CN116738669A - Urban surface runoff simulation method, device, equipment and storage medium - Google Patents
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Abstract
The embodiment of the disclosure provides a city surface runoff simulation method, a device, equipment and a storage medium, which are applied to the technical field of computers. The method comprises the following steps: dividing the target area according to the selected urban geographic grid level to obtain a plurality of urban geographic grids; generating ground surface cells corresponding to the urban geographic grids, and initializing the ground surface cells according to geographic information of a target area; and circularly calculating the water depth of each surface cell at the end of the simulation time step and the water quantity transferred to each downstream neighborhood surface cell in the simulation time step by taking the simulation time step as a unit until the total simulation time length is reached. In this way, urban surface runoff simulation can be realized by combining the urban geographic grid with the cellular automaton, so that the urban surface runoff simulation effect is greatly improved.
Description
Technical Field
The disclosure relates to the technical field of computers, and in particular relates to a city surface runoff simulation method, a device, equipment and a storage medium.
Background
With the continuous development of urban construction, urban surface soil is gradually replaced by hardened pavement and building facilities with poor water permeability, so that urban water circulation is obviously changed, and the urban surface soil is characterized by reduced surface infiltration, increased surface runoff, increased urban flood risk, increased difficulty in resisting disasters and the like. Under the condition, the urban surface runoff can be accurately simulated with high precision, urban flood risks can be accurately predicted, weak links of prevention and control are found, technical support is provided for rapid development of modern cities, and meanwhile effective tools are provided for pollutant diffusion treatment and urban pipe network planning.
It is worth noting that most of the conventional urban surface runoff simulation schemes have the problem of poor simulation effect, and cannot be applied to urban drainage planning and small-scale street inundation early warning. Therefore, how to improve the simulation effect of urban surface runoff becomes a technical problem to be solved at present.
Disclosure of Invention
The embodiment of the disclosure provides a city surface runoff simulation method, device, equipment and storage medium.
In a first aspect, embodiments of the present disclosure provide a method for simulating urban surface runoff, the method comprising:
dividing the target area according to the selected urban geographic grid level to obtain a plurality of urban geographic grids;
generating ground surface cells corresponding to the urban geographic grids, and initializing the ground surface cells according to geographic information of a target area;
and circularly calculating the water depth of each surface cell at the end of the simulation time step and the water quantity transferred to each downstream neighborhood surface cell in the simulation time step by taking the simulation time step as a unit until the total simulation time length is reached.
In some implementations of the first aspect, partitioning the target area according to the selected urban geography grid level to obtain a plurality of urban geographies includes:
and dividing the target area according to the size of the specification block corresponding to the urban geographic grid level to obtain a plurality of urban geographic grids.
In some implementations of the first aspect, initializing each of the cells according to geographic information of the target area includes:
determining geographic information of geographic grids of each city according to the geographic information of the target area;
binding the geographic information of each urban geographic grid with the corresponding ground surface cell, and initializing each ground surface cell.
In some implementations of the first aspect, cyclically calculating the water depth at the end of the simulation time step and the amount of water transferred to each downstream neighbor cell in the simulation time step, includes:
identifying the underlying surface type of each ground surface cell, and eliminating the ground surface cells with the underlying surface type being a house layer;
the cyclic calculation does not exclude the depth of water at the end of the simulation time step and the amount of water transferred by the cells to each downstream neighbor cell in the simulation time step.
In some implementations of the first aspect, calculating the depth of water at the end of the simulation time step and the amount of water transferred to each downstream neighbor cell within the simulation time step without excluding cells includes:
calculating the water depth of the non-excluded ground cells at the end of the simulation time step according to the rainfall, the soil infiltration, the vegetation retention and the gully discharge of the non-excluded ground cells in the simulation time step, and taking the water depth and the topography Gao Chengzhi of the non-excluded ground cells and the water level as the non-excluded ground cells;
for any non-excluded ground cell, taking the non-excluded ground cell as a central ground cell, determining a downstream neighborhood ground cell according to the water level of the central ground cell and the water level of the neighborhood ground cell, and calculating the first time length required by all water quantity transferred from the central ground cell to each downstream neighborhood ground cell;
calculating the maximum transfer water quantity corresponding to each downstream neighborhood ground cell according to the water quantity of the central ground cell and the gradients of the central ground cell and each downstream neighborhood ground cell;
if the simulation time step length is greater than or equal to the first time length, determining that the water quantity transferred from the central ground cell to the downstream neighborhood ground cell corresponding to the first time length in the simulation time step length is the corresponding maximum transfer water quantity;
if the simulation time step is smaller than the first time length, determining that the quantity of water transferred from the central ground cell to the downstream neighborhood ground cell corresponding to the first time length in the simulation time step is the product of the corresponding maximum transfer quantity of water and the ratio of the simulation time step to the first time length.
