determined by a Nash coefficient NS The degree of coincidence between the water quantity and water quality simulation value and the measured value in the rainfall event is analyzed, so as to rate and verify the model parameters.
Selecting three typical rainfall events of light rain, medium rain and heavy rain, and monitoring the change process of rainfall along with time through a rain gauge; monitoring the change process of the overflow water quantity along with time in the whole rainfall process by using a Doppler ultrasonic flowmeter; sampling the overflow water sample at a certain time interval and analyzing the water quality index. By a Nash coefficient R NS The degree of coincidence between the simulated value and the measured value is analyzed to determine the model parameters. R NS The closer to 1, the higher the coincidence between the simulation value and the measured value, and the better the simulation effect of the model.
Further, R NS The calculation formula of (a) is as follows:
Figure BDA0003665844070000081
in the formula, R NS Is the Nash coefficient; q obs The measured value at the moment i; q sim Is the analog value at the time i; q ave Is the average of all measured values; and n is the monitoring times.
Further, the specific content of S301 is: based on a designed rainstorm intensity formula, selecting a Chicago rain type with a rainfall recurrence period P and a rainfall duration t as input conditions of the SWMM model, wherein the rainstorm intensity formula is as follows:
Figure BDA0003665844070000082
in the formula, q is designed rainstorm intensity; p is a designed rainfall recurrence period; t is the duration of rainfall; x, Y, Z, k is a local parameter.
Taking Anhui province, Maanshan city as an example, the formula of the rainstorm intensity is as follows:
Figure BDA0003665844070000083
further, the specific content of S501 is: determining the number m of the storage tanks and the position of each storage tank i according to the land utilization type of the research area; wherein m is an integer not less than 1, i is the number of the regulating storage tank, and i is an integer in the interval [1, m ].
Specifically, according to the land use type of the research area, the number m of the storage tanks is 2, and the position of each storage tank i is determined. Wherein i is the number of the regulation and storage tank, and i is an integer in the interval [1, 2 ].
Further, the specific content of S601 is: in the SWMM model, the starting closure time t of the regulation reservoir is controlled by a control rule 1 And ending the closure time t 2 To determine the volume V of the reservoir i at different positions i (ii) a The maximum available land area S at different positions is optimized by minimizing the total volume of the storage tank and maximizing the reduction of overflow pollution load i As a constraint, the volume V of the storage tank i is regulated at different positions i And constructing a distributed rainwater storage tank optimization model for the objective function.
Specifically, a Python language is used for compiling the NSGA-II multi-objective optimization algorithm, the SWMM model is called through the SWMM _ api third-party tool box, so that the SWMM model and the NSGA-II multi-objective optimization algorithm are coupled, and a coupling flow diagram is shown in FIG. 2.
Further, the volume V of the reservoir i is adjusted at different positions i The calculation formula of (a) is as follows:
Figure BDA0003665844070000091
the calculation formula of the total volume V of the storage tank is as follows:
Figure BDA0003665844070000092
in the formula, V i For adjusting different positionsThe volume of reservoir i; q (t) is a function of the inflow rate over time; t is t 1 For starting the closure time; t is t 2 To end the cut-off time; v is the total volume of the regulation and storage tank.
Further, referring to fig. 2, the specific content of S701 is: firstly, randomly generating an initial population, calling an SWMM model for each individual in the initial population to perform simulation calculation, simultaneously obtaining a storage tank total volume objective function and a discharge port overflow pollution load objective function, and generating a new population through selection, intersection and variation operations; and judging whether the maximum iteration times is reached, if so, ending the iteration to obtain a new population, otherwise, continuing returning to the step of calling the SWMM model to perform simulation calculation until the maximum iteration times is reached. The optimization results under the 0.5 year-round design condition are shown in fig. 3.
Further, in S801, under the design condition of 0.5 year meeting, if the target COD pollution load reduction rates are 40%, 60%, and 80%, respectively, the cut-off time and volume of each corresponding rainwater storage tank are shown in table 1.
