Dynamic water quality simulation and prediction coupling model method for gravity flow sewer network

Abstract

The application discloses a gravity flow drainage pipe network dynamic water quality simulation and prediction coupling model method, belongs to the field of intelligent water management, and particularly relates to dynamic water quality transformation simulation and prediction in a gravity flow drainage pipe network. The application discloses a gravity flow drainage pipe network dynamic water quality simulation and prediction coupling model method, belongs to the field of intelligent water management, and particularly relates to dynamic water quality transformation simulation and prediction in a gravity flow drainage pipe network. The application discloses a gravity flow drainage pipe network dynamic water quality simulation and prediction coupling model method, belongs to the field of intelligent water management, and particularly relates to dynamic water quality transformation simulation and prediction in a gravity flow drainage pipe network. The application discloses a gravity flow drainage pipe network dynamic water quality simulation and prediction coupling model method, belongs to the field of intelligent water management, and particularly relates to dynamic water quality transformation simulation and prediction in a gravity flow drainage pipe network. The application discloses a gravity flow drainage pipe network dynamic water quality simulation and prediction coupling model method, belongs to the field of intelligent water management, and particularly relates to dynamic water quality transformation simulation and prediction in a gravity flow drainage pipe network.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of smart water management, and particularly relates to dynamic water quality transformation simulation prediction in gravity flow sewer network. BACKGROUND

[0002] Sewer network is the main component of sewage collection system, and its main function is to collect and transport sewage.

[0003] In addition to the engineering reasons such as rainwater and sewage mixing and external water infiltration, the sewer network itself also plays the role of biochemical reactor, and a series of physical-chemical-biological transformation processes of pollutants (i.e. water quality transformation process) occur inside it. The water quality transformation process of the sewer network will produce a series of adverse results, which is always wanted to be avoided by those skilled in the art. For example, the particles deposited in the dry season are reflushed during the high flow period such as the rainy season, causing the short-term load of the downstream sewage treatment plant to increase beyond the treatment capacity, resulting in the formation of sediments; the formation of sediments reduces the flow capacity of the sewer network, reducing the resistance to flooding, and the sewage exceeding the treatment capacity will be directly discharged into the water body; the sediments and biofilms growing on the inner wall of the sewer network have biological activity, which continuously consumes carbon source substances in the sewage, leading to imbalance of C / N ratio of the sewage, increasing the carbon source adding cost of the downstream sewage treatment plant, and further increasing the cost of operation, regulation and management of the sewage treatment plant, and the indirect emission of greenhouse gases caused by unnecessary additional reagent addition and other environmental impacts. The water quality transformation process in the sewer network aggravates the deterioration of the water environment, but those skilled in the art lack sufficient attention and research on this transformation process.

[0004] In summary, accurate understanding and quantitative analysis of the water quality transformation process in sewer networks are of great significance for comprehensive water environment management. Water quality transformation models in sewer networks use existing data from sewer facilities nodes to analyze the spatial and temporal distribution characteristics of pollutants in the global sewer network, and are important tools for solving problems related to water quality transformation in sewer networks. According to the differences in sewage flow driving force, sewer networks can be divided into gravity flow and pressure flow. Gravity flow sewer networks account for 95% of sewer networks and are the most widely used operation mode. Water quality transformation models usually include hydrodynamic and biochemical reaction kinetics modules. According to the complexity of the hydrodynamic module, it can be divided into fluid mechanics models based on the N-S equation and hydrology models based on various inflow-outflow relationships. Fluid mechanics models based on the N-S equation are widely used in the hydraulic calculation of pressure flow and gravity flow sewer networks. However, due to the inherent computational load of the NS equation, this type of model can only consider simple linear degradation patterns for pollutant indicators and does not consider mass conservation relationships, making it difficult to reflect complex biochemical reaction processes, such as the influence of dynamic aerobic-anoxic-anaerobic environmental changes on microbial metabolism in gravity flow sewer networks. Therefore, this type of model is often used to solve water-related problems, such as combined sewer overflow, online control of flood drainage, etc.

[0005] Another type of hydrology model based on various inflow-outflow relationships can usually couple more complex biochemical reaction kinetics models, such as the ASM series of models, which consider various biochemical reaction processes under aerobic-anoxic-anaerobic environmental conditions in actual sewer networks. However, due to the fact that current research mainly focuses on pressure flow pipelines with relatively simple hydraulic conditions, the hydrology module only needs to consider the hydraulic conditions of full pipe flow and does not need to consider the changes in water level in the pipeline, so the hydrology module only needs to use a simple CSTR model to meet the conditions.

[0006] Current water quality transformation models that comprehensively consider the complex environmental changes in the sewer network are mostly applied to pressure flow sewer networks, and the simulation of water quality transformation in gravity flow (drainage) sewer networks is still relatively blank. The reason is that gravity flow sewer networks exhibit more complex hydraulic conditions than pressure flow sewer networks due to their non-full pipe flow operation state and changing flow conditions, specifically:

[0007] Firstly, the highly variable hydraulic conditions in gravity flow sewer networks often result in the formation and scouring of sediments, and biofilms are usually found on the inner walls of the pipes; while in pressure flow sewer networks, only biofilms on the pipe walls exist. Both sediments and biofilms are active in gravity flow sewer networks, so their biochemical reactions will affect water quality, such as hydrolysis and fermentation processes. In addition, due to the changes in inflow flow rate, the hydraulic conditions in non-full pipe flow gravity flow pipelines change dramatically, affecting the contact reaction area between sediments, biofilms, and sewage, thereby affecting the water quality transformation process in the sewer network.

[0008] Secondly, the gravity flow pipe network also has a headspace (or headspace air layer, headspace layer), and there is gas-liquid exchange between the sewage and the headspace, so the gravity flow pipe network has an aerobic-anoxic-anaerobic state transition process; the pressure flow pipe network is full of sewage and does not have a headspace layer, and is usually an anaerobic environment. The existence of these processes makes the water quality transformation simulation of the gravity flow pipe network more complex.

[0009] In summary, the current water quality transformation model is mostly applied to the pressure flow pipe network, and cannot comprehensively and accurately simulate the gravity flow pipe network with more complex hydraulic conditions. SUMMARY

[0010] The application provides a gravity flow drainage pipe network dynamic water quality simulation and prediction coupling model method, which considers the actual pipe network as a multiphase (sewage-sediment-biofilm-headspace) reactor, couples the influences of hydraulic changes, sediment generation and resuspension, biofilm adsorption and desorption, gas-liquid interface mass transfer and biochemical reactions on various processes of sewage water quality transformation, and solves the problem of simulating the water quality transformation process in the current gravity flow pipe network.

[0011] The gravity flow drainage pipe network dynamic water quality simulation and prediction coupling model method provided by the application has the technical scheme as follows.

[0012] The method comprises the following steps:

[0013] A step of constructing a gravity flow drainage pipe water quality transformation model for any drainage pipe in a drainage pipe network, wherein:

[0014] The gravity flow drainage pipe water quality transformation model comprises a hydraulics module, a biochemical reaction kinetics module, and a mass conservation module.

[0015] The hydraulics module comprises a hydraulics expression of sewage flowing and migrating in the drainage pipe network, and a volume change relationship expression of the liquid phase, sediment, biofilm and headspace in the drainage pipe; the hydraulics module is used to reflect the hydraulics state change relationship in the drainage pipe.

[0016] The biochemical reaction kinetics module comprises a list of pollutant state variables and a stoichiometry and kinetics matrix; the list of pollutant state variables is constructed based on unit process elements of reaction physical and biochemical conversion processes; the biochemical reaction kinetics module is used to reflect the biochemical reaction conversion relationship in the drainage pipe.

[0017] The mass conservation module is used to reflect the mass conservation relationship of pollutants in the sewage, sediment, biofilm and headspace.

[0018] The step of correcting the gravity flow sewer pipe water quality transformation model according to the characteristics of the actual gravity flow sewer pipe, to obtain a corrected gravity flow sewer pipe water quality transformation model;

[0019] The step of combining the corrected gravity flow sewer pipe water quality transformation model of all sewer pipes into an actual regional full-scale regional sewer network water quality transformation model with a tree topology according to the structure of the actual sewer network;

[0020] The step of obtaining the water quality transformation simulation result of the actual gravity flow sewer network according to the actual regional full-scale regional sewer network water quality transformation model with a tree topology.

[0021] Further, a preferred embodiment of the step of correcting the gravity flow sewer pipe water quality transformation model according to the characteristics of the actual gravity flow sewer pipe, to obtain a corrected gravity flow sewer pipe water quality transformation model is provided, which comprises the following steps:

[0022] The step of performing parameter sensitivity analysis on the gravity flow sewer pipe water quality transformation model to obtain the to-be-corrected parameters;

[0023] The step of obtaining the characteristics of the actual gravity flow sewer pipe;

[0024] The step of correcting the to-be-corrected parameters of the gravity flow sewer pipe water quality transformation model according to the characteristics of the actual gravity flow sewer pipe, to obtain a corrected gravity flow sewer pipe water quality transformation model.

[0025] Further, a preferred embodiment of the step of combining the corrected gravity flow sewer pipe water quality transformation model of all sewer pipes into an actual regional full-scale regional sewer network water quality transformation model with a tree topology according to the structure of the actual sewer network is provided, which comprises the following steps:

[0026] Obtaining the connection relationship of each sewer pipe of the actual gravity flow sewer network;

[0027] Taking the corrected gravity flow sewer pipe water quality transformation model of each sewer pipe as a unit model;

[0028] According to the connection relationship of the actual gravity flow sewer network, the unit models are constructed into an actual regional full-scale regional sewer network water quality transformation model with a tree topology.

[0029] Further, a preferred embodiment of the construction method of the biochemical reaction kinetics module is as follows:

[0030] All unit process elements are obtained by selecting generic compatible physical and biochemical transformation processes based on gravity flow sewer pipes using a plant-wide modeling approach;

[0031] Based on all unit process elements obtained, a list of pollutant state variables is created and stoichiometric and kinetic matrices for the pollutant state variables are defined.

