A method, device, equipment and storage medium for predicting urban rainfall runoff

Abstract

The present application provides a method, device, equipment and storage medium for predicting urban rainfall runoff, and relates to the field of urban rainfall runoff simulation prediction. The method comprises: obtaining the grid data of each unit grid in the prediction area according to the regional data of the prediction area; obtaining the flow production and flow confluence of the corresponding unit grid according to the grid data of each unit grid; predicting the rainfall runoff in the prediction area according to the flow production and flow confluence of each unit grid, and evaluating the prediction results of the rainfall runoff prediction. It solves the problem that the simulation of the flow production process in the sub-catchment area in the prior art is relatively generalized, and the vertical movement of water flow cannot be considered in the calculation of two-dimensional hydraulic slope confluence, which are greatly deviated from the actual situation, and the prediction result is low in accuracy and has limitations. The current method cannot dynamically couple the water exchange between the pipe network and the river channel and slope, lacks flexibility and scalability, and leads to the technical problem of low efficiency in urban rainfall runoff prediction.

Description

Technical Field

[0001] The present application relates to the field of urban rainfall runoff simulation prediction, and in particular to an urban rainfall runoff prediction method, device, equipment and storage medium. Background Art

[0002] In the process of urban rainfall runoff simulation and prediction, the simulation of runoff generation and confluence is an important link. At present, the calculation of runoff generation and confluence is mainly based on the method of coupling the hydrological runoff generation model with the two-dimensional hydraulic confluence model. The coupling form organically links the one-dimensional river network or pipe network model with the two-dimensional surface confluence model to achieve a comprehensive simulation of the runoff generation and confluence process. When the hydrological model is coupled with the hydraulic model, the one-dimensional pipe network module, the one-dimensional river network module, and the two-dimensional surface flow model are used to construct the urban rainfall runoff simulation and prediction system.

[0003] However, the current flow generation and confluence methods in the coupled models are mostly based on a single connection method, and the two are calculated independently, which cannot dynamically couple the water exchange process. At the same time, they also fail to fully consider the flow generation mechanism of the complex underlying surface in each sub-catchment area of ​​the urban basin, as well as the dynamic water exchange between each sub-catchment area and between surface flow and pipe network.

[0004] At present, the simulation of runoff generation process in sub-catchment areas is relatively generalized, and the vertical movement of water flow cannot be considered in the calculation of two-dimensional hydraulic slope confluence. These are greatly deviated from the actual situation, resulting in low accuracy of rainfall runoff simulation prediction results and certain limitations. At the same time, the prediction method cannot dynamically couple the water exchange between the pipeline network and the river channel and slope, and lacks flexibility and scalability. These problems have led to inefficient urban rainfall runoff prediction. Summary of the invention

[0005] The present application provides a method, device, equipment and storage medium for predicting urban rainfall runoff, which are used to solve the current problems that the simulation of the flow generation process in the sub-catchment area is relatively generalized, and the vertical movement of water flow cannot be considered in the two-dimensional hydraulic slope confluence calculation. These problems deviate greatly from the actual situation, resulting in low accuracy of rainfall runoff simulation prediction results and certain limitations; at the same time, the prediction method cannot dynamically couple the water exchange between the pipeline network and the river channel and slope, and lacks flexibility and scalability. These problems lead to the problem of low efficiency in urban rainfall runoff prediction.

[0006] In a first aspect, the present application provides a method for predicting urban rainfall runoff, the method comprising:

[0007] According to the regional data of the prediction area, the grid data of each unit grid in the prediction area is obtained; wherein the multiple unit grids are obtained by gridding the prediction area according to the mutation degree of the regional data, and the grid area of ​​the unit grid is negatively correlated with the mutation degree; the regional data is used to indicate the geographic information data attribute of the prediction area, and each grid data is used to indicate the geographic information data attribute of the corresponding unit grid;

[0008] According to the grid data of each unit grid, the flow production and sink of the corresponding unit grid are obtained;

[0009] According to the flow production and runoff of each unit grid, rainfall runoff prediction is carried out for the prediction area, and the prediction results of rainfall runoff prediction are evaluated.

[0010] In a possible design, the prediction area includes multiple terrain areas, and each unit grid is located in one terrain area; the drainage network includes multiple network nodes, and each network node is a unit grid;

[0011] According to the grid data of each unit grid, the flow production and sink of the corresponding unit grid are obtained, including:

[0012] According to the grid data and flow generation algorithm of each unit grid, the flow generation of the corresponding unit grid is obtained; wherein each flow generation algorithm is determined based on the area information and node information of the corresponding unit grid, each area information is used to indicate the terrain area where the corresponding unit grid is located, and each node information is used to indicate whether the corresponding unit grid is a pipe network node;

[0013] According to the flow generation and confluence algorithm of each unit grid, the confluence of the corresponding unit grid is obtained; wherein each confluence algorithm is jointly determined according to the area information and node information of the corresponding unit grid.

[0014] In a possible design, the multiple terrain regions include slopes and river channels; the target unit grid is any one of the multiple unit grids;

[0015] For the target unit grid, according to the grid data and flow generation algorithm of each unit grid, the flow generation of the corresponding unit grid is obtained, including:

[0016] When the regional information indicates that the target unit grid is located on the slope, and the node information indicates that the target unit grid is a pipe network node, the net rainfall of the target unit grid is used as the flow production of the target unit grid;

[0017] When the regional information indicates that the target unit grid is located in a river channel, and the node information indicates that the target unit grid is a pipe network node, determining that the flow production of the target unit grid is zero;

[0018] When the node information indicates that the target unit grid is not a pipe network node, the flow generation algorithm is determined to be the Greenampt infiltration algorithm. Then, the flow generation of the target unit grid is obtained through the Greenampt infiltration algorithm based on the net rainfall and grid data of the target unit grid.

[0019] In a possible design, the grid data includes vegetation information and soil information, the vegetation information is used to indicate the vegetation condition of the target unit grid, and the soil information is used to indicate the soil condition of the target unit grid;

[0020] According to the net rainfall and grid data of the target unit grid, the flow production of the target unit grid is obtained through the Greenampt infiltration algorithm, including:

[0021] According to the vegetation information, the vegetation interception amount is calculated through the vegetation interception model, and the net rainfall of the target unit grid is calculated according to the vegetation interception amount;

[0022] According to the net rainfall and soil information, the infiltration rate of the target unit grid is calculated by using the Greenampt infiltration equation.

[0023] Based on the net rainfall and infiltration rate, the flow yield of the target unit grid is calculated.

[0024] In a possible design, for a target unit grid, the flow rate of the corresponding unit grid is obtained according to the flow generation and flow confluence algorithm of each unit grid, including:

[0025] When the slope node information indicates that the slope target unit grid is a pipe network node, the water exchange amount of the slope target unit grid is used as the slope sink amount of the slope target unit grid;

[0026] When the slope node information indicates that the slope target unit grid is not a pipe network node, the slope confluence algorithm is determined to be a two-dimensional shallow water equation group. Then, according to the slope grid data of the slope target unit grid, the slope confluence of the slope target unit grid is obtained through the slope two-dimensional shallow water equation group.

[0027] In a possible design, based on the grid data of the target unit grid, the confluence of the target unit grid is obtained through the two-dimensional shallow water equations, including:

[0028] When the target unit grids are all located on the slope surface and the target unit grids are outside the pipeline, the flow of the target unit grids is obtained through the two-dimensional shallow water equations according to the flow production and elevation difference information of the target unit grids, wherein the elevation difference information is used to indicate the elevation difference between the target unit grid and the object unit grid;

[0029] When the target unit grid is located on the slope and inside the pipeline, the confluence of the target unit grid is obtained through the two-dimensional shallow water equations according to the elevation difference information of the target unit grid;

[0030] When the target unit grid is located in the river channel and outside the pipeline, the flow of the target unit grid is obtained through the two-dimensional shallow water equations according to the flow production and water exchange information of the target unit grid, wherein the water exchange information is used to indicate the water exchange between the target unit grid and the object unit grid;

[0031] When the target unit grid is located in the river channel and inside the pipe, the flow rate of the target unit grid is obtained through the two-dimensional shallow water equations according to the water exchange information of the target unit grid.