TABLE 1 optimal rainwater storage tank volume under different COD pollution load reduction rate
Figure BDA0003665844070000093
Figure BDA0003665844070000101
Further, the fitting equation in S901 is a quadratic function relationship, which is specifically shown in the following formula:
L＝AV 2 +BV+C (3)
in the formula, L is the pollution load of the overflow of the discharge port, and the unit is kg; v is the total volume of the minimum regulation and storage tank and is in m 3 (ii) a A. B, C are fitting equation coefficients.
Specifically, under the design conditions of different rainfall recurrence periods P being 0.1a, P being 0.2a, and P being 0.5a, the Pareto front-edge fitting curve equation is shown in table 2. Based on pollution at the tail end discharge port when the regulation and storage tank is not arrangedThe total load discharge amount and the solution on the Pareto optimal curve are used for obtaining COD and NH under different design working conditions 3 N contamination load reduction rate, as shown in Table 3. The relation curve of the total volume of the minimum regulating reservoir and the COD pollution load at the discharge port is shown in figure 4, and the relation curve of the total volume of the minimum regulating reservoir and the ammonia nitrogen pollution load at the discharge port is shown in figure 5.
TABLE 2 Pareto front edge fitting curve under different rainfall recurrence period working conditions
Figure BDA0003665844070000102
In the above table, L COD The COD pollution load is the overflow load of the discharge port, and the unit is kg; l is a radical of an alcohol NH3-N For discharging NH by overflow 3 -N pollution load in kg; v is the total volume of the storage tank, m 3 。
TABLE 3 Ammonia nitrogen pollution load discharge and reduction rate under different design conditions
Figure BDA0003665844070000103
Figure BDA0003665844070000111
Further, before S101, a model data obtaining step is further included, configured to obtain data for constructing the SWMM model.
Referring to fig. 6, the invention also discloses a distributed rainwater storage tank optimization design system based on overflow pollution load control, which comprises an SWMM model construction module, a model parameter calibration and verification module, a rainfall process line design module, an overflow water quality simulation module, a storage tank position and quantity determination module, a distributed rainwater storage tank optimization model construction module, a distributed rainwater storage tank optimization model solving module, a distributed rainwater storage tank volume determination module and a Pareto optimal curve and fitting equation acquisition module which are connected in sequence.
The SWMM model building module: constructing an SWMM model which comprises a hydrological module, a hydrodynamic module and a water quality module;
a model parameter calibration and verification module: selecting three typical rainfall events of light rain, medium rain and heavy rain, and monitoring at least m effective rainfall events to carry out calibration and verification on SWMM model parameters, wherein m is more than or equal to 3;
rainfall process line design module: a rainfall process line is generated by utilizing a Chicago rain type, and rainfall intensity-time sequences under different rainfall recurrence period conditions are generated;
an overflow water quality simulation module: simulating to obtain a change curve of the quality of the water of the overflow water at the tail discharge port of the rainwater pipe network along with time under different rainfall recurrence periods and the total discharge amount of pollution load at the discharge port when the regulation and storage pool is not arranged based on the calibrated SWMM model;
storage tank position and quantity determination module: determining the number of the storage tanks and the position of each storage tank according to the land utilization type of the research area;
the distributed rainwater regulation and storage tank optimization model building module comprises: constructing a distributed rainwater storage tank optimization model by taking the minimization of the total volume of the storage tank and the maximization of overflow pollution load reduction as optimization targets, taking the maximum available land areas at different positions as constraint conditions and the volumes of the storage tanks at different positions as objective functions;
the distributed rainwater regulation and storage tank optimization model solving module comprises: firstly, randomly generating an initial population, and generating a new population through a distributed rainwater storage tank optimization model;
distributed rainwater regulation pond volume determination module: determining a target overflow pollution load reduction rate, searching in all individuals of the population to obtain an optimal individual corresponding to the target reduction rate, and thus obtaining the closure time and volume of each corresponding rainwater storage tank;