[0032] Further, a preferred embodiment is provided, where the mass balance of a pollutant i in the sewer is represented by the following basic mass balance equation for the pollutant i in the pipe element:

[0033] ;

[0034] ;

[0035] wherein, Ci is the concentration of the pollutant i in the sewer in the pipe element; V is the volume of the sewer in the pipe element; Qi is the inflow; Qo is the outflow; Ci_in is the concentration of the pollutant i in the inflow; Ci_out is the concentration of the pollutant i in the outflow; Rtot is the total reaction rate of the pollutant i in the pipe, including mass transfer and biochemical transformation; Rsed is the rate of deposition of the pollutant i from the sewer to the sediment; Rdes is the rate of desorption of the pollutant i from the sediment; Dif is the rate of diffusion of the pollutant i from the sewer to the sediment in the pipe element; Ads is the rate of adsorption of the pollutant i from the sewer to the biofilm; Des is the rate of desorption of the pollutant i from the biofilm; Dif is the rate of diffusion of the pollutant i from the sewer to the biofilm in the pipe element; G is the gas-liquid mass transfer rate; B is the biochemical reaction rate of the pollutant i in the liquid phase;

[0036] Further, a preferred embodiment is provided, where the mass balance of a pollutant i in the sediment is represented by the following basic mass balance equation for the pollutant i in the sediment layer:

[0037] ;

[0038] wherein, Ci is the concentration of the pollutant i in the sediment layer in the pipe element; V is the volume of the sediment in the pipe element; Boil is the rate of boil-off of the pollutant i from the sediment; Biochemical reaction rate of contaminant i in the biofilm.

[0039] Further, a preferred embodiment is provided, the mass balance of contaminant i in the biofilm is expressed by the following basic mass balance equation of contaminant i in the biofilm layer:

[0040] ;

[0041] wherein, Ci is the concentration of contaminant i in the biofilm layer in the pipe unit; V is the biofilm volume in the pipe unit; B is the boiling off rate of contaminant i in the biofilm; R is the biochemical reaction rate of contaminant i in the biofilm;

[0042] Expression of adsorption and diffusion between the biofilm layer and the water phase:

[0043] ;

[0044] ;

[0045] ;

[0046] ;

[0047] wherein, Kmax is the maximum adsorption rate of the biofilm; A is the contact area of the biofilm with the wastewater; D is the desorption rate of the biofilm; Cbio is the concentration of TSS in the biofilm; Cbio,ss is the concentration of TSS in the biofilm under steady state conditions; L is the thickness of the biofilm; E is the empirical enhancement factor for the diffusion rate in the biofilm; B is the boiling off rate of contaminant i in the biofilm; R is the biochemical reaction rate of contaminant i in the biofilm.

[0048] Further, a preferred embodiment is provided, the mass balance of contaminant i in the headspace layer is expressed by the following basic mass balance equation of contaminant i in the headspace layer:

[0049] ;

[0050] wherein, Ci is the concentration of contaminant i in the headspace layer in the pipe unit; V is the headspace volume in the pipe unit; G is the gas flow into the headspace; Concentration of the pollutant i in the gas entering the headspace layer; Gas flow rate leaving the pipe segment unit; Mass transfer rate between the headspace layer and other phases.

[0051] Further, a preferred embodiment is provided, which corrects the gravity flow sewer water quality transformation model according to the characteristics of the actual gravity flow sewer, including correction of pipe parameters, influent pollutant load parameters, and gas phase input parameters:

[0052] The pipe parameters, influent pollutant load parameters, and gas phase input parameters are determined according to the actual gravity flow sewer network.

[0053] Further, a preferred embodiment is provided, which corrects the gravity flow sewer water quality transformation model according to the characteristics of the actual gravity flow sewer, further including correction of parameters in the biochemical reaction kinetics module, the hydrodynamic module, and the mass conservation module.

[0054] The present application has the following beneficial effects:

[0055] 1. The gravity flow sewer network dynamic water quality simulation prediction coupling model method adopts a hydrodynamic module including hydrodynamic expressions of sewage flowing and migrating in the sewer network, introduces pipe network water depth, fullness, wet perimeter, etc. as intermediate variables based on a nonlinear outflow algorithm, calculates the relationship between the current pipe network (channel) sewage volume and pipe network outflow, can be used to describe the hydrodynamic conversion relationship in the gravity flow sewer network with more complex hydraulic conditions, and finally obtains a common differential equation which can be solved by numerical method. Compared with the spatial gridding of N-S equation, this method is simpler, effectively balances the calculation load, and can be coupled with ASM, SUMO2S, etc. pollutant dynamics model based on conservation relationship for complex pollutant transformation simulation research.

[0056] 2. The gravity flow sewer network dynamic water quality simulation prediction coupling model method adopts a hydrodynamic module using a nonlinear outflow algorithm, which depends on pipe network (channel) design parameters such as pipe length and slope, does not require other correction processes, and can also reflect the influence of hydraulic fluctuations on mass transfer, gas-liquid mass transfer, and sediment formation, reflecting the actual mass transfer process rate changes caused by hydraulic fluctuations.

[0057] 3. The gravity flow sewer network dynamic water quality simulation prediction coupling model method adopts a biochemical reaction kinetics construction method based on the full-plant modeling method, which can couple various complexity biochemical reaction kinetics modules as needed, can simulate and study conventional pollutants COD, N, P, etc., and can also metabolize COD, SO4 2-The generated and emitted quantity of the difficult-to-monitor network management and control substance is studied, the total emission quantity and emission hotspots are analyzed, and more effective network management and control reduction measures are evaluated.

[0058] 4. The gravity flow sewer network dynamic water quality simulation prediction coupling model method is suitable for water quality transformation simulation of a gravity flow network with more complex hydraulic conditions.

[0059] 5. The gravity flow sewer network dynamic water quality simulation prediction coupling model method is based on the full-plant model methodology and is suitable for water quality transformation process modeling of a gravity flow sewer network from the perspectives of water operation and maintenance and optimization and water planning.

[0060] The gravity flow sewer network dynamic water quality simulation prediction coupling model method is suitable for water quality transformation simulation of a gravity flow network with more complex hydraulic conditions. BRIEF DESCRIPTION OF DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0062] Figure 1For an embodiment of the present application, the flow chart of the dynamic water quality simulation prediction coupling model method of the gravity flow sewer network;

[0063] Figure 2 For an embodiment of the present application, the structural diagram of the water quality conversion model of the gravity flow sewer;

[0064] Figure 3 For an embodiment of the present application, the schematic diagram of the exchange of each phase of matter in the sewer;

[0065] Figure 4 For an embodiment of the present application, the system structure diagram of the actual gravity flow sewer built in the laboratory;

[0066] Figure 5 For an embodiment of the present application, the partial structural diagram of the gravity flow sewer water quality conversion model of the actual gravity flow sewer built in the laboratory;

[0067] Figure 6 For an embodiment of the present application, the comparison diagram of the simulated value and the measured value of the COD of the pipe effluent in the flow period of a day;

[0068] Figure 7 For an embodiment of the present application, the simulated value change diagram of the COD form conversion in the influent and effluent;

[0069] Figure 8 For an embodiment of the present application, the comparison diagram of the simulated value and the measured value of the TP of the influent and effluent;

[0070] Figure 9 For an embodiment of the present application, the comparison diagram of the simulated value and the measured value of the TKN concentration of the influent and effluent;

[0071] Figure 10 For an embodiment of the present application, the comparison diagram of the simulated value and the measured value of the pipe sediment thickness in the experimental period;

[0072] Figure 11 For an embodiment of the present application, the comparison diagram of the simulated value and the measured value of the SS concentration of the influent and effluent in the experimental period of 180 days;

[0073] Figure 12 For an embodiment of the present application, the comparison diagram of the simulated value and the measured value of the volatile acid VFA in the experimental period under the condition of having sediment;

[0074] Figure 13 For an embodiment of the present application, the comparison diagram of the simulated value and the measured value of the volatile acid VFA concentration in the experimental period under the condition of having no sediment;

[0075] Figure 14Figure 1 shows a schematic diagram of microbial activity in wastewater, sediments and biofilm in a sewer pipe in terms of consumption rates of different types of electron acceptors in an embodiment of the present application.

[0076] Figure 15 Figure 4 shows a schematic diagram of a part of a full-scale regional sewer network water quality transformation model with a tree topology for a regional sewer network in an embodiment of the present application. DETAILED DESCRIPTION

[0077] In order to make the technical solutions and advantages of the present application clearer, the specific embodiments of the present application will be further described in detail below with reference to the drawings. The various embodiments described below are only some preferred solutions of the present application, rather than all the embodiments; the various embodiments described below are intended to explain the present application, and cannot be understood as limiting the present application; any reasonable combination of the technical features defined in the various embodiments of the present application, and all other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative labor, all fall within the scope of protection of the present application.

[0078] In an embodiment, a dynamic water quality simulation and prediction coupling model method for a gravity flow sewer network is provided.

[0079] The method comprises the following steps:

[0080] a step of constructing a gravity flow sewer pipe water quality transformation model for any sewer pipe in a sewer network, wherein:

[0081] The gravity flow sewer pipe water quality transformation model comprises a hydrodynamics module, a biochemical reaction kinetics module and a mass conservation module;

[0082] The hydrodynamics module comprises a hydrodynamics expression of wastewater flow migration in a sewer pipe, and a volume change relationship expression of liquid phase, sediments, biofilm and headspace in the sewer pipe; the hydrodynamics module is used to reflect the hydrodynamics transformation relationship in the sewer pipe;

[0083] The biochemical reaction kinetics module comprises a list of pollutant state variables and a stoichiometry and kinetics matrix; the list of pollutant state variables is constructed based on unit process elements of reaction physical and biochemical transformation processes; the biochemical reaction kinetics module is used to reflect the biochemical reaction transformation relationship in the sewer pipe;

[0084] The mass conservation module is used to reflect the mass conservation relationship of pollutants in wastewater, sediments, biofilm and headspace;

[0085] a step of correcting a gravity flow sewer pipe water quality transformation model according to characteristics of an actual gravity flow sewer pipe to obtain a corrected gravity flow sewer pipe water quality transformation model;

[0086] a step of combining corrected gravity flow sewer pipe water quality transformation models of all sewer pipes into an actual regional full-scale regional sewer network water quality transformation model having a tree topology according to a structure of an actual sewer network;

[0087] a step of obtaining a water quality transformation simulation result of an actual gravity flow sewer network according to the actual regional full-scale regional sewer network water quality transformation model having a tree topology.