In some implementations of the first aspect, the method further includes:
and correcting the water quantity transferred from the central ground cell to each downstream neighborhood ground cell in the simulation time step according to the upper limit of the water quantity transferred corresponding to each downstream neighborhood ground cell.
In some implementations of the first aspect, the boundary tracking rule of the cells of the ground are a mole-based neighborhood method.
In a second aspect, embodiments of the present disclosure provide an urban surface runoff simulation apparatus, the apparatus comprising:
the segmentation module is used for segmenting the target area according to the selected urban geographic grid level to obtain a plurality of urban geographic grids;
the generation module is used for generating ground cells corresponding to the urban geographic grids and initializing the ground cells according to the geographic information of the target area;
and the calculation module is used for circularly calculating the water depth of each ground cell at the end of the simulation time step and the water quantity transferred to each downstream neighborhood ground cell in the simulation time step by taking the simulation time step as a unit until the simulation total duration is reached.
In a third aspect, embodiments of the present disclosure provide an electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method as described above.
In a fourth aspect, embodiments of the present disclosure provide a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform a method as described above.
In the embodiment of the disclosure, a target area can be segmented according to a selected urban geographic grid level to obtain a plurality of urban geographic grids, the ground cells corresponding to each urban geographic grid are generated, each ground cell is initialized according to geographic information of the target area, the water depth of each ground cell at the end of the simulation time step and the water quantity transferred to each downstream neighborhood ground cell in the simulation time step are circularly calculated by taking the simulation time step as a unit until the total simulation time length is reached, so that urban surface runoff simulation is effectively realized, and the accuracy and speed of urban surface runoff simulation are improved.
It should be understood that what is described in this summary is not intended to limit the critical or essential features of the embodiments of the disclosure nor to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following description.
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The above and other features, advantages and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. For a better understanding of the present disclosure, and without limiting the disclosure thereto, the same or similar reference numerals denote the same or similar elements, wherein:
FIG. 1 illustrates a flow chart of a method of urban surface runoff simulation provided by an embodiment of the present disclosure;
FIG. 2 illustrates a hierarchical schematic view of a geographic grid of a city provided by an embodiment of the present disclosure;
FIG. 3 illustrates a schematic diagram of a boundary tracking rule provided by an embodiment of the present disclosure;
FIG. 4 illustrates a block diagram of an urban surface runoff simulation device provided by an embodiment of the present disclosure;
fig. 5 illustrates a block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are some embodiments of the present disclosure, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the disclosure, are within the scope of the disclosure.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
In view of the problems occurring in the background art, embodiments of the present disclosure provide a method, an apparatus, a device, and a storage medium for simulating urban surface runoff. Specifically, a target area is segmented according to a selected urban geographic grid level, a plurality of urban geographic grids are obtained, ground cells corresponding to the urban geographic grids are generated, each ground cell is initialized according to geographic information of the target area, water depth of each ground cell at the end of a simulation time step and water quantity transferred to each downstream neighborhood ground cell in the simulation time step are circularly calculated by taking the simulation time step as a unit until the total simulation time length is reached, so that urban surface runoff simulation is effectively realized, and accuracy and speed of urban surface runoff simulation are improved.
Therefore, the urban surface runoff simulation can be realized by combining the urban geographic grid with the cellular automaton, so that the urban surface runoff simulation effect is greatly improved.
The urban surface runoff simulation method, device, equipment and storage medium provided by the embodiment of the disclosure are described in detail below through specific embodiments with reference to the accompanying drawings.