a Pareto optimal curve and fitting equation obtaining module: and aiming at the optimal individuals in the population, drawing a Pareto optimal curve according to the corresponding objective function, and fitting the relation between the discharge outlet overflow pollution load and the minimum storage tank total volume under different typical rainfall recurrence period conditions by utilizing a quadratic function to obtain a fitting equation.
Further, the system also comprises a data acquisition module (not shown in the figure), which is connected with the input end of the SWMM model building module and is used for acquiring data for building the SWMM model.
On the premise of improving the urban water environment quality, a distributed rainwater storage tank optimization model is constructed by taking the minimization of the total volume of a storage tank and the maximization of the reduction of the overflow pollution load as optimization targets and taking the maximum available land areas at different positions as constraint conditions, a Pareto optimal curve is obtained by coupling an SWMM model and an NSGA-II optimization algorithm to solve the model, and an equation between the overflow pollution load and the minimum total volume of the storage tank is fitted by combining a quadratic function. The method is based on analysis of a discharge outlet overflow water quantity change process line and a water quality change process line, and a reasonable, scientific and efficient rainwater storage tank volume design method capable of achieving accurate sewage interception is established.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention in a progressive manner. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. The distributed rainwater storage tank optimization design method based on overflow pollution load control is characterized by comprising the following steps of:
s101, construction of an SWMM model: constructing an SWMM model which comprises a hydrological module, a hydrodynamic module and a water quality module;
s201, the calibration and verification steps of the SWMM model parameters are as follows: selecting three typical rainfall events of light rain, medium rain and heavy rain, and monitoring at least m effective rainfall events to carry out calibration and verification on SWMM model parameters, wherein m is more than or equal to 3;
s301, designing a rainfall process line: a rainfall process line is generated by utilizing a Chicago rain type, and rainfall intensity-time sequences under different rainfall recurrence period conditions are generated;
s401, simulating the water quality of overflow water: obtaining a change curve of the quality of overflow water at a tail end discharge outlet of a rainwater pipe network along with time under different rainfall recurrence periods and the total discharge amount of pollution load at the discharge outlet when a storage regulation pool is not arranged on the basis of the calibrated SWMM model simulation;
s501, rainwater storage tank position and quantity determination step: determining the number of the storage tanks and the position of each storage tank according to the land utilization type of the research area;
s601, constructing a distributed rainwater storage tank optimization model: constructing a distributed rainwater storage tank optimization model by taking the minimization of the total volume of the storage tank and the maximization of overflow pollution load reduction as optimization targets, taking the maximum available land areas at different positions as constraint conditions and the volumes of the storage tanks at different positions as objective functions;
s701, solving an optimization model of the distributed rainwater storage tank: firstly, randomly generating an initial population, and generating a new population through a distributed rainwater storage tank optimization model;
s801, determining the volume of a distributed rainwater storage tank: determining a target overflow pollution load reduction rate, searching in all individuals of the population to obtain an optimal individual corresponding to the target reduction rate, and thus obtaining the closure time and volume of each corresponding rainwater storage tank;
s901.pareto optimal curve and fitting equation obtaining steps: and aiming at the optimal individuals in the population, drawing a Pareto optimal curve according to the corresponding objective function, fitting the relation between the overflow pollution load and the total volume of the minimum storage tank under different typical rainfall recurrence period conditions by using a quadratic function to obtain a fitting equation, and realizing the optimal design of the rainwater storage tank by using the fitting equation.
2. The distributed rainwater storage tank optimization design method based on overflow pollution load control according to claim 1,