[0088] In addition, in an embodiment, the step of correcting a gravity flow sewer pipe water quality transformation model according to characteristics of an actual gravity flow sewer network to obtain a corrected gravity flow sewer pipe water quality transformation model includes the following steps:

[0089] a step of performing parameter sensitivity analysis on the gravity flow sewer pipe water quality transformation model to obtain a parameter to be corrected;

[0090] a step of obtaining characteristics of an actual gravity flow sewer pipe;

[0091] a step of correcting the parameter to be corrected of the gravity flow sewer pipe water quality transformation model according to characteristics of an actual gravity flow sewer pipe to obtain a corrected gravity flow sewer pipe water quality transformation model.

[0092] In the embodiment, the gravity flow sewer pipe water quality transformation model can be implemented on most simulation platforms, and via correction according to characteristics of an actual gravity flow sewer pipe, accurate simulation of water quality transformation of most gravity flow sewer pipes can be achieved.

[0093] In the embodiment, the unit process element is an element (such as carbon, nitrogen, oxygen, phosphorus, hydrogen, etc.) participating in physical (including hydrodynamic changes, three-phase changes) and biochemical (i.e., biochemical reaction kinetics) transformation processes in a gravity flow sewer pipe. The gravity flow sewer pipe water quality transformation model is constructed based on the unit process element, which can comprehensively describe the dynamic behavior of the entire sewage (sewer) pipe.

[0094] In the embodiment, the method is based on a full-plant model construction methodology to construct a gravity flow sewer pipe water quality transformation model from the perspective of water planning and water operation maintenance and optimization, comprehensively considers hydrodynamic changes and biochemical reaction kinetics in sewage and drainage (network / pipes), and can comprehensively and accurately simulate and predict gravity flow networks (pipes) with more complex hydraulic conditions.

[0095] In the embodiment, the corrected gravity flow sewer water quality transformation model is constructed based on the full-plant modeling methodology, and is used to obtain the distribution and transformation relationship of the pollutants (indicators) in the sewer network.

[0096] In the embodiment, the corrected gravity flow sewer water quality transformation model helps the water management personnel to analyze the spatial and temporal distribution and transformation direction of the pollutants in the sewer network through the node water quality monitoring data in the sewer network, and provides a simulation tool and accurate data support for the daily operation of the sewer network.

[0097] In the embodiment, the corrected gravity flow sewer water quality transformation model can be used as a tool for predicting the influent water quality of the sewage plant in the planning stage. The planner can use the model to perform scenario prediction on the influent water quality of the sewage plant.

[0098] In addition, in an embodiment, the step of combining the corrected gravity flow sewer water quality transformation models of all the sewers into an actual regional full-scale regional sewer network water quality transformation model with a tree topology according to the structure of the actual sewer network comprises the following steps:

[0099] Obtaining the connection relationship of each sewer of the actual gravity flow sewer network;

[0100] Taking the corrected gravity flow sewer water quality transformation model of each sewer as a unit model;

[0101] According to the connection relationship of the actual gravity flow sewer network, the unit models are constructed into an actual regional full-scale regional sewer network water quality transformation model with a tree topology.

[0102] It should be noted that the sewer network is composed of multiple sewers. The gravity flow sewer water quality transformation model corresponds to the sewer, and the actual regional full-scale regional sewer network water quality transformation model with a tree topology corresponds to the sewer network.

[0103] In addition, in an embodiment, the construction method of the biochemical reaction kinetics module is as follows:

[0104] Using the full-plant modeling method, a general compatible physical and biochemical conversion process is selected based on the gravity flow sewer to obtain all unit process elements;

[0105] According to the obtained all unit process elements, a list of pollutant state variables (referred to as LT) is created, and a stoichiometry and kinetics matrix (referred to as Gujer matrix) of the pollutant state variables therein is defined.

[0106] In this embodiment, the unit process elements are obtained by selecting general compatible process conversion, which belongs to the "conversion-based" modeling method. Traditional modeling methods are mostly "process-based" modeling methods. Compared with the traditional "process-based" method, this "conversion-based" method does not need to develop a specific converter to connect the obtained unit process model, and helps to build an integrated plant network model.

[0107] In this embodiment, by defining stoichiometry, redundancy in component definition can be avoided, and continuity of all converted element mass (expressed as C, N, O, P, H and S) and charge contained in the LT can be ensured.

[0108] In this embodiment, the list of pollutant state variables and its stoichiometry and kinetics matrix can be improved based on the activated sludge series model (ASM) such as ASM1, ASM2d, ASM3, etc.

[0109] In addition, in an embodiment, the biochemical reaction kinetics module includes sulfate reduction metabolism to explain the COD loss consumed by sulfate-reducing bacteria metabolic growth for sewer systems containing certain sulfate.

[0110] It should be noted that the sewer network is a biological reactor with aerobic-anoxic-anaerobic conditions, and biological conversion of C, N and P pollutants occurs inside. Metabolic sulfate bacteria SRB often exist in the sewer environment. The environment in the sewer network often supports the coexistence of sulfate-reducing bacteria (SRB) and methanogens (MA), but MA and SRB have common metabolic substrate volatile acid (VFA), and the two organisms have a competitive relationship for carbon sources. SRB usually has a stronger volatile acid uptake rate, so it is more competitive than MA. When there is a high concentration of sulfate, methanogenesis is usually low. The biochemical reaction kinetics module includes sulfate reduction metabolism to explain the carbon source COD loss consumed by hydrogen sulfide generation in sewer systems containing certain sulfate, to consider the impact of SRB on MA, and to more comprehensively and accurately model the gravity flow sewer network.

[0111] In addition, in an embodiment, the given components in the stoichiometry act as source-sink or compensation terms to explain the imbalance of carbon, nitrogen, oxygen, phosphorus, hydrogen and charge.

[0112] In addition, in an embodiment, the kinetics matrix contains penetration and inhibition terms in order to express the activity of microorganisms under different environmental conditions (i.e. aerobic, anoxic and anaerobic) in the sewer network.

[0113] In this embodiment, Tables 1 to 3 show a part of the construction of LT, and the symbolization rule of LT is the standardization symbolization recommended by IWA.

[0114] In this embodiment, S in the table header of Table 2 and Table 2 i represents the soluble component i, X i represents the particulate (microorganism) component i, such as S VFA represents the soluble substrate volatile acid, X OHO represents the heterotrophic bacteria.

[0115] In this embodiment, the values in the tables of Tables 1 to 3 represent stoichiometric coefficients, and the values without numbers represent 0.

[0116] In this embodiment, Table 4 is a part of the stoichiometric (matrix) and the parameter value of the maximum specific growth rate of microorganisms (i.e., the kinetic matrix) in the model.

[0117] Table 1 Stoichiometric matrix of AMETO and HMETO bacteria

[0118]

[0119] Note that, in Table 1, S i represents the soluble substance i, X i represents the particulate (microorganism) substance i, such as S B is a soluble fast biodegradable substance, S VFA is a soluble volatile fatty acid, X B is a particulate slow biodegradable substance, X E is a particulate endogenous degradation substance, X E，ana is a particulate endogenous degradation substance generated under anaerobic conditions, X N,B is biodegradable organic nitrogen, X P,B is biodegradable organic phosphorus, X AMETO is AMETO bacteria, X HMETO is HMETO bacteria. The remaining substances are expressed by chemical formulas, such as S NHx represents soluble ammonia, S CH4 represents soluble CH4, etc.

[0120] Table 2 Stoichiometric matrix of OHO

[0121]

[0122] Table 2 (continued)

[0123]

[0124] Note that, in Table 2, the substances not described in the table header have the same meanings as those in Table 1. XOHO represents general heterotrophic bacteria, S NO2 represents dissolved nitrite, S NO3 represents dissolved nitrate. It is noted that, for the sake of brevity, parameters and kinetic matrices not mentioned can be found at http: / / wiki.dynamita.com:3000 / en / process_model.

[0125] Table 2 is extended in Table 2a, which includes components such as nitrate.

[0126] Table 3 Methanogenic bacteria, hydrolysis process and OHO metabolic reaction rate expressions

[0127]

[0128] Table 3a

[0129]

[0130] It is noted that Table 3 Methanogenic bacteria, hydrolysis process and OHO metabolic reaction rate expressions are kinetic matrices.

[0131] It is noted that, for the sake of brevity, parameters and kinetic matrices not mentioned can be found at http: / / wiki.dynamita.com:3000 / en / process_model.

[0132] Table 4 Partial parameter value references

[0133]

[0134] Table 4a

[0135]

[0136] In addition, in an embodiment, the hydrodynamics module comprises hydrodynamic expressions of the migration of the wastewater in the sewer and volume change relations of the liquid phase, the sediment, the biofilm and the headspace in the sewer; the hydrodynamics module is used for hydrodynamic conversion relations in the sewer;

[0137]

[0138] wherein, ρin is the influent wastewater density, in g / m 3 ρout is the effluent wastewater density, in g / m 3 V is the wastewater volume in the sewer unit; Qin is the influent flow rate, in m 3 / s;​​​ is the outflow, unit m 3 / s;

[0139] Assuming that the density of sewage is irrelevant to the concentration of pollutants in sewage, then:

[0140] ;

[0141] In this embodiment, unit g / m 3 ; unit g / m 3 ; unit m 3 / s; unit m 3 / s; unit g / m 3 ; unit g / m 3 .

[0142] In this embodiment, let be the concentration of pollutant i in the influent, be the concentration of pollutant i in the effluent; assuming that the density of sewage is irrelevant to the concentration of pollutants in sewage, that is, is irrelevant to , is irrelevant to , that is, the density is constant.