[0032] In a possible design, based on the flow rate and elevation difference information of the target unit grid, the flow rate of the target unit grid is obtained through the two-dimensional shallow water equations, including:

[0033] According to the elevation difference information, the inflow water volume of the target unit grid is calculated;

[0034] According to the inflow water volume, the lateral flow velocity and longitudinal flow velocity of the target unit grid are calculated;

[0035] According to the transverse flow velocity and the longitudinal flow velocity, a flow vector, a flux vector in a first direction, and a flux vector in a second direction are calculated; wherein the second direction is perpendicular to the first direction;

[0036] According to the grid data, the bottom slope source term and friction source term of the target unit grid are calculated, and combined with the flow production of the target unit grid, the source term of the target unit grid is calculated;

[0037] According to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are obtained through the two-dimensional shallow water equation group; wherein the lateral flow velocity and the longitudinal flow velocity represent the sinking amount of the target unit grid;

[0038] According to the flow production and water exchange information of the target unit grid, the flow of the target unit grid is obtained through the two-dimensional shallow water equations, including:

[0039] According to the water exchange information, the water exchange amount of the target unit grid is calculated;

[0040] According to the water exchange amount, the lateral flow velocity and longitudinal flow velocity of the target unit grid are calculated;

[0041] According to the transverse flow velocity and the longitudinal flow velocity, a flow vector, a flux vector in a first direction, and a flux vector in a second direction are calculated;

[0042] According to the grid data, the bottom slope source term and friction source term of the target unit grid are calculated, and combined with the flow production of the target unit grid, the source term of the target unit grid is calculated;

[0043] According to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are obtained through the two-dimensional shallow water equations; wherein the lateral flow velocity and the longitudinal flow velocity represent the sinking amount of the target unit grid.

[0044] In a possible design, the inflow water volume of the target unit grid is calculated based on the elevation difference information, including:

[0045] Obtain the elevation difference information between the target unit grid and the object unit grid, and calculate the updated elevation of the target unit grid through weighted adjustment;

[0046] According to the updated elevation of the target unit grid, the adjusted elevation of the target unit grid is calculated;

[0047] Based on the adjusted elevation, the inflow water volume of the target unit grid is calculated.

[0048] In a possible design, according to vegetation information, the vegetation interception amount is calculated by a vegetation interception model, and the net rainfall of the target unit grid is calculated according to the vegetation interception amount, which specifically includes:

[0049]

[0050] in, It is The vegetation interception amount of each of the unit grids; It is The vegetation coverage of each unit grid, It is The leaf area index of the unit grid, It is Leaf surface water holding capacity of each of the unit grids;

[0051]

[0052] Where N is the net rainfall of the target unit grid; is the original water volume of the target cell grid; is the water loss of the target unit grid; is the vegetation interception of the target cell grid;

[0053] According to the grid data, the bottom slope source term and friction source term of the target unit grid are calculated. Combined with the flow production of the target unit grid, the source term of the target unit grid is calculated, including:

[0054]

[0055] in, is the bottom slope source term of the target cell grid; is the friction source term of the target cell grid, is the flow production of the target unit grid;

[0056] According to the adjusted elevation, the inflow water volume of the target unit grid is calculated, including:

[0057]

[0058] in, is the adjusted elevation of the target cell grid; is the original inflow water volume of the target unit grid; is the inflow water volume of the target unit grid;

[0059] According to the water exchange information, the water exchange amount of the target unit grid is calculated, including:

[0060]

[0061] in, It is the amount of water exchange between the network nodes and the river; is the outflow coefficient of the network node, is the effective cross-sectional area of ​​the network node; is the acceleration due to gravity; is the water level at the network node; It is the water level of the river.

[0062] In a possible design, the grid accuracy of a unit grid is positively correlated with the terrain variation degree of the corresponding unit grid, wherein each terrain variation degree is used to indicate the variation degree of the corresponding terrain area.

[0063] In one possible design, the prediction results of rainfall-runoff prediction are evaluated, including:

[0064] Obtain measured data of rainfall runoff in the prediction area;

[0065] According to the measured data, the predicted data of rainfall runoff in the prediction area are evaluated for effectiveness through at least one evaluation index, wherein the evaluation index includes: Nash efficiency coefficient, runoff relative error and deviation coefficient.

[0066] In a second aspect, the present application provides an urban rainfall runoff prediction device, comprising: a data acquisition device, a data processing device and a data evaluation device;

[0067] The data acquisition device is used to obtain the grid data of each unit grid in the prediction area according to the regional data of the prediction area; wherein the plurality of unit grids are obtained by gridding the prediction area according to the mutation degree of the regional data, and the grid area of ​​the unit grid is negatively correlated with the mutation degree; the regional data is used to indicate the geographic information data attribute of the prediction area, and each grid data is used to indicate the geographic information data attribute of the corresponding unit grid;

[0068] A data processing device, used for obtaining the flow generation and sink flow of the corresponding unit grid according to the grid data of each unit grid;

[0069] The data evaluation device is used to predict the rainfall runoff in the prediction area according to the flow production and flow confluence of each unit grid, and to predict and evaluate the prediction results of the rainfall runoff prediction.

[0070] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0071] Memory stores computer-executable instructions;

[0072] When the processor executes the computer-executable instructions stored in the memory, it is used to implement a method for predicting urban rainfall runoff according to the first aspect of the invention.

[0073] In a fourth aspect, the present application provides a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed by a processor, they are used to implement a method for predicting urban rainfall runoff according to the invention content of the first aspect.

[0074] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, is used to implement a method for predicting urban rainfall runoff according to the invention content of the first aspect.

[0075] The present application provides a method, device, equipment and storage medium for predicting urban rainfall runoff. According to the regional data of the prediction area, the grid data of each unit grid in the prediction area is obtained; according to the grid data of each unit grid, the flow production and flow confluence of the corresponding unit grid are obtained; according to the flow production and flow confluence of each unit grid, the rainfall runoff of the prediction area is predicted, and the prediction results of the rainfall runoff prediction are predicted and evaluated. Compared with the prior art, the simulation of the runoff generation process in the sub-catchment area is relatively generalized, and the vertical movement of water flow cannot be considered in the two-dimensional hydraulic slope confluence calculation, which deviates greatly from the actual situation, resulting in low accuracy of rainfall runoff simulation prediction results and certain limitations; at the same time, the prediction method cannot dynamically couple the water exchange between the pipeline network and the river and slope, and lacks flexibility and scalability. These problems have led to the low efficiency of urban rainfall runoff prediction. This application performs grid refinement processing for complex terrain, optimizes runoff generation calculation based on the plant interception model, optimizes confluence calculation based on the elevation difference between the slope and the pipeline and the water exchange between the river and the pipeline, and adds the vertical movement of water flow to the confluence calculation, which is fully close to the movement of water flow in actual conditions, thereby improving the efficiency of urban rainfall runoff prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0077] Figure 1 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 1 ;

[0078] Figure 2 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 2 ;

[0079] Figure 3 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 3 ;

[0080] Figure 4 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 4 ;

[0081] Figure 5 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 5 ;

[0082] Figure 6 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 6 ;

[0083] Figure 7 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 7 ;

[0084] Figure 8 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 8 ;

[0085] Fig. 9 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 9 ;

[0086] Fig.10 A schematic diagram of the structure of an urban rainfall runoff prediction device provided in an embodiment of the present application;

[0087] Fig.11 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0088] Reference numerals:

[0089] 11-data acquisition device; 12-data processing device; 13-data evaluation device;

[0090] 20 - electronic device; 21 - processor; 22 - memory; 23 - communication component; 24 - bus. DETAILED DESCRIPTION

[0091] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0092] In the embodiments of the present application, words such as "first" and "second" are used to distinguish the same or similar items with basically the same functions and effects. Those skilled in the art will understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit the difference. It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way. In the embodiments of the present application, "at least one" refers to one or more, and "more" refers to two or more.

[0093] It should be noted that the "at..." in the embodiments of the present application can be the instant when a certain situation occurs, or can be a period of time after a certain situation occurs, and the embodiments of the present application do not specifically limit this. In addition, the urban rainfall runoff prediction method provided in the embodiments of the present application is only used as an example, and the urban rainfall runoff prediction method can also include more or less content.

[0094] Based on this, in order to solve the above technical problems, the embodiments of the present application provide a method, device, equipment and storage for predicting urban rainfall runoff, which can be used in the field of urban rainfall runoff prediction. The inventive concept of the present application is: how to effectively improve the efficiency of urban rainfall runoff prediction.

[0095] Figure 1 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 1 ,like Figure 1 As shown, the method includes:

[0096] S101. Obtaining grid data of each unit grid in the prediction area according to the area data of the prediction area.

[0097] Among them, multiple unit grids are obtained by gridding the prediction area according to the mutation degree of regional data, and the grid area of ​​the unit grid is negatively correlated with the mutation degree; the regional data is used to indicate the geographic information data attributes of the prediction area, and each grid data is used to indicate the geographic information data attributes of the corresponding unit grid.

[0098] It should be noted that before predicting the regional data of a region, the regional data needs to be acquired and preprocessed.

[0099] Specifically, regional data may include: land use data, soil data, terrain data, vegetation data, and pipe network space and attribute data.

[0100] Optionally, the image data is preprocessed, including: band synthesis, projection transformation, image enhancement, image cropping, etc.

[0101] Optionally, the maximum likelihood classification (MLC) method is used to classify the land use of the image, and the classification accuracy of the land use classification results is tested until the accuracy requirements are met to obtain the land use type data of the urban study area.

[0102] Optionally, remote sensing technologies such as stereo measurement, radar interferometry (InSAR), and laser radar (LiDAR) are used to obtain high-precision data. According to the geographical location of the urban study area, the original data is projected and cut to obtain the terrain data of the study area.

[0103] Optionally, soil type information can be indirectly obtained using remote sensing images by analyzing the spectral response and surface characteristics of the soil, and the accuracy of soil type classification can be improved by combining spectral feature analysis with ground verification data.

[0104] Furthermore, grid generation is performed based on the regional data.

[0105] Optionally, when generating slope meshes, a denser mesh is used in areas where the underlying surface changes more complexly, such as land use and topography, and a larger mesh is used in areas where the changes are more stable.

[0106] Optionally, a more refined grid division is required for the flow generation and confluence of the river channel, using finer grids in areas that require detailed simulation and coarser grids in slope areas with lower simulation requirements.

[0107] Specifically, a buffer zone is generated by the river channel, and a threshold value of the river channel range that needs to be refined is set. Within the range from the river channel to the threshold value, an unstructured grid is used to perform refined grid division based on the fluid dynamic characteristics of the river channel and the shore or the gradient of related physical quantities. Grid optimization technology is applied to improve the grid quality, such as eliminating grid elements that are too small and adjusting the grid distribution to avoid overly dense or overly sparse grids.

[0108] More specifically, at the junction of the river channel and slope meshes, in order to ensure the proper transition between meshes, the mesh smoothing can be manually adjusted to avoid generating mesh elements that are too large or too small, to ensure the coherence and consistency of the entire mesh system, and to ensure that different types of meshes can be effectively combined to transmit information on boundaries and interfaces.

[0109] In addition, after the river grid is divided, the elevation information of the river grid is assigned by the elevation reading data, and the river bottom and water surface elevation can be interpolated in combination with the field survey data.

[0110] Furthermore, after the grid is generated, the relevant geographic information data attributes are assigned to each grid cell.

[0111] Specifically, when assigning attributes, the above spatial data layers are analyzed through spatial analysis operations, including clipping, overlay and attributes, to obtain the attribute content of each grid unit, which is achieved through the "overlay analysis" or "attribute" tool.

[0112] Optionally, underground drainage network data may come from the urban network design drawing, including node information, rainwater pipe information, drainage outlet information and their attribute information, especially elevation-related network attribute information such as bottom height and well depth.

[0113] It should also be noted that the grid accuracy of a unit grid is positively correlated with the terrain change degree of the corresponding unit grid, wherein each terrain change degree is used to indicate the change degree of the corresponding terrain area.

[0114] S102. Obtain the flow generation and sink of the corresponding unit grid according to the grid data of each unit grid.

[0115] The prediction area includes a variety of terrain areas, and each unit grid is located in a terrain area; the drainage network includes a plurality of network nodes, and each network node is a unit grid.

[0116] Specifically, according to the grid data of each unit grid and the flow generation algorithm, the flow generation of the corresponding unit grid is obtained.

[0117] Among them, each flow generation algorithm is determined based on the area information and node information of the corresponding unit grid. Each area information is used to indicate the terrain area where the corresponding unit grid is located, and each node information is used to indicate whether the corresponding unit grid is a pipeline network node.

[0118] Specifically, according to the flow generation and flow confluence algorithm of each unit grid, the flow confluence of the corresponding unit grid is obtained.

[0119] Among them, each confluence algorithm is determined based on the area information and node information of the corresponding unit grid.

[0120] S103. According to the flow production and runoff of each unit grid, a rainfall runoff forecast is conducted for the forecast area, and a forecast evaluation is conducted on the forecast result of the rainfall runoff forecast.

[0121] The present embodiment provides a method for predicting urban rainfall runoff. The method obtains grid data of each unit grid in the prediction area based on the regional data of the prediction area; obtains the flow generation and flow confluence of the corresponding unit grid based on the grid data of each unit grid; performs rainfall runoff prediction on the prediction area based on the flow generation and flow confluence of each unit grid, and performs prediction evaluation on the prediction results of the rainfall runoff prediction. Compared with the prior art, the simulation of the runoff generation process in the sub-catchment area is relatively generalized, and the vertical movement of water flow cannot be considered in the two-dimensional hydraulic slope confluence calculation, which deviates greatly from the actual situation, resulting in low accuracy of rainfall runoff simulation prediction results and certain limitations; at the same time, the prediction method cannot dynamically couple the water exchange between the pipeline network and the river and slope, and lacks flexibility and scalability. These problems have led to the low efficiency of urban rainfall runoff prediction. This application performs grid refinement processing for complex terrain, optimizes runoff generation calculation based on the plant interception model, optimizes confluence calculation based on the elevation difference between the slope and the pipeline and the water exchange between the river and the pipeline, and adds the vertical movement of water flow to the confluence calculation, which is fully close to the movement of water flow in actual conditions, thereby improving the efficiency of urban rainfall runoff prediction.

[0122] Figure 2 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 2 ,exist Figure 1 Based on the example, Figure 2 As shown, the various terrain areas include slopes and rivers; the target unit grid is any one of the multiple unit grids. For the target unit grid, the specific implementation steps of the above S102 include:

[0123] S201. When the area information indicates that the target unit grid is located on a slope, and the node information indicates that the target unit grid is a pipe network node, the net rainfall of the target unit grid is used as the flow production of the target unit grid.

[0124] In this embodiment, when the target unit grid is located at the pipe network node where the slope and the pipeline intersect, most of the pipe network nodes are inspection wells. Only the flow production is calculated at the inspection well, and the flow production is equal to the net rainfall. The calculation result is affected by the bottom material of the pipe network. Different pipe network bottom materials have different water losses.

[0125] S202: When the region information indicates that the target unit grid is located in a river channel and the node information indicates that the target unit grid is a pipe network node, determine that the flow production of the target unit grid is zero.

[0126] In this embodiment, when the target unit grid is located at a pipe network node where a river channel and a pipeline intersect, the pipe network node is mostly a drainage outlet, and the flow production cannot be calculated at the drainage outlet, so the flow production is zero.

[0127] S203. When the node information indicates that the target unit grid is not a pipe network node, the flow generation algorithm is determined to be the Greenampt infiltration algorithm, and the flow generation of the target unit grid is obtained through the Greenampt infiltration algorithm according to the net rainfall and grid data of the target unit grid.

[0128] In this embodiment, based on refined grid division, the flow rate is calculated by subdividing the pipe network nodes on different terrains, which improves the accuracy of urban rainfall runoff prediction and further improves the efficiency of urban rainfall runoff prediction.

[0129] Figure 3 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 3 ,exist Figure 1 and Figure 2 Based on the example, Figure 3 As shown, the grid data includes vegetation information and soil information. The vegetation information is used to indicate the vegetation condition of the target unit grid, and the soil information is used to indicate the soil condition of the target unit grid. The specific implementation steps of the above S203 include:

[0130] S301. According to vegetation information, a vegetation interception model is used to calculate a vegetation interception amount, and a net rainfall of a target unit grid is calculated according to the vegetation interception amount.

[0131] Specifically, we first need to determine whether the target unit grid is a vegetation grid. We can use the vegetation index to determine whether it is a vegetation grid. When it is determined to be a vegetation grid, the vegetation interception amount is calculated using the vegetation interception model:

[0132]

[0133] in, It is Vegetation interception of each unit grid; It is The vegetation coverage of each unit grid, It is The leaf area index of the unit grid, It is Leaf surface water holding capacity of a unit grid.

[0134] Specifically, for vegetation grids, the vegetation interception model is used to optimize the net rainfall:

[0135]

[0136] Where N is the net rainfall of the target unit grid; is the original water volume of the target cell grid; is the water loss of the target unit grid; is the vegetation interception of the target cell grid.

[0137] S302. According to the net rainfall and soil information, the infiltration rate of the target unit grid is calculated by using the Greenampt infiltration equation.

[0138] Specifically, the infiltration rate in each grid can be calculated by inputting soil information into the Green-Ampter infiltration equation:

[0139]

[0140] in, It is a grid The infiltration rate at the moment; is the saturated hydraulic conductivity; It is soil suction; is the field water holding capacity of the soil; is the initial water content, obtained by remote sensing inversion.

[0141] in, yes The cumulative infiltration at each moment can be set to a minimum value at the initial moment; at a specific moment of , which can be determined by the flow rate , Net rainfall and the infiltration volume at the previous moment The loop calculation yields:

[0142]

[0143] S303. Calculate the flow rate of the target unit grid according to the net rainfall and the infiltration rate.

[0144] Specifically, the flow rate Computable:

[0145]

[0146] In this embodiment, based on the refined grid division, in order to solve the problem of the relatively generalized runoff generation process in the sub-catchment area, a slope grid surface runoff calculation method based on topography, land use and soil information is proposed. The runoff generation is calculated based on the soil, topography, land use, vegetation and other information in each grid, rather than simply generalizing it into permeable surface areas and impervious surfaces, thereby improving the efficiency of urban rainfall runoff prediction.

[0147] Figure 4 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 4 ,exist Figure 1 Figure 2 as well as Figure 3 Based on the example, Figure 4As shown, for the target unit grid, the specific implementation steps of the above S102 also include:

[0148] S401. When the slope node information indicates that the slope target unit grid is a pipe network node, the water exchange amount of the slope target unit grid is used as the slope confluence amount of the slope target unit grid.

[0149] In this embodiment, when the target unit grid is located at the network node where the slope and the pipeline intersect, the network node is mostly a manhole, and at the manhole, the confluence is the water exchange amount. When the target unit grid is located at the network node where the river and the pipeline intersect, the network node is mostly a drain, and at the drain, the confluence is the water exchange amount.

[0150] S402, when the slope node information indicates that the slope target unit grid is not a pipe network node, the slope confluence algorithm is determined to be a two-dimensional shallow water equation group, and the slope confluence of the slope target unit grid is obtained through the slope two-dimensional shallow water equation group according to the slope grid data of the slope target unit grid.

[0151] In this embodiment, based on refined grid division, the flow rate is calculated by subdividing the pipe network nodes on different terrains, which improves the accuracy of urban rainfall runoff prediction and further improves the efficiency of urban rainfall runoff prediction.

[0152] Figure 5 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 5 ,exist Figure 1 Figure 2 Figure 3 as well as Figure 4 Based on the example, Figure 5 As shown, the specific implementation steps of the above S403 include:

[0153] S501. When the target unit grids are all located on the slope and the target unit grids are outside the pipeline, the flow rate of the target unit grids is obtained through a two-dimensional shallow water equation group according to the flow production and elevation difference information of the target unit grids, wherein the elevation difference information is used to indicate the elevation difference between the target unit grid and the object unit grid.

[0154] Optionally, when the target unit grid is located on the slope and outside the pipe, in the water circulation of the target unit grid, the water flow moves longitudinally between the soil in addition to the horizontal movement, so the flow rate is calculated in combination with the flow production (longitudinal flow movement flow) of the target unit grid.

[0155] Optionally, the elevation difference information between the sum of the depth and bottom height of the pipe network node and the slope elevation will affect the inflow of water into the target unit grid, thereby affecting the lateral and longitudinal flow velocities of the water flow. Therefore, it is necessary to adjust the inflow of water and calculate the flow rate in combination with the optimized terrain adjustment factor elevation.

[0156] S502: When the target unit grid is located on the slope and inside the pipeline, the flow rate of the target unit grid is obtained through a two-dimensional shallow water equation group according to the elevation difference information of the target unit grid.

[0157] Optionally, when the target unit grid is located on a slope and inside a pipe, in the water circulation of the target unit grid, the water flow only moves laterally in the horizontal direction.

[0158] Optionally, the elevation difference information between the sum of the depth and bottom height of the pipe network node and the slope elevation will affect the inflow of water into the target unit grid, thereby affecting the lateral flow velocity of the water flow. Therefore, it is necessary to adjust the inflow of water and calculate the flow rate in combination with the optimized terrain adjustment factor elevation.

[0159] S503. When the target cell grid is located in the river channel and the target cell grid is outside the pipeline, the flow rate of the target cell grid is obtained through a two-dimensional shallow water equation group according to the flow production and water exchange information of the target cell grid, wherein the water exchange information is used to indicate the water exchange between the target cell grid and the object cell grid.

[0160] Optionally, when the target unit grid is located in the river channel and outside the pipeline, in the water circulation of the target unit grid, the water flow not only moves horizontally but also moves vertically between the soils, so the flow rate is calculated in combination with the flow production (longitudinal flow rate) of the target unit grid.

[0161] Optionally, the different heights of the pipe network nodes and the river water levels will affect the water exchange volume, thereby affecting the lateral and longitudinal flow velocities of the water flow. Therefore, it is necessary to calculate the confluence volume in combination with the water exchange volume.

[0162] S504. When the target unit grid is located in the river channel and the target unit grid is inside the pipe, the flow rate of the target unit grid is obtained through a two-dimensional shallow water equation group according to the water volume exchange information of the target unit grid.

[0163] Optionally, when the target unit grid is located in a river channel and inside a pipe, in the water circulation of the target unit grid, the water flow only moves laterally in the horizontal direction.

[0164] Optionally, the different heights of the pipe network nodes and the river water levels will affect the water exchange volume, thereby affecting the lateral and longitudinal flow velocities of the water flow. Therefore, it is necessary to calculate the confluence volume in combination with the water exchange volume.

[0165] In this embodiment, the flow rate is calculated by combining the flow rate and elevation difference information with the water exchange information, thereby solving the problems that the longitudinal movement of water flow cannot be considered in the two-dimensional hydraulic slope confluence calculation, the difference between the sum of the depth and bottom height of the pipe network node and the slope elevation will affect the inflow of water, and the different water level heights between the pipe network node and the river will affect the water exchange volume, thereby improving the efficiency of urban rainfall runoff prediction.

[0166] Figure 6 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 6 ,exist Figure 1-Figure 5 Based on all the above embodiments, Figure 6 As shown, the specific implementation steps of the above S501 include:

[0167] S601. Calculate the inflow water volume of the target unit grid according to the adjusted elevation.

[0168]

[0169] in, is the adjusted elevation of the target cell grid; is the original inflow water volume of the target unit grid; is the inflow water volume of the target cell grid.

[0170] S602: Calculate the lateral flow velocity and the longitudinal flow velocity of the target unit grid according to the inflow water volume.

[0171] Specifically, according to , the lateral flow velocity and longitudinal flow velocity of the target unit grid can be obtained.

[0172] S603. Calculate a flow vector, a flux vector in a first direction, and a flux vector in a second direction according to the transverse flow velocity and the longitudinal flow velocity; wherein the second direction is perpendicular to the first direction.

[0173] Specific:

[0174]

[0175] in, is the lateral flow velocity; is the longitudinal flow velocity; is the flow vector; is the flux vector in the first direction; is the flux vector in the second direction; It's the water depth.

[0176] S604. Calculate the bottom slope source term and friction source term of the target unit grid according to the grid data, and calculate the source term of the target unit grid in combination with the flow production of the target unit grid.

[0177] Specific:

[0178]

[0179] in, is the bottom slope source term of the target cell grid; is the friction source term of the target cell grid, is the flow production of the target cell grid.

[0180]

[0181] in, and They are Cartesian coordinates; is the density of water; It is the river bottom elevation; yes Bottom friction in Cartesian direction; yes Bottom friction in Cartesian direction; yes Bottom friction source term in Cartesian direction; yes Bottom friction source term in Cartesian direction; is the bottom surface roughness coefficient, , is the Manning coefficient.

[0182] S605. According to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are obtained through the two-dimensional shallow water equations; wherein the lateral flow velocity and the longitudinal flow velocity represent the confluence of the target unit grid.

[0183] Specific:

[0184]

[0185] in, It's time.

[0186] It should be noted that another implementation of S501 is S502. The specific implementation steps of S502 include:

[0187] According to the elevation difference information, the inflow water volume of the target unit grid is calculated:

[0188] According to the inflow water volume, the lateral flow velocity and longitudinal flow velocity of the target unit grid are calculated.

[0189] According to the transverse flow velocity and the longitudinal flow velocity, a flow vector, a flux vector in a first direction, and a flux vector in a second direction are calculated.

[0190] According to the grid data, the bottom slope source term and the friction source term of the target unit grid are calculated, and according to the bottom slope source term and the friction source term, the source term of the target unit grid is calculated.

[0191] According to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are obtained through the two-dimensional shallow water equations; wherein the lateral flow velocity and the longitudinal flow velocity represent the sinking amount of the target unit grid.

[0192] Specific:

[0193]

[0194] In this embodiment, the runoff generation is integrated into the two-dimensional hydraulic confluence method, and a combined model of hydrological runoff generation and two-dimensional hydraulic confluence is established with the advantages of both. This solves the problem that the vertical movement of water flow cannot be considered in the two-dimensional hydraulic slope confluence calculation, thereby improving the efficiency of urban rainfall runoff prediction.

[0195] Figure 7 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 7 ,exist Figure 1-Figure 6 Based on all the above embodiments, Figure 7 As shown, the specific implementation steps of the above S503 include:

[0196] S701. Calculate the water exchange amount of the target unit grid according to the water exchange information.

[0197] Specific

[0198]

[0199] in, It is the amount of water exchange between the network nodes and the river; is the outflow coefficient of the network node, is the effective cross-sectional area of ​​the network node; is the acceleration due to gravity; is the water level at the network node; It is the water level of the river.

[0200] Optionally, if the water level at the network node is higher than the river level, water will flow into the river through the drainage outlet; otherwise, river water backflow may occur.

[0201] Optional, when hour, A positive value indicates that water is flowing from the pipe network to the river.

[0202] Optional, when hour, If it is negative, it means that water flows from the river into the pipe network, and the formula can be adjusted accordingly. and Usually determined by the design of the drainage system, It depends on the design of the drain outlet and is affected by the shape and size of the drain outlet.

[0203] S702. Calculate the lateral flow velocity and the longitudinal flow velocity of the target unit grid according to the water exchange amount.

[0204] Specifically, according to , the lateral flow velocity and longitudinal flow velocity of the target unit grid can be obtained.

[0205] S703. Calculate a flow vector, a flux vector in a first direction, and a flux vector in a second direction according to the transverse flow velocity and the longitudinal flow velocity.

[0206]

[0207] S704. Calculate the bottom slope source term and friction source term of the target unit grid according to the grid data, and calculate the source term of the target unit grid in combination with the flow production of the target unit grid.

[0208]

[0209]

[0210] S705. According to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are obtained through the two-dimensional shallow water equations; wherein the lateral flow velocity and the longitudinal flow velocity represent the confluence of the target unit grid.

[0211] Specific:

[0212]

[0213] It should be noted that another implementation of S503 is S504. The specific implementation steps of S504 include:

[0214] According to the water exchange information, the water exchange amount of the target unit grid is calculated.

[0215] According to the water exchange volume, the lateral flow velocity and longitudinal flow velocity of the target unit grid are calculated.

[0216] According to the transverse flow velocity and the longitudinal flow velocity, a flow vector, a flux vector in a first direction, and a flux vector in a second direction are calculated.

[0217] According to the grid data, the bottom slope source term and the friction source term of the target unit grid are calculated, and according to the bottom slope source term and the friction source term, the source term of the target unit grid is calculated.

[0218] According to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are obtained through the two-dimensional shallow water equations; wherein the lateral flow velocity and the longitudinal flow velocity represent the sinking amount of the target unit grid.

[0219]

[0220]

[0221] In this embodiment, the flow rate is calculated based on the water exchange information based on the elevation difference information, thereby solving the problems that the difference between the sum of the depth and bottom height of the pipe network node and the slope elevation will affect the inflow of water, and the different water level heights between the pipe network node and the river will affect the water exchange volume, thereby improving the efficiency of urban rainfall runoff prediction.

[0222] Figure 8 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 8 ,exist Figure 1-Figure 7 Based on all the above embodiments, Figure 8 As shown, the specific implementation steps of the above S601 include:

[0223] S801, obtaining elevation difference information between a target unit grid and an object unit grid, and calculating an updated elevation of the target unit grid through weighted adjustment.

[0224] First, read the grid data and pipe network node data.

[0225] Second, for each point in the point layer, calculate its corresponding row and column number in the elevation raster layer:

[0226]

[0227] in, is the column number in the grid; is the row number in the grid, , is the resolution of the grid; is the coordinate of the upper left corner of the elevation grid; are geographic coordinates, represent Round down.

[0228] Again, create a new raster layer using the same dimensions as the original elevation raster layer, with all initial markers set to 0.

[0229] Finally, according to the calculated row and column numbers, the new layer exist The value of position is set to 1: ; If this pipe network node is a drain outlet, adjust:

[0230] Furthermore, the slope elevation is optimized based on the attribute information of the pipeline network nodes.

[0231] First, for the grid where the pipe network node is located, the relationship between the sum of the pipe network node depth and bottom height and the slope elevation is calculated.

[0232] Optionally, if the sum of the depth and bottom elevation of the pipe network node is close to the slope elevation, the sum of the depth and bottom elevation of the pipe network node can be used as the slope elevation to correct the elevation of the pipe network node:

[0233] Calibrate the network node data and remeasure the elevations of the network nodes; correct time differences; update the slope elevation data and use the calibrated network node data to update the slope elevation data. Use spatial analysis tools to analyze and compare the differences between the network node data and the slope elevation data, identify areas that need correction, and correct the slope elevation data in a cyclical manner.

[0234] Optionally, optimize the situation where there are multiple pipe network nodes around a grid:

[0235] set up For the The location and bottom elevation of each pipe network node can be re-measured on site or other accurate data sources can be used to obtain the calibrated bottom elevation of the pipe network node. .

[0236] For each network node, calculate the elevation adjustment value , according to the elevation adjustment value, the elevation of each point in the elevation data The distance between the nearest one or more pipe network nodes is weighted.

[0237] Adjusted elevation

[0238]

[0239] in, Is a distance-weighted function used to calculate A common choice for elevation adjustment is the inverse distance weighted method:

[0240]

[0241] in, is the weighting factor, .

[0242] in, is a positive parameter (usually 2); yes With pipe network node The distance between.

[0243] S802. Calculate the adjusted elevation of the target unit grid according to the updated elevation of the target unit grid.

[0244] If the sum of the depth and bottom height of the pipe network node is much different from the slope elevation, it means that the settlement or bulge of the pipe network node causes it to be not on the same plane as the ground surface. At this time, the slope elevation and the pipe network node elevation are recorded truthfully, and the bulge or settlement distance is set as the adjusted elevation. .

[0245] S803. Calculate the inflow water volume of the target unit grid according to the adjusted elevation.

[0246] Specific:

[0247]

[0248] in, is the adjusted elevation of the target cell grid; is the original inflow water volume of the target unit grid; is the inflow water volume of the target cell grid.

[0249] It should be noted that there are other methods for calculating the inflow of water:

[0250]

[0251] in, It is The unit grid at time The amount of water stored; It is The unit grid at time The water flow input; It's in time Directly from the The amount of water discharged from the unit grid at (the amount of water flowing into the pipe network); It is The rainfall infiltration of the unit grid at (can be directly the rainfall); is the time step.

[0252] The input and output of water flow can be further refined into water exchange with adjacent grid cells:

[0253]

[0254] in, Represents the value from the adjacent grid cells To grid cell The amount of water flow can be determined based on water level differences, pipe connections, gravity, and other physical factors. At the same time, the grid will no longer flow to adjacent grids unless overflow occurs.

[0255] In this embodiment, by optimizing the elevation, the problem that the difference between the sum of the depth and bottom height of the pipe network node and the slope elevation will affect the inflow of water is solved, thereby improving the efficiency of urban rainfall runoff prediction.

[0256] Fig. 9 A schematic diagram of a method for predicting urban rainfall runoff provided in an embodiment of the present application Figure 8 ,exist Figure 1-Figure 8 Based on all the above embodiments, Fig. 9 As shown, the specific implementation steps of the above S103 include:

[0257] S901. Obtain measured data of rainfall runoff in the prediction area.

[0258] S902. According to the measured data, the predicted data of rainfall runoff in the prediction area are evaluated by at least one evaluation index, wherein the evaluation index includes: Nash efficiency coefficient, runoff relative error and deviation coefficient.

[0259] Specific:

[0260]

[0261] in, is the Nash efficiency coefficient, is the relative error of runoff, is the coefficient of variation, is the measured flow rate, is the simulated flow, is the mean of the measured flow rate, is the simulated peak flow, It is the measured peak flow.

[0262] In this embodiment, based on the urban rainfall runoff prediction, the model performance is evaluated by using public rainfall runoff data, and the evaluation is performed using common indicators according to the Chinese hydrological forecast specifications, which increases the reliability of the urban rainfall runoff prediction and further improves the efficiency of the urban rainfall runoff prediction.

[0263] Fig.10 A schematic diagram of the structure of a device for predicting urban rainfall runoff provided in an embodiment of the present application is shown in FIG. Fig.10 As shown, the device comprises: a data acquisition device 11, a data processing device 12 and a data evaluation device 13.

[0264] The data acquisition device 11 is used to obtain the grid data of each unit grid in the prediction area according to the regional data of the prediction area; wherein the multiple unit grids are obtained by gridding the prediction area according to the mutation degree of the regional data, and the grid area of ​​the unit grid is negatively correlated with the mutation degree; the regional data is used to indicate the geographic information data attributes of the prediction area, and each grid data is used to indicate the geographic information data attributes of the corresponding unit grid.

[0265] The data processing device 12 is used to obtain the flow generation and sink of the corresponding unit grid according to the grid data of each unit grid.

[0266] The data evaluation device 13 is used to perform rainfall runoff prediction on the prediction area according to the runoff generation and runoff of each unit grid, and to perform prediction evaluation on the prediction results of the rainfall runoff prediction.

[0267] In a possible design, the prediction area includes multiple terrain areas, and each unit grid is located in one terrain area; the drainage pipe network includes multiple pipe network nodes, and each pipe network node is a unit grid. The data processing device 12 is further used to:

[0268] According to the grid data and flow generation algorithm of each unit grid, the flow generation of the corresponding unit grid is obtained; wherein each flow generation algorithm is determined based on the area information and node information of the corresponding unit grid, each area information is used to indicate the terrain area where the corresponding unit grid is located, and each node information is used to indicate whether the corresponding unit grid is a pipeline network node.

[0269] According to the flow generation and confluence algorithm of each unit grid, the confluence of the corresponding unit grid is obtained; wherein each confluence algorithm is jointly determined according to the area information and node information of the corresponding unit grid.

[0270] In a possible design, the multiple terrain areas include slopes and river channels; the target unit grid is any one of the multiple unit grids, and for the target unit grid, the data processing device 12 is further used to:

[0271] When the regional information indicates that the target unit grid is located on the slope, and the node information indicates that the target unit grid is a pipe network node, the net rainfall of the target unit grid is used as the flow production of the target unit grid;

[0272] When the regional information indicates that the target unit grid is located in a river channel, and the node information indicates that the target unit grid is a pipe network node, determining that the flow production of the target unit grid is zero;

[0273] When the node information indicates that the target unit grid is not a pipe network node, the flow generation algorithm is determined to be the Greenampt infiltration algorithm. Then, the flow generation of the target unit grid is obtained through the Greenampt infiltration algorithm based on the net rainfall and grid data of the target unit grid.

[0274] In a possible design, the grid data includes vegetation information and soil information, the vegetation information is used to indicate the vegetation condition of the target unit grid, and the soil information is used to indicate the soil condition of the target unit grid. The data processing device 12 is further used to:

[0275] According to the vegetation information, the vegetation interception amount is calculated through the vegetation interception model, and the net rainfall of the target unit grid is calculated according to the vegetation interception amount;

[0276] According to the net rainfall and soil information, the infiltration rate of the target unit grid is calculated by using the Greenampt infiltration equation.

[0277] Based on the net rainfall and infiltration rate, the flow yield of the target unit grid is calculated.

[0278] In a possible design, for the target unit grid, the data processing device 12 is further configured to:

[0279] When the slope node information indicates that the slope target unit grid is a pipe network node, the water exchange amount of the slope target unit grid is used as the slope sink amount of the slope target unit grid;

[0280] When the slope node information indicates that the slope target unit grid is not a pipe network node, the slope confluence algorithm is determined to be a two-dimensional shallow water equation group. Then, according to the slope grid data of the slope target unit grid, the slope confluence of the slope target unit grid is obtained through the slope two-dimensional shallow water equation group.

[0281] In a possible design, the data processing device 12 is further configured to:

[0282] When the target unit grids are all located on the slope surface and the target unit grids are outside the pipeline, the flow of the target unit grids is obtained through the two-dimensional shallow water equations according to the flow production and elevation difference information of the target unit grids, wherein the elevation difference information is used to indicate the elevation difference between the target unit grid and the object unit grid;

[0283] When the target unit grid is located on the slope and inside the pipeline, the confluence of the target unit grid is obtained through the two-dimensional shallow water equations according to the elevation difference information of the target unit grid;

[0284] When the target unit grid is located in the river channel and outside the pipeline, the flow of the target unit grid is obtained through the two-dimensional shallow water equations according to the flow production and water exchange information of the target unit grid, wherein the water exchange information is used to indicate the water exchange between the target unit grid and the object unit grid;

[0285] When the target unit grid is located in the river channel and inside the pipe, the flow rate of the target unit grid is obtained through the two-dimensional shallow water equations according to the water exchange information of the target unit grid.

[0286] In a possible design, the data processing device 12 is further configured to:

[0287] Based on the elevation difference information, the inflow water volume of the target unit grid is calculated.

[0288] According to the inflow water volume, the lateral flow velocity and longitudinal flow velocity of the target unit grid are calculated.

[0289] According to the transverse flow velocity and the longitudinal flow velocity, a flow vector, a flux vector in a first direction, and a flux vector in a second direction are calculated; wherein the second direction is perpendicular to the first direction.

[0290] According to the grid data, the bottom slope source term and friction source term of the target unit grid are calculated, and combined with the flow production of the target unit grid, the source term of the target unit grid is calculated.

[0291] According to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are obtained through the two-dimensional shallow water equations; wherein the lateral flow velocity and the longitudinal flow velocity represent the sinking amount of the target unit grid.

[0292] In a possible design, the data processing device 12 is further configured to:

[0293] According to the water exchange information, the water exchange amount of the target unit grid is calculated.

[0294] According to the water exchange volume, the lateral flow velocity and longitudinal flow velocity of the target unit grid are calculated.

[0295] According to the transverse flow velocity and the longitudinal flow velocity, a flow vector, a flux vector in a first direction, and a flux vector in a second direction are calculated.

[0296] According to the grid data, the bottom slope source term and friction source term of the target unit grid are calculated, and combined with the flow production of the target unit grid, the source term of the target unit grid is calculated.

[0297] According to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are obtained through the two-dimensional shallow water equations; wherein the lateral flow velocity and the longitudinal flow velocity represent the sinking amount of the target unit grid.

[0298] In a possible design, the data processing device 12 is further configured to:

[0299] The elevation difference information between the target unit grid and the object unit grid is obtained, and the updated elevation of the target unit grid is calculated through weighted adjustment.

[0300] According to the updated elevation of the target unit grid, the adjusted elevation of the target unit grid is calculated.

[0301] Based on the adjusted elevation, the inflow water volume of the target unit grid is calculated.

[0302] In a possible design, the data processing device 12 is further used to calculate:

[0303]

[0304] in, It is Vegetation interception of each unit grid; It is The vegetation coverage of each unit grid, It is The leaf area index of the unit grid, It is Leaf surface water holding capacity of each unit grid;

[0305]

[0306] Where N is the net rainfall of the target unit grid; is the original water volume of the target cell grid; is the water loss of the target unit grid; is the vegetation interception of the target cell grid;

[0307] According to the grid data, the bottom slope source term and friction source term of the target unit grid are calculated. Combined with the flow production of the target unit grid, the source term of the target unit grid is calculated, including:

[0308]

[0309] in, is the bottom slope source term of the target cell grid; is the friction source term of the target cell grid, is the flow production of the target unit grid;

[0310] According to the adjusted elevation, the inflow water volume of the target unit grid is calculated, including:

[0311]

[0312] in, is the adjusted elevation of the target cell grid; is the original inflow water volume of the target unit grid; is the inflow water volume of the target unit grid;

[0313] According to the water exchange information, the water exchange amount of the target unit grid is calculated, including:

[0314]

[0315] in, It is the amount of water exchange between the network nodes and the river; is the outflow coefficient of the network node, is the effective cross-sectional area of ​​the network node; is the acceleration due to gravity; is the water level at the network node; It is the water level of the river.

[0316] In a possible design, the grid accuracy of a unit grid is positively correlated with the terrain variation degree of the corresponding unit grid, wherein each terrain variation degree is used to indicate the variation degree of the corresponding terrain area.

[0317] In a possible design, the data evaluation device 13 is further used for:

[0318] Obtain measured data of rainfall runoff in the prediction area.

[0319] According to the measured data, the predicted data of rainfall runoff in the prediction area are evaluated for effectiveness through at least one evaluation index, wherein the evaluation index includes: Nash efficiency coefficient, runoff relative error and deviation coefficient.

[0320] Fig.11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Fig.11 As shown, the electronic device 20 includes: at least one processor 21 and a memory 22. The electronic device 20 also includes a communication component 23. The processor 21, the memory 22 and the communication component 23 are connected via a bus 24.

[0321] In the specific implementation process, at least one processor 21 executes the computer execution instructions stored in the memory 22, so that at least one processor 21 executes an urban rainfall runoff prediction method belonging to claims 1 to 11 as executed by the electronic device side as above.

[0322] The specific implementation process of the processor 21 can refer to the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here. In the above embodiment, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or the processor can be any conventional processor, etc. The steps of the method disclosed in the invention can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor.

[0323] The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk storage.

[0324] The second bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0325] The above-mentioned functions implemented by the electronic device and the main control device introduce the scheme provided by the embodiment of the present invention. It can be understood that in order to implement the above-mentioned functions, the electronic device or the main control device includes a hardware structure and / or software module corresponding to the execution of each function. In combination with the units and algorithm steps of each example described in the embodiment disclosed in the embodiment of the present invention, the embodiment of the present invention can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the technical solution of the embodiment of the present invention.

[0326] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, it is used to implement the above-mentioned urban rainfall runoff prediction method.

[0327] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0328] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist as discrete components in an electronic device or a main control device.

[0329] The present application also provides a computer program product, which includes: a computer program, which is stored in a readable storage medium. At least one processor of an electronic device can read the computer program from the readable storage medium, and at least one processor executes the computer program so that the electronic device executes the solution provided by any of the above embodiments.

[0330] Those skilled in the art can understand that all or part of the steps of the above method embodiments can be completed by hardware related to program instructions. The above program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above method embodiments are executed; and the above storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0331] So far, the technical solution of the present application has been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present application is obviously not limited to these specific embodiments, and the above embodiments are only used to illustrate the technical solution of the present application rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for predicting urban rainfall runoff, characterized in that: The method comprises: According to the regional data of the prediction area, grid data of each unit grid in the prediction area is obtained; wherein the plurality of unit grids are obtained by gridding the prediction area according to the mutation degree of the regional data, and the grid area of ​​the unit grid is negatively correlated with the mutation degree; the regional data is used to indicate the geographic information data attribute of the prediction area, and each of the grid data is used to indicate the geographic information data attribute of the corresponding unit grid; According to the grid data of each unit grid, the flow generation and sink of the corresponding unit grid are obtained; According to the runoff production and the runoff inflow of each unit grid, a rainfall runoff forecast is performed on the forecast area, and a forecast evaluation is performed on the forecast result of the rainfall runoff forecast; The prediction area includes a plurality of terrain areas, the plurality of terrain areas include slopes and rivers, and the target unit grid is any one of the plurality of unit grids; Get the corresponding unit grid sink flow, including: When the target unit grids are all located on the slope surface and the target unit grids are outside the pipeline, the flow of the target unit grids is obtained through a two-dimensional shallow water equation group according to the flow production and elevation difference information of the target unit grids, wherein the elevation difference information is used to indicate the elevation difference between the target unit grid and the object unit grid; The method of obtaining the flow rate of the target unit grid according to the flow rate and the elevation difference information of the target unit grid through the two-dimensional shallow water equation group includes: Calculate the inflow water volume of the target unit grid according to the elevation difference information; According to the inflow water volume, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are calculated; According to the transverse flow velocity and the longitudinal flow velocity, a flow vector, a flux vector in a first direction, and a flux vector in a second direction are calculated; wherein the second direction is perpendicular to the first direction; According to the grid data, a bottom slope source term and a friction source term of the target unit grid are calculated, and combined with the flow production of the target unit grid, a source term of the target unit grid is calculated; According to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are obtained through a two-dimensional shallow water equation group; wherein the lateral flow velocity and the longitudinal flow velocity represent the sinking amount of the target unit grid; When the target unit grid is located in the river channel and the target unit grid is outside the pipeline, the flow of the target unit grid is obtained through the two-dimensional shallow water equations according to the flow production and water exchange information of the target unit grid, wherein the water exchange information is used to indicate the water exchange between the target unit grid and the object unit grid; The method of obtaining the flow rate of the target unit grid according to the flow production and the water exchange information of the target unit grid through the two-dimensional shallow water equation group includes: Calculating the water exchange amount of the target unit grid according to the water exchange information; According to the water exchange amount, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are calculated; Calculating the flow vector, the flux vector in the first direction, and the flux vector in the second direction according to the transverse flow velocity and the longitudinal flow velocity; According to the grid data, a bottom slope source term and a friction source term of the target unit grid are calculated, and combined with the flow production of the target unit grid, a source term of the target unit grid is calculated; According to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term, the lateral flow velocity and the longitudinal flow velocity of the target unit grid are obtained through a two-dimensional shallow water equation group; wherein the lateral flow velocity and the longitudinal flow velocity represent the sink amount of the target unit grid.

2. The method according to claim 1, characterized in that Each of the unit grids is located in a type of terrain area; the drainage pipe network includes a plurality of pipe network nodes, and each of the pipe network nodes is a unit grid; The step of obtaining the flow generation and sink of the corresponding unit grid according to the grid data of each unit grid comprises: According to the grid data and flow generation algorithm of each unit grid, the flow generation of the corresponding unit grid is obtained; wherein each flow generation algorithm is determined based on the area information and node information of the corresponding unit grid, each area information is used to indicate the terrain area where the corresponding unit grid is located, and each node information is used to indicate whether the corresponding unit grid is a pipe network node; The confluence of the corresponding unit grid is obtained according to the flow generation and confluence algorithm of each unit grid; wherein each confluence algorithm is jointly determined according to the area information and the node information of the corresponding unit grid.

3. The method according to claim 2, characterized in that For the target unit grid, obtaining the flow generation of the corresponding unit grid according to the grid data and flow generation algorithm of each unit grid includes: When the area information indicates that the target unit grid is located on the slope, and the node information indicates that the target unit grid is a pipe network node, the net rainfall of the target unit grid is used as the flow production of the target unit grid; When the area information indicates that the target unit grid is located in the river channel, and the node information indicates that the target unit grid is a pipe network node, determining that the flow production of the target unit grid is zero; When the node information indicates that the target unit grid is not a pipe network node, the flow generation algorithm is determined to be the Greenampt infiltration algorithm, and the flow generation of the target unit grid is obtained through the Greenampt infiltration algorithm based on the net rainfall of the target unit grid and the grid data.

4. The method according to claim 3, characterized in that The grid data includes vegetation information and soil information, wherein the vegetation information is used to indicate the vegetation condition of the target unit grid, and the soil information is used to indicate the soil condition of the target unit grid; The method of obtaining the flow production of the target unit grid by using the Greenampt infiltration algorithm according to the net rainfall of the target unit grid and the grid data includes: According to the vegetation information, a vegetation interception amount is calculated by a vegetation interception model, and the net rainfall of the target unit grid is calculated according to the vegetation interception amount; According to the net rainfall and the soil information, the infiltration rate of the target unit grid is calculated by using the Greenampt infiltration equation; The flow production of the target unit grid is calculated based on the net rainfall and the infiltration rate.

5. The method according to claim 4, characterized in that For the target unit grid, obtaining the confluence of the corresponding unit grid according to the flow generation and confluence algorithm of each unit grid includes: When the node information indicates that the target unit grid is a pipe network node, the water exchange amount of the target unit grid is used as the sink amount of the target unit grid; When the node information indicates that the target unit grid is not a pipe network node, the confluence algorithm is determined to be a two-dimensional shallow water equation group, and the confluence flow of the target unit grid is obtained according to the grid data of the target unit grid through the two-dimensional shallow water equation group.

6. The method according to claim 5, characterized in that The method of obtaining the sinking amount of the target unit grid by using the two-dimensional shallow water equations according to the grid data of the target unit grid includes: When the target unit grid is located on the slope and is inside the pipeline, the confluence of the target unit grid is obtained through the two-dimensional shallow water equations according to the elevation difference information of the target unit grid; When the target unit grid is located in the river channel and the target unit grid is inside a pipe, the confluence of the target unit grid is obtained through the two-dimensional shallow water equations according to the water exchange information of the target unit grid.

7. The method according to claim 6, characterized in that The step of calculating the inflow water volume of the target unit grid according to the elevation difference information includes: Acquire the elevation difference information between the target unit grid and the object unit grid, and calculate the updated elevation of the target unit grid through weighted adjustment; Calculating the adjusted elevation of the target unit grid according to the updated elevation of the target unit grid; According to the adjusted elevation, the inflow water volume of the target unit grid is calculated.

8. The method according to claim 7, characterized in that The step of calculating the vegetation interception amount according to the vegetation information by using a vegetation interception model, and calculating the net rainfall of the target unit grid according to the vegetation interception amount specifically includes: in, It is The vegetation interception amount of each of the unit grids; It is The vegetation coverage of each unit grid, It is The leaf area index of the unit grid, It is Leaf surface water holding capacity of each of the unit grids; Wherein, N is the net rainfall of the target unit grid; is the original water volume of the target unit grid; is the water loss of the target unit grid; is the vegetation interception amount of the target unit grid; The step of calculating the bottom slope source term and the friction source term of the target unit grid according to the grid data, and calculating the source term of the target unit grid in combination with the flow production of the target unit grid, specifically includes: in, is the bottom slope source term of the target cell grid; is the friction source term of the target cell grid, is the flow production of the target unit grid; The step of calculating the inflow water volume of the target unit grid according to the adjusted elevation specifically includes: in, is the adjusted elevation of the target cell grid; is the original inflow water volume of the target unit grid; is the inflow water volume of the target unit grid; The step of calculating the water exchange amount of the target unit grid according to the water exchange information specifically includes: in, is the water exchange amount between the pipe network node and the river channel; is the outflow coefficient of the network node, is the effective cross-sectional area of ​​the pipe network node; is the acceleration due to gravity; is the water level at the node of the pipe network; is the water level of the river channel.

9. The method according to claim 3, characterized in that: The grid accuracy of the unit grid is positively correlated with the terrain change degree of the corresponding unit grid, wherein each terrain change degree is used to indicate the change degree of the corresponding terrain area.

10. The method according to claim 1, characterized in that The prediction and evaluation of the prediction results of the rainfall runoff prediction includes: Obtaining measured data of rainfall runoff in the prediction area; According to the measured data, the predicted data of rainfall runoff in the predicted area is evaluated for effectiveness by using at least one evaluation index, wherein the evaluation index includes: Nash efficiency coefficient, runoff relative error and deviation coefficient.

11. An urban rainfall runoff prediction device, characterized in that: include: Data acquisition device, data processing device and data evaluation device; The data acquisition device is used to obtain the grid data of each unit grid in the prediction area according to the regional data of the prediction area; wherein the plurality of unit grids are obtained by gridding the prediction area according to the mutation degree of the regional data, and the grid area of ​​the unit grid is negatively correlated with the mutation degree; the regional data is used to indicate the geographic information data attribute of the prediction area, and each of the grid data is used to indicate the geographic information data attribute of the corresponding unit grid; The data processing device is used to obtain the flow generation and sink of the corresponding unit grid according to the grid data of each unit grid; The data evaluation device is used to perform rainfall runoff prediction on the prediction area according to the runoff production and the runoff flow of each unit grid, and to perform prediction evaluation on the prediction result of the rainfall runoff prediction; The prediction area includes a plurality of terrain areas, the plurality of terrain areas include slopes and rivers, and the target unit grid is any one of the plurality of unit grids; The data processing device is further used for obtaining the confluence of the target unit grid through a two-dimensional shallow water equation group according to the flow production and elevation difference information of the target unit grid when the target unit grids are all located on the slope surface and the target unit grids are outside the pipeline, wherein the elevation difference information is used to indicate the elevation difference between the target unit grid and the object unit grid; The data processing device is further used to calculate the inflow water volume of the target unit grid according to the elevation difference information; calculate the lateral flow velocity and the longitudinal flow velocity of the target unit grid according to the inflow water volume; calculate the flow vector, the flux vector in the first direction and the flux vector in the second direction according to the lateral flow velocity and the longitudinal flow velocity; wherein the second direction is perpendicular to the first direction; calculate the bottom slope source term and the friction source term of the target unit grid according to the grid data, and calculate the source term of the target unit grid in combination with the flow production of the target unit grid; obtain the lateral flow velocity and the longitudinal flow velocity of the target unit grid through a two-dimensional shallow water equation group according to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term; wherein the lateral flow velocity and the longitudinal flow velocity represent the flow of the target unit grid; The data processing device is further used for obtaining the flow of the target cell grid through the two-dimensional shallow water equations according to the flow production and water exchange information of the target cell grid when the target cell grid is located in the river channel and the target cell grid is outside the pipeline, wherein the water exchange information is used to indicate the water exchange between the target cell grid and the object cell grid; The data processing device is also used to calculate the water exchange amount of the target unit grid according to the water exchange information; calculate the lateral flow velocity and the longitudinal flow velocity of the target unit grid according to the water exchange amount; calculate the flow vector, the flux vector in the first direction and the flux vector in the second direction according to the lateral flow velocity and the longitudinal flow velocity; calculate the bottom slope source term and the friction source term of the target unit grid according to the grid data, and calculate the source term of the target unit grid in combination with the flow production of the target unit grid; obtain the lateral flow velocity and the longitudinal flow velocity of the target unit grid through a two-dimensional shallow water equation group according to the flow vector, the flux vector in the first direction, the flux vector in the second direction and the source term; wherein the lateral flow velocity and the longitudinal flow velocity represent the confluence of the target unit grid.

12. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; When the processor executes the computer-executable instructions stored in the memory, it is used to implement the urban rainfall runoff prediction method as described in any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the urban rainfall runoff prediction method according to any one of claims 1 to 10.

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