the hydrologic and hydrodynamic module parameters in S101 include, but are not limited to: manning coefficient, depression water storage depth and infiltration model parameters; the water quality module parameters comprise: maximum cumulant, half-saturation accumulation time, scouring coefficient and scouring index corresponding to different land utilization types.
3. The distributed rainwater storage tank optimization design method based on overflow pollution load control according to claim 1,
in S201, the coefficient R is determined by a Nash coefficient NS The degree of coincidence between the water quantity and water quality simulation value and the measured value in the rainfall event is analyzed, so as to rate and verify the model parameters.
4. The distributed rainwater storage tank optimization design method based on overflow pollution load control according to claim 3,
R NS the calculation formula of (a) is as follows:
Figure FDA0003665844060000021
in the formula, R NS Is the Nash coefficient; q obs The measured value at the moment i; q sim Is the analog value at the moment i; q ave Is the average of all measured values; and n is the monitoring times.
5. The distributed rainwater storage tank optimization design method based on overflow pollution load control according to claim 1,
the specific content of S301 is: based on a designed rainstorm intensity formula, selecting a Chicago rain type rainfall generation process line as an input condition of the SWMM model, wherein the rainstorm intensity formula is as follows:
Figure FDA0003665844060000031
in the formula, q is designed rainstorm strength; p is the designed rainfall recurrence period; t is the duration of rainfall; x, Y, Z, k are all local parameters, and are obtained according to historical statistical rainfall data.
6. The distributed rainwater storage tank optimization design method based on overflow pollution load control according to claim 1,
the specific content of S501 is: determining the number m of the storage tanks and the position of each storage tank i according to the land utilization type of the research area; wherein m is an integer more than or equal to 1, i is the number of the regulation and storage tank, and i is an integer in the interval [1, m ].
7. The distributed rainwater storage tank optimization design method based on overflow pollution load control according to claim 1,
the specific content of S601 is: in the SWMM model, the starting closure time t of the regulation reservoir is controlled by a control rule 1 And ending the closure time t 2 To determine the volume V of the reservoir i at different positions i (ii) a The maximum available land area S at different positions is optimized by minimizing the total volume of the storage tank and maximizing the reduction of overflow pollution load i Regulating the volume V of the storage tank i at different positions as a constraint condition i And constructing a distributed rainwater storage tank optimization model for the objective function.
8. The distributed rainwater storage tank optimization design method based on overflow pollution load control according to claim 1,
the specific content of S701 is as follows: firstly, randomly generating an initial population, calling an SWMM model for each individual in the initial population to perform simulation calculation, simultaneously obtaining a total volume objective function and an overflow pollution load objective function of a storage tank, and generating a new population through selection, intersection and variation operations; and judging whether the maximum iteration times is reached, if so, ending the iteration to obtain a new population, otherwise, continuing returning to the step of calling the SWMM model to perform simulation calculation until the maximum iteration times is reached.
9. The distributed rainwater storage tank optimization design method based on overflow pollution load control according to claim 1,
in S901, the fitting equation is a quadratic function relationship, which is specifically shown in the following formula:
L＝AV 2 +BV+C (3)
in the formula, L is the pollution load of the overflow of the discharge port, and the unit is kg; v is the total volume of the minimum regulation and storage tank and is in m 3 (ii) a A. B, C are fitting equation coefficients.
10. The distributed rainwater storage tank optimization design method based on overflow pollution load control according to any one of claims 1 to 9,
a model data acquisition step is further included before S101, for acquiring data for constructing the SWMM model.
CN202210585675.1A 2022-05-27 2022-05-27 Distributed rainwater storage tank optimization design method based on overflow pollution load control Pending CN114861550A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210585675.1A CN114861550A (en) 2022-05-27 2022-05-27 Distributed rainwater storage tank optimization design method based on overflow pollution load control