[0143] In this embodiment, the outflow is a function of the water level in the pipeline, and is obtained by using a nonlinear outflow algorithm. The nonlinear outflow algorithm introduces the parameters such as the water depth of the pipe network, the fullness, and the wet perimeter as intermediate variables to calculate the relationship between the current sewage volume in the pipe network and the outflow of the pipeline.

[0144] In this embodiment, it can be seen from the above expression that V liquid is a state variable and C (the concentration of pollutants) is solved at the same time, realizing the synchronous calculation of hydraulics and pollutant biochemical reaction kinetics.

[0145] In this embodiment, the obtained parameters such as the water depth in the pipeline and the wet perimeter can also be used to calculate the contact mass transfer area of sewage and sediment and biofilm; the same calculation method can also be used to calculate the height of the sediment.

[0146] ;

[0147] ;

[0148] ;

[0149] ;

[0150] ;

[0151] ;

[0152] ;

[0153] ;

[0154] ;

[0155] ;

[0156] ;

[0157] ;

[0158] ;

[0159] wherein, is the water surface width when the pipe is completely full; is the water surface depth when the pipe is completely full; is the fullness; is the water surface width in the pipe; is the water surface depth in the pipe; is the half central angle; is the pipe diameter; is the relative wet perimeter; is the hydraulic radius; is the hydraulic radius when completely full; is the relative flow area; is the relative hydraulic radius; is the wet perimeter; is the flow section area of the pipe; is the flow section area when the pipe is full; is the pipe slope; is the outflow flow of the pipe network (channel); is the flow when the pipe network (channel) is full; is the Chezy coefficient;

[0160] The following is derived:

[0161] ;

[0162] The formula cannot be solved analytically, and Newton's method is used for numerical solution:

[0163] ;

[0164] ;

[0165] ;

[0166] Given an initial estimate of ξ ini , iteration is performed so that τ converges within a given error value; after solving for ξ and τ, the rest of the hydraulic parameters can be obtained, including semi-central angle φ, wet perimeter P, and other parameters.

[0167] In this embodiment, is in m; is in m; is dimensionless; is in m; is in m; is in rad; is in m; is dimensionless; is in m; is in m; is dimensionless; is dimensionless; is in m; is in m 2 ; is in m 2 ; is in m / km; is in m 3 / s; is in m 3 / s; is in m 0.5 / s.

[0168] The hydraulic calculation affects the volume of each phase, which is used for subsequent calculations of the contact area with the biofilm and the gas-liquid mass transfer coefficient, etc.:

[0169] ;

[0170] ;

[0171] ;

[0172] ;

[0173] ;

[0174] ;

[0175] ;

[0176] Wherein, Min function is to find the minimum value in the parentheses; Max function is to find the maximum value in the parentheses; is the water depth in the pipe segment; is the gas-liquid contact area; is the biofilm contact area with sewage; is the biofilm area excluding the sediment part; is the actual sewage contact area with the pipe wall; is the average flow velocity of the pipe network over the flow section; is the water depth in the pipe, m; is the pipe length, m; is the corresponding half-full angle under the design fullness, rad; is the corresponding half-full angle of the sediment, rad; is the half-full angle of the sewage, rad; is the biofilm volume, m 3 ; is the biofilm thickness, m.

[0177] In the present embodiment, has the unit of m; has the unit of m 2 ; has the unit of m 2 ; has the unit of m 2 ; has the unit of m 2 ; has the unit of m / s;

[0178] The hydraulic calculation of the sediment is based on the flux into the sediment layer, combined with the biochemical reaction kinetics module and the mass conservation module of the sediment layer material conservation relationship, to calculate the TSS concentration of the sediment layer, and the volume change of the sediment is calculated according to the following formula:

[0179] ;

[0180] Wherein, is the sediment volume; is the TSS concentration in the sediment; is the TSS concentration in the sediment under steady-state conditions.

[0181] In the present embodiment, has the unit of m 3 ; has the unit of g / m 3 ; has the unit of g / m 3 .

[0182] It should be noted that the mass conservation relationship of each phase of the pollutants involves the mass transfer exchange relationship between each phase. The mass transfer exchange relationship includes the deposition, resuspension and diffusion of the pollutants in the wastewater to the sediment, the adsorption, desorption and diffusion of the pollutants in the wastewater to the biofilm layer, and the gas transfer process between the wastewater, the sediment, the biofilm and the headspace air. The detailed calculation relationship of each process is as follows:

[0183] In addition, in an embodiment, the mass conservation relationship of the pollutants in the wastewater is expressed by using the basic mass conservation equation of the pollutants i in the pipe unit as follows:

[0184]

[0185]

[0186] wherein, is the concentration of the pollutant i in the wastewater in the pipe unit; is the wastewater volume in the pipe unit; is the influent flow rate; is the effluent flow rate; is the concentration of the pollutant i in the influent; is the concentration of the pollutant i in the effluent; is the total reaction rate of the pollutant i in the pipe, including the mass transfer and biochemical conversion. is the rate of the pollutant i deposited from the wastewater to the sediment; is the resuspension rate of the pollutant i in the sediment; is the diffusion rate of the pollutant in the pipe unit from the wastewater to the sediment; is the rate of the pollutant i adsorbed from the wastewater to the biofilm; is the desorption rate of the pollutant i in the biofilm; is the diffusion rate of the pollutant in the pipe unit from the wastewater to the biofilm; is the gas-liquid mass transfer rate; is the biochemical reaction rate of the pollutant i in the liquid phase;

[0187] In the embodiment, has the unit of g / m 3 ; has the unit of m 3 ; has the unit of m 3 / s; has the unit of m 3 / s; has the unit of g / m 3 ; has the unit of g / m 3 ; ​​g / (m 3 d).

[0188] Assuming that the condition in any pipe segment is well-mixed, there is no concentration gradient, and C eff = C i , then:

[0189] .

[0190] In this embodiment, Q eff is calculated according to the foregoing, and Q inf is an input parameter. R i is the reaction phase, including the exchange of substances between the sewage and each phase and the biochemical reaction rate in the sewage phase.

[0191] In addition, in an embodiment, the mass conservation relationship of the pollutants in the sediment is expressed by the basic mass conservation equation of the pollutant i in the sediment layer:

[0192] ;

[0193] wherein, is the concentration of the pollutant i in the sediment layer in the pipe unit; is the sediment volume in the pipe unit; is the rate at which the pollutant i is deposited from the sewage to the sediment; is the rate at which the pollutant i in the sediment is washed and resuspended; is the rate at which the pollutant in the pipe unit diffuses from the sewage to the sediment; is the rate at which the pollutant i in the sediment is boiled and escaped; is the biochemical reaction rate of the pollutant i in the sediment.

[0194] In this embodiment, the unit of which is g / m 3 ; the unit of which is m 3 ; the unit of which is g / d; the unit of which is g / d; the unit of which is g / d; the unit of which is g / d; the unit of which is g / d.

[0195] Wherein, the calculation of each flux is as follows:

[0196] ;

[0197] ;

[0198] ;

[0199] ;

[0200] wherein, is the deposition rate of the pollutant i; is the resuspension rate of the deposit; is the diffusion coefficient of the pollutant i; is the thickness of the deposit boundary layer; is the permeation concentration of the gaseous form G.SV of the pollutant i at the surface; is the saturation of the gas in the bubble overflow of the deposit and biofilm; is the volumetric mass transfer coefficient of the gaseous form G.SV of the pollutant i in liquid at the surface under standard conditions (clear water).

[0201] In the present embodiment, is expressed in d -1 ; is expressed in d -1 ; is expressed in m 2 ·d -1 ; is expressed in m 2 ; is expressed in g / m 3 ; is dimensionless; is expressed in d -1 .

[0202] In addition, in an embodiment, the material balance of the pollutant in the biofilm is expressed by the basic material balance equation of the pollutant i in the biofilm layer:

[0203] ;

[0204] wherein, is the concentration of the pollutant i in the biofilm layer in the pipe unit; is the biofilm volume in the pipe unit; is the rate of adsorption of the pollutant i from the wastewater to the biofilm; is the desorption rate of the pollutant i in the biofilm; is the diffusion rate of the pollutant from the wastewater to the biofilm in the pipe unit; is the bubble overflow rate of the pollutant i in the biofilm; is the biochemical reaction rate of the pollutant i in the biofilm;

[0205] The expression of adsorption and diffusion between the biofilm layer and the water phase:

[0206] ;

[0207] ;

[0208] ;

[0209] ;

[0210] wherein, is the maximum adsorption rate of the biofilm; is the contact area of the biofilm with the wastewater; is the detachment rate of the biofilm; is the concentration of TSS in the biofilm; is the concentration of TSS in the biofilm under steady state conditions; is the thickness of the biofilm; is the empirical enhancement factor of the diffusion rate in the biofilm; is the ebullition emission rate of the pollutant i in the biofilm, ( ) means ebullition; is the biochemical reaction rate of the pollutant i in the sediment.

[0211] In the present embodiment, the biofilm and the headspace layer are simplified to balance the calculation burden. The biofilm layer is a one-dimensional single layer with a fixed thickness. The headspace layer is also a completely mixed layer with a fixed volume.

[0212] In the present embodiment, has the unit of g / m 3 ; has the unit of m 3 ; has the unit of g / d;

[0213] has the unit of g / d; has the unit of g / d; has the unit of g / d; has the unit of g / d.

[0214] In the present embodiment, has the unit of m 2 / d; has the unit of m 2 ; has the unit of g / d;

[0215] has the unit of g / m 3 ; has the unit of g / m 3 ; has the unit of m; has the unit of g / d; in g / d; in g / d.

[0216] In addition, in an embodiment, the mass conservation of the pollutants in the headspace is represented by the basic mass conservation equation of the pollutant i in the headspace:

[0217]

[0218] where, Ci is the concentration of the pollutant i in the headspace gas layer in the pipe element; Vh is the headspace volume in the pipe element; Qin is the gas flow into the headspace; Cin is the concentration of the pollutant i in the gas entering the headspace layer; Qout is the gas flow out of the pipe element; Klh is the mass transfer rate between the headspace and other phases.

[0219] In this embodiment, in g / m 3 ; in m 3 ; in m 3 / d;

[0220] in g / m 3 ; in m 3 / d; in g / d.

[0221] In addition, in an embodiment, assuming that the flow of the incoming and outgoing gas is equal, assuming that the headspace volume is constant (to simplify the calculation), Q gas,inf = Q gas,eff , and the gas is completely mixed, then:

[0222]

[0223] where, KLa is the gas-liquid mass transfer rate at the wastewater and headspace interface.

[0224] In this embodiment, in g / d.

[0225] In addition, in an embodiment, the mass transfer process between the gas in the headspace of the gravity flow sewer network and other elements includes gas-liquid mass transfer and direct gas boiling escape; the gas-liquid mass transfer is calculated by KLa (gas-liquid interface volume mass transfer coefficient, d -1 ​​The mass transfer coefficients of gases other than oxygen are obtained from the concentration of saturated dissolved gases and the concentration of KLa. KLa is obtained based on the current hydraulic conditions of the pipeline network. The mass transfer coefficients of gases other than oxygen are obtained by comparing them with the gas-liquid interface volumetric mass transfer coefficient of KLaO2 (oxygen, d). -1 The ratio correction was obtained;

[0226] The method for calculating evaporation has been explained in the previous sections on sediments and biofilms.

[0227] The rate of a gas-liquid mass transfer process controlled by mass transfer is:

[0228] ;

[0229] ;

[0230] ;

[0231] ;

[0232] ;

[0233] ;

[0234] ;

[0235] ;

[0236] ;

[0237] ;

[0238] in, This represents the concentration of dissolved gaseous substance G.SV in wastewater. For Froude number; The average hydraulic depth; Let GSV be the gas-liquid interface volumetric mass transfer coefficient. It is the alpha factor; This is the temperature correction factor for KLA; The temperature of the wastewater; Wave factor; For the β factor; This refers to the partial pressure of gas G.SV at the surface of the enterprise under standard conditions; This represents the molar concentration of gas G.SV in the headspace. This is the sum of the molar concentrations of all gases (G.SV) in the headspace. Atmospheric pressure under standard conditions; The shear rate on the pipe wall; This represents the specific contact area between the gas phase and the liquid phase on the surface. This is the acceleration due to gravity.

[0239] In this embodiment, The unit is g / m 3 ; Dimensionless; The unit is m; The unit is d -1 ; Dimensionless; Dimensionless; The unit is ℃; Dimensionless; Dimensionless; The unit is Pa; The unit is mol / m 3 ; The unit is mol / m 3 ; The unit is Pa; The unit is m / s; The unit is m 2 / m 3 ; The unit is m / s 2 .

[0240] In another embodiment, the calibration (or input setting) of the gravity flow drainage pipeline water quality transformation model based on the characteristics of the actual gravity flow drainage network includes calibration (or input setting) of pipeline parameters, influent pollutant load parameters, and gas phase input parameters:

[0241] The pipeline parameters, influent pollutant load parameters, and gas phase input parameters are determined based on the actual gravity flow drainage network.

[0242] In this embodiment, actual gravity flow drainage pipe network is surveyed, and its pipe parameters, influent pollutant load parameters, and gaseous pollutant concentration are collected for parameter input and setting.

[0243] In this embodiment, Tables 5 to 8 provide reference values ​​for influent pollutant load parameters, gas phase input parameters, and pipeline parameters, respectively. In actual cases, actual measurements need to be taken based on the characteristics of the actual gravity flow pipeline network for receiving sewage.

[0244] Table 5 shows the reference values ​​for the influent pollutant concentration parameters in the influent pollutant load parameters.

[0245] Table 5. Examples of reference values ​​for influent pollutant concentration parameters

[0246]

[0247] In addition to the input water pollutant concentration parameters, the input water (or input water state variable) component parameters in the input water pollutant load parameters also need to be set to correctly divide the input water components.

[0248] The input water component parameters can be determined by experimental analysis of the input water of the actual gravity flow sewer network.

[0249] Table 6 shows the reference values of the input water component parameters.

[0250] Table 6 shows the reference values of the input water component parameters.

[0251]

[0252] The gas phase input parameters include the total gas flow in the input gas and the gas volume percentage, or the pipe unit input gas parameters.

[0253] Table 7 shows the reference values of the gas phase input parameter settings.

[0254] Table 7 shows the reference values of the gas phase input parameter settings.

[0255]

[0256] The pipe length L, pipe diameter D, slope, and other data in the pipe parameters should be obtained by actual survey of the actual gravity flow sewer network or according to design data.

[0257] Table 8 shows the reference values of the input settings of the pipe parameters.

[0258] Table 8 shows the reference values of the input settings of the pipe parameters.

[0259]

[0260] In addition, in an embodiment, the correction of the gravity flow sewer pipe water quality transformation model according to the characteristics of the actual gravity flow sewer network also includes correction of the parameters in the biochemical reaction kinetics module, the hydrology module, and the mass conservation module.

[0261] In this embodiment, the parameters in the biochemical reaction kinetics module, the hydrology module, and the mass conservation module are the pipe phase mass transfer process transformation rate parameters, which affect the biochemical reaction conversion relationship in the biochemical reaction kinetics module, the hydrology conversion relationship in the hydrology module, and the mass conservation relationship in the mass conservation module.

[0262] In the embodiment, the parameters in the biochemical reaction kinetics module, the hydrodynamic module and the mass conservation module include biochemical kinetics constants, sediment mass transfer process parameters, sediment rate related parameters, biofilm characteristics parameters, biofilm mass transfer process parameters, gas phase parameters (or pipe unit gas phase parameters) and auxiliary parameters.

[0263] In the embodiment, Table 9 to Table 13 respectively give reference values of the sediment mass transfer process parameters and the sediment rate related parameters, the biofilm characteristics parameters, the biofilm mass transfer process parameters, the gas phase parameters and the auxiliary parameters, which can be used as default values for parameter correction when the gravity flow sewer water quality transformation model is constructed. By collecting data of the actual gravity flow sewer network, some parameters can be modified and corrected, so that the simulation results of the model are consistent with the actual measured results of the pollutants in the gravity flow sewer network.

[0264] Table 9 is the reference value of the sediment process parameters in the hydrodynamic module, such as rate_settling representing the settling rate of particulate matter.

[0265] Table 9 Reference value example of sediment mass transfer process parameters and sediment rate related parameters

[0266]

[0267] Table 10 and Table 11 are biofilm related parameters.

[0268] Table 10 defines the thickness of the biofilm and the specific mass of the biofilm, which can be obtained by measuring the biofilm on the wall of the actual gravity flow sewer network.

[0269] Table 10 Reference value example of biofilm characteristics parameters

[0270]

[0271] Table 11 defines the mass transfer coefficient related to the biofilm, such as r attach is the biofilm adsorption rate.

[0272] Table 11 Reference value example of biofilm mass transfer process parameters

[0273]

[0274] Table 12 is the reference value of the pipe unit gas phase parameters, which determines the headspace gas temperature according to the actual monitoring data. If there is no measured data, the headspace gas temperature can be considered to be consistent with the sewage temperature.

[0275] Table 12 Reference value example of gas phase parameters

[0276]

[0277] Table 13 is a reference value example of auxiliary parameters, which is used to assist the calculation of the calculation formula of the aforementioned partial model formula, and does not need to be changed in most cases.

[0278] Table 13 Reference value example of auxiliary parameters

[0279]

[0280] In addition, in an embodiment, the step of correcting the gravity flow sewer water quality transformation model according to the characteristics of the actual gravity flow sewer to obtain a corrected gravity flow sewer water quality transformation model includes the following steps:

[0281] The step of performing sensitivity analysis on the gravity flow sewer water quality transformation model to determine the parameters to be corrected;

[0282] The step of collecting characteristic data of the actual gravity flow sewer according to the parameters to be corrected;

[0283] The step of correcting the parameters to be corrected according to the collected characteristic data of the actual gravity flow sewer.

[0284] In the embodiment, the basic principle of the sensitivity analysis (Sensitivity Analysis) is to determine which input variables are most critical to the model or decision-making process by evaluating the impact of changes in input variables on output results.

[0285] In the embodiment, the simulation method can accurately simulate the physical-chemical-biological transformation process occurring in the sewer by incorporating a comprehensive sewer hydraulics module and considering the generation of sediments and the interactive mass transfer process of the sewage-sediment-biofilm-headspace multiphase system. It can be used for sewer network water quality management and operation optimization research.

[0286] In the embodiment, the simulation method is corrected based on the collected data of the actual gravity flow sewer on the basis of the gravity flow sewer water quality transformation model, which can more accurately simulate.

[0287] In the embodiment, the corrected gravity flow sewer water quality transformation model and its modeling process have wide applicability and operability, and can be implemented on most simulation platforms, providing support for smart operation of urban water sewage network.

[0288] In this embodiment, the simulation method can be applied to obtain the spatial and temporal transformation analysis of pollutants in the regional drainage pipeline. By analyzing and modeling the COD, N, P and other conventional pollutant indicators of the nodes in the constructed regional drainage pipeline (network) model, data support can be provided for daily maintenance and optimized operation without increasing special monitoring sites and monitoring equipment.

[0289] In addition, in an embodiment, a specific embodiment is provided, in which the aforementioned simulation method is implemented in SUMO software.

[0290] It should be noted that the implementation in SUMO software is only a reference implementation, and the aforementioned simulation method can also be implemented in other software or using open source programming languages such as C language.

[0291] Taking a laboratory-built actual gravity flow drainage pipeline as an example, the model construction process and the simulation results of the model output are demonstrated.

[0292] The laboratory-built actual gravity flow drainage pipeline is a gravity flow pilot pipeline with a length of 32 m and a pipe diameter of 200 mm, which mainly includes a circulating water tank (for water inlet), a regulating valve (for flow regulation), and a 32 m long pipeline main body.

[0293] The system structure of the laboratory-built actual gravity flow drainage pipeline is shown in Figure 4 The figure shows: 1 is municipal sewage; 2 is a circulating water tank; 3 is a submersible pump; 4 is a regulating valve; 5 is a return pipe; 6 is a rotor flowmeter; 7 is an inlet pipe; 8 is an exhaust valve; 9 is an organic glass pipeline; 10 is a manhole; 11 is a water outlet valve; 12 is drainage; 13 is a cooling outer cylinder; 14 is an inspection port; 15 is an overflow weir; and 16 is a sampling port.