FIG. 1 shows a flowchart of a method for simulating urban surface runoff provided by an embodiment of the disclosure, as shown in FIG. 1, the method 100 for simulating urban surface runoff may include the following steps:
and S110, dividing the target area according to the selected urban geographic grid level to obtain a plurality of urban geographic grids.
In some embodiments, the target area may be partitioned according to a specification block size corresponding to the selected urban geographic grid level, so as to quickly obtain a plurality of urban geographic grids.
It should be noted that the urban geographic grid is a coding format developed based on Geo SOT, and assigns a value to the discretized position of everything in the earth space, and the core is to divide the earth into grid groups of 32 levels, seamless nesting and minimum scale of 1.5cm2, and simultaneously assign a globally unique integer code to each grid. Illustratively, the city geographic grid hierarchy may be as shown in FIG. 2.
And S120, generating cells corresponding to the urban geographic grids, and initializing the cells according to the geographic information of the target area.
In some embodiments, cells corresponding to each urban geography grid one by one may be generated according to each urban geography grid, where each cell corresponds to a unique cell code, and the cell code may be formed by "cell code=urban geography code+time code+data type+spreading code".
Determining geographic information of each urban geographic grid according to the geographic information of the target area, wherein the geographic information can comprise: the type of underlying surface, the elevation of DEM, the rainfall, the roughness coefficient, etc.
The geographic information of each urban geographic grid is bound to the corresponding cells so as to effectively initialize each cell (i.e., cell parameter initialization). Illustratively, the initialized cell parameters may be as shown in Table 1:
TABLE 1
It should be noted that the boundary tracking rule of the cells may be a higher-precision mole-type neighborhood method, that is, the central cells transfer water to the neighboring cells in eight directions around, as shown in fig. 3.
S130, circularly calculating the water depth of each surface cell at the end of the simulation time step and the water quantity transferred to each downstream neighborhood surface cell in the simulation time step by taking the simulation time step as a unit until the total simulation time length is reached.
In some embodiments, the underlying surface type of each cell may be identified, cells whose underlying surface type is the house layer may be excluded, and the cyclic calculation does not exclude the depth of water at the end of the simulation time step and the amount of water transferred by the cell to each downstream neighbor cell within the simulation time step.
In this way, it is considered that the urban ground drainage system is directly drained by the drainage pipeline, so that urban surface runoff simulation is not required to be performed on the ground surface cells with the underlying surface type being the house layer, and the calculation amount of the urban surface runoff simulation is greatly reduced.
Illustratively, for any one simulation time step, the water depth (i.e., the water depth obtained by the flow calculation) of the non-excluded cells at the end of the simulation time step may be calculated according to the rainfall, soil infiltration, vegetation retention, and gully discharge of the non-excluded cells in the simulation time step, and the water depth and topography Gao Chengzhi of the non-excluded cells and the water level as the non-excluded cells.
The calculation formula of the water depth can be as follows:
h＝R-I-O-N (1)
wherein h is the water depth (i.e. the water depth of the produced flow), R is the rainfall of the ground cells, I is the soil infiltration of the ground cells, O is the water drainage of the water inlet of the ground cells, N is the vegetation retention of the ground cells, and the units are mm.
Alternatively, the rainfall R, the soil infiltration amount I, the vegetation retention N, and the gully drainage O may be obtained by:
rainfall R: based on the measured data of the monitoring stations near the simulation area, the rainfall intensity in the simulation area can be calculated by a heavy rain intensity formula:
wherein q is the intensity of heavy rain, and the unit ist is rainfall duration (min), and P is design reproduction period (a); a1, C, n and b are regional parameters, and are calculated and determined by a statistical method according to regional rainfall historical data.
Soil infiltration amount I: calculating the soil infiltration rate by adopting a Horton model:
f t ＝f c +(f 0 -f c )e -kt (3)
wherein f t The soil infiltration rate at the simulation time t is in mm/h; f (f) 0 The unit is mm/h for the initial infiltration rate at the beginning of the simulation; f (f) c To stabilize the hypotonic rate, the unit is mm/h; k is the attenuation coefficient, unit h -1 。
And calculating the soil infiltration amount I according to the soil infiltration rate.