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210585675.1A CN114861550A (en) 2022-05-27 2022-05-27 Distributed rainwater storage tank optimization design method based on overflow pollution load control

Publications (1)

Publication Number Publication Date
CN114861550A true CN114861550A (en) 2022-08-05

Family

ID=82640968

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210585675.1A Pending CN114861550A (en) 2022-05-27 2022-05-27 Distributed rainwater storage tank optimization design method based on overflow pollution load control

Country Status (1)

Country Link
CN (1) CN114861550A (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115730769A (en) * 2022-11-25 2023-03-03 武汉大学 Composite rain type construction method and device for evaluating drainage capacity of pipe network of rich water city
CN115806345A (en) * 2022-12-14 2023-03-17 中国长江三峡集团有限公司 Composite microorganism system and method for runoff sewage in-situ treatment
CN115907429A (en) * 2022-12-28 2023-04-04 清华大学 PSO algorithm-based combined overflow optimization control method and device
CN116011756A (en) * 2022-12-28 2023-04-25 清华大学 NSGA-II algorithm-based river channel water quality multi-objective optimization scheduling method
CN116495888A (en) * 2023-04-13 2023-07-28 河海大学 Ecological regulation pool and volume allocation method thereof

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115730769A (en) * 2022-11-25 2023-03-03 武汉大学 Composite rain type construction method and device for evaluating drainage capacity of pipe network of rich water city
CN115730769B (en) * 2022-11-25 2023-08-22 武汉大学 Composite rain type construction method and device for evaluating drainage capacity of urban pipe network
CN115806345A (en) * 2022-12-14 2023-03-17 中国长江三峡集团有限公司 Composite microorganism system and method for runoff sewage in-situ treatment
CN115806345B (en) * 2022-12-14 2023-09-12 中国长江三峡集团有限公司 Composite microorganism system and method for runoff sewage in-situ treatment
CN115907429A (en) * 2022-12-28 2023-04-04 清华大学 PSO algorithm-based combined overflow optimization control method and device
CN116011756A (en) * 2022-12-28 2023-04-25 清华大学 NSGA-II algorithm-based river channel water quality multi-objective optimization scheduling method
CN115907429B (en) * 2022-12-28 2023-08-25 清华大学 PSO algorithm-based combined overflow optimization control method and device
CN116011756B (en) * 2022-12-28 2023-10-27 清华大学 NSGA-II algorithm-based river channel water quality multi-objective optimization scheduling method
CN116495888A (en) * 2023-04-13 2023-07-28 河海大学 Ecological regulation pool and volume allocation method thereof
CN116495888B (en) * 2023-04-13 2024-01-26 河海大学 Ecological regulation pool and volume allocation method thereof

Similar Documents

Publication Publication Date Title
CN114861550A (en) Distributed rainwater storage tank optimization design method based on overflow pollution load control
CN109492299B (en) Water resource simulation method based on SWMM and MODIflow coupling
Ao et al. Replenishment of landscape water with reclaimed water: Optimization of supply scheme using transparency as an indicator
CN109583035B (en) Cellular automaton-based urban non-point source pollutant accumulated scouring process calculation method
Yu et al. Application of the stormwater management model to a piedmont city: a case study of Jinan City, China
CN113435630B (en) Basin hydrological forecasting method and system with self-adaptive runoff yield mode
CN107247888B (en) Method for soft measurement of total phosphorus TP (thermal transfer profile) in sewage treatment effluent based on storage pool network
CN112685880A (en) Design method for optimizing scale of combined system overflow storage tank
CN112766669A (en) Drainage basin pollution limit value emission verification method based on water quality model
CN115758886A (en) Optimal distribution method of storage tanks based on rain flood pipe network model and decision tree algorithm
CN112215504B (en) Gate-controlled heavy pollution small-river-basin pollutant flux observation method
CN112907047A (en) Sponge city performance evaluation system
CN114969655A (en) Simulation estimation method for sediment transport amount of drainage basin
CN101858107B (en) Method for designing rainwater treatment and utilization facility
CN110033139A (en) A kind of urban rainwater optimization system and method based on sponge the idea of the city
CN110580377A (en) Grass planting ditch design parameter optimization method based on response surface method
CN115293574A (en) Comprehensive evaluation method of urban rainfall flood management scheme based on low-impact development
CN114386796A (en) Sponge city project construction effect and overall quality evaluation method
CN112183123B (en) Method for analyzing water demand of ecological environment in river channel for water bloom prevention and control
CN115015504A (en) Surface water quality monitoring method based on surface land type
CN114331787A (en) Reservoir ecological discharge quantity accounting method with aim of improving water quality of downstream river
CN114595631A (en) Water quality prediction method based on EFDC model and machine learning algorithm
CN113536444A (en) Rainwater storage tank volume calculation method for water disaster prevention and control
CN111539596A (en) Storage regulation capability evaluation method for drainage basin grey infrastructure
CN111539153A (en) Water and sand combined optimization scheduling method based on pre-constructed sediment information base

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination