Urban water cycle simulation system, method, computer equipment and medium

Abstract

The present invention provides a system, method, computer equipment and medium for simulating urban water cycle. The system includes: a mountain subsystem for simulating the flow and water quality of the upstream mountain area; a rainwater subsystem for simulating the flow, pollutant accumulation and pollutant flushing of different underlying surfaces in the city; a sewage subsystem for receiving the flow, pollutant accumulation and pollutant flushing of the corresponding drainage outlet in the rainwater subsystem, and simulating the flow and water quality under various drainage systems in the city; a river channel subsystem for simulating the flow and water quality of each section in the river channel according to the flow and water quality in the mountain subsystem, the flow, pollutant accumulation and pollutant flushing of the corresponding drainage outlet in the rainwater subsystem, and the flow and water quality in the sewage subsystem; a lake subsystem for receiving the flow and water quality of each section in the river channel and simulating the water level and water quality of each river section in the lake. Through the present invention, a comprehensive simulation of urban water cycle is achieved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of urban water system simulation, and in particular to an urban water cycle simulation system, method, computer equipment and medium. Background Art

[0002] The rapid urbanization process divides the urban water system into multiple relatively independent yet interacting subsystem coupling processes.

[0003] Existing urban water system simulation methods have little consideration for the coupled simulation of multiple subsystems of urban water systems. Most of them are simulations of basin water systems or urban water systems alone, ignoring the hydrodynamic, water environment, and water ecological interaction processes and feedback mechanisms of the coupled basin and urban water systems. For example, existing basin water system simulations mainly conduct hydrological simulations, hydrodynamic simulations, or water environment simulations for basin water systems; existing urban water systems mainly conduct hydrological simulations, water environment simulations for urban rivers and lakes, or hydrodynamic simulations for urban pipe networks in terms of waterlogging. Summary of the invention

[0004] In order to realize the comprehensive simulation of the urban water system, the present invention proposes an urban water cycle simulation system, method, computer equipment and medium.

[0005] The system includes: mountain subsystem, rainwater subsystem, sewage subsystem, river subsystem and lake subsystem;

[0006] The mountain subsystem simulates flow and water quality in the upper mountainous areas;

[0007] The rainwater subsystem is used to simulate the flow, pollutant accumulation and pollutant flushing of different underlying surfaces in the city. The drainage outlets in the rainwater subsystem include the drainage outlets connected to the sewage subsystem and the drainage outlets connected to the river subsystem;

[0008] The sewage subsystem is used to receive the flow, pollutant accumulation and pollutant flushing of the corresponding drainage outlets in the rainwater subsystem, and simulate the flow and water quality under various drainage systems in the city;

[0009] The river channel subsystem is used to simulate the flow and water quality of each section in the river channel according to the flow and water quality in the mountain subsystem, the flow, pollutant accumulation and pollutant flushing of the corresponding drainage outlets in the rainwater subsystem, and the flow and water quality in the sewage subsystem;

[0010] The lake subsystem is used to receive the flow and water quality of each section in the river and simulate the water level and water quality of each section in the lake.

[0011] Taking into account that most of the existing urban water cycle simulations are simulations of the basin water system alone or the urban water system alone, the hydrodynamics, water environment, and water ecology in the basin water system and the urban water system interact with each other. Therefore, through the system in the embodiment of the present invention, the runoff generation and convergence in mountainous areas, urban runoff generation and convergence, as well as multiple water bodies such as rainwater, sewage, rivers, and lakes are comprehensively simulated, combining the interaction of different water bodies and the migration and transformation process of pollutants to achieve a comprehensive simulation of the urban water system.

[0012] In combination with the first aspect, in a first embodiment of the first aspect, the rainwater subsystem includes:

[0013] Wetland module, used to simulate the flow, pollutant accumulation and pollutant washoff of wetland subsurface;

[0014] Lake module, used to simulate the flow, pollutant accumulation and pollutant washoff of lake underlying surface;

[0015] Drainage area module, used to simulate the flow, pollutant accumulation and pollutant washoff of the drainage area underlying surface;

[0016] The rainwater pollution module is used to calculate the pollutant accumulation of each urban underlying surface according to the saturated accumulation model, and calculate the pollutant washoff of each urban underlying surface according to the exponential model.

[0017] In combination with the first aspect, in a second embodiment of the first aspect, the drainage system in the sewage subsystem includes a separate drainage system and a combined drainage system, and the sewage subsystem includes:

[0018] The water quality change module is used to receive the corresponding pollutant accumulation and pollutant flushing in the rainwater subsystem and simulate the water quality change process under various drainage systems in the city;

[0019] The pipeline confluence module is used to receive the corresponding flow in the rainwater subsystem and simulate the flow change process under various drainage systems in the city.

[0020] In combination with the first aspect, in a third embodiment of the first aspect, the river channel subsystem includes:

[0021] The river hydrodynamic module is used to simulate the flow of each section of the river according to the flow corresponding to the mountain subsystem, rainwater subsystem, and sewage subsystem and the one-dimensional hydrodynamic model;

[0022] The river water quality module is used to simulate the water quality of each section of the river according to the water quality corresponding to the mountain subsystem, rainwater subsystem, sewage subsystem and the one-dimensional water quality model.

[0023] In combination with the first aspect, in a fourth embodiment of the first aspect, the lake subsystem includes:

[0024] Lake hydrodynamics module, used to simulate the water level of each river section in the lake based on the flow of each section in the river channel and the two-dimensional shallow water control equations;

[0025] The lake water quality module is used to simulate the water quality of each river section in the lake based on the water quality of each section in the river and the 5X comprehensive water quality model.

[0026] In a second aspect, the present invention further provides a method for simulating an urban water cycle, which is used in the urban water cycle simulation system in the first aspect or any embodiment of the first aspect, and the method comprises:

[0027] Obtain the first flow, first pollutant accumulation and first pollutant washoff of different underlying surfaces in the city;

[0028] According to the first flow, first pollutant accumulation and first pollutant washoff of different underlying surfaces in the city, the flow and water quality under various drainage systems in the city are simulated;

[0029] Obtain the second flow, second pollutant accumulation and second pollutant washoff of different underlying surfaces in the city, and the flow and water quality of the upstream mountainous areas;

[0030] According to the second flow, second pollutant accumulation and second pollutant washout of different underlying surfaces in the city, the flow and water quality in the upstream mountainous area, and the flow and water quality under various drainage systems in the city, the flow and water quality of each section in the river are simulated;

[0031] According to the flow and water quality of each section in the river, the water level and water quality of each river section in the lake are simulated.

[0032] Taking into account that most of the existing urban water cycle simulations are simulations of the basin water system alone or the urban water system alone, the hydrodynamics, water environment, and water ecology in the basin water system and the urban water system interact with each other. Therefore, through the method in the embodiment of the present invention, the runoff generation and confluence in mountainous areas, urban runoff generation and confluence, as well as rainwater, sewage, rivers, lakes and other water bodies are comprehensively simulated, combining the interaction of different water bodies and the migration and transformation process of pollutants, to achieve a comprehensive simulation of the urban water system.

[0033] In combination with the second aspect, in a first embodiment of the second aspect, the urban underlying surface includes a wetland underlying surface, a lake underlying surface, and a drainage area underlying surface, and obtaining the first pollutant accumulation amount and the first pollutant flushing amount of different urban underlying surfaces includes:

[0034] According to the saturated accumulation model, the accumulation of the first pollutant on different underlying surfaces in the city is calculated;

[0035] Based on the exponential model, the washoff amount of the first pollutant on different underlying surfaces in the city is calculated.

[0036] In combination with the second aspect, in a second embodiment of the second aspect, based on the second flow, the second pollutant accumulation and the second pollutant wash amount of different underlying surfaces in the city, the flow and water quality in the upstream mountainous area, and the flow and water quality under various drainage systems in the city, the flow and water quality of each section in the river are simulated, including:

[0037] According to the second flow of different underlying surfaces in the city, the flow in the upstream mountainous area, the flow under various drainage systems in the city and the one-dimensional hydrodynamic model, the flow of each section in the river is simulated;

[0038] The flow and water quality of each section in the river are simulated based on the accumulation and washout of the second pollutants on different underlying surfaces in the city, the water quality in the upstream mountainous area, the water quality under various drainage systems in the city, and a one-dimensional water quality model.

[0039] In a third aspect, the present invention further provides a computer device, comprising a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the steps of the urban water cycle simulation method of the second aspect or any embodiment of the second aspect by executing the computer instructions.

[0040] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the urban water cycle simulation method of the second aspect or any embodiment of the second aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 is a schematic structural diagram of an urban water cycle simulation system proposed according to an exemplary embodiment;

[0043] Figure 2 is a schematic diagram of the Preissmann four-point eccentric format in one example;

[0044] Figure 3 is a schematic diagram of a central difference format in an example;

[0045] Figure 4 is a flow chart of a lake subsystem simulation in one example;

[0046] Figure 5 is a simulation schematic diagram of a 5X comprehensive water quality model in one example;

[0047] Figure 6 is a flow chart of a method for simulating an urban water cycle according to an exemplary embodiment;

[0048] Figure 7 It is a schematic diagram of the hardware structure of a computer device proposed according to an exemplary embodiment. DETAILED DESCRIPTION

[0049] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0051] In order to realize the comprehensive simulation of the urban water system, the present invention proposes an urban water cycle simulation system, method, computer equipment and medium.

[0052] Figure 1 1 is a schematic diagram of a structure of an urban water cycle simulation system proposed according to an exemplary embodiment. The system includes: a mountain subsystem 101, a rainwater subsystem 102, a sewage subsystem 103, a river subsystem 104 and a lake subsystem 105.

[0053] The mountain subsystem 101 is used to simulate the flow and water quality in the upstream mountain areas.

[0054] In an optional embodiment, the flow in the upstream mountainous area is simulated and calculated using a time-variant gain model (TVGM).

[0055] In an optional embodiment, the water quality in the upstream mountainous area is defined by assigning values ​​to major pollutants according to the water quality indicators of Class III water.

[0056] The rainwater subsystem 102 is used to simulate the flow, pollutant accumulation and pollutant flushing of different underlying surfaces in the city. The drainage outlets in the rainwater subsystem 102 include drainage outlets connected to the sewage subsystem 103 and drainage outlets connected to the river subsystem 104.

[0057] In an optional embodiment, different urban underlying surfaces include but are not limited to wetland underlying surfaces, lake underlying surfaces, and drainage area underlying surfaces.

[0058] In an optional embodiment, the pollutants include but are not limited to Chemical Oxygen Demand (COD), Total Phosphorus (TP) and Total Nitrogen (TN).

[0059] The sewage subsystem 103 is used to receive the flow, pollutant accumulation and pollutant flushing of the corresponding drainage outlet in the rainwater subsystem 102, and simulate the flow and water quality under various drainage systems in the city.

[0060] The river channel subsystem 104 is used to simulate the flow and water quality of each section in the river channel according to the flow and water quality in the mountain subsystem 101, the flow, pollutant accumulation and pollutant flushing of the corresponding drainage outlet in the rainwater subsystem 102, and the flow and water quality in the sewage subsystem 103.

[0061] The lake subsystem 105 is used to receive the flow and water quality of each section in the river channel and simulate the water level and water quality of each river section in the lake.

[0062] Taking into account that most of the existing urban water cycle simulations are simulations of the basin water system alone or the urban water system alone, the hydrodynamics, water environment, and water ecology in the basin water system and the urban water system interact with each other. Therefore, through the system in the embodiment of the present invention, the runoff generation and convergence in mountainous areas, urban runoff generation and convergence, as well as multiple water bodies such as rainwater, sewage, rivers, and lakes are comprehensively simulated, combining the interaction of different water bodies and the migration and transformation process of pollutants to achieve a comprehensive simulation of the urban water system.

[0063] In one example, the flow in the upstream mountainous area is simulated and calculated through the time-varying gain model. The time-varying gain model is a nonlinear rainfall-runoff model. Its main idea is to discover the nonlinear relationship between rainfall and runoff. Its main influence comes from the changes in runoff caused by different soil moisture (i.e. soil water content) and different rainfall intensities during the runoff generation process. In the form of runoff generation, the net rain R (Rain) is expressed as the product of the gain factor and the rainfall. The gain factor is expressed by a simple power exponential function that affects the rainfall and rainfall intensity in the previous period. The specific formula is as follows:

[0064]

[0065] Among them, G(t) is the gain factor; API and I are the normalized previous influencing rainfall and rainfall intensity, both of which are dimensionless values, ranging from 0 to 1; g1, g2, g3 and are time-varying gain model parameters related to the underlying surface characteristics and climate characteristics of the basin.

[0066] In one example, the stormwater subsystem 102 includes a wetland module, a lake module, a drainage area module, and a stormwater pollution module.

[0067] The wetland module in the rainwater subsystem 102 is used to simulate the flow rate, pollutant accumulation and pollutant washoff of the wetland ground surface.

[0068] In an optional embodiment, the wetland ground surface is divided into two layers, upper and lower. After rainfall falls on the upper layer, it infiltrates to the lower layer at a certain infiltration rate, and the remaining water is stored in the upper layer. When the water volume in the upper layer exceeds the maximum water storage capacity, the excess water is used as the flow production (flow) of the upper layer.

[0069] In an optional embodiment, the flow rate of the lower layer is calculated using a nonlinear flow rate calculation formula, and the specific formula is as follows:

[0070]

[0071] Among them, g1 and g2 are runoff parameters; W is the water content of the lower layer; W m is the maximum water holding capacity of the lower layer; I f is the infiltration rate; R sd It is the flow rate (discharge) of the lower layer of the wetland surface.

[0072] The lake module in the rainwater subsystem 102 is used to simulate the flow, pollutant accumulation and pollutant flushing of the lake underlying surface.

[0073] In an optional embodiment, the flow calculation method of the lake underlying surface is that when the water storage capacity of the lake exceeds a certain threshold, the maximum pumping flow rate is used for pumping according to the dam information of the lake. This part of the pumped water is used as the flow of the lake and enters the river or pipeline connected to it.

[0074] The drainage area module in the rainwater subsystem 102 is used to simulate the flow rate, pollutant accumulation and pollutant flushing of the underlying surface of the drainage area.

[0075] In an optional embodiment, the drainage area underlying surface can be divided into six small categories of underlying surfaces, including depressions, bare soil, roads, buildings, small ponds, and low impact development (LID). The flow rate of the drainage area underlying surface is the sum of the flow rates of the six small categories of underlying surfaces.

[0076] For example, the flow calculation mode of the depression storage type is that flow is generated only when the depression storage water volume is greater than the maximum storage water volume. The calculation formula is as follows:

[0077]

[0078] Among them, S s S is the water storage capacity of the depression; smax R is the maximum water storage capacity of the depression; s is the flow rate of the depression; P is the rainfall.

[0079] For example, the flow of bare soil type is calculated using a time-varying gain flow generation model, and the calculation formula is as follows:

[0080]

[0081] Among them, α, β, and γ are three runoff parameters; S is the soil water storage capacity; S m is the maximum soil water storage capacity; I is the rainfall intensity; P is the rainfall amount; R p It is the flow of bare soil.

[0082] Exemplarily, the flow of road types is divided into permeable roads and impermeable roads and calculated separately. The calculation of impermeable roads is the same as that of building types. The calculation mode of permeable roads is divided into two layers, upper and lower. The upper layer directly generates flow after rainfall, and the rainfall after deducting the flow enters the lower layer and becomes the water storage of the lower layer. When the water storage of the lower layer exceeds the water storage capacity of the lower layer, the excess water generates flow and enters the connected pipe. The calculation formula is shown as follows:

[0083]

[0084] Where μ is the surface runoff coefficient; P is the rainfall; W d is the water storage capacity of the lower layer; W dm is the water storage capacity of the lower layer; R r1 , R r2 They are upper layer traffic and lower layer traffic respectively.

[0085] For example, the calculation formula of the building type is as follows:

[0086] R C =ωP

[0087] Where ω is the building surface runoff coefficient; R c is the flow generated by the building; P is the rainfall.

[0088] Exemplarily, the calculation mode of small pond flow is consistent with the calculation mode of lake module flow. When the water storage capacity of small lake pond exceeds its water storage threshold, the flow of small lake pond is obtained by pumping out through the dam.

[0089] Exemplarily, low-impact measures include, but are not limited to, six types: rain gardens, permeable paving, grass-planted ditches, green roofs, rain barrels, and bioretention ponds.

[0090] The runoff generation pattern of the rain garden includes two areas: the reservoir and the soil. When the water storage in the reservoir exceeds the threshold water storage capacity of the reservoir area, the water in the reservoir begins to be pumped out at a fixed rate; while the soil part adopts the over-infiltration runoff generation mode, generating runoff when the rainfall intensity is greater than the infiltration rate.

[0091] The flow pattern of permeable paving bricks is divided into three layers from top to bottom: surface layer, permeable layer, and soil layer. Water is transferred between the surface layer and the permeable layer, and between the permeable layer and the soil layer at different infiltration rates, and each layer flows at a different outflow rate.

[0092] The grass-planted ditch is divided into two layers: the surface layer and the soil layer. The surface layer flows out with a fixed runoff coefficient and is transferred to the soil layer at a certain infiltration rate. The soil layer is drained at a fixed drainage rate.

[0093] The green roof is divided into two layers, the surface layer and the water storage layer. The surface layer flows out at a fixed drainage rate and is transferred to the water storage layer through a certain infiltration rate. When the water storage capacity of the water storage layer exceeds its drainage water threshold, it begins to flow out at a fixed drainage rate.

[0094] The flow generation pattern of the rain barrel is that when the accumulated rainfall in the rain barrel exceeds the maximum storage capacity of the rain barrel, the excess water is used as the flow of the rain barrel.

[0095] The biological retention pond is divided into two layers: the aquifer and the soil layer. Water seeps from the aquifer into the soil layer. When the aquifer is full, it flows out, and the soil layer flows out at a fixed outflow rate.

[0096] The model parameters in the rainwater subsystem 102 are shown in Table 1.

[0097] Table 1 Model parameters of rainwater subsystem 102

[0098]

[0099] The rainwater pollution module in the rainwater subsystem 102 is used to calculate the pollutant accumulation amount of each urban underlying surface according to the saturated accumulation model, and calculate the pollutant flushing amount of each urban underlying surface according to the exponential model.

[0100] In an optional embodiment, the saturation accumulation model formula is as follows:

[0101]

[0102] Among them, B is the accumulated amount of pollutants; C1 is the maximum accumulated amount; C2 is the accumulation rate; and t is the duration.

[0103] In an optional embodiment, the exponential model formula is as follows:

[0104]

[0105] Among them, W is the pollutant washoff; D1 is the washoff coefficient; D2 is the washoff index; q is the runoff rate per unit area; and H is the pollutant growth amount.

[0106] In an optional embodiment, the pollutant parameters in the rainwater subsystem 102 are selected from the empirical values ​​of different pollutants on roofs (buildings), roads, and green spaces in relevant literature, as shown in Table 2. The pollutants considered in the present invention include COD, TP, and TN.

[0107] Table 2 Parameter settings in pollutant saturation function and washoff function

[0108]

[0109]

[0110] The sewage subsystem 103 is used to simulate the rainwater runoff generated by urban rainfall, the water volume and water quality of rainwater and sewage under different drainage systems. For example, the Storm Water Management Model (SWMM) model is used to simulate multiple processes such as surface runoff generation, surface confluence, pipeline confluence and water quality change: first, the target area is divided into multiple sub-catchment areas, and surface runoff generation and confluence calculations are performed in each catchment area. The surface runoff is collected through the slope to the pipeline or river for confluence calculation, and then superimposed and calculated to the drainage outlet, which can reflect the process of rainwater formation, water volume and pollutant transmission, and realize the simulation of flow and water quality under different drainage systems in the city.

[0111] In one example, the drainage system in the sewage subsystem 103 includes a separate drainage system and a combined drainage system, and the sewage subsystem 103 includes:

[0112] The water quality change module is used to receive the corresponding pollutant accumulation and pollutant flushing amount in the rainwater subsystem 102, and simulate the water quality change process under various drainage systems in the city.

[0113] The pipeline confluence module is used to receive the corresponding flow in the rainwater subsystem 102 and simulate the flow change process under various drainage systems in the city.

[0114] In an optional embodiment, the water quality change process simulated in the water quality change module in the sewage subsystem 103 includes pollutant change processes from 6 different sources, as shown in Table 3.

[0115] Table 3 Pollutant sources and simulation methods in SWMM model

[0116]

[0117]

[0118] In an optional embodiment, in the pipe confluence module of the sewage subsystem 103, the pipe confluence process is approximately regarded as the movement of flood waves without bypass flow, and the pipe confluence process can be simulated by using three methods: constant flow method, motion wave method and dynamic wave method.

[0119] Exemplarily, in the pipeline confluence module of the sewage subsystem 103, the dynamic wave method is used to simulate the pipeline confluence process, and the specific parameters and their determination methods are shown in Table 4.

[0120] Table 4 Simulation parameters and determination methods of pipeline confluence module

[0121]

[0122] The calculation process using the dynamic wave method is as follows:

[0123] The governing equations of the dynamic wave method can be expressed through the Saint-Venant Equations as follows:

[0124]

[0125]

[0126] Where: Q is the flow rate (m 3 / s); A is the cross-sectional area of ​​water flow (m 2 ); H is the water depth (m); g is the acceleration due to gravity (m / s 2 );S f is the friction drop; x is the depth (m); t is the time (s).

[0127] At the same time, the continuity equation needs to be solved simultaneously:

[0128]

[0129] Where, H is the node head (m); Q i is the flow through the node (m 3 / s); w is the free water surface area at the node (m 2 ). By combining the above three equations, the pipeline flow rate and the water head at each node in the time period △t can be solved. For example, since it is a set of partial differential equations, the finite difference method can be used to solve it, and the differential equations can be solved by the modified Euler method.

[0130] In one example, the roughness in the river channel subsystem 104 is an important simulation parameter, which is a comprehensive dimensionless number reflecting the influence of the river bed boundary on the water flow resistance. The rougher the boundary surface, the greater the roughness; the smoother the boundary surface, the smaller the roughness. The roughness of the river channel in the embodiment of the present invention ranges from 0.028 to 0.035.

[0131] In one example, the river channel subsystem 104 includes a river channel hydrodynamic module and a river channel water quality module.

[0132] The river hydrodynamic module is used to simulate the flow of each section of the river according to the flow corresponding to the mountain subsystem 101, the rainwater subsystem 102, and the sewage subsystem 103 and the one-dimensional hydrodynamic model.

[0133] The river water quality module is used to simulate the water quality of each section of the river according to the water quality corresponding to the mountain subsystem 101, the rainwater subsystem 102, the sewage subsystem 103 and the one-dimensional water quality model.

[0134] In an optional embodiment, in the river hydrodynamic module of the river subsystem 104, the one-dimensional hydrodynamic model uses the finite difference method to solve the Saint-Venant equations. The Saint-Venant equations are basic equations that describe the motion of non-steady, gradually changing flow in a one-dimensional open channel, including the continuity equation and the motion equation, which can be expressed in various forms depending on the selected basic variables. In the embodiment of the present invention, the flow rate Q and the water level Z are used as basic variables, and the side inlet and outlet flow are considered, and the Saint-Venant equations in the following form are used:

[0135]

[0136] Where A is the area (m); t is the time (s); Q is the flow (m 3 / s); x is the flow rate (m); q is the lateral flow per unit flow rate, a positive value indicates inflow (m 2 / s); g is the acceleration due to gravity, which is 9.81 (m / s 2 ); B is the width of the water surface (m); Z is the water level (m); n is the roughness (dimensionless); R is the wetted perimeter (m). The first formula is the continuity equation, which reflects the continuous medium assumption of water flow and embodies the conservation of mass; the second formula is the momentum equation, which reflects the relationship between gravity, pressure, resistance and inertia force of non-steady flow, reflects Newton's second law, and embodies the conservation of momentum.

[0137] In the solution process, the Preissmann four-point eccentric format is used for discretization. This format converts the differential of the dependent variable into a difference for a point M in the middle of the rectangular grid. Point M is located at the exact center of the spatial step, and in the time step, it is biased towards the known time layer θΔt and towards the unknown time layer (1-θ)Δt, where θ is the weight factor, as shown in Figure 2 shown.

[0138] Taking flow rate Q as an example, the specific form of Preissmann four-point eccentric format is as follows:

[0139]

[0140]

[0141]

[0142] Where i is the distance, j is the time, and θ is the weight factor. The discretization method of water level Z is the same as above.

[0143] The Preissmann four-point eccentricity scheme is an implicit difference scheme, which can be theoretically proven to be unconditionally stable, but the spatial step size must be appropriate and the time step size cannot be too long. The stability is greatly affected by the weight factor θ. Too small or too large θ will deteriorate the stability of the calculation. For example, θ is generally 0.7 to 0.75, which has better stability and higher accuracy.

[0144] Substituting the Preissmann four-point eccentricity format into the Saint-Venant equations, we obtain the difference format of the continuity equation and momentum equation:

[0145]

[0146]

[0147] in:

[0148] a 1i =1

[0149]

[0150]

[0151]

[0152]

[0153]

[0154]

[0155]

[0156]

[0157] Among them, the coefficient e 2i Q M Traffic containing unknown layers and Therefore, multiple iterative calculations are required to solve the equation.

[0158] Before solving the Saint-Venant equations, in addition to the upstream and downstream control sections providing boundary conditions (water level, flow rate or water level-flow rate relationship), it is also necessary to provide initial conditions, that is, the water level (or water depth) and flow rate (or flow velocity) of each section at the initial moment. For rivers with generally smaller bottom slopes, an assumed value can be given for the initial water level, such as the same as the initial water level of the control station. However, for mountainous rivers or river sections with large water level fluctuations, the assumed water level may sometimes not be able to run the model. The present invention generates initial conditions by means of constant flow simulation, which can avoid the problem of difficulty in starting the model.

[0159] For example, the open channel steady-state gradually varying flow equation is used to generate the initial conditions:

[0160]

[0161] Where: Q is the flow rate (m 3 / s); x is the flow rate (m); q is the lateral flow per unit flow rate, a positive value indicates inflow (m 2 / s); g is the acceleration due to gravity, which is 9.81m / s 2 ; A is the cross-sectional area (m 2) ; Z is the water level (m); n is the roughness, dimensionless; R is the wetted perimeter (m).

[0162] Using difference approximation instead of differential, the following equation is obtained after discretization:

[0163]

[0164] in: The equation can be solved by using the binary search method multiple times and iteratively.

[0165] In actual calculation, the whole river section is divided into N+1 sections, each section has two unknowns, Q and Z, and there are 2(N+1) unknowns in total. N+1 sections have N sub-sections, and each sub-section can establish two equations, so there are 2N equations in total for the whole river section. Then, two boundary conditions can be added from the upstream and downstream control stations to solve the equations. The equation form of the added boundary conditions is as follows:

[0166]

[0167]

[0168] If the boundary condition provided by the upstream control section is flow, then a0 = 0, c0 = 1, e0 = Q; if the boundary condition provided is water level, then a0 = 1, c0 = 0, e0 = Z. If the boundary condition provided by the downstream control section is flow, then a N =0, c N =1,e N=Q; if the boundary condition provided is water level, then a N =1, c N =0,e N =Z.

[0169] The coefficient matrix of the system of equations is as follows:

[0170]

[0171] According to the coefficient matrix, the equation form can be transformed into a standard form by elimination, and then solved by elimination method. Taking the upstream boundary as an example, the flow rate and the downstream boundary as an example, it can be transformed into the following form:

[0172] Q i =P i +R i Z i

[0173] Among them, since it is the first section, i=0; P0=e0 / c0, Q0=-a0 / c0; since the boundary condition given upstream is flow, in fact P0=Q, Q0=0.

[0174] Furthermore, we get the following set of equations:

[0175]

[0176] in:

[0177]

[0178]

[0179]

[0180]

[0181] For the last section, it is clear that

[0182]

[0183] Since the downstream Z N It is known that the equation can be solved once by working backwards through the "inverse" process of the double elimination method.

[0184] In an optional embodiment, in the river water quality module of the river subsystem 104, the one-dimensional water quality model is expressed as follows:

[0185]

[0186] Where C is the pollutant concentration (mg / L); t is time (s); u is the average flow velocity of the section (m / s); x is the flow rate (m); M is the comprehensive diffusion coefficient, which is mainly based on shear flow dispersion (m 2 / s); K is the comprehensive attenuation coefficient, which is mainly based on the first-order reaction, d -1 ; S is the exogenous term, mg / (m 3 ·s). The degradation coefficient and diffusion coefficient in the one-dimensional water quality model are determined according to the flow velocity and cross-sectional parameters, and are automatically calculated by the embedded program after the flow field calculation is completed.

[0187] For example, the finite difference method is used to discretize the one-dimensional water quality model, combined with the initial conditions and boundary conditions, and then driven by the flow field calculation results of the hydrodynamic module, the water quality equation can be solved to obtain the concentration field distribution. The forward difference format is used for the spatial step x, the backward difference format is used for the time step t, and the central difference format is used for the second-order derivative of x. The format of the implicit format discretization is as follows Figure 3 As shown. The difference form of the Cainite format is as follows:

[0188]

[0189]

[0190]

[0191]

[0192] Where C is the pollutant concentration (mg / L).

[0193] After substituting the difference form of the implicit format into the one-dimensional water quality model, the discretized water quality difference equation is obtained:

[0194]

[0195] After sorting, we get:

[0196]

[0197] in:

[0198]

[0199]

[0200]

[0201]

[0202] Among them, f is mainly determined by the headwind pattern and the direction of the river flow, with 1 being in the forward direction and -1 being in the reverse direction.

[0203] When i=1, the boundary condition is When i = n, the transfer boundary is used as the lower boundary condition but

[0204] in:

[0205] '

[0206] α n =α n -γ n

[0207] β n ′=β n +2γ n

[0208] When i=2, n-1,

[0209] In summary, the differential equation forms the following tridiagonal matrix:

[0210]

[0211] The matrix is ​​solved using the pursuit method.

[0212] When i=1,

[0213] When i=2, n-1,

[0214] When i=n,

[0215] Obviously, using the catch-up method, first calculate the coefficient g in the order of i=1, n i and w i , and then inverse the process in the order of i=n, ​​1 to solve the C of the j+1th unknown layer i By iterating the time t multiple times, the pollutant concentration value of each time layer can be solved, that is, the water quality of each section of the river.

[0216] In one example, the lake subsystem 105 includes a lake hydrodynamics module and a lake water quality module. Figure 4As shown, the specific simulation process of the lake subsystem 105 includes: first, terrain processing and model parameter selection; then setting the initial boundary conditions of the model; simulating the water level and water quality of each river section in the lake through the lake hydrodynamic module and the lake water quality module; when the model error is less than the preset value, output the simulation result of the lake subsystem 105 until the simulation time reaches the preset time. In the lake subsystem 105, the initial hydrodynamic conditions of the simulation: set a global initial water level, set the velocity field u=v=0; the initial water quality conditions: give the initial concentration c0 of each pollutant according to the measured water quality; the boundary conditions of the simulation are solid wall boundaries: the normal component velocity is zero, that is, And the tangential flow velocity satisfies that at least one direction is zero, that is, or Water boundary: Inflow boundary - given inflow flow Q at each time period in (t) and pollutant concentration c in (t); Outflow boundary - given water level value Z at each time period out (t).

[0217] In an optional embodiment, the lake hydrodynamic module in the lake subsystem 105 is used to simulate the water level of each section in the lake based on the flow rate of each section in the river channel and the two-dimensional shallow water control equations.

[0218] For example, in the lake hydrodynamics module, a planar two-dimensional shallow water control equation system based on a Cartesian coordinate system is used, where the continuity equation is as follows:

[0219]

[0220] The momentum equation in the x-direction is as follows:

[0221]

[0222] The momentum equation in the y direction is as follows:

[0223]

[0224] Among them, x and y are the longitudinal and transverse distances of the river, respectively; u and v are the flow velocities in the x and y directions, respectively; t is time; h is the water depth; z is the water level; q is the inflow of the river section; g is the gravitational acceleration; c is the concentration of a certain pollutant in the river section; is the Coriolis force coefficient; is the latitude; Ω=2π / (24×3600) is the geostrophic angular velocity; ε x , ε y are the eddy viscosity coefficients in the x and y directions respectively; n is the roughness coefficient of the river channel; u w 、v w are the components of wind speed in the x and y directions respectively; λ is the wind stress coefficient.

[0225] In an optional embodiment, the lake water quality module in the lake subsystem 105 is used to simulate the water quality of each section in the lake based on the water quality of each section in the river and the 5X comprehensive water quality model.

[0226] The 5X comprehensive water quality model simplifies the complex coupling relationship between various water quality components in the water body, and comprehensively simulates the following 7 water quality indicators: dissolved oxygen, permanganate index, chlorophyll-a, ammonia nitrogen, nitrate nitrogen, total phosphorus and X characteristic index, so as to achieve a balance between ease of use and scientificity, and improve the practicality of the comprehensive water quality model.

[0227] The existing commonly used comprehensive water quality models, such as the WASP model, QUAL model, MIKE model, EFDC model, and Delft3D model, have many parameters, and a large amount of measured water quality data is required to set the initial conditions and boundary conditions during simulation. Due to the lack of some water quality data, and the inconsistency between the index system of these commonly used comprehensive water quality models and the existing "9+X" index system (water temperature, pH, dissolved oxygen, conductivity, turbidity, permanganate index, ammonia nitrogen, total phosphorus, total nitrogen and other 9 indicators and X characteristic indicators, X characteristic indicators are indicators that exceed the Class III standard limit in the previous year and the current year in addition to the 9 basic indicators in the "Surface Water Environmental Quality Standard" (GB3838-2002) project) and the "5+X" index system (pH, dissolved oxygen, permanganate index, ammonia nitrogen, total phosphorus and other 5 indicators and X characteristic indicators), these water quality models are very difficult to apply in rivers and lakes.

[0228] In the 5X comprehensive water quality model, the two-dimensional water quality convection-diffusion equation (the basic equation for the migration and transformation of two-dimensional water quality) is used for solution:

[0229]

[0230] Among them, E x 、E y Respectively represent the comprehensive diffusion coefficient in the x and y directions; ∑S i It is the source leakage item of pollutants in river water, which mainly considers natural degradation; the meanings of other symbols are the same as before.

[0231] The 5X comprehensive water quality model is an improvement on the QUAL-II model. It simulates and couples seven water quality indicators, including chlorophyll-a, ammonia nitrogen, nitrate nitrogen, total phosphorus, permanganate index, dissolved oxygen and X characteristic index, such as Figure 5The specific contents include: ① using chlorophyll-a to reflect the absorption and metabolic process of algae in water bodies; ② generalizing the transformation relationship between ammonia nitrogen, nitrite nitrogen and nitrate nitrogen, only considering the process of ammonia nitrogen being finally oxidized to nitrate nitrogen, reducing the demand for initial condition data, and the sources of ammonia nitrogen are algae (chlorophyll-a) and sediment release; ③ replacing orthophosphate with total phosphorus, the source is sediment release; ④ converting BOD to permanganate index for simulation; ⑤ considering the balance of dissolved oxygen in water bodies and various oxygen consumption and production processes.

[0232] For any water quality index, the following two-dimensional water quality migration transformation basic equation can be used to solve it:

[0233] ∑S i =S int +S ext

[0234] Among them, S int is the internal source leakage term of water quality variables; S ext is the external source and leakage term of water quality variables, such as tributary inflow. The main simulation parameters are shown in Table 5.

[0235] Table 5 Main parameters of the model

[0236]

[0237]

[0238] In the 5X comprehensive water quality model, the concentration of chlorophyll-a is proportional to the concentration of algae biomass. In order to establish the relationship between chlorophyll-a and other water quality components, a conversion coefficient is used to reflect the conversion relationship between chlorophyll-a and algae biomass, as shown in the following formula:

[0239] C a =α0C A

[0240] The differential equation for algae growth is shown below:

[0241] Among them, C a is the concentration of chlorophyll-a in the lake, μg / L; C A is the concentration of cyanobacteria biomass in the lake, mg / L; α0 is the conversion coefficient; μ is the specific growth rate of algae in the lake, 1 / d; ρ A is the algal metabolic rate constant, 1 / d;

[0242] The specific growth rate of algae is related to available nutrients and light intensity, and can be calculated using the following formula:

[0243]

[0244] Where: μ max is the maximum specific growth rate, 1 / d, which is related to temperature T and can be expressed by μ max =μ max (20)θ T-20 Correction; C N3 is the concentration of nitrate nitrogen, mg / L; C p is the concentration of total phosphorus, mg / L; K N is the half-rate constant of nitrate nitrogen, mg / L; K P is the half-rate constant of total phosphorus, mg / L; K I is the half-rate constant of light, g·W / m 2 ; η is the extinction coefficient, 1 / m; I is the light intensity, g·W / m 2 .

[0245] In the 5X comprehensive water quality model, the equation for the change of ammonia nitrogen is:

[0246]

[0247] Among them, C N1 is the concentration of ammonia nitrogen in the lake, mg / L; α1 is the proportion of ammonia nitrogen in algal biomass; K N1 is the rate constant for the conversion of ammonia nitrogen into nitrite nitrogen through oxidation, 1 / d.

[0248] In the 5X comprehensive water quality model, the equation for the change of nitrite nitrogen is:

[0249]

[0250] Among them, C N2 is the ammonia nitrogen concentration, mg / L; K N2 is the rate constant for the conversion of nitrite nitrogen into nitrate nitrogen through oxidation, 1 / d.

[0251] In the 5X comprehensive water quality model, the equation for the change of nitrate nitrogen is:

[0252]

[0253] In the 5X comprehensive water quality model, the changing equation for phosphorus cycle is:

[0254] In the 5X comprehensive water quality model, the mutual influence between total phosphorus and algae is considered as shown in the following formula:

[0255]

[0256] Among them, C p is the total phosphorus concentration, mg / L; α2 is the proportion of phosphorus in algae.

[0257] In the 5X comprehensive water quality model, the rate of change of biochemical oxygen demand (BOD) is considered according to first-order reaction kinetics, as shown in the following formula:

[0258]

[0259] Where, L is the BOD concentration, mg / L; K1 is the BOD degradation rate constant, 1 / d.

[0260] In the 5X comprehensive water quality model, the equation for dissolved oxygen change is:

[0261]

[0262] Where C is the dissolved oxygen concentration, mg / L; C s is the saturated dissolved oxygen concentration, mg / L; α3 is the oxygen production rate of algae photosynthesis; α4 is the oxygen consumption rate of algae respiration; K2 is the reoxygenation coefficient; α5 is the oxygen consumption rate of unit ammonia nitrogen converted into nitrite nitrogen; α6 is the oxygen consumption rate of unit nitrite nitrogen converted into nitrate nitrogen.

[0263] In the 5X comprehensive water quality model, the X characteristic index is generalized as degradable water pollutants, and its source leakage term can be written as:

[0264]

[0265] Where: K X is the degradation rate constant of characteristic index X, 1 / d; C X is the concentration of characteristic index X, mg / L.

[0266] Figure 6 A method for simulating an urban water cycle is proposed according to an exemplary embodiment, the method comprising:

[0267] Step S201: Obtain the first flow rate, first pollutant accumulation and first pollutant flushing amount of different underlying surfaces in the city.

[0268] Step S202: According to the first flow, the first pollutant accumulation and the first pollutant flushing amount of different underlying surfaces in the city, simulate the flow and water quality under various drainage systems in the city.

[0269] Step S203: Obtain the second flow, the second pollutant accumulation and the second pollutant washoff of different underlying surfaces in the city, and the flow and water quality in the upstream mountainous area.

[0270] Step S204: Simulate the flow and water quality of each section in the river according to the second flow, second pollutant accumulation and second pollutant washout of different underlying surfaces in the city, the flow and water quality in the upstream mountainous area, and the flow and water quality under various drainage systems in the city.

[0271] Step S205: According to the flow and water quality of each section in the river, simulate the water level and water quality of each river section in the lake.

[0272] Taking into account that most of the existing urban water cycle simulations are simulations of the basin water system alone or the urban water system alone, the hydrodynamics, water environment, and water ecology in the basin water system and the urban water system interact with each other. Therefore, through the method in the embodiment of the present invention, the runoff generation and confluence in the mountain area, the runoff generation and confluence in the city, as well as multiple water bodies such as rainwater, sewage, rivers, and lakes are comprehensively simulated, and the interaction of different water bodies is combined to achieve a comprehensive simulation of the urban water system.

[0273] In one example, the urban underlying surface includes a wetland underlying surface, a lake underlying surface, and a drainage area underlying surface, and obtaining the first pollutant accumulation amount and the first pollutant flushing amount of different urban underlying surfaces includes:

[0274] According to the saturated accumulation model, the accumulation of the first pollutant on different underlying surfaces in the city is calculated;

[0275] Based on the exponential model, the washoff amount of the first pollutant on different underlying surfaces in the city is calculated.

[0276] In one example, based on the second flow, second pollutant accumulation and second pollutant washout of different underlying surfaces in the city, the flow and water quality in the upstream mountainous area, and the flow and water quality under various drainage systems in the city, the flow and water quality of each section in the river are simulated, including:

[0277] According to the second flow of different underlying surfaces in the city, the flow in the upstream mountainous area, the flow under various drainage systems in the city and the one-dimensional hydrodynamic model, the flow of each section in the river is simulated;

[0278] The flow and water quality of each section in the river are simulated based on the accumulation and washout of the second pollutants on different underlying surfaces in the city, the water quality in the upstream mountainous area, the water quality under various drainage systems in the city, and a one-dimensional water quality model.

[0279] Figure 7 FIG. 1 is a schematic diagram of a hardware structure of a computer device according to an exemplary embodiment. Figure 7 As shown, the device includes one or more processors 710 and a memory 720, and the memory 720 includes a persistent memory, a volatile memory, and a hard disk. Figure 7 A processor 710 is taken as an example. The device may also include: an input device 730 and an output device 740.

[0280] The processor 710, the memory 720, the input device 730 and the output device 740 may be connected via a bus or other means. Figure 7 The example of connecting through bus is taken in the following.

[0281] The processor 710 may be a central processing unit (CPU). The processor 710 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips. A general-purpose processor may be a microprocessor or the processor may be any conventional processor.