Vegetation retention N: calculated according to the following formula:
wherein N is vegetation retention, and the unit is mm; l (L) 0 The maximum interception amount of the forest canopy is in mm; c is a characteristic function of the canopy, and can be represented by the canopy closure degree of vegetation; p is the rainfall in mm.
Gutter inlet displacement O: calculated according to the following formula:
wherein O is the drainage quantity of a gully; w is the area of the aperture of the rain grate; g is gravity acceleration; c is the orifice flow coefficient; h is the water depth on the rain grate; k is the orifice blocking coefficient.
And determining a downstream neighborhood ground cell according to the water level of the central ground cell and the water level of the neighborhood ground cell by taking any non-excluded ground cell as the central ground cell.
For example, comparing the water level of the central cell with that of the neighbor cells, excluding the neighbor cells having a water level higher than that of the central cell, and taking the neighbor cells not excluded as downstream neighbor cells.
The first time period required for the total transfer of the water quantity of the central ground cells to each downstream neighborhood ground cell is calculated.
For example, the first time period required for the total transfer of the water volume of the central cell to each downstream neighborhood cell is calculated by using the Manning formula, and is specifically as follows:
wherein V is the flow rate; h is the water depth of the central ground surface cell; j is the gradient; n is the roughness coefficient.
Wherein T is ij For the first time period required for the maximum transfer water quantity corresponding to the downstream neighborhood ground cells j in the central ground cells i to be completely transferred to the downstream neighborhood ground cells j, L is the distance between the central ground cells i and the downstream neighborhood ground cells j, the side length of the ground cells is set to be d, L=d when the downstream neighborhood ground cells are located in the up, down, left and right directions, L=d when the downstream neighborhood ground cells are located in the diagonal directions,
and calculating the maximum transfer water quantity corresponding to each downstream neighborhood ground cell according to the water quantity of the central ground cell and the gradient of the central ground cell and each downstream neighborhood ground cell.
For example, according to the gradient of the central cell and each downstream neighborhood cell, the flow distribution proportion of the water quantity transferred from the central cell to each downstream neighborhood cell is determined as follows:
wherein d ij For the flow distribution ratio from the central cell i to the downstream neighborhood cell j, p is an empirical parameter, S ij Slope from the center cell i to the downstream neighbor cell j. Z is Z i The topography elevation of the central ground surface cell i, Z j Terrain elevation for downstream neighborhood ground cell j, D ij Is the distance between the central cell i and the downstream neighbor cell j.
According to the water quantity of the central ground surface cells and the flow distribution proportion of each downstream neighborhood ground surface cell, calculating the maximum transfer water quantity corresponding to each downstream neighborhood ground surface cell, wherein the maximum transfer water quantity is as follows:
P ij ＝P i ×d ij ，P i ＝h×A (9)
wherein P is ij For maximum transfer from central cell i to downstream neighbor cell jWater amount, P i Water quantity d being the central ground cell ij For the flow distribution ratio from the central cell i to the downstream neighborhood cell j, h is the water depth of the central cell i, and A is the terrain area, namely the area of the urban geographic grid where the cells are located.
Comparing the simulated time step with the first time length, if the simulated time step is greater than or equal to the first time length, determining that the water quantity transferred from the central ground cell to the downstream neighborhood ground cell corresponding to the first time length in the simulated time step is the corresponding maximum transfer water quantity, namely the maximum transfer water quantity corresponding to the downstream neighborhood ground cell in the central ground cell can be completely transferred.
If the simulation time step is smaller than the first time length, determining that the amount of water transferred from the central ground cell to the downstream neighborhood ground cell corresponding to the first time length in the simulation time step is the product of the corresponding maximum transfer amount of water and the ratio of the simulation time step to the first time length, namely that the maximum transfer amount of water corresponding to the downstream neighborhood ground cell in the central ground cell can only be partially transferred, wherein the method comprises the following specific steps of:
wherein P is i ′ j For the central cell i, the amount of water, P, is transferred to the downstream neighborhood cell j within a simulated time step Deltat ij T for maximum transfer of water from central cell i to downstream neighbor cell j ij Is the corresponding first duration.
In this way, urban surface runoff simulation can be rapidly achieved based on the cells of the ground cells combined with the urban geographic grid.
In addition, referring to the assumption that the power system tends to develop towards an equilibrium state, the water quantity transferred from the central ground cell to each downstream neighborhood ground cell in the simulation time step can be corrected according to the upper limit of the water quantity transferred corresponding to each downstream neighborhood ground cell, so that the simulation precision of urban surface runoff is further improved, and the method specifically comprises the following steps:
wherein P is i ′ j ′ For the corrected central cell i to transfer the amount of water, P, to the downstream neighborhood cell j within the simulated time step Deltat i ′ j The amount of water, h, transferred to the downstream neighborhood cell j for the central cell i within the simulated time step deltat ij The average value of water levels of the central ground cell i and the downstream neighborhood ground cell j is expressed as m and h j The water level of the downstream neighborhood ground cell j is expressed as m, and A is the terrain area, namely the area of the urban geographic grid where the ground cell is located.
In the embodiment of the disclosure, urban surface runoff simulation can be realized by combining the urban geographic grid with the cellular automaton, so that the urban surface runoff simulation effect is greatly improved. In addition, the absolute positions of the cells are defined through the urban geography grid system, the cell codes are unified, meanwhile, the efficient calculation characteristics of the urban geography grid codes are fully exerted, the big data information is organized and managed, and the query and calculation efficiency is greatly improved.
The urban surface runoff simulation method provided by the embodiment of the disclosure is described in detail below with reference to a specific embodiment, and specifically as follows:
(1) And selecting an area where a certain two-dimensional urban geographic grid with the 13 th urban geographic grid level in the target city is located as a target area, and selecting the 19 th urban geographic grid level based on the urban geographic grids to divide the target area so as to obtain a plurality of urban geographic grids.
(2) And generating the ground cells corresponding to the urban geographic grids, and initializing the ground cells according to the geographic information of the target area.
(3) And circularly calculating the water depth of each surface cell at the end of the simulation time step and the water quantity transferred to each downstream neighborhood surface cell in the simulation time step by taking the simulation time step as a unit until the total simulation time length is reached.
It can be understood that the target area can be divided into urban geography grids of various urban geography grid levels in advance, so that the ground surface cells with different level scales are generated, the ground surface cells with corresponding scales can be conveniently and rapidly selected for carrying out urban surface runoff simulation according to different data precision requirements, and the simulation requirements of different precision are met.
Further, by means of a 32-level urban geographic grid system, the urban underlying surface can be subjected to multi-scale subdivision, and minimum monomer municipal facilities which have important influence on runoffs in cities can be bound to corresponding minimum-level ground surface cells, so that simulation accuracy is improved.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present disclosure is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present disclosure. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all alternative embodiments, and that the acts and modules referred to are not necessarily required by the present disclosure.
The foregoing is a description of embodiments of the method, and the following further describes embodiments of the present disclosure through examples of apparatus.
FIG. 4 illustrates a block diagram of an urban surface runoff simulation device provided by an embodiment of the present disclosure, as illustrated in FIG. 4, an urban surface runoff simulation device 400 may include:
the segmentation module 410 is configured to segment the target area according to the selected urban geographic grid level, so as to obtain a plurality of urban geographic grids.
The generating module 420 is configured to generate cells corresponding to the geographic grids of each city, and initialize each cell according to geographic information of the target area.
The calculating module 430 is configured to circularly calculate, in units of the simulation time step, the water depth of each cell at the end of the simulation time step and the amount of water transferred to each cell in the downstream neighborhood in the simulation time step until the total simulation time length is reached.
In some embodiments, the segmentation module 410 is specifically configured to:
and dividing the target area according to the size of the specification block corresponding to the urban geographic grid level to obtain a plurality of urban geographic grids.
In some embodiments, the generating module 420 is specifically configured to:
determining geographic information of geographic grids of each city according to the geographic information of the target area;
binding the geographic information of each urban geographic grid with the corresponding ground surface cell, and initializing each ground surface cell.
In some embodiments, the computing module 430 is specifically configured to:
identifying the underlying surface type of each ground surface cell, and eliminating the ground surface cells with the underlying surface type being a house layer;
the cyclic calculation does not exclude the depth of water at the end of the simulation time step and the amount of water transferred by the cells to each downstream neighbor cell in the simulation time step.