[0294] Using SUMO software, a gravity flow drainage pipeline water quality transformation model is constructed according to the structure design of the laboratory-built actual gravity flow drainage pipeline.

[0295] Among them, Figure 5 is a partial structure diagram of the gravity flow drainage pipeline water quality transformation model. As shown in the figure, the Gravity sewers, i.e., the gravity flow drainage pipeline water quality transformation model, is used to simulate the entire organic glass pipeline 9; the effluent unit is used to simulate the drainage port 12; the laboratory-built actual gravity flow drainage pipeline continuously pumps sewage into the pipeline through a circulating water tank, so in the gravity flow drainage pipeline water quality transformation model, the influent unit represents the municipal sewage inlet in the system, and the equalization unit simulates the circulating water tank 2; the equalization unit includes a pumping outlet that can adjust the water outlet flow to simulate the function of the regulating valve 4.

[0296] It should be noted that, compared with the prior art, the gravity flow drainage pipe network dynamic water quality simulation prediction coupling model method constructs a hydraulic module, which calculates the hydraulic state of the pipeline by coupling the nonlinear outflow algorithm, and defines the mass transfer relationship of sewage, sediment, biofilm, headspace and volume change of each phase in the pipeline in the subsequent mass transfer process, while the previous biochemical reaction kinetics model is applicable in each phase. Therefore, the complex pollutant conversion relationship can be calculated.

[0297] Compared with the conceptual model adopted by the traditional method, the hydraulic module can rely on the existing design data and does not need to be complicated to correct the flow relationship, and solves the problem that the conceptual model cannot simulate the influence of hydraulic change on water quality conversion.

[0298] Compared with the fluid mechanics model adopted by the traditional method, the hydraulic module balances the calculation load and can couple a relatively complex biochemical kinetics model, which is the SUMO2S model in this example.

[0299] It should be noted that, compared with the prior art, the gravity flow drainage pipe network dynamic water quality simulation prediction coupling model method defines the conservation of mass and hydraulic change in the entire drainage pipeline, and constructs a framework methodology for simulating water quality conversion in the gravity flow drainage pipeline, which has a creative contribution.

[0300] It should be noted that, compared with the prior art, the gravity flow drainage pipe network dynamic water quality simulation prediction coupling model method solves the problem that the previous pollutant conversion simulation process in the gravity flow drainage pipe network (way) is not well considered (such as not considering the aerobic-anaerobic-anoxic process, sulfate, etc.), which is solved by a reasonable LT methodology definition, and a reasonable kinetic matrix is constructed (in the embodiment, the SUMO2S model is used as an example to demonstrate, but it is not limited to the SUMO2S model).

[0301] The SUMO2S model comprehensively considers the following processes of microorganisms in the pipe network (way) under different environments (aerobic, anoxic and anaerobic conditions): hydrolysis, fermentation, anaerobic digestion, sulfur metabolism and chemical cycle, COD removal, two-step nitrification and denitrification, biological phosphorus removal, temperature sensitivity of microbial activity, chemical precipitation, pH shift and other processes.

[0302] The chemical equilibrium process includes: precipitation of various metal hydroxides and carbonates (such as iron salt addition for chemical phosphorus removal). Calculation of pH chemical equilibrium and gas-liquid equilibrium with CO2 and CH4 and other gases.

[0303] The biochemical reaction kinetics module based on the SUMO2S model has 88 state variables and 127 dynamic processes, covering hydrolysis, fermentation, two-step nitrification / denitrification, COD removal, enhanced biological phosphorus removal, anaerobic methane production, etc.

[0304] SUMO2S model considers the following processes and representative microorganisms and metabolic processes: general heterotroph X OHO : removal of BOD under aerobic conditions, fermentation under anaerobic conditions, carbon storage organism X CASTO : process simulates the behavior of phosphorus accumulating organisms (X PAO ) and glycogen accumulating organisms (X GAO ), the biochemical transformation processes of nitrogen consider ammonia oxidizing bacteria (X AOB ) oxidizing ammonium ions S NHX to nitrite (S NO2 ) under aerobic conditions, nitrite oxidizing bacteria (X NOB ) oxidizing nitrite S NO2 to nitrate (S NO3 ) under aerobic conditions, denitrification processes consider X OHO denitrifying under anoxic conditions using nitrate and nitrite as electron acceptors.

[0305] The biochemical transformation processes of phosphorus consider competition processes between X GAO and X PAO : storage of volatile fatty acids (S VFA ), production of glycogen (X GAO ) by X GLY or release of phosphate to produce polyhydroxyalkanoates (X PAO ) by X PHA under anaerobic conditions, consumption of readily biodegradable substrate (S B ) by X PAO under anaerobic conditions, storage of phosphate by X PHA under aerobic conditions by consuming stored X AMETO , the methanogenic processes consider two types of methanogens, acidotrophic methanogens X HMETO and hydrogenotrophic methanogens X VFA , producing methane from S H2 and dissolved hydrogen (S 2- ) under anaerobic conditions, respectively. The sulfur related biochemical transformation processes consider three different valence states of sulfur as state variables: sulfate (SO4 SOO ), elemental sulfur (S°) and hydrogen sulfide (H2S) and three microorganisms X ASRO (sulfur oxidizing bacteria), X HSRO (sulfate reducing bacteria with volatile acids as substrate), X 3 (sulfate reducing bacteria with hydrogen as substrate) simulate the sulfur cycle in sewer networks, including sulfate reduction, sulfide bio-oxidation and chemical oxidation and the interactions of the sulfur cycle with the phosphorus and iron cycles.

[0306] The change of gas phase matter needs to be considered, make sure the option "Calculate gas phase concentrations" is selected in the model "Gas Phase" setting, i.e. the concentrations of gas phase are always calculated. Select whether the pH is calculated or not according to the need, the calculation of pH will increase the calculation load, select the appropriate pH calculation mode according to the simulation accuracy requirement and the purpose of the model. Do not calculate the pH, i.e. the pH is always a fixed value.

[0307] According to the characteristics of the actual gravity flow drainage pipeline, the gravity flow drainage pipeline water quality transformation model is corrected, and the corrected gravity flow drainage pipeline water quality transformation model is obtained:

[0308] According to the (physical) size parameters of the actual gravity flow drainage pipeline built in the laboratory, the pipeline parameters are input.

[0309] The pipeline parameters include circulating water tank (capacity, pumping flow and other physical structures) parameters and gravity flow drainage pipeline parameters.

[0310] Table 14 is the circulating water tank parameter setting, and the default value provided by the SUMO software is used for the unexplained value.

[0311] Table 14 Circulating water tank parameter setting

[0312]

[0313] Table 15 is the gravity flow drainage pipeline parameter setting.

[0314] Table 15 Gravity flow drainage pipeline parameter setting

[0315]

[0316] According to the water quality data of the actual gravity flow drainage pipeline built in the laboratory, the influent pollutant load parameters are set.

[0317] Among them, the influent pollutant load parameters include influent pollutant concentration parameters and influent pollutant component parameters.

[0318] Table 16 is the influent pollutant concentration parameter setting.

[0319] Table 16 Influent pollutant concentration setting

[0320]

[0321] Table 17 is the influent pollutant component parameter input setting.

[0322] Table 17 Influent pollutant component setting

[0323]

[0324] The gas phase input parameters were set: as the pipeline as a whole was sealed, in order to ensure the stability of the numerical simulation, a small air flow was given, as shown in Table 18, the flow rate of the inlet air was 0.04 m 3 / d at NTP.

[0325] Table 18 Setting of gas phase input parameters (gas flow input)

[0326]

[0327] The parameters in the biochemical reaction kinetics module, the hydraulic module and the mass conservation module were set.

[0328] Among them, according to the measured COD, N, P, CH4, SO4 2- degradation in the effluent indicators of the actual gravity flow drainage pipeline built in the laboratory, the parameters of the biochemical reaction kinetics module were corrected, so that the predicted value of the model was close to the measured value.

[0329] Table 19 is the corrected value of the biochemical kinetics constant.

[0330] Table 19 Corrected value of part of the biochemical kinetics constant

[0331]

[0332] Table 20 is the corrected sediment and biofilm mass transfer process parameters.

[0333] Table 20 Corrected sediment and biofilm mass transfer process parameters

[0334]

[0335] According to the water quality data before and after treatment, the sediment rate related parameters were corrected.

[0336] Table 21 is the corrected sediment rate related parameters.

[0337] Table 21 Corrected sediment rate related parameters

[0338]

[0339] The corrected gravity flow drainage pipeline water quality conversion model was used for simulation prediction, and the simulation results were compared with the measured results of the actual gravity flow drainage pipeline built in the laboratory. The comparison results are shown in Figures 6 to 14 Fig. 1, where the green points represent the measured values, and the blue curves represent the simulation values.

[0340] Figure 6The COD simulation value of the pipe water outflow in a day is compared with the measured value. As can be seen from the figure, the simulation prediction value of the model is more consistent with the actual measured value, the COD simulation value decreases from 543 mg / L to 378 mg / L, and the degradation amount is 165 mg / L, which is close to the actual degradation amount (168 mg / L). The actual degradation amount of the dissolved state is 58 mg / L, and the simulation value is 40 mg / L. The actual degradation amount of the particulate COD is 110 mg / L, and the simulation degradation amount is 124 mg / L.

[0341] Figure 7 The simulation value change of the COD form conversion in the influent and effluent (i.e. the TCOD, SCOD and particulate COD simulation value change of the influent and effluent) is shown in the figure. As can be seen from the figure, the value of the particulate COD decreases from 244 mg / L to 200 mg / L, and the value of the dissolved SCCOD decreases from 294 mg / L to 180 mg / L, which is basically equivalent to the measured value reduction, proving that the model accurately reflects the main COD degradation proportion in detail. As can also be seen from the figure, the removal efficiency of the particulate COD in the early stage (0~0.35d) is higher than that in the later stage, while the SCCOD is the opposite, because a large amount of COD enters the sediment and the biofilm through deposition and adsorption in the early stage, and is generated through hydrolysis in the later stage, and is removed through the microbial metabolic pathway in the two phases.