[0282] The memory 720 is a non-transient computer-readable storage medium, including a persistent memory, a volatile memory, and a hard disk, and can be used to store non-transient software programs, non-transient computer executable programs, and modules, such as program instructions / modules corresponding to the urban water cycle simulation method in the embodiment of the present application. The processor 710 executes various functional applications and data processing of the server by running the non-transient software programs, instructions, and modules stored in the memory 720, that is, implementing any of the above-mentioned urban water cycle simulation methods.

[0283] The memory 720 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required by at least one function; the data storage area may store data required for use, etc. In addition, the memory 720 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 720 may optionally include a memory remotely arranged relative to the processor 710, and these remote memories may be connected to the data processing device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0284] The input device 730 can receive input digital or character information and generate signal input related to user settings and function control. The output device 740 can include display devices such as display screens.

[0285] One or more modules are stored in the memory 720, and when executed by one or more processors 710, the execution is as follows: Figure 6 The method shown.

[0286] The above-mentioned product can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to Figure 6 Related description of the illustrated embodiment.

[0287] The embodiment of the present invention further provides a non-transitory computer storage medium, which stores computer executable instructions, and the computer executable instructions can execute the simulation method in any of the above method embodiments. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory (Flash Memory), a hard disk (HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above types of memory.

[0288] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0289] The above is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features applied herein.

Claims

1. An urban water cycle simulation system, characterized in that: The system includes: mountain subsystem, rainwater subsystem, sewage subsystem, river subsystem and lake subsystem; The mountain subsystem is used to simulate the flow and water quality in the upstream mountain areas; The rainwater subsystem is used to simulate the flow, pollutant accumulation and pollutant flushing of different underlying surfaces in the city. The drainage outlets in the rainwater subsystem include drainage outlets connected to the sewage subsystem and drainage outlets connected to the river channel subsystem. The sewage subsystem is used to receive the flow, pollutant accumulation and pollutant flushing of the corresponding drainage outlets in the rainwater subsystem, and simulate the flow and water quality under various drainage systems in the city; The river channel subsystem is connected to the mountain subsystem and the sewage subsystem, and is used to simulate the flow and water quality of each section in the river channel according to the flow and water quality in the mountain subsystem and the flow and water quality in the sewage subsystem; The lake subsystem is used to receive the flow and water quality of each section in the river channel and simulate the water level and water quality of each river section in the lake; The river channel subsystem includes: The river hydrodynamic module is used to simulate the flow of each section of the river according to the flow corresponding to the mountain subsystem and sewage subsystem and the one-dimensional hydrodynamic model; The river water quality module is used to simulate the water quality of each section of the river according to the water quality corresponding to the mountain subsystem, sewage subsystem and the one-dimensional water quality model. The one-dimensional water quality model is expressed as follows: in, C is the pollutant concentration (mg / L); t is time (s); u is the average flow velocity of the cross section (m / s); x is the process (m); M is the comprehensive diffusion coefficient, mainly based on shear flow dispersion (m 2 / s); K is the comprehensive attenuation coefficient, mainly based on the first-order reaction, d -1 ; S is the exogenous term, mg / (m 3 ·s).

2. The system according to claim 1, characterized in that The rainwater subsystem includes: Wetland module, used to simulate the flow, pollutant accumulation and pollutant washoff of wetland subsurface; Lake module, used to simulate the flow, pollutant accumulation and pollutant washoff of lake underlying surface; Drainage area module, used to simulate the flow, pollutant accumulation and pollutant washoff of the drainage area underlying surface; The rainwater pollution module is used to calculate the pollutant accumulation of each urban underlying surface according to the saturated accumulation model, and calculate the pollutant washoff of each urban underlying surface according to the exponential model.

3. The system according to claim 1, characterized in that The drainage system in the sewage subsystem includes a separate drainage system and a combined drainage system. The sewage subsystem includes: The water quality change module is used to receive the corresponding pollutant accumulation and pollutant flushing in the rainwater subsystem and simulate the water quality change process under various drainage systems in the city; The pipeline confluence module is used to receive the corresponding flow in the rainwater subsystem and simulate the flow change process under various drainage systems in the city.

4. The system according to claim 1, characterized in that The lake subsystem includes: Lake hydrodynamics module, used to simulate the water level of each river section in the lake based on the flow of each section in the river channel and the two-dimensional shallow water control equations; The lake water quality module is used to simulate the water quality of each river section in the lake based on the water quality of each section in the river and the 5X comprehensive water quality model.

5. A method for simulating urban water cycle, characterized in that: The urban water cycle simulation system according to any one of claims 1 to 4, the method comprising: Obtaining a first flow rate, a first pollutant accumulation amount, and a first pollutant wash amount on different underlying surfaces in the city, wherein the first flow rate, the first pollutant accumulation amount, and the first pollutant wash amount are the flow rate, the pollutant accumulation amount, and the pollutant wash amount generated after rainfall; According to the first flow, first pollutant accumulation and first pollutant washoff of different underlying surfaces in the city, the flow and water quality under various drainage systems in the city are simulated; Obtaining flow and water quality in the upper mountainous areas; According to the flow and water quality in the upstream mountainous area and the flow and water quality under various drainage systems in the city, simulate the flow and water quality of each section in the river; According to the flow and water quality of each section in the river, simulate the water level and water quality of each section in the lake; According to the flow and water quality in the upstream mountainous area and the flow and water quality under various drainage systems in the city, the flow and water quality of each section in the river are simulated, including: According to the flow in the upstream mountainous area, the flow under various urban drainage systems and the one-dimensional hydrodynamic model, the flow of each section in the river is simulated; Based on the water quality in the upstream mountainous area, the water quality under the urban drainage systems, and the one-dimensional water quality model, the flow and water quality of each section in the river are simulated.

6. The method according to claim 5, characterized in that Urban underlying surfaces include wetland underlying surfaces, lake underlying surfaces, and drainage area underlying surfaces. The accumulation and washout of the first pollutants on different urban underlying surfaces are obtained, including: According to the saturated accumulation model, the accumulation of the first pollutant on different underlying surfaces in the city is calculated; Based on the exponential model, the washoff amount of the first pollutant on different underlying surfaces in the city is calculated.

7. A computer device, characterized in that: It comprises a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the steps of the urban water cycle simulation method according to claim 5 or 6 by executing the computer instructions.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the urban water cycle simulation method according to claim 5 or 6 are implemented.

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