In some embodiments, the computing module 430 is specifically configured to:
calculating the water depth of the non-excluded ground cells at the end of the simulation time step according to the rainfall, the soil infiltration, the vegetation retention and the gully discharge of the non-excluded ground cells in the simulation time step, and taking the water depth and the topography Gao Chengzhi of the non-excluded ground cells and the water level as the non-excluded ground cells;
for any non-excluded ground cell, taking the non-excluded ground cell as a central ground cell, determining a downstream neighborhood ground cell according to the water level of the central ground cell and the water level of the neighborhood ground cell, and calculating the first time length required by all water quantity transferred from the central ground cell to each downstream neighborhood ground cell;
calculating the maximum transfer water quantity corresponding to each downstream neighborhood ground cell according to the water quantity of the central ground cell and the gradients of the central ground cell and each downstream neighborhood ground cell;
if the simulation time step length is greater than or equal to the first time length, determining that the water quantity transferred from the central ground cell to the downstream neighborhood ground cell corresponding to the first time length in the simulation time step length is the corresponding maximum transfer water quantity;
if the simulation time step is smaller than the first time length, determining that the quantity of water transferred from the central ground cell to the downstream neighborhood ground cell corresponding to the first time length in the simulation time step is the product of the corresponding maximum transfer quantity of water and the ratio of the simulation time step to the first time length.
In some embodiments, urban surface runoff simulation apparatus 400 further comprises:
and the correction module is used for correcting the water quantity transferred from the central ground cell to each downstream neighborhood ground cell in the simulation time step according to the upper limit of the transferred water quantity corresponding to each downstream neighborhood ground cell.
In some embodiments, the boundary tracking rule for a cell is a mole-based neighborhood approach.
It can be appreciated that each module/unit in the urban surface runoff simulation apparatus 400 shown in fig. 4 has a function of implementing each step in the urban surface runoff simulation method 100 shown in fig. 1, and can achieve corresponding technical effects, which are not described herein for brevity.
Fig. 5 illustrates a block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure. Electronic device 500 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic device 500 may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 5, the electronic device 500 may include a computing unit 501 that may perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM) 502 or a computer program loaded from a storage unit 508 into a Random Access Memory (RAM) 503. In the RAM503, various programs and data required for the operation of the electronic device 500 may also be stored. The computing unit 501, ROM502, and RAM503 are connected to each other by a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
A number of components in electronic device 500 are connected to I/O interface 505, including: an input unit 506 such as a keyboard, a mouse, etc.; an output unit 507 such as various types of displays, speakers, and the like; a storage unit 508 such as a magnetic disk, an optical disk, or the like; and a communication unit 509 such as a network card, modem, wireless communication transceiver, etc. The communication unit 509 allows the electronic device 500 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The computing unit 501 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 501 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as method 100. For example, in some embodiments, the method 100 may be implemented as a computer program product, including a computer program, tangibly embodied on a computer-readable medium, such as the storage unit 508. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 500 via the ROM502 and/or the communication unit 509. When the computer program is loaded into RAM503 and executed by computing unit 501, one or more steps of method 100 described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform the method 100 by any other suitable means (e.g., by means of firmware).
The various embodiments described above herein may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems-on-a-chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a computer-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a computer-readable storage medium would include one or more wire-based electrical connections, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
It should be noted that the present disclosure further provides a non-transitory computer readable storage medium storing computer instructions, where the computer instructions are configured to cause a computer to perform the method 100 and achieve corresponding technical effects achieved by performing the method according to the embodiments of the present disclosure, which are not described herein for brevity.
In addition, the present disclosure also provides a computer program product comprising a computer program which, when executed by a processor, implements the method 100.
To provide for interaction with a user, the embodiments described above may be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The above-described embodiments may be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (10)
1. A method for simulating urban surface runoff, the method comprising:
dividing the target area according to the selected urban geographic grid level to obtain a plurality of urban geographic grids;
generating ground surface cells corresponding to the urban geographic grids, and initializing the ground surface cells according to the geographic information of the target area;
and circularly calculating the water depth of each surface cell at the end of the simulation time step and the water quantity transferred to each downstream neighborhood surface cell in the simulation time step by taking the simulation time step as a unit until the total simulation time length is reached.