[0342] Figure 8 The simulation value of the TP in the influent and effluent is compared with the measured value. As can be seen from the figure, the simulation value decreases from 17.6 mg P / L to 17.3 mg P / L, and the measured value decreases from 17.6 mg P / L to 15.1 mg P / L. The prediction conversion effect is good, and the possible deviation is that the influent may contain more particulate refractory P on that day, and the total phosphorus concentration (17.6 mg P / L) on that day is much higher than the steady-state influent (8 mg P / L), and the change caused by the influent P component cannot be accurately identified.

[0343] Figure 9 The simulation value of the TKN concentration in the influent and effluent is compared with the measured value. As can be seen from the figure, the simulation value decreases from 45.7 mg N / L to 44.6 mg N / L, and the measured value decreases from 45.7 mg N / L to 41.1 mg N / L. The simulation prediction effect is good.

[0344] Figure 10 The simulation value of the pipe network sediment thickness in the experimental period is compared with the measured value. The sediment thickness is calculated according to the hydrodynamics in the sediment layer. As can be seen from the figure, the simulation value is in good agreement with the measured value. After 109 days, the sediment gradually stabilizes and reaches the maximum thickness.

[0345] Figure 11 The simulated and measured values of the influent and effluent SS concentrations in the experimental period (steady-state influent simulation) are compared. To simplify the simulation complexity, the model uses steady-state influent. The main difference is that the effluent SS concentration of the experimental device is still low after the sediment is stable, and the algorithm simulation has some difference in capturing this phenomenon.

[0346] Figure 12 The simulated and measured values of the volatile acid VFA concentration in the experimental period with sediment are compared. As can be seen from the figure, the simulated effluent concentration of VFA is 34.6 mgCOD / L, which is close to the average measured value of 30.2 mgCOD / L, expressed in the form of steady-state input of 10 mgCOD / L.

[0347] At the same time, a set of experiments are carried out in the case of removing sediment in this embodiment:

[0348] Figure 13 The simulated and measured values of the volatile acid VFA concentration in the experimental period without sediment are compared, and the scenario is simulated by setting the sedimentation rate to 0 by closing the sedimentation process. As can be seen from the figure, the average value of the simulated influent is 8.4, the average value of the simulated effluent is 20.6, and the measured value is 19.3 (unit: mgCOD / L).

[0349] Based on the corrected gravity flow sewer water quality transformation model, the dynamic changes of other products defined in the pollutant state variable list LT can be analyzed.

[0350] Figure 14 The schematic diagram of microbial activity in sewage, sediment and biofilm in the pipeline expressed by the consumption rate of different types of electron acceptors (variation law diagram of oxygen utilization rate OUR, aerobic nitrogen utilization rate NOUR, sulfate reduction rate SRR and biological phosphorus utilization rate PURBIO in sewage, sediment and biofilm in the pipeline) is shown, which shows the change curves in dissolved oxygen (state variable), microbial concentration (state variable), OUR, NUR, PUR and SRR. As can be seen from the figure, the types and consumption rates of substrates used by microorganisms in different phases are quite different, and the OUR in sewage is significantly higher than that in sediment and biofilm, while the main biological phosphorus transformation occurs in the sediment, and the sulfate reduction is mainly from the biofilm.

[0351] It should be noted that according to the simulation results, the concentration of microorganisms in the sediment is higher than that in other phases, indicating that the biochemical reaction in the sediment is an important part of the water quality transformation of the sewer network that cannot be ignored.

[0352] In addition, in an embodiment, a specific embodiment is provided, which uses a real regional full-scale regional sewer network water quality transformation model with a tree topology to simulate a tree-shaped sewer network of a certain region. By considering the sediment generation and the mass transfer process of the sewage-sediment-biofilm-headspace multi-phase system, the physical, chemical and biological transformation processes in the pipe network are accurately simulated, which provides a scientific basis for pipe network water quality management and operation optimization. Based on the actual system data, the parameters are corrected and integrated into a reference parameter database, which provides support for the intelligent operation of urban water sewage pipe network, and verifies the applicability of the method.

[0353] In this specific embodiment, according to the pipe network data provided by the water department, the split points are set at the pipe diameter, slope change or tributary confluence. A drainage pipe unit is formed between two split points, and a gravity flow drainage pipe water quality transformation model (i.e. unit model) is applied in the unit to simulate and analyze the water quality transformation, including a hydraulics module, a biochemical reaction kinetics module and a mass conservation module. The effluent of the upstream unit and the tributary confluence water are used as the influent of the downstream pipe section. In the area without upstream pipe section, only the source strength confluence needs to be considered, and the source strength refers to the pollutant concentration in residential, industrial or commercial sewage.

[0354] Figure 15 A real regional full-scale regional sewer network water quality transformation model with a tree topology structure of a certain region constructed based on sewage water quality data is shown, and the model can be realized on the SUMO software platform. In the model, A1-A8 are source strength units, and gravity sewers 1-8 are drainage pipe unit models, i.e. the gravity flow drainage pipe water quality transformation model. Each unit model is connected according to the actual layout of the sewer network and the flow direction of the sewage, and finally forms a real regional full-scale regional sewer network water quality transformation model with a tree topology structure of the regional sewer network.

[0355] Table 22 is a comparison of the pollutant source strength (A6) of the conventional pollutant index (COD, N, P) with the effluent water quality at the end of the pipe network. From the A6 port, the transport is carried out through the gravity sewer 7-8 unit, and there is also confluence sewage such as A7, and finally the simulated value of COD at the pipe network outlet is 405 mg / L, and the total COD degradation rate is about 3.3%. The time and space quantitative analysis of the quantitative analysis of the conventional pollutant index is provided for the management department of the region. Without increasing the arrangement of special monitoring sites and monitoring equipment, data support is provided.

[0356] Table 22 Comparison of pollutant source strength (A6) of conventional pollutant index (COD, N, P) with effluent water quality at end of pipe network

[0357]

[0358] The existing water quality transformation model is supplemented and explained below, and the advantages of the gravity flow sewer network dynamic water quality simulation prediction coupling model method are compared and explained:

[0359] It should be noted that according to the difference of construction principle, the water quality transformation model can be divided into data driven model and mechanism model.

[0360] It should be noted that the data driven model refers to a type of model that uses the input and output data of the system to find a specific pattern to generalize to a larger range of data for prediction. Empirical model, statistical model and various machine learning models are typical data driven models. Sewer network is usually buried underground and closed pipe, it is difficult to carry out in-situ monitoring experiment; And the sewage pipe network has the characteristics of tree diagram, which is distributed in network in space, receiving sewage discharged by various sewage discharge pollution sources in the catchment area, subject to the huge spatial scale of sewage pipe network, if you want to carry out effective monitoring activities to obtain the data needed to build data driven model, it will consume huge monitoring cost. In short, data driven model is not suitable for water quality simulation and prediction of complex sewer network.

[0361] It should be noted that mechanism model is a model based on conservation relation, which is based on existing process mechanism to build model, which can carry out effective system identification of sewer network system by using limited pump station, inspection well and sewage plant data, which can fully utilize the existing monitoring data to carry out sewer network water quality simulation and prediction, and realize quantitative identification of material transformation process of pipe network, so as to optimize the operation mode of sewer network.

[0362] It should be noted that the current mechanism model cannot fully and accurately simulate the water quality transformation process in gravity flow pipe network, i.e. physical-chemical-biochemical process, for example:

[0363] It should be noted that the modeling method of hydrodynamics is usually limited to various types of micro-pollutants in the study of water quality transformation in gravity flow pipe network, and the first-order kinetic simulation method is usually adopted; But this method cannot fully evaluate the pipe network water quality transformation process.

[0364] It should be noted that the water quality transformation simulation of the drainage pipe network in the hydrology mode has the limitation of the pressure flow pipe network which is only applicable to simple hydrological conditions. In addition, the biochemical kinetics module part usually adopts the ASM-based model structure, and there are problems such as not considering the reaction process or important components, such as ignoring the influence of other elements such as N. In the anoxic anaerobic environment, nitrate in the sewage pipe network can also act as an electron acceptor, and microorganisms can utilize substrates such as volatile acids to carry out denitrification process, and the decrease of substrate concentration reduces the biological metabolism process rate of MA, which may cause errors in some drainage pipe network systems that add nitrate to control the production of hydrogen sulfide. Secondly, some of these models do not fully consider the influence of the change of dissolved oxygen concentration in the pipe network, do not contain dynamic aerobic-anoxic-anaerobic process, especially in gravity flow pipe network, there is an oxygen mass transfer process between sewage and headspace, and the aerobic process in the gravity flow pipe network cannot be ignored for COD degradation and other water quality transformation processes.

[0365] In contrast, the gravity flow drainage pipe network dynamic water quality simulation prediction coupling model method of the above embodiment defines a list of pollutant state variables LT, gives the pollutants to be included and the corresponding stoichiometry and kinetics matrix, and specifically includes elements such as sulfur in the pollutants, and the dynamic reaction includes aerobic-anaerobic-anoxic process, and at the same time, the aerobic process is related to the oxygen mass transfer process, and the method also defines the gas-liquid interface mass transfer process in the pipe section.

[0366] It should be noted that most of the existing models for hydraulic simulation do not include dynamic hydraulic simulation, and do not consider the changes of hydraulic conditions and the corresponding volume changes of liquid phase, sediment, biofilm and gas phase, so that the current models describing the water quality transformation of the pipe network are only applied to the pressure pipe with simple hydraulic relationship or rely on the externally introduced hydraulic relationship, and cannot describe the gravity flow pipe section with more complex hydraulic conditions.

[0367] In contrast, the gravity flow drainage pipe network dynamic water quality simulation prediction coupling model method of the above embodiment adopts a hydraulic module including the hydraulic expression of the flow and migration of sewage in the drainage pipe network, introduces pipe network water depth, fullness, wet perimeter and other parameters as intermediate variables based on the nonlinear outflow algorithm, calculates the relationship between the sewage volume in the current pipe network and the pipe network outflow, and can reflect the hydraulic conversion relationship in the drainage pipe network, and can be used to describe the gravity flow pipe section with more complex hydraulic conditions.

[0368] It should be noted that the existing model based on hydrological simulation may use a conceptual model. Although the conceptual model has good flexibility, the highly abstract model structure and the uncertainty of the modeling process (simplified process) bring greater uncertainty to the model results, thus being not conducive to use. The conceptual model mostly establishes a mapping model based on the similarity of hydraulic retention time, but not all water quality transformation processes are only related to hydraulic retention time, and the conceptual model is difficult to reflect the rate change of the mass transfer process caused by the real hydraulic fluctuation, while the biochemical process is largely controlled by the mass transfer mixing process, and the cumbersome correction process of the conceptual model limits its further use.

[0369] In contrast, the gravity flow drainage pipe network dynamic water quality simulation prediction coupling model method described in the above embodiments uses a non-linear outflow algorithm for the hydraulic module, only needs the design parameters of the pipe network such as pipe length and slope, and does not need other correction processes, and can also reflect the dynamic influence of hydraulic fluctuation on the mass transfer, gas-liquid mass transfer process rate and sediment generation rate.

[0370] It should be noted that the existing model for hydraulic simulation may use a model based on the N-S equation. Due to the inherent computational load of the NS equation, it is usually difficult to couple complex ordinary differential equations such as the ASM series model. Its description of pollutant indicators can usually only consider simple linear degradation patterns, so it is difficult to represent the conservation relationship of some unconventional detection indicators, and therefore this type of model is often used to solve water-related problems, such as combined overflow, on-line control of flood control and drainage, etc.

[0371] In contrast, the gravity flow drainage pipe network dynamic water quality simulation prediction coupling model method described in the above embodiments uses a non-linear outflow algorithm for the hydraulic module, and finally obtains an ordinary differential equation, which can be solved by numerical method, which is simpler than the space gridding required by the N-S equation, and balances the computational load, and can be used for complex pollutant transformation, and can be coupled with ASM, SUMO2S and other pollutant dynamics models.

[0372] The above describes the technical solutions provided by the present application in further detail through several specific embodiments, in order to highlight the advantages and benefits of the technical solutions provided by the present application. However, the above several specific embodiments are not used as a limitation on the present application, and any reasonable changes and improvements to the present application, reasonable combinations and equivalent replacements of embodiments, etc. based on the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A coupled model method for dynamic water quality simulation and prediction in gravity flow drainage networks, characterized in that, The method includes the following steps: The steps for constructing a gravity flow drainage pipe water quality transformation model for any drainage pipe within a drainage network include: The gravity flow drainage pipeline water quality transformation model includes a hydraulics module, a biochemical reaction kinetics module, and a mass conservation module. The hydraulic module includes hydraulic expressions for the flow and migration of wastewater in drainage pipes, as well as volume change relationships of liquid phase, sediment, biofilm, and headspace in drainage pipes; the hydraulic module is used to reflect the hydraulic transformation relationships in drainage pipes. The biochemical reaction kinetics module includes a list of pollutant state variables and their stoichiometry and kinetic matrices; the list of pollutant state variables is constructed based on unit process elements of the reaction physical and biochemical transformation processes; the biochemical reaction kinetics module is used for the biochemical reaction transformation relationships in the reaction drainage pipeline; The mass conservation module is used to reflect the material conservation relationships of wastewater, sediment, biofilm, and pollutants in the headspace. The mass conservation relationship of pollutants is calculated based on the mass transfer and exchange relationship; The mass transfer and exchange relationships include the deposition, resuspension, and diffusion of pollutants from wastewater to sediments, the adsorption, desorption, and diffusion of pollutants from wastewater to biofilm layers, and the gas transport processes between wastewater, sediments, biofilms, and headspace gases. The steps are used to correct the water quality transformation model of the gravity flow drainage pipeline based on the characteristics of the actual gravity flow drainage pipeline, and to obtain the corrected water quality transformation model of the gravity flow drainage pipeline. The steps are used to combine the corrected gravity flow drainage pipe water quality transformation model of all drainage pipes into a real-area full-scale regional drainage pipe network water quality transformation model with a tree-like topology, based on the actual structure of the drainage pipe network. The steps are for obtaining simulation results of water quality transformation in actual gravity flow drainage networks based on a full-scale regional drainage network water quality transformation model with a tree-like topology.

2. The coupled model method for dynamic water quality simulation and prediction of gravity flow drainage pipe network according to claim 1, characterized in that, The step of correcting the water quality transformation model of a gravity flow drainage pipeline based on the characteristics of the actual gravity flow drainage pipeline, and obtaining the corrected water quality transformation model of the gravity flow drainage pipeline, includes the following steps: This step is used to perform parameter sensitivity analysis on a gravity flow drainage pipeline water quality transformation model to obtain the parameters to be corrected. Steps for obtaining the features of the actual gravity flow drainage pipes needed to build the model; The steps are used to correct the parameters to be corrected in the water quality transformation model of the gravity flow drainage pipeline based on the characteristics of the actual gravity flow drainage pipeline, and to obtain the corrected water quality transformation model of the gravity flow drainage pipeline.

3. The coupled model method for dynamic water quality simulation and prediction of gravity flow drainage pipe network according to claim 1, characterized in that, The step of combining the corrected gravity flow drainage pipe water quality transformation models of all drainage pipes into a real-area full-scale regional drainage pipe network water quality transformation model with a tree-like topology, based on the actual drainage pipe network topology, includes the following steps: Obtain the connection relationships of each drainage pipe in the actual gravity flow drainage network; The corrected gravity flow drainage water quality transformation model for each drainage pipe is used as a unit model. Based on the actual gravity flow drainage network connection relationship, each unit model is constructed into a real-world full-scale regional drainage network water quality transformation model with a tree-like topology.

4. The coupled model method for dynamic water quality simulation and prediction of gravity flow drainage pipe network according to claim 1, characterized in that, The construction method of the biochemical reaction kinetics module is as follows: A plant-wide modeling approach was adopted, based on gravity flow drainage pipes, to select universally compatible physical and biochemical transformation processes and obtain all unit process elements; Based on all the obtained unit process elements, create a list of pollutant state variables and define the stoichiometry and kinetic matrices of the pollutant state variables.

5. The coupled model method for dynamic water quality simulation and prediction of gravity flow drainage pipe network according to claim 1, characterized in that, The mass conservation relationship of pollutants in wastewater is expressed by the basic mass conservation equation for pollutant i within the pipeline unit: ； ； in, The concentration of pollutant i in the sewage within the pipeline unit; The volume of sewage within the pipeline unit; This refers to the influent flow rate; This refers to the outflow rate; The concentration of pollutant i in the influent; The concentration of pollutant i in the effluent; The total reaction rate of contaminant i within the pipeline includes mass transfer and biochemical transformation. The rate at which pollutant i is deposited from wastewater into sediment; The resuspension rate of contaminants i within the sediment; The rate at which pollutants diffuse from sewage to sediment within the pipeline unit; The rate at which pollutant i is adsorbed from wastewater onto the biofilm; The desorption rate of pollutant i within the biofilm; The rate at which pollutants diffuse from wastewater to the biofilm within the pipeline unit; This refers to the gas-liquid mass transfer rate; Let i be the biochemical reaction rate of pollutant i in the liquid phase.

6. The coupled model method for dynamic water quality simulation and prediction of gravity flow drainage pipe network according to claim 1, characterized in that, The mass conservation relationship of pollutants within sediments is expressed by the basic mass conservation equation for pollutant i within the sediment layer: ； in, The concentration of pollutant i in the sediment layer within the pipeline unit; This represents the volume of sediment within the pipe unit. denoted as , representing the biochemical reaction rate of pollutant i within the sediment.

7. The coupled model method for dynamic water quality simulation and prediction of gravity flow drainage pipe network according to claim 1, characterized in that, The conservation of matter among pollutants within the biofilm is expressed by the basic conservation equation for pollutant i within the biofilm layer: ； in, The concentration of pollutant i in the biofilm layer within the pipeline unit; The volume of the biofilm within the pipeline unit; The boiling escape rate of pollutant i within the biofilm; The biochemical reaction rate of pollutant i within the biofilm; Expressions for adsorption and diffusion between the biofilm layer and the aqueous phase: ； ； ； ； in, This represents the maximum adsorption rate of the biofilm. The contact area between the biofilm and the wastewater; This represents the biofilm desorption rate. This refers to the TSS concentration within the biofilm. This represents the TSS concentration within the biofilm under steady-state conditions. The thickness of the biofilm; An empirical enhancer of diffusion rate in biofilms; Let be the diffusion coefficient of pollutant i; Let GSV be the permeation concentration on the surface of the gaseous form of pollutant i. The saturation level of gases boiling out of sediments and biofilms; GSV is the volumetric mass transfer coefficient of the liquid surface corresponding to the gaseous form of pollutant i under standard conditions.

8. The coupled model method for dynamic water quality simulation and prediction of gravity flow drainage pipe network according to claim 1, characterized in that, The mass conservation relationship of pollutants in the headspace is expressed by the basic mass conservation equation for pollutant i in the headspace: ； in, The concentration of pollutant i in the headspace gas layer within the pipeline unit; The volume of the headspace within the pipe unit; The flow rate of gas entering the headspace; The concentration of pollutant i in the gas entering the headspace; The gas flow rate leaving the pipe section unit; This represents the mass transfer rate between the headspace layer and other phases.

9. The coupled model method for dynamic water quality simulation and prediction of gravity flow drainage network according to claim 1, characterized in that, The calibration of the water quality transformation model for gravity flow drainage pipelines based on the characteristics of actual gravity flow drainage pipelines includes calibration of pipeline parameters, influent pollutant load parameters, and gas phase input parameters.

10. The coupled model method for dynamic water quality simulation and prediction of gravity flow drainage network according to claim 1, characterized in that, The calibration of the water quality transformation model of gravity flow drainage pipeline based on the characteristics of actual gravity flow drainage pipeline also includes calibrating the parameters in the biochemical reaction kinetics module, hydraulics module, and mass conservation module.

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