2. The method of claim 1, wherein the dividing the target area according to the selected urban geographic grid level to obtain a plurality of urban geographic grids comprises:
and dividing the target area according to the size of the specification block corresponding to the urban geographic grid level to obtain a plurality of urban geographic grids.
3. The method of claim 1, wherein initializing each cell based on geographic information of the target area comprises:
determining geographic information of each urban geographic grid according to the geographic information of the target area;
binding the geographic information of each urban geographic grid with the corresponding ground surface cell, and initializing each ground surface cell.
4. The method of claim 1, wherein the cyclically calculating the water depth at the end of the simulation time step and the amount of water transferred to each downstream neighbor cell in the simulation time step comprises:
identifying the underlying surface type of each ground surface cell, and eliminating the ground surface cells with the underlying surface type being a house layer;
the cyclic calculation does not exclude the depth of water at the end of the simulation time step and the amount of water transferred by the cells to each downstream neighbor cell in the simulation time step.
5. The method of claim 4, wherein said calculating the depth of water at the end of the simulation time step and the amount of water transferred to each downstream neighbor cell in the simulation time step by the non-excluded cells comprises:
calculating the water depth of the non-excluded ground cells at the end of the simulation time step according to the rainfall, the soil infiltration, the vegetation retention and the gully discharge of the non-excluded ground cells in the simulation time step, and taking the water depth and the topography Gao Chengzhi of the non-excluded ground cells and the water level as the non-excluded ground cells;
for any non-excluded ground cell, taking the non-excluded ground cell as a central ground cell, determining a downstream neighborhood ground cell according to the water level of the central ground cell and the water level of the neighborhood ground cell, and calculating the first time length required by all water quantity transferred from the central ground cell to each downstream neighborhood ground cell;
calculating the maximum transfer water quantity corresponding to each downstream neighborhood ground cell according to the water quantity of the central ground cell and the gradients of the central ground cell and each downstream neighborhood ground cell;
if the simulation time step length is greater than or equal to the first time length, determining that the water quantity transferred from the central ground cell to the downstream neighborhood ground cell corresponding to the first time length in the simulation time step length is the corresponding maximum transfer water quantity;
if the simulation time step is smaller than the first time length, determining that the water quantity transferred from the central ground cell to the downstream neighborhood ground cell corresponding to the first time length in the simulation time step is the product of the corresponding maximum transferred water quantity and the ratio of the simulation time step to the first time length.
6. The method of claim 5, wherein the method further comprises:
and correcting the water quantity transferred from the central ground cell to each downstream neighborhood ground cell in the simulation time step according to the upper limit of the water quantity transferred corresponding to each downstream neighborhood ground cell.
7. The method of any one of claims 1-5, wherein the boundary tracking rule for the cells of the earth is a molar neighborhood method.
8. An urban surface runoff simulation device, the device comprising:
the segmentation module is used for segmenting the target area according to the selected urban geographic grid level to obtain a plurality of urban geographic grids;
the generation module is used for generating ground cells corresponding to the urban geographic grids and initializing the ground cells according to the geographic information of the target area;
and the calculation module is used for circularly calculating the water depth of each ground cell at the end of the simulation time step and the water quantity transferred to each downstream neighborhood ground cell in the simulation time step by taking the simulation time step as a unit until the simulation total duration is reached.
9. An electronic device, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.
10. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1-7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117252132A (en) * | 2023-11-20 | 2023-12-19 | 中山大学 | Basin production and confluence simulation method, device, equipment and storage medium |
| CN117829033A (en) * | 2024-03-04 | 2024-04-05 | 中山大学 | Mountain torrent hydrodynamic simulation method, system, equipment and medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117252132A (en) * | 2023-11-20 | 2023-12-19 | 中山大学 | Basin production and confluence simulation method, device, equipment and storage medium |
| CN117252132B (en) * | 2023-11-20 | 2024-04-02 | 中山大学 | Basin production and confluence simulation method, device, equipment and storage medium |
| CN117829033A (en) * | 2024-03-04 | 2024-04-05 | 中山大学 | Mountain torrent hydrodynamic simulation method, system, equipment and medium